Long-term sustainable econo-mix

LONG-TERM SUSTAINABLE ECONO-MIX Book series of the Magyar Nemzeti Bank © Magyar Nemzeti Bank, 2019 Contributors: Directorate Monetary Policy Instruments, Foreign Exchange Reserves and Risk Management Directorate for Fiscal and Competitiveness Analysis Directorate Economic Forecast and Analysis Directorate Methodology Directorate Monetary Policy and Financial Market Analysis Directorate for International Monetary Policy Analysis and Training of Economic Sciences Directorate Money and Foreign Exchange Markets Directorate Financial System Analysis PAGEO Research Institute Edited by: Barnabás Virág The editors would like to express their gratitude to the Governor György Matolcsy, Deputy Governors Márton Nagy, Mihály Patai and Csaba Kandrács for their professional comments during editing. Published by: Magyar Nemzeti Bank Szabadság tér 9. 1054 Budapest, Hungary www.mnb.hu All rights reserved. Prepress and printing: Prospektus Kft. ISSN: 2416-3503 ISBN: 978-615-5318-29-0 2019

Contents

Foreword 7 1 Introduction 9 2 Where could a new evolutionary wave of economics come from? 13 2.1 What is the economics of sustainability?

2.2 What can economics learn from the crisis?

2.3 Measuring GDP – The origins of the problem

3 5 challenges of the future 53 3.1 Ecological consequences of economic growth

3.2 Demographic challenges: how long and how large the world’s population will grow?

3.3 How to keep up with technology?

3.4 Geopolitical challenges: long-term sustainable Eurasian growth

3.5 Money in the digital age

4 Ecological sustainability – Green growth 107 4.1 Green growth framework

109

4.2 Regulatory opportunities fostering ecological sustainability

129

4.3 The growing use of green tax

143

4.4 Investments and green financing

166

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Contents

5 Demographic changes in the world 199 5.1 Economic challenges of ageing populations

201

5.2 Inequalities and growth in the 21st century

243

6 Social effects of the development of technology 273 6.1 Changes in the labour market in regard to the development of technology

275

6.2 Information (data) is the new oil

297

6.3 How to convert economic growth into social well-being

317

7 The future of money and the money of the future 333 7.1 Challenges of the digital era

335

7.2 The role of the financial system in sustainable development

359

8 Geopolitics and economy in the 21st century 395 8.1 The current state and the future of globalisation

397

8.2 New commercial and economic systems

424

8.3 Global cities are the new power centres of the 21st century: Long-term sustainable urban growth

443

9 Closing thoughts 463

â&#x20AC;&#x201D;6â&#x20AC;&#x201D;

Foreword The latest crisis that started in 2007 and became global in 2008 left deep scars on the global economy that will take decades to heal. Great economic crises tend to trigger sweeping changes in economics as a science. New paradigms and cognitive frameworks appear that define how the world and science develop for decades. This change led to the emergence and rise of John Maynard Keynes in the 1930s and the dominance of monetarism and neoclassical synthesis in the aftermath of the crises in the 1970s. The past decade saw a similar period of reflection in economics, which has proved to be particularly fruitful. Economists now tend to use the theses of psychology and behavioural science, while the operation of diverse national economies is understood deeply based on system theory comparisons. Network theory, geopolitics and IT are used ever more widely from university education to the preparation of economic decisions. Despite this progression, economics is still far from being completely reformed, although our world needs the “queen of social sciences” to be overhauled more than ever. We can look at our era with mixed feelings. At this moment, the world is experiencing one of the longest economic growth periods in the past hundred years. Unemployment rates are around historical lows in most countries, and stock markets are reaching unprecedented highs every day. Yet our societies are still highly uncertain about the future. Natural resources are being depleted at an alarming rate, everyone has first-hand experience with the consequences of climate change, while wealth inequalities have continued to widen in the past decade. Robotics and AI are transforming an increasing portion of our lives, and the geopolitical map of the world is also being redrawn fundamentally. In the rapidly changing 21st century, we need to prepare for unprecedented, completely new trends. Swift economic growth is not enough; sustainable development is needed. We need to achieve

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Foreword

development which is sustainable from financial, environmental and social perspectives as well. Technology, a new monetary system, mobility: these are just a few examples of the greatest challenges of the century ahead. Only a new, open-minded approach in economics, using a wide range of results from social sciences, can provide the appropriate answers for decisionmakers, governments, corporate managers and families, so all of us. But there should be no taboos on the road to reform, and the work should start with the fundamentals. How and under what conditions does competition result in welfare for a broad spectrum of society? What is money in the modern economy? How can we conserve our natural environment for our children and grandchildren in the same condition we received it from our parents while achieving economic growth? These are burning issues that need to be tackled urgently. However, the right answers can only be reached by posing questions in the proper way. This is the latest volume in the Magyar Nemzeti Bank’s book series. In these momentous times, it aims to provide an overview to the Reader about the topics determining our sustainable future, with open, new and sometimes provocative questions and the related deliberations. We are convinced that a complete renewal of economic thinking is one of the keys to finding the right answers. It is in our common interest to succeed. György Matolcsy, Márton Nagy, Mihály Patai, Csaba Kandrács

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Introduction Barnabás Virág

Readers hold in their hands a book that is unusual in several ways. Perhaps the first surprising aspect is that professionals from the fields of economics and finance have written a book on environmental protection, social inequalities, geopolitics and urbanisation. It is also rare to find works on economics guiding Readers along world events through the lens of various different questions, instead of providing answers and comprehensive solutions. The latest volume in the Magyar Nemzeti Bank’s book series undertakes these two tasks simultaneously. Since its inception, modern economics has sought to comprehend the functioning of the economy and grasp the conditions for achieving sustainable growth. The main issue is how economic development and the highest possible level of welfare can be provided to members of society. This question and the answers offered have been the driving force behind the evolution of economics. The results so far have been characterised by a great deal of duality. Since the First Industrial Revolution, the income levels generated by the global economy have been rising steadily apart from some periods of crisis and GDP per capita has reached unprecedented heights, while hundreds of millions of people have escaped deprivation and joined the global middle class. On the other hand, we are paying an increasingly high price for this growth. Overexploitation of the Earth’s natural resources, irreversible transformation of the biosphere, widening wealth inequalities and the uninterrupted expansion of financial debt are all part of the present operation of the world economy. Although in today’s economics textbooks, the Homo economicus acting in self-interest makes every decision based on all expected (short- and long-term) effects, the —9—

1 Introduction

aforementioned trends can hardly be considered the cornerstones of long-term sustainability. Despite the significant growth, the global economy has not been guided towards sustainability. At the same time, our world has also become more complex. In addition to trends which have emerged and been treated as less important than warranted by their actual significance, new megatrends linked to the technological revolution have emerged and are fundamentally transforming our world and the functioning of our economies in particular. The appearance of robotics and artificial intelligence, the spread of digitalisation, the transformation of the energy mix, genetic engineering and many other new technologies are opening up possibilities that were once unimaginable, but also pose serious challenges. We believe that economics also needs to be reformed to achieve sustainable development and widespread social welfare. This new economics must play a pivotal role in thinking about a more sustainable future. This process of transformation started in the past decade after the 2008â&#x20AC;&#x201C;2009 global crisis, but it continues to progress slowly. Meanwhile, the problems to be solved are increasingly complex, and their number is steadily rising. The goal of this publication is to offer a list of these problems and review the instruments that can guide the world economy onto a more sustainable path. The English title of the book, Econo-mix, is an intentional play on words. Scientific progress has shown countless times that new ideas often come from fields that were previously considered peripheral. Strengthening interdisciplinary ties must also be a major focus in economics. Fortunately, this process is already under way. Several new results have been achieved in recent years in the areas of behavioural science, institutional economics, economic history, geosciences and political science, and understanding these results more thoroughly and integrating them into economics as a discipline will greatly facilitate development. â&#x20AC;&#x201D; 10 â&#x20AC;&#x201D;

1 Introduction

In many areas of life, finding the right answers requires asking the right questions. The authors pose 95 crucial questions about the way our economies currently function and how they may function in the future. Although there are no straightforward answers yet, the authors not only understand the issues raised in these questions, they also shed some light on potential routes to solutions. If the reader devises possible new solutions or has further questions regarding these issues, the book has already served its purpose, because the only way to ensure a sustainable future is by reshaping our thinking and placing the functioning of our economies on a new footing. It is worth the effort.

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Where could aÂ new evolutionary wave of economics come from?

2.1

What is the economics of sustainability? Eszter Baranyai – CUB-MNB Department

Nobel Prize-winning economist Paul Samuelson referred to economics as the queen of social sciences.1 It is a social science because it examines the functioning of the economy in the context of human activities, incentives and decisions. It is much more than a collection of narrowly defined or abstract financial or economic topics, and it goes beyond the mere interpretation of data: it makes policy proposals. “Economics is the mother tongue of public policy […] and the mindset that shapes society.”2 It may not be obvious at first glance but economics exerts a fundamental influence on our everyday lives. Despite this positive characterisation, calls for redefining the discipline have been growing in recent years (Chapter 2.3). In 2016 the secretary general of the Club of Rome – which includes heads of nation, scientists and diplomats – went so far as to proclaim that the queen of social sciences was dying.3 It disregards vitally important issues and it is out of touch with the real world. In order to help redefine the discipline one must first ponder what the goal of economics should be. Leafing through the studies of major economists from recent decades and the last few centuries, one can find a plethora of responses to this seemingly simple question. Some Pühringer (2016) Raworth (2017) 3 Club of Rome (2016) 1 2

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2 Where could a new evolutionary wave of economics come from?

definitions focus on the relationship between society and the scarcity of resources, while others highlight the contribution to wealth and welfare. Adam Smith, also known as the father of economics, places the emphasis on providing adequate revenue – enabling people to provide it to themselves and ensuring that the state’s revenues are sufficient to cover public services.4 Nevertheless, since the mid-20th century the goal has increasingly become economic growth – which nowadays is mostly measured by gross domestic product (GDP). Interestingly, Simon Kuznets – the Nobel laureate who played a central role in developing the measurement of national income – warned that: “the welfare of a nation can scarcely be inferred from a measure of national income”, the quality, sustainability, costs and returns of growth also need to be taken into account.5 For example, the global economic growth of recent decades has coincided with carbon dioxide emissions almost quadrupling and the income of the wealthiest increasing disproportionately (Chart 2-1). A goal that better captures the desired social and economic development is long-term welfare. The idea is hardly new. Swiss economist Jean Sismondi referred to human welfare as the aim of the political economy in the early 19th century,6 however, it is largely only in recent decades that economists have renewed their interest in the topic. Indian economist Amartya Sen, who was awarded the Nobel Prize for his work in welfare economics and development economics, suggests that one should focus on the richness of human life and the development of human capabilities rather than on the wealth of the economy that surrounds humankind.7 Keeping these in mind, as a next step it is worth thinking through both the problems and the phenomena that economics should make sure it covers, as well as the general approach of the discipline. Smith (1776) Kuznets (1934) and (1962) 6 Raworth (2017) 7 Shaikh (2004) 4 5

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2.1 What is the economics of sustainability?

Chart 2-1: GDP, CO2 emission and the income share of the top 1 per cent in the world 90,000

USD billions/megatonnes

80,000 20

70,000 60,000

50,000 40,000

30,000 20,000

10,000 0 2017

2014

2011

2008

2005

2002

1999

1996

1993

1990

1987

1984

1981

1978

1975

1972

1969

1966

1963

1960

GDP (Current USD bn) CO2 emission (Mt) Top 1% share (right-hand scale)

Source: World Bank, World Inequality Database, CDIAC, UNFCCC, BP.

Many would argue that economists should have a better understanding of economic crises. How is it possible that in 2003, just five years before the start of the greatest economic crisis in 80 years, a prominent figure of the discipline – the Nobel laureate Robert Lucas – claimed that macroeconomics had achieved its most important goal and economic crises had become avoidable?8

Lucas (2003)

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2 Where could a new evolutionary wave of economics come from?

Concerned about the discipline’s understanding of crises, Nobel Prize laureate Joseph Stiglitz suggests the following are the central questions of macroeconomics:9 • What is the source of the disturbances in economic development? • Why do seemingly small disturbances have such huge effects? • Why do (deep) downturns last so long? In order to answer these questions as well as to understand the functioning of the broader economy, the financial ecosystem and the characteristics of irrational human behaviour must be appropriately reflected in economic thinking, as should the institutional context – laws, customs, culture, voluntary and civil society organisations, etc. In particular, environmental considerations, social changes, technological innovations and geopolitical developments should not be disregarded. Chart 2-2: What needs to be better integrated into macroeconomics? Financial system

Human behaviour

Social change

Technology

Nature conservation

Geopolitics

Source: Author’s own compilation.

In the 1980s the deterioration of the natural environment coupled with the realisation that resources were finite prompted the UN to establish an international commission examining the environmental aspects of 9

Stiglitz (2014)

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2.1 What is the economics of sustainability?

economic development. In its Brundtland Report,10 the commission examined the issue of sustainable development, a development “that meets the needs of the present without compromising the ability of future generations to meet their own needs”. In the three decades since then, however, it has become unclear whether economics, economic policymakers or society as a whole have integrated the natural environment into their thinking in line with the seriousness of the issue. For example, the UN found that between 1979 and 2012, the Arctic ice cap shrunk by roughly 4 per cent each decade, when using average annual data. The UN forecasts that sea levels will rise by 24–30 centimetres by 2065 compared to 1986–2005, assuming similar greenhouse gas emissions as today.11 The organisation emphasises that climate change is mostly a result of human activities, yet, unfortunately, in most countries, narrowly defined economic growth remains the primary objective. 12 The social context – inequality, poverty, demographic changes – has a fundamental bearing on the economic framework. As with the environmental context, the relationship is two-way, because more than being merely inputs into the economic machine, these factors are shaped by economic policy decisions and the mindset of a given era – both influenced by economics. Issues related to the social context have been seen as particularly important by students. Amongst other studies, this is confirmed by a CORE project survey, in which 4,442 economics students from 25 universities and 12 countries took part between 2016 and 2018.13 Looking at the answers broken down by universities shows that inequality was amongst the top three issues in almost all cases, frequently closely followed by poverty and unemployment. This should not come as a surprise. According to the World Income Database14 data compiled through laborious research, the richest 1 per cent of the world World Commission on Environment and Development (1987) United Nations (2019) 12 IPCC (2013) and (2018) 13 CORE Economics Education (2019) 14 World Income Database (2019) 10 11

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2 Where could a new evolutionary wave of economics come from?

increased their income share from 16 per cent to 20 per cent between 1980 and 2016. And during the same period, the middle class’s share (those between the lower 50 per cent and the upper 10 per cent based on income) of total global income fell from 43 per cent to 38 per cent. The change is particularly marked in the US: the richest 1 per cent almost doubled their share from 11 per cent to 20 per cent, while the poorer half of the population (based on their income) saw their share plummet from 20 per cent to 13 per cent. Since the publication of Thomas Piketty’s book on inequality, “Capital in the Twenty-First Century” – which might seem an unlikely bestseller with its 700 pages and detailed economic contemplations – there can be little doubt about the topicality of the issue. What is perhaps surprising is that the traditional macroeconomic models that are used in BA-level university courses do not address the subject, or at least not in sufficient depth. Important questions such as the drivers of inequality or the relationship between inequality and the economy cannot be disregarded by the part of the discipline that is accessible to the wider public and economic policymakers. In the long run, productivity growth, which serves as a pillar of economic development, is mainly attributable to technological progress.15 Technological advancement occurs continuously, shaping how we work, how we live, affecting our society, the economy and even our health. Economics not only needs to keep up with the change, for example by reflecting the decline of money or the potential spread of blockchain technology in its monetary models, it is also important to create an environment that fosters technological innovation – bearing in mind of course the sustainability of development. Sustainability includes an accurate understanding of the role of short- and long-term incentives and their integration into economics. There could be greater emphasis in economic studies on the financial incentives of corporate managers and the behaviour of capital market investors. Incentives may, in fact, play an important role in the 15

National Research Council (2012)

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2.1 What is the economics of sustainability?

development of macroeconomic trends through investment and the shortening of the investment horizon. Both the stock compensation of corporate managers and the way institutional investors conduct performance assessment encourage the realisation of short-term profits to the detriment of investments supporting long-term sustainable growth. “If managers’ incentives are not aligned with those of the owners’, their interests may considerably diverge. The literature on the principal-agent problem has shown that managers are interested in increasing their own power and comfort, which often acts to boost the company’s size and wealth instead of encouraging innovation. This is why managers’ incentives were tied to the performance of the given company’s shares on the stock exchange.”16 The shareholder interest approach, however, did not produce the desired results. This is mainly because managers have several tools that impact stock prices, which may, at the same time, prove detrimental to the company’s long-term profitability. Such tools include share buybacks, the dividend payment policy and the selling of company assets. “Shareholders should penalise the managers”17 who misuse these tools, “but in practice they behave as portfolio investors rather than owners, selling stocks that do not perform well in the short run and replacing them with a more profitable alternative.” Having discussed some examples of the topics to which economics should have due regard, it is worth sparing a thought on the general approach of the discipline. First, economics cannot exist in an ivory tower. The complexity of its tasks, the various connections to other disciplines and the responses to current problems demanded by broader society all call for an openness towards other disciplines. If one compares the citations of different disciplines’ flagship journals, one finds that in economics authors are much less likely to cite articles from other fields than the other way around (Table 2-1). Yet there are 16 17

Szalai, 2016. p. 4 Szalai, 2016. p. 4

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2 Where could a new evolutionary wave of economics come from?

plenty of potential connections. For example, political science could help in deciphering geopolitical situations, psychology could come in handy when making sense of decision-making or human behaviour; natural sciences could assist in quantifying the impact of economic activity on the environment; and medicine could be used to estimate the effects of ageing on productivity, to name but a few. Table 2-1: Select journals’ reliance on or connections to other disciplines Select journals' reliance on or connections to other disciplines Citing journal Citing journal

Cited journals (% of all references) Economics

Political sciences

Sociology

American Economic Review

40%

American Political Science Review

18%

American Sociological Review

22%

Note: Citations from the flagship journal to articles published in the top 25 journals in each discipline, 2000-2009. Source: Fourcade et al., 2015.

Second, focussing on sustainability and the road towards sustainable development, humility may prove to be a useful companion that could also support the aforementioned open mindset. According to economist David Colander, the gravest ethical problem of the economics profession that also contributed to the outbreak of the financial crisis is that economists fail to demonstrate sufficient humility when communicating their findings; and more should be done to stress the limitations of their results and the caveats.18 In 1927 the influential economist Lionel Robbins argued that:19 “in the present state of knowledge, the man who can claim for economic science much exactitude is a quack.” Despite the progress made in the discipline since then, this statement may not have lost its relevance. The so-called ailing queen of social sciences may therefore wish to bear this in mind. 18 19

Colander (2014) Robbins (1927)

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2.1 What is the economics of sustainability?

References Club of Rome (2016): The Queen of the social sciences is dying, available at https://www.clubofrome. org/2016/05/18/the-queen-of-the-social-sciences-is-dying/ (accessed 25 June 2019). Colander, D. (2014): Creating humble economists: a code of ethics for economists, in The Oxford Handbook of Professional Economic Ethics, Oxford University Press (2016). CORE Economics Education (2019): Escaping from imaginary worlds – update, available at https:// www.core-econ.org/escaping-from-imaginary-worlds-update/ (accessed 25 June 2019). IPCC (2013): Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. IPCC (2018): Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. In Press. Fourcade, M. – Ollion, E. – Algan, Y. (2015): The Superiority of Economists, Journal of Economic Perspectives, Vol. 29 No.1, pp 89–114. Kuznets, S. (1934): National Income 1929–1932, 73rd US Congress, 2nd session, Senate document no. 124 (7). Kuznets, S. (1962): How to judge quality, in The New Republic, 147: 16, pp. 29. Lucas, Robert E. (2003): Macroeconomic priorities, Presidential Address delivered at the American Economic Association, 4 January 2003. National Inventory Submissions (2018): United Nations Framework Convention on Climate Change. Available at: http://unfccc.int/process/transparency-and-reporting/reporting-and-reviewunder-the-convention/greenhouse-gas-inventories-annex-i-parties/national-inventorysubmissions-2018 (accessed 25 June 2019). National Research Council (2012): Aging and the macroeconomy, The National Academies Press, Washington, D.C. Piketty, T. (2013): Capital in the Twenty-First Century, The Belknap Press of Harvard University Press, Cambridge, Massachusetts. Pühringer, S. (2016): Still the queen of social sciences? ICAE Working Paper Series No 52. Raworth, K. (2017): Doughnut Economics: seven ways to think like a 21-st century economist, Chelsea Green Publishing. Robbins, L. (1927): Mr. Hawtrey on the scope of Economics, Economica 172–178. Shaikh, N. (2004), Amartya Sen: A more human theory of development, Asia Society.

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2 Where could a new evolutionary wave of economics come from? Smith, A. (1776): An inquiry into the nature and causes of the wealth of nations, Book 4. Stiglitz, J. E. (2014): Reconstructing macroeconomic theory to manage economic policy, NBER Working paper 20517. Szalai, Z. (2016): Hol maradnak a türelmes befektetők? – A globális növekedés hosszú távú kilátásai (Where are patient investors? – Long-term prospects of global growth), https://www.mnb.hu/letoltes/ szalai-zoltan-hol-maradnak-a-turelmes-befektetok.pdf United Nations (2019): Climate change, available at https://www.un.org/en/sections/issuesdepth/climate-change/ (accessed 25 June 2019). World Commission on Environment and Development (1987): Our common future, available at https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf (accessed 25 June 2019). World Income Database (2019), available at https://wid.world/world (accessed 25 June 2019).

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2.2

What can economics learn from the crisis? Balázs Vonnák – CUB-MNB Department

Many people believe that modern economics foundered with the 2007–2008 economic crisis, and this is not entirely false. At the time of the meltdown when visiting the London School of Economics Queen Elizabeth asked: “Why did nobody notice it?”. This seemingly naïve question is actually damning criticism: the fact that the experts who focus on the functioning of the economy were dumbfounded by an event of such magnitude suggests that they do not understand how the economy works. Chart 2-3: GDP per capita and recessions in the US 60,000

US$

50,000 40,000 30,000 20,000 10,000 0 1855

1875

1895

1915

1935

1955

Recessions Real GDP per capita (in 2011 US$) Source: Maddison Project Database, version 2018; NBER.

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1975

1995

2015

2 Where could a new evolutionary wave of economics come from?

However, this is not the failure of every economist and every field of the discipline but merely that of its prevailing trends. The mainstream has marginalised the representatives of the theories who would have provided an alternative to understanding economic developments. These alternative views received less publicity and were overlooked by economic policymakers. Therefore, several issues surfaced only when the crisis erupted, and economic policy had to tackle them without knowing the proper way to go about it. Which are the areas and trends that economists should have focussed on earlier? Since the whole downturn began as a financial crisis, the role of the financial system in the economy needs to be mentioned first. Although undoubtedly a great deal has been learnt about the functioning of the financial system itself (banks, capital markets etc.) over the years, the relationship between the sector and the real economy has been neglected by economists. The crisis showed, however, that banks’ irresponsible behaviour not only threatens the wealth of their owners and lenders but may also cause mass unemployment and impoverishment in the whole of society. The other important area is human behaviour. Even though several economists researching behavioural economics have received a Nobel Prize, mainstream economics still treats people as if they made optimal decisions to achieve their most preferred outcome. This view of man, called “Homo economicus”, has been refuted by many papers in behavioural economics. When making economic decisions, we do not decide rationally. Experiments have shown that we often do not know what is in fact good for us, and even if we do, we do not always decide accordingly. The claim that we are always self-interested is also false. The relationship between economic actors is often characterised by cooperation rather than competition. It has also been confirmed that besides our own well-being that of others is also important to us.

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2.2 What can economics learn from the crisis?

Economics has also failed to focus enough on social inequalities. Most economists believed that what was good for the “average” was good for everyone. It was enough to concentrate on output per capita, as that was the best measure of social welfare. However, the disparities and inequalities within society are closely related to the well-being of society as a whole and the economy’s performance. In some cases, economic development may widen social inequalities, which in turn may impede development in the long run. Chart 2-4: The global wealth pyramid 46% 39.7%

11.6%

2.7%

Note: The pyramid shows the distribution of global wealth. The area of each slice is proportional to the population share. The lower grey area, for instance, shows that the poorest 70 per cent of world’s population controls only 2.7 per cent of global wealth. The red area on the top indicates that the richest 0.7 per cent of world’s population possesses 46 per cent of global wealth. Source: Credit Suisse 2017 Global Wealth Report.

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2 Where could a new evolutionary wave of economics come from?

Moreover, the relationship between the natural environment and the economy should also be mentioned. William Nordhaus was awarded the Nobel Prize in 2018 for researching this topic, yet it hardly appeared in the mainstream. Can human economic activity be understood from the perspective of long-term sustainability if it is not considered as part of the global ecosystem? Economics has become narrow-minded not only in its approach but also in its methodology. The most striking example of this was the mathematization of the profession. While Keynes, one of the most influential economists, presented his theories mainly verbally, without using mathematical equations, in recent decades the only scientific publications that are taken seriously are those riddled with Greek letters and integral signs. Of course, mathematics can be a very useful tool for formulating or, if necessary, enhancing an economic theory, since the economy is ultimately about numbers. But it leads to no good when a tool starts to control the user. According to Nobel laureate Akerlof,20 this characterises today’s economics, therefore if young researchers need to choose between a socially important issue that is difficult to capture with mathematics or a socially less important one that can be easily formalised mathematically, they are highly likely to pick the latter. It would be useful if economists dared to use less formal tools as well (for example case studies) that may help understand major problems and developments. The above-mentioned shortcomings also define the areas to which future economists need to devote more attention. Fortunately, some progress has already been made in this regard. The relationship between the financial system and the economy as a whole has become a thoroughly researched field. The results of behavioural economics are permeating the other branches of economics. Publications about the

George A. Akerlof: “Sins of Omission and the Practice of Economics”, Journal of Economic Literature, forthcoming.

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2.2 What can economics learn from the crisis?

causes and effects of social inequalities and the natural environment are appearing with increasing frequency in major journals. But this is not enough. As shown by a recent study,21 the focus shifts very slowly, and not much has changed in research methodology, as papers are still expected to involve a fair amount of mathematics. This is probably heavily influenced by education as well as the institutional system of academic progress and publication. Textbooks still mostly present the pre-crisis “best knowledge”. The outdated mindset of economic journals continues to weigh on the decisions regarding which research results to publish, and progress depends largely on the number of publications in well-known journals. Economics undoubtedly needs to be revamped. This renewal is necessitated by the changing global economy. In the age of digitalisation, the financial system, production technologies, logistics and market research are transformed just as much as consumer habits. As enormous databases (“big data”) are available in real time and rapid analysis technologies become widespread, the production side of the economy will be able to respond to the changes in demand, as well as production and delivery conditions with unprecedented promptness. Artificial intelligence may soon take over many differentiated human activities, which may bring revolutionary changes not only in production technologies but also in research and development. Is economics ready to understand the relationships of a knowledge and information based economy and support future economic policymakers and regulators?

Aigner, E., M. Aistleitner, F. Glötzl and J. Kapeller (2018): “The Focus of Academic Economics: Before and After the Crisis”, Institute for New Economic Thinking, Working Paper No. 75.

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2 Where could a new evolutionary wave of economics come from?

References Akerlof, A. G. (2019): Sins of Omission and the Practice of Economics, Journal of Economic Literature, forthcoming. Aigner, E. – Aistleitner, M. – Glötzl, F. – Kapeller, J. (2018): The Focus of Academic Economics: Before and After the Crisis, Institute for New Economic Thinking, Working Paper No. 75.

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2.3

Measuring GDP – The origins of the problem Balázs Spéder

Today, the economics profession uses gross domestic product and several variants of it as the best-known metrics for describing economic development. However, the measurement framework developed during the manufacturing driven growth period of the 1930s needs to be revisited from time to time – in tandem with the developments in modern economies. During the last century, economies underwent a tremendous structural transformation. Therefore, measuring economic performance based on the industrial sector’s value added is being repeatedly called into question, especially in light of the digitalisation and the new industrial revolution of the 21st century. Firstly, GDP focuses on the value of production and hence measures welfare only up to a certain point. GDP does not consider other factors besides consumption that are crucial for people’s subjective well-being and happiness, most of which take place in the digital world. Secondly, this measure disregards the role of natural resources and the problem of ecological sustainability. Thirdly, GDP being condensed into a single number shows only an average standard of living, hence it fails to take into account distributional issues and thus also social sustainability. Average value added does not show how growth is realised within the individual income groups, nor its effect on the development of income inequalities. Recent years have seen numerous proposals for developing various complex indicators and the extension of the System of National Accounts, which will be discussed in detail in the chapter below.

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2 Where could a new evolutionary wave of economics come from?

What does GDP show? One of the most important issues in economics is the study of the welfare and sustainable development of countries and people, which is currently approximated by the country level development of productivity in the macroeconomics literature. The profession uses the gross domestic product (GDP), or its population-dependent variant of GDP per capita as the best-known measure of economic development. GDP shows the value of products and services for final use produced by a country in a given period, therefore it is both an indicator of countries’ output and the value and volume of the transactions. The methodology of GDP calculation was developed in the 1930s, by a working group headed by Simon Kuznets, a Ukrainian-American. During the interwar period, the growth of most advanced economies was mainly characterised by booming industrial production and the rapid expansion of construction. This was the time when the first skyscrapers were built in American metropolises and when the mass production of certain products culminated. Kuznets’ task in this economic situation was to measure the extent of the economic downturn of the Great Depression, provide a detailed description of manufacturing-driven growth and to present the production opportunities of war economies. The system of national accounts created by the working group made it possible to quantify economic output on a regular basis. In practice, the system of national accounts started measuring the production of economic sectors, industries (e.g. agriculture, industry, construction, services) and subsectors based on value added. Aggregating the value added of all sectors (households, companies, the state) on a country level, e.g. companies’ output after deducting material expenditures, gives the value added of all economic actors in a country. The measure of productivity and economic development can be obtained after dividing GDP by the number of residents or workers in the economy (Chart 2-5).

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2.3 Measuring GDP – The origins of the problem

Chart 2-5: Measures of economic development DEVELOPMENT=

size of living space

Hunter-gatherer age 70000 B.C. – 8000 B.C.

population living space

GDP capita

aka population density

aka labor productivity

Agricultural age 8000 B.C. – 1800 A.D.

Industrial age 1800 – 1980

data GDP

Digital age 1980 –

Source: Author’s work based on Growiec (2018).

The measurement of GDP has obviously undergone several improvements since the 1930s, but despite this, there remains a continuous debate among economists on the framework used for measuring economic activity. The value of the actual performance of the economy changes in tandem with the structural transformation of the economy, which requires updating the methodology. Kuznets warned about the welfare interpretation of GDP as early as in 1934, however, other aspects of measuring social welfare have become especially important in light of the distributional issues, digitalisation, robotization, the degradation of renewables and non-renewable natural resources in the 21st century. As modern economies develop, GDP is increasingly neglecting several elements of subjective well-being and sustainability, while it is embracing numerous activities the positive impact of which on welfare is rather questionable. Nonetheless, GDP remains the most widely accepted measure of economic performance, as it compresses “all” important, visible factors into a single figure for the general public, and it is readily comprehensible for a wide range of people due to its universal, easy-to-understand nature. Collecting data optimised for the national accounts remains the most comprehensive approach to — 33 —

2 Where could a new evolutionary wave of economics come from?

a country’s economic performance, even though it is struggling to keep up with the continuous economic development.

Does GDP equal welfare? Yet GDP is coming in for increasing levels of criticism because it misses the ever-changing factors of subjective happiness and well-being due to the structural transformation of economies. The subjective wellbeing of individuals is not exclusively dependent on the productivity of their country. If the production of arms manufacturing companies grows, then worker’s wages and GDP will both increase, even though the prospect of a potential war negatively influences the well-being of every person. Pollution, the depletion of natural resources, the role of leisure time spent with family and friends and the significance of high-quality education and healthcare - these are all factors that materially affect people’s welfare.22 Using Maslow’s (1943) approach, a hierarchy of needs pyramid of GDP can be illustrated. As a result of the calculation methodology of GDP which focuses on the value of production and economic transactions, GDP can measure welfare only up to a certain level in the hierarchy. Hence it does not consider a number of things that are important from the perspective of people’s subjective well-being and sense of happiness (Chart 2-6).

The critique of GDP as the measure of welfare is clustered around three major issues, on which an excellent general summary can be found in the report of 2009 by Stiglitz et al. and Jorgenson (2018).

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2.3 Measuring GDP – The origins of the problem

Chart 2-6: Interpretation of GDP in Maslow’s hierarchy of needs

Available, clean natural resources

SELF-REALIZATION Free time

Learning possibilities

RECOGNITION

Art, entertainment

SOCIAL NEEDS

Savings industrial products, job opportunities food, clean water, public utilities, housing

SECURITY

GDP

? GDP



PHYSIOLOGICAL NEEDS

Source: Authors’ own compilation.

The data approximating production does not include people’s social needs, the welfare effects of entertainment and leisure opportunities, access to information and digital assets, the importance of health or the effects of acknowledgement and education on welfare.

What else influences people’s subjective well-being? Easterlin (1974) was the first to point out that the relationship between GDP per capita and happiness shows a positive correlation only up to a certain point, while individuals’ happiness does not increase after a given income level (Chart 2-7).

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2 Where could a new evolutionary wave of economics come from?

Chart 2-7: Relationship between the happiness index, infant mortality and GDP per capita

World Happiness Indext

% of world population

Infant mortality (below 5) 140

100

Hungary

120

50,000

100,000

0 150,000

GDP per capita (USD,PPP)

20 0

50,000

100,000 150,000

GDP per capita (USD,PPP)

Population (right-hand scale) Source: Author’s work based on WDI and World Happiness Report.

The profession has suggested numerous answers for this paradox; however, it still exists today despite the past 50 years. One reason for this could be that in the case of high- and low-income countries different things bring happiness and result in well-being. The services sector plays a huge role in the advanced economies and comprises a wide range of activities, therefore observing the output and the prices of the sector is much harder than, for example, in the case of manufactured goods. Due to the variety within the sector, a basic unit of services cannot be clearly defined either. Moreover, in the developed economies most leisure time is spent in digital space (experiencebased economy), hence as national accounts reflect only a distorted picture of the digital services, GDP can capture only a small portion of the benefits brought. Thus, GDP can be considered less and less an adequate indicator of individual well-being in a country.

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2.3 Measuring GDP – The origins of the problem

The welfare-adjusted GDP by Jones and Klenow (2016) attempts to aggregate several variables influencing subjective well-being. The aggregate “Welfare” measure calculates not just income, but also integrates the role of consumption, leisure time, inequality and life expectancy into an individual utility calculation. Based on the derived macro-level consumption-equivalent Welfare (which is a specially adjusted GDP per capita), Western Europe and the United States are much closer to each other in terms of their level of development than evidenced by national accounts statistics (Chart 2-8). According to national accounts data, most Western European countries barely reach 70 per cent of the American level of development, while according to this welfare indicator, they are around 85–90 per cent of the US, mainly due to longer expected lifetime, lower mortality rates and a happier life stemming from more leisure time. In line with this, the welfare of the less advanced Asian and African countries is even lower than suggested by national accounts data, owing to lower life expectancy and significant inequalities. Chart 2-8: Relationship between GDP per capita and Welfare

Welfare / Per capita GDP

1.5 GDP is underestimating Welfare

GDP is overestimating Welfare

0.5

1/64

1/32

1/16

1/8

1/4

1/2

Per capita GDP (United States = 1) Source: Author’s illustration based on Jones and Klenow (2016, p.2451).

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2 Where could a new evolutionary wave of economics come from?

Jones (2016) analyses the effect of healthcare innovations on welfare by substituting in the importance of human life for consumption within the standard economic framework. If people can choose the value of life instead of consumption, the utility of consumption quickly becomes negligible, therefore the validity of official statistics is also questionable in measuring peopleâ&#x20AC;&#x2122;s welfare. Income and consumption surveys measuring well-being have important additional information for poorer populations, including less developed countries, as described by Deaton (2005) extensively. These surveys estimate the income, the wealth and the consumption levels to be much lower than in the national account figures, hence implying an even higher degree of underdevelopment in poorer regions. This is partially due to a much lower willingness to participate in surveys in poorer countries than in richer ones, and while GDP collects data on production, surveys do so on the actual welfare of the public, which, however, may include major distortions on the account of its subjectivity.

How should we treat our natural environment? The inclusion of the environment in economic models is a complex process, since ecology is not only a factor of production but a framework for growth as well. However, the generally accepted measure of economic development today does not quantify the role of the environment and natural resources, employing it as neither a factor of production nor a framework. GDP disregards the issue of ecological sustainability, which is a highly underrated but an important part of welfare. What is more, the national accounts interpret the negative externalities of pollution as positive value added. One only needs to think of the oil production of a factory, which is represented as positive value added in statistics, even if the availability of natural resources declines in the long run. Similarly, reconstruction after a negative environmental shock, such as an earthquake or a flood, may be recorded as huge â&#x20AC;&#x201D; 38 â&#x20AC;&#x201D;

2.3 Measuring GDP – The origins of the problem

positive value added, even though the long-term carrying capacity of the Earth is severely damaged. Therefore, according to environmental economics, the national accounts-based GDP currently in use cannot properly measure development, since the framework does not include the environment in which we live. Environmental economics approximates the role of the ecology around us based on the theories of the recent Nobel laureate of 2018, namely William Nordhaus (1974, 1977). Samuelson and Nordhaus (1992) proposed an alternative measure of Net Economic Welfare, instead of the gross national product, which mainly summed up consumption and investment contributing to national welfare, then deducted the social costs of pollution, traffic congestion and crime. Their proposal did not become widespread but significantly contributed to the fact that ecological factors became widespread in mainstream thinking. Environmental factors can be integrated into the national accounts framework by deducting the items that contribute negatively to them (Mäler 1991). A similar proposal was made by Okafor (2012) in connection with non-renewables, for example oil production. Obst et al. (2016) show a practical solution for this based on the use of the System of Environmental-Economic Accounting (SEEA), where the environment appears as a sort of capital investment in the future alongside capital of merely economic significance (physical and human capital). Using UN data, the SEEA takes into account environmental economic considerations and integrates several issues into the System of National Accounts, namely the carrying capacity of the biosphere, the condition and use of natural resources, emissions and waste, the possibility of environmental disasters and natural crises, the development of energy crises, the interaction between nature and humans and environmental commitment. The system that assigns volumes and prices to the final figures adjusted for degradation and depletion is a complex extension of GDP, and the first international results are expected to be published in 2019–2020.

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2 Where could a new evolutionary wave of economics come from?

How is growth distributed across social groups? Crucial questions of economic development include which income groups and to what extent they benefit from growth, as well as how it impacts inequalities and thus social sustainability. GDP growth and GDP per capita condensed into a single figure show only an average standard of living, without taking into account the issues of distribution and thus also social sustainability. This is because the average value added does not appropriately represent how growth is realised in the individual income groups or what effect it has on income inequality. To supplement this and characterise the developments linked to income distribution, the literature mainly uses indicators based on surveys and micro data, such as the number of people living on less than 60 per cent of the median income or the number of those living in extreme material deprivation. The latest studies have developed several indicators, including the questionnaire-based median welfare growth and the System of National Accounts extended with income-distribution. The aim of the Distributional National Accounts (DINA) is to quantify not only an average personâ&#x20AC;&#x2122;s income growth but also the net real income growth in various social groups. Therefore, the distributional system links the macro-level growth path to the development of inequalities at the micro level. The macro data provides growth rates consistent with the System of National Accounts, while the same figure is derived bottom up as well by aggregating individual income and taxation micro data and surveys for the various income groups and so for society as a whole. The ground-breaking study by Piketty et al. (2018) estimated the distribution of the economic growth in the United States by income percentile for the period from 1980 to 2014. The distribution of growth benefits across social groups provides a comprehensive picture about the beneficiaries of development. Furthermore, the authors focus on net real income instead of production, thereby acquiring information about income inequality as well. According to their findings, there are

â&#x20AC;&#x201D; 40 â&#x20AC;&#x201D;

2.3 Measuring GDP – The origins of the problem

major differences in the distribution of growth across social groups: although per capita income increased by 60 per cent in this period, there was no substantial income growth in the lower 50 per cent of society during this 34-year period, despite the favourable GDP figures, whereas in the 50th–90th percentile income was up by 40 per cent. And the income of the top 1 per cent skyrocketed (Chart 2-9).

Per cent

Per cent Top 0.001%

P99.99

P99.9

P99

Average adult

Post-tax Pre-tax

100

1 5

Real average annual growth, 1 80 2014

Chart 2-9: Distribution of average annual income growth in the United States by percentile, 1980–2014

Income percentile Source: Piketty, Saez and Zucman (2018, p. 579).

The drawback of the Distributional System of National Accounts is that its calculation is extremely data-intensive and time-consuming, therefore besides the United States the only detailed analysis was made for France (Barbinti et al. 2018). In their latest study, Blanchet et al. (2019) provide an analysis for the whole of Europe based on the simplified accounts. According to their findings, although growth is distributed unevenly across Europe, it is much more balanced than in the United States.

— 41 —

2 Where could a new evolutionary wave of economics come from?

What do composite indicators show? Social sciences have developed several sub-indicators for capturing economic development and welfare in recent decades, which principally aim to describe important but partial issues more accurately. Table 2-2: Rankings of GDP and some composite indices in the first 15 countries and Hungary Ranking

GDP per capita (PPP)

Human Development Index

Inclusive Development Index

World Happiness Report

Qatar

Norway

Finland

Luxembourg

Switzerland

Iceland

Norway

Singapore

Australia

Luxembourg

Denmark

Brunei

Ireland

Switzerland

Iceland

Ireland

Germany

Denmark

Switzerland

Norway

Iceland

Sweden

Netherlands

United Arab Emirates

Hong Kong

Netherlands

Canada

Kuwait

Sweden

Ireland

New Zealand

Switzerland

Singapore

Australia

Sweden

Hong Kong

Netherlands

Austria

Australia

United States

Denmark

Finland

Israel

Netherlands

Canada

Germany

Austria

Saudi Arabia

United States

New Zealand

Costa Rica

Iceland

United Kingdom

Belgium

Ireland

Sweden

Finland

Czech Republic

Germany

Hungary

44.

45.

32.

69.

Source: IMF (2019), Human Development Index (2018), Inclusive Development Index (2018), World Happiness Report (2019).

Among the composite indicators aggregated from various variables, the Human Development Index weights life expectancy, literacy, education and the standard of living, while the Inclusive Development Index weights intergenerational sustainability, with inclusion and the World Happiness Index quantifying people’s happiness, and all of them focus — 42 —

2.3 Measuring GDP – The origins of the problem

on the comparability of the countries. There are substantial differences in the list of the top 15 countries when ranked according to GDP or some composite indicators (Table 2-2). Other interesting measures designed to help the development of less advanced countries include the Human Opportunity Index, which quantifies the opportunities of social advancement and the distribution of equal opportunities as well as the Inclusive Green Growth Index ,which focuses on environmental sustainability.

Statistical measurement problems The limits of interpretation and global comparability of GDP as the single accepted development indicator are exacerbated by several other issues. One potential problem is the instability of statistical reporting. As the complexity of economies has increased, the calculation methodology of national accounts has become so extensive that statistical offices often revise the growth rate of several previous years for not only the subsectors but also the economy as a whole. So whatever is known about the economy at a given moment might become very different two years later. The assessment of a near-zero growth may be especially problematic: weak positive growth may be revised to negative growth or contraction a few years later, and the opposite is also possible. Based on a country’s GDP, can it be determined whether it is good to live there? GDP as the measure of a country’s economic development may mask several regional heterogeneities, as life is completely different in the centre of the capital than on a small farm without any utilities. There are significant differences between Milan and southern Italy but also between Budapest and Nógrád County. The standard of living might be much better in certain northern Italian villages than in some East German states.

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2 Where could a new evolutionary wave of economics come from?

The methodology of calculating GDP cannot address the quality differences between products and services, as the quality of work appears only indirectly through workers’ wages. GDP cannot differentiate between a world champion hairdresser and a haircut in the back of a small shop, nor can it do so between two buildings built using concrete of two different qualities, even though it is possible that in the case of the lower-quality house the cement may have been replaced by sand but the material costs amount to the same due to invoicing procedures. Similarly, GDP cannot measure the quality of healthcare services, medical coverage, the waiting times in hospitals, the cleanliness of the rooms and the equipment in the operating theatres. The quality of the curriculum cannot be quantified, and nor can whether pupils leave school with useful knowledge under their belts. Numerous pointless construction projects and large investments are part of GDP, irrespective of whether they generate returns or not. A good example of this is the construction of Chinese ghost cities, teeming with skyscrapers. In a similar fashion, the repairs after poorly done work increase countries’ GDP, therefore the newly implemented street lighting and the repeated road works are reflected several times in GDP, although repairs are often necessitated because the work was not up to scratch in the first place. Yet all is recorded as positive value added in the national accounts. Another distortive factor may be that GDP does not include household chores and bringing up children, which are traditionally performed by women. However, if people look after a neighbour’s child instead of their own, it is considered economic activity and thus represented in the System of National Accounts. Likewise, work at home is not part of GDP either, and this also raises problems due to its widespread nature in the 21st century.

— 44 —

2.3 Measuring GDP – The origins of the problem

The measurement and global comparability issues of GDP may be exacerbated by the fact that in developing and less developed countries the system of surveys is unreliable, statistical capacities are underdeveloped and the shadow economy is large. The transactions arising from illegal activities, the sales of stolen goods and the price of services that are not invoiced do not appear in the system of accounts. To tackle this, Henderson et al. (2012) and Pinkovskiy and Sala-i-Martin (2016) developed a growth indicator based on high-resolution nighttime satellite images. In less developed countries, night-time lights can be used to approximate economic activity: night-time satellite images clearly show construction activity and the operating industrial facilities, whereas the economic activity of more advanced countries is reflected less in night-time lights, such as the operation of the services sector or technological innovations (Chart 2-10). By optimally weighting national accounts GDP growth and the observed night-time lights, it has been found that in the less developed countries of the world, actual average growth may vary from the annual growth rate published by the World Bank by 2–3 percentage points, i.e. half of the actual growth on average. Chart 2-10: The lights of India on satellite images from outer space in 1994 and in 2010

Source: Pinkovskiy and Sala-i-Martin (2016).

— 45 —

2 Where could a new evolutionary wave of economics come from?

Technology: Ways to measure the digital economy Recent decades have seen a dramatic change in how people use their leisure time as well as their corresponding consumption habits. While 20 years ago people spent hours planning their family holiday and adding up the kilometres on paper-based maps, today this is done for us in seconds by online maps. The reading of traditional newspapers has been replaced by browsing online news portals, cassette players were supplanted by the CD and the Discman, then CD/DVD purchases were made obsolete by streaming media content from sites such as YouTube or Spotify. The emergence of new forms of consumption is also demonstrated by the hundreds of thousands of messages sent on social media every minute. Due to the newly emerging industries, forms of services and ways of entertainment, GDP is increasingly criticised for not properly measuring the factors that bring people happiness. Economies have undergone a major structural transformation since the 1940s. The proportion of agriculture within output has declined in tandem with economic development, and the significance of industry has considerably diminished in most advanced countries, following an inverted “U” shape. The services sector has played an increasingly central role in economic activity on the growth path of modern economies, while digital space and the world of information have considerably expanded. Total internet traffic has been skyrocketing in recent decades. While in 1992 the daily traffic on the global network of the internet amounted to 100 gigabytes, this had risen to 100 gigabytes per second by 2002, and by 2014, it had exceeded 16 thousand gigabytes per second. The growth of online data traffic epitomises how digital content has taken the place of traditional content in modern economies (Chart 2-11).

— 46 —

2.3 Measuring GDP – The origins of the problem

Chart 2-11: Developments in global GDP and global internet use between 1700 and 2018 120

Trillion USD

Exabyte / month

180

100

150

120

0 1700

0 1750

1800

1850

World GDP (left axis)

1900

1950

2000

Total internet use (right axis)

Source: Author’s calculations based on IMF, World Bank and University of Michigan.

In tandem with the expansion of online traffic, the prices of products and services related to digitalisation have continuously fallen in the past two years, and in most cases they have become completely free (Kurzweil 2005). Most of people’s leisure time is spent in the free, digital world, which, however, is completely missing from the national accounts. Brynjolfsson et al. (2019) have developed a new measure called GDP-B, which measures not only output but also benefits by quantifying and aggregating the consumer surplus. Brynjolfsson et al. sought to find out the value people attribute to the free digital services they use (Table 2-3). With an iterative process, respondents are asked to choose between two goods and decide which

— 47 —

2 Where could a new evolutionary wave of economics come from?

they would give up for a month and how much they would pay for not giving up the other. By doing this for all pairs, a ranking of goods can be derived, which can be coupled with consumers’ subjective assessment. For example, the median consumer would forego using Facebook for 48 dollars a month, and based on the alternative GDP measure expanded with Facebook use, the gross national product of the United States would be higher by 0.05–0.11 percentage points than in 2004. Table 2-3: Consumer surplus stemming from free digital goods in the USA Digital product

2016 (USD)

2017 (USD)

Online search engines (e.g. Google)

14,760

17,530

E-mail

6,139

8,414

Digital maps

2,693

3,648

Online videos

991

1,173

E-commerce

634

842

Social media

205

322

Online stores

135

155

Music

140

168

Total

25,697

32,252

59.1

72.3

As a percentage of households’ disposable income

Note: Question: How much money would you wish to be paid yearly for giving up the following services? Source: Author’s illustration based on Brynjolfsson, Collis and Eggers (2019).

However, the experiment not only lends us a more accurate measure for gauging the utility of digital services, since this alternative GDP quantifying the benefits of digital technology provides more information to both the government and policy-makers. Moreover, it makes it clearer what has additional value for society, which may even alter governments’ approach during investments in community developments and infrastructure.

— 48 —

2.3 Measuring GDP – The origins of the problem

Another challenge is posed by the quantification of the sharing economy in national accounts, which industry is unfolding rapidly as the digital world is proliferating (MNB 2017). Although the problem is not new, as unregistered taxis and unreported letting existed in the past, these were adjusted for by statistical offices through estimates. However, modern economies shift generally from ownership towards renting, as the Internet, smartphones and digital technologies become widespread. As the line between leisure time and work is rather blurred, the question arises, which services are part of GDP and which are not. Moreover, the extent of services’ and prices are also unknown. Therefore, it is extremely difficult to include the sharing economy in the national statistics, which have grown enormously in the past few years. Although numerous new indicators have been developed in recent decades, economics has not produced one generally accepted variable measuring tool for everything. Perhaps one can get the most accurate picture by, besides observing several sub-indicators, taking a rather more unusual approach, by looking at Bhutan, one of the world’s poorest countries. Its official welfare “measure” has been the Gross National Happiness since 1971. This is because the happiness value is actually a way of life or lifestyle, focusing on how one should and can live in the world. A happy, sustainable, fair and equitable life is just as important as output and consumption. Precisely because of this, one could and should use several indicators besides GDP, since economic development should not only be as strong as possible, but should also mean a better life for many people.

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2 Where could a new evolutionary wave of economics come from?

References Blanchet, T., Chancel, L., & Gethin, A. (2019). How unequal is Europe? Evidence from distributional national accounts. WID. world Working Paper, 6. Brynjolfsson, E., Collis, A., & Eggers, F. (2019). Using massive online choice experiments to measure changes in well-being. Proceedings of the National Academy of Sciences, 116(15), 7250–7255. Brynjolfsson, E., & Saunders, A. (2009). What the GDP gets wrong (why managers should care). MIT Sloan Management Review, 51(1), 95. Brynjolfsson, E., Collis, A., Diewert, W. E., Eggers, F., & Fox, K. J. (2019). GDP-B: Accounting for the Value of New and Free Goods in the Digital Economy. NBER Working Paper, No. 25695. Deaton, A. (2005). Measuring Poverty in a Growing World (or Measuring Growth in a Poor World). Review of Economics and Statistics, 87(1), 1–19. Easterlin, R. A. (1974). Does economic growth improve the human lot? Some empirical evidence. In: Nations and households in economic growth (pp. 89–125). Academic Press. Easterlin, R. A. (1995). Will raising the incomes of all increase the happiness of all? Journal of Economic Behavior & Organization, 27(1), 35–47. Garbinti, B., Goupille-Lebret, J., & Piketty, T. (2018). Income inequality in France, 1900–2014: Evidence from Distributional National Accounts (DINA). Journal of Public Economics, 162, 63–77. Growiec, J. (2018). The Digital Era, Viewed From a Perspective of Millennia of Economic Growth. Collegium of Economic Analysis SGH-KAE Working Papers, 34. Henderson, J. V., Storeygard, A., & Weil, D. N. (2012). Measuring Economic Growth from Outer Space. American Economic Review, 102(2), 994–1028. Jones, C. I. (2016). Life and Growth. Journal of Political Economy, 124(2), 539–578. Jorgenson, D. W. (2018). Production and Welfare: Progress in Economic Measurement. Journal of Economic Literature, 56(3), 867–919. Kurzweil, R. (2005). The singularity is near: When humans transcend biology. Penguin. Mäler, K. G. (1991). National Accounts and Environmental Resources. Environmental and Resource Economics, 1(1), 1–15. Maslow, A.H. (1943). A theory of human motivation. Psychological Review. 50 (4), 370–396. MNB (2017). Growth Report 2017. Magyar Nemzeti Bank, Budapest. Nordhaus, W. D. (1974). Resources as a Constraint on Growth. American Economic Review, 64(2), 22–26. Nordhaus, W. D. (1977). Economic Growth and Climate: the Carbon Dioxide Problem. American Economic Review, 67(1), 341–346.

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2.3 Measuring GDP – The origins of the problem Obst, C., Hein, L., & Edens, B. (2016). National Accounting and the Valuation of Ecosystem Assets and Their Services. Environmental and Resource Economics, 64(1), 1–23. Okafor, T. (2012). Natural resources accounting and sustainable development: The challenge to economics and accounting profession. African Research Review, 6(3), 59–70. Oulton, N. (2012). Hooray for GDP!, CEP Occasional Paper, 30. Piketty, T., Saez, E., & Zucman, G. (2017). Distributional National Accounts: Methods and Estimates for the United States. The Quarterly Journal of Economics, 133(2), 553–609. Pinkovskiy, M., & Sala-i-Martin, X. (2016). Lights, Camera… Income! Illuminating the National Accounts-Household Surveys Debate. The Quarterly Journal of Economics, 131(2), 579–631. Samuelson, P. A., & Nordhaus, W. D. (1992). Economics. McGraw-Hill. Stiglitz, J. E., Sen, A. & Fitoussi, J.-P. (Eds.) (2009). Report by the commission on the measurement of economic performance and social progress. Paris: European Commission.

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5 challenges of the future

3.1

Ecological consequences of economic growth Gábor Gyura

The essence of the challenge that goes hand in hand with economic and social development is perhaps best captured by the concept of the Great Acceleration, which showed that in the period since industrialisation, also referred to as Anthropocene, the human population, economic activity and the corresponding demand for resources have increased exponentially, even though natural resources are finite. This obviously calls into question the sustainability of the earlier (traditional) growth models and paths. The depletion of natural resources in tandem with overpopulation could lead to anomalies coupled with new technological challenges, simultaneously causing and effecting geopolitical conflicts and efforts. Of course, this calls for the rethinking of the functions and forms of the money and financial system that are the “lifeblood” of the economy and society. The negative externalities entailed by growth, pollution and the exhaustion of natural resources have been recognised problems for decades, but their urgency has become obvious to a wide range of people only in recent years. While comprehensive analyses were made in the 1960s on the issues of environmental sustainability (for example the seminal book, The Limits to Growth), action was hampered by political considerations as well as by measurement and forecasting uncertainties. Another factor that may have hindered decisive environmental action was technological progress and the belief in the environmental Kuznets curve (Chart 3-1). In other words, many considered it realistic and highly rational to assume that economic growth entailed an increasing — 55 —

3 5 challenges of the future

Chart 3-1: Environmental Kuznets curve

Source: Authors’ own compilation based on Panayotou (1993).

environmental impact only in the beginning, and after a turning point, the ecological impact would diminish thanks to the structural change in the economy and more advanced technologies. However, in reality the latter happened only partly (Stern 2004; Van Alstine-Neumayer 2010).

How serious is the problem? As countries’ economies expanded, they increasingly exploited natural resources, which was reflected in their growing ecological footprint deficit. National economies, and then, starting in the 1970s, every the country in the world, increasingly used more natural resources for consumption and absorbing their pollution and waste than their biocapacity (the amount which their grazing land, forests, waters and built-up land can regenerate each year). For example Japan uses more than seven times its biocapacity, but most countries with the top GDP figures have a value between two and five. The ecological deficit of Earth as a whole is 1.75, so almost two Earths would be necessary to maintain the current consumption levels (Global Footprint Network 2019) (Chart 3-2). — 56 —

3.1 Ecological consequences of economic growth

Chart 3-2: Ecological footprint deficit of certain countries a and the world

Note: The chart shows how many times countries use up their biocapacity. Source: Global Footprint Network (2019).

Although the ecological footprint is also a widely accepted concept, as time has passed and ecological problems have become greater and greater, there have been increasing calls for a highly accurate assessment officially accepted by governments. One of the most important assessments was the UN Millennium Ecosystem Assessment programme, which sought to provide a picture about Earth’s natural capital and its ability to sustain future generations, in other words ecosystem services, through a four-year analysis process. The assessment pointed out that in previous decades 15 out of the 24 ecosystem services had been severely degraded, and in three areas (species’ extinction rates, the breaking of the nitrogen cycle and greenhouse gas emissions responsible for climate change) humanity had already gone beyond the limits of the Earth’s biological carrying capacity (Board of the Millennium Ecosystem Assessment 2005).

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3 5 challenges of the future

Where are we now? Another recent influential comprehensive assessment was made with a similar approach by the researchers of the Resilience Centre at Stockholm University. They argue that out of the nine basic ecosystem services, four have been exploited by humanity to such an extent that a critical threshold of safe human existence has been crossed. These services are climate change (greenhouse gas emissions), biosphere integrity (a concept similar to the reduction of the diversity of species or biodiversity loss) and land use (erosion of forests and croplands) as well as phosphorus and nitrogen cycles (Steffen et. al 2015) (Chart 3-3). Chart 3-3: Limits of safe human existence

Source: Steffen et. al (2015).

One of the crucial messages of these comprehensive assessments is that human activities have become the most important and strongest factor determining the physical, chemical and biological reality of Earth. The bottom line of the concept referred to as the Great Acceleration is that â&#x20AC;&#x201D; 58 â&#x20AC;&#x201D;

3.1 Ecological consequences of economic growth

humanity has basically become the most important geological factor in a generation, and the almost exponential growth of the population and the economy essentially goes hand in hand with excessive greenhouse gas emissions, the increasing acidification of the oceans, the shrinking of forested areas and biodiversity loss (Steffen et al. 2015b) (Chart 3-4). Chart 3-4: The Great Acceleration: Impact of human activities on the natural environment

Source: based on Steffen et al. (2015b).

â&#x20AC;&#x201D; 59 â&#x20AC;&#x201D;

3 5 challenges of the future

What common ecological goals can be defined in light of the problems? The scientifically increasingly sound and alarming ecological assessments have expedited the international intergovernmental negotiations under the auspices of the UN with respect to concerted action. One of the greatest milestones was the Rio+20 UN conference in 2012, which led to the adoption of the world’s Sustainable Development Framework in 2015. The latter set out a sustainability programme for after 2015, with the main pillars of balanced social development, sustained economic growth and environmental protection, and it covers both developing and advanced countries. The document called “Agenda 2030” not only aims to preserve the ecosystem, as the UN General Assembly also determined very concrete goals (Sustainable Development Goals) for social objectives, such as eliminating poverty UN General Assembly (2015). The Agenda 2030 contains 17 goals and 169 associated targets. From the perspective of environmental protection, one should perhaps highlight the action to combat climate change, the protection of the oceans and seas as well as terrestrial ecosystems. It should be borne in mind, however, that the goals reflect a holistic approach, aiming to tackle environmental and social needs at the same time (e.g. clean water and basic sanitation, affordable and clean energy, sustainable cities and communities), but even the seemingly purely social goals take into account the requirements of environmental sustainability. The strength of the Agenda 2030 is that it not only sets general goals but also endeavours to make the progress towards these aims measurable. Related to the document, 232 indicators were created that enable the progress made on the road towards sustainable development to be monitored and analysed. The ecological indicators do not present a promising picture of the achievement of the sustainability goals. For

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3.1 Ecological consequences of economic growth

example, one of the most important indicators, the Red List Index linked to Development Goal 15 (Protect, restore and promote sustainable use of terrestrial ecosystems), shows that species are going extinct at an accelerating rate (Chart 3-5). Chart 3-5: Red List Index of species survival, 1993–2019, and projections for 2020–2030 0.85

0.85

0.80

0.75

Upp

onfi

Low

0.70

0.65 1993

0.75

er c

2000

2007

2014

den

con

2021

fide

ce b

oun

nce

0.70

bou

2028

0.65

Source: UN (2019).

References Board of the Millennium Ecosystem Assessment (2005): Living Beyond Our Means: Natural Assets and Human Well-being. Internet source: www.millenniumassessment.org. Last download time: 18 March 2016. UN General Assembly (2015) (2015): Transforming our world: the 2030 Agenda for Sustainable Development. UN General Assembly decision of 25 September 2015. (A/RES/70/1). Internet source: www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E. Last download time: 30 January 2016. Ministry of Foreign Affairs and Trade (s.a.): A 2030 fenntartható fejlődési keretrendszer – Agenda 2030. Availability: https://nefe.kormany.hu/agenda2030. Download time: 2019.07.05.

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3 5 challenges of the future Panayotou, T. (1993): Empirical tests and policy analysis of environmental degradation at different stages of economic development. World Employment Programme Research Working Paper WEP222/WP 238 STEFFEN et al. (2015): Planetary boundaries: Guiding human development on a changing plane. Science, 2015. February 13; Vol. 347, Issue 6223, DOI: 10.1126/science.1259855 Steffen et al. (2015b): The trajectory of the Anthropocene: The Great Acceleration. Anthropocene Review, 15 January 2015. Stern, D. (2004): The Rise and Fall of the Environmental Kuznets Curve. World Development Vol. 32, No. 8, pp. 1419–1439, 2004. Van Alstine-Neumayer (2010): The Environmental Kuznets Curve. In: Gallagher, Kevin P., (ed.) Handbook on Trade and the Environment. Elgar original reference. Edward Elgar, Cheltenham, UK, pp. 49-59. ISBN 9781847204547. UN (2019): The Sustainable Development Goals Report 2019. Internet source: https://unstats.un.org/ sdgs/report/2019/. Retrieved: 2019.07.24.

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3.2

Demographic challenges: how long and how large the world’s population will grow? Emese Kreiszné Hudák – Géza Rippel

The world’s population may further increase in the coming decades, but divergent trends are expected on different continents. Global population was 2.5 billion in 1950, it had tripled by 2015, and it may be close to 10 billion in 2050. However, population growth rate may decelerate in the next decades: while between 2010 and 2015 the population grew by 1.2 per cent on average annually, the average annual population growth rate may fall below 1 per cent in the first half of the 2020s and to around half a per cent in the second half of the 2040s (UN 2019a). In the decades ahead, population may continue to grow on every continent except for Europe.23

What divergent trends can characterise the world’s population developments in the coming decades? The population is forecast to grow the most dynamically in Africa. Between 2015 and 2050, Africa’s population may expand from 1.2 billion to 2.5 billion, thereby increasing the share of Africa’s population within the world’s total population from 16 to 26 per cent (Chart 3-6). Nevertheless, Asia will continue to be the continent with the largest population in the coming decades, as its population is set to increase 23

In this subchapter, we present the expected development of global demographic trends until 2050, based on the results of the 2019 UN Population Prospects (UN 2019a).

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3 5 challenges of the future

from 4.4 billion in 2015 to 5.3 billion. India and China may remain the most populous countries in the world, with a combined population of over 3 billion in 2050. Chart 3-6: Development of world population size and its distribution across regions (per cent) 2050

2015 9

7 26

1950 7 7 22 9

55 2.5 billion people

7.4 billion people

Europe Asia Northern America

9.7 billion people

Africa Latin America and the Caribbean Oceania

Source: UN (2019a).

In the decades ahead, Europe may be the only continent with a shrinking population. Within the global population, Europe’s share was 22 per cent in 1950, it had decreased to 10 per cent by 2015, and it may shrink further to 7 per cent by 2050. Europe’s population may decrease from 743 million in 2015 to 710 million in 2050, due to the low fertility rate. One of the greatest challenges of the global economy is population ageing, caused by declining total fertility rates and expanding life expectancy. The number and population share of those aged 60 and over is expected to increase in all regions in the coming decades. The number of those aged 60 and over may increase at an unprecedented rate from 900 million in 2015 to 2 billion in 2050 (Chart 3-7). Their group may grow faster than any younger cohorts (UN 2019b).

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3.2 Demographic challenges: how long and how large the world’s population will grow?

Chart 3-7: Number of those aged 60 and over in different regions of the world, 1950–2050 2,250

Million persons

+247%

1,750 1,500

+152%

1,250

1,750 1,500 1,250 1,000

1,000

750

750 500

2050

2045

2035

2030

2025

2020

2015

2010

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

Europe Northern America Latin America and the Caribbean

2040

+168% +64% +41%

250 0

2,250 2,000

2,000

500 250 0

Oceania Asia Africa

Note: Values denoted by percentage change in the chart show the increase in the number of persons aged 60 and over between 2015 and 2050 on the different continents. Source: UN (2019a).

An ageing population may entail a rise in the ratio of the old and the younger generations and thus, ceteris paribus, a growing burden on the economically active population. The old-age dependency ratio is the ratio of those aged 65 and older to the working-age population (age 15–64).24 It may double in the world between 2015 and 2050, increasing from 13 to 25 per cent (Chart 3-8). This means that while in 2015 there were 14 elderly persons for every 100 persons of working age, in 2050 there will be 25.

As the old-age retirement age will approximate 65 years in even more countries in the coming period, when examining the long-run development of the old-age dependency ratio, the elderly population means those aged 65 and over.

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3 5 challenges of the future

There are significant differences across the countries of the world in terms of old-age dependency ratio. In Europe, there were 26 elderly for every 100 persons of working-age in 2015 (so 4 working-age people for 1 old), in 2050 there will be 49 elderly for every 100 working-age people (2 people of working age people caring for 1 old person). Similarly, Japan may see an especially steep rise in the ratio of the elderly to the working-age population, albeit from a higher initial value, experiencing an increase from 43 to 74 per cent between 2015 and 2050. The old-age dependency ratio may continue to be the lowest in African countries, due to the considerably expanding size of the working-age population in the coming decades. Chart 3-8: Old-age dependency ratio in the different regions of the world in 2015 and 2050 (per cent)

2015

2050

37 30

Europe

North-America

Latin-America and the Caribbean

Oceania

Asia

World

Africa

Note: The old-age dependency ratio is the ratio of those aged 65 and older to the working-age population (15â&#x20AC;&#x201C;64 years). Source: UN (2019a).

Demographic changes may have significant economic consequences in both advanced and less advanced regions, increasing the environmental impact, transforming the labour market, affecting labour productivity, changing consumption and savings rates, influencing income distribution and changing the structure of production. At the same â&#x20AC;&#x201D; 66 â&#x20AC;&#x201D;

3.2 Demographic challenges: how long and how large the world’s population will grow?

time, in the long run, an ageing population poses challenges to public pension systems and healthcare systems.

How did inequalities develop in the past period? Income inequalities:

In the past century, the world’s population increased 4.5-fold, though the social consequences of this and the distribution of global assets should be examined properly. The share of those living in poverty has continuously decreased since 1900. The proportion of people living on less than USD 1.9 a day (at purchasing power parity) was over 75 per cent in the early 20th century, but it diminished to below 10 per cent by 2015 (Roser – Ortiz-Ospina 2019). In parallel with the rise in national median income, an increasing number of people were over the absolute poverty threshold in recent decades, however, falling poverty does not necessarily mean a more equitable society. The growth in income has not been equal across national economies (between country inequalities) and social groups (within country inequalities). Inequalities can be measured in different ways25, but Niño-Zarazúa et al. (2017) found that between 1975 and 2010 the global relative Gini declined, therefore overall median incomes converged across countries. Until 1980, poverty declined in parallel with the decreasing share of the top income decile from national income, but in the past almost four decades, overall, the share of the wealthiest 1 per cent grew in the world’s major economies (Chart 3-9). In line with this, the share of the bottom 50 per cent practically stagnated globally. Although an ever 25

Several indicators are available for measuring the distribution of income (wealth) in the population. Inequalities can be measured in absolute terms (income differences) and in relative terms (proportion of incomes). The most popular indicator is the Gini index, which measures the inequalities in statistical distributions. It takes values between 0 and 1 (0 and 100 per cent), where zero means complete equality. Furthermore, the literature often uses various income- (wealth)-to-population ratios. A possible method for demonstrating income inequalities is to present the income share of the top 1 per cent and the bottom 50 per cent.

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3 5 challenges of the future

smaller proportion of the world’s population lives on less than USD 1.9 a day, it is striking that incomes grew more in the upper portion of the distribution. Chart 3-9: Evolution of the top 1 per cent national income share and global extreme poverty 30

Per cent

2010

0 2000

0 1990

1980

1970

1960

1950

1940

1930

1920

1910

1900

Share of people in extreme poverty (right-hand scale) USA France India Russia UK Sweden Germany China

Source: MNB based on Piketty et al. (2018) and Roser – Ortiz-Ospina (2019).

Wealth inequalities:

Between the early 2000s and the economic crisis, the expansion of household wealth was characterised by the so-called “golden age”. In the first years of the century, wealth increased dynamically and inclusively, so large swathes of society benefited from it. Per capita wealth was up by 8 per cent globally between 2000 and 2007, and growth was even greater in the lower portion of the distribution (Credit Suisse 2018). However, the global economic crisis halted wealth accumulation, which has increased only at a modest rate in recent years.

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3.2 Demographic challenges: how long and how large the world’s population will grow?

Similar to income, wealth is distributed unevenly between countries and among the various wealth groups within countries. Besides the differences between countries, wealth is distributed unevenly among various social groups. 0.8 per cent of the world’s adult population holds 44.8 per cent of global wealth, whereas 63.9 per cent control a mere 2 per cent of the wealth (Chart 3-10). While in the wealth category below USD 10 thousand is mostly formed by African and Asian economies, the range between USD 10 thousand and 100 thousand is dominated by the Chinese middle class (they have a 48 per cent share within this wealth group). In 2018, almost 74 per cent of dollar millionaires originated from North America and Europe. Chart 3-10: Distribution of global wealth 100

Per cent

100 90

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Africa Latin America Asia and Pacific India China Europe North America

Per cent

2018

44.8

63.9

Adult population

Wealth

> 1 million 100,000 1 million 10,000 100,000 < 10,000

Note: Wealth ranges in USD. Source: Credit Suisse (2018).

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3 5 challenges of the future

Inequality of opportunity:

Individual decisions, talent, effort and luck obviously play a role in the development of income and wealth inequality. However, when examining the issue of inequality, one should take into account the inherited factors (path dependence) and analyse the so-called “inequality of opportunity” (Sen, 2001; World Bank, 2006; Kanbur – Wagstaff, 2015). Individuals’ social and income position is influenced by parental background, access to basic necessities, public infrastructure and services. In Sub-Saharan Africa, the population’s access to electricity (38 per cent) and drinking water (58 per cent) falls well short of other major regions of the world, where these ratios are consistently over 86 per cent. In North America and Europe, a mere 3 per cent of the population is undernourished, while the same figure is 16 per cent in South Asia and over 20 per cent in Africa (Chart 3-11). Access to healthcare and education is a crucial precondition of getting by in life. In North America, life expectancy is 20 years higher and secondary school enrolment is 55 percentage points higher than in Africa. Inequality of education is also substantial within countries: in low-income countries, just 36 per cent of the bottom income quintile finish basic education, while the same figure is 80 per cent in the richest group.

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3.2 Demographic challenges: how long and how large the world’s population will grow?

Chart 3-11: Physiological characteristics and access to basic services in major regions

76%

79year

91%

44%

70%

76%

91%

year

18% 54%

70%

60year

year

35%

23%

59%

16%

year

50%

80%

year

21%

internet users share in population life expectancy

secondary school enrollment (share) prevalence of undernourishment (share)

Source: World Bank WDI, UNESCO WIDE, OECD (2016).

References Bloom, D. E. – Canning, D. – Sevilla, J. (2003): The Demographic Dividend – A New Perspective on the Economic Consequences of Population Change. Credit Suisse (2018): Global Wealth Databook 2018. https://www.credit-suisse.com/media/assets/ corporate/docs/about-us/research/publications/global-wealth-databook-2018.pdf Kanbur, R. – Wagstaff, A. (2015): How useful is inequality of opportunity as a policy construct? CEPR Discussion Paper 10508, March. Lee, R. D. – Reher, D. S. (2011): Introduction: The Landscape of Demographic Transition and Its Aftermath. Population and Development Review 37 (Supplement): 1–7 (2011). Niño-Zarazúa, M. – Roope, L. – Tarp, F. (2017): Global Inequality: Relatively Lower, Absolutely Higher. Review of Income and Wealth, Series 63, Number 4, December 2017. OECD (2016): OECD Science, Technology and Innovation Outlook 2016. OECD Publishing, Paris. https://doi.org/10.1787/sti_in_outlook-2016-en Piketty, T. – Saez, E. – Zucman, G. (2018): World Inequality Report 2018. https://wir2018.wid. world/

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3 5 challenges of the future Roser, M. – Ortiz-Ospina, E. (2019): Global Extreme Poverty. Published online at OurWorldInData. org. https://ourworldindata.org/extreme-poverty Sen, A. (2001): Ten theses on globalization. New Perspectives Quarterly, Vol. 18 No. 4, pp. 9–15. United Nations, Department of Economic and Social Affairs, Population Division (2017): Government Policies to raise or lower the fertility level. December 2017, No. 2017/10. https://www. un.org/en/development/desa/population/publications/pdf/popfacts/PopFacts_2017-10.pdf United Nations, Department of Economic and Social Affairs, Population Division (2019a): World Population Prospects 2019. https://population.un.org/wpp/DataQuery/ United Nations (2019b): Ageing. https://www.un.org/en/sections/issues-depth/ageing/ World Bank (2006): World Development Report: Equity and Development. New York: Oxford University Press.

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3.3

How to keep up with technology? Levente Erdélyi – Katalin Kis

Future economic growth may be defined by productivity growth related to artificial intelligence as a new input of production. Digitalisation, data processing, innovations in artificial intelligence and automation create new opportunities for companies and the state alike, but they also pose several challenges. Technological innovations affect the firms in the various sectors differently, therefore a technological breakthrough may transform the ecosystem of firms, assigning a greater role to tech giants. In respect to the current trends, the use of digital technologies varies from a geographical perspective as well. Europe is lagging behind the United States in digital skills, which is even more pronounced in artificial intelligence innovations. The emergence of digital technologies put the concept of data in a new context, as data collection methodology has changed and data processing has also taken on a new form. This also highlights issues such as data ownership, data security and cyber protection. One of the most often cited challenges of technological progress is the increasing substitution of human labour for robots, which may polarise employment. This is the first time in the history of industrial revolutions that even white-collar jobs have been threatened. Thus decision-makers and societies need to prepare for future technologies, and it is crucial to take stock of the potential economic and social implications.

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3 5 challenges of the future

How fast is artificial intelligence transforming our present period? Nowadays, we are experiencing the golden age of new technologies. Technological innovations now appear in all walks of life, changing firms’ opportunities for generating profits and how people work and live, and they are doing so faster and faster. Around a decade ago, social media was unknown, whereas today there are roughly 2.4 billion active Facebook users on the platform connected to friends, family and colleagues (Manyika et al. 2013). The technological boom took place a long time ago. In the early 1800s, the First Industrial Revolution started with the advent of the steam engine. From that moment on, the power of the new technologies to shape the economy grew even further, and the speed of technologies’ proliferation has also increased considerably in the past 200 years. It took around 100 years for the railway to become widespread, while telephones and electricity became widely used in just over 50 years. However, in the second half of the 20th century, mobile phones, personal computers (PCs) and the Internet spread in a mere 15 years (Chart 3-12). The appearance of new technologies also exerts a significant impact on economic activity by raising productivity. As noted in the MNB’s Growth Report (2017), the widespread adoption of the general-purpose technologies of the given technological era expands productivity and affects several sectors. Technologies are considered general-purpose if they appear in a wide range of economic sectors, entail massive cost reductions and contribute to the development and use of new products (Jovanovic–Rousseau 2005). Steam power at the time of the First Industrial Revolution or electric energy as of the end of the 19th century were general-purpose technologies like this.

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3.3 How to keep up with technology?

Chart 3-12: Appearance of new technologies and the number of years necessary for their widespread adoption

Number of years necessary for widespread adoption

140

Steamboat

120 Railway

100 80

icity Electricity

Phone

Flying Cars Radio di

20 0 1750

T TV

1800

1850

1900

Mob phone Mobile PC PC I Internet MRI RII 1950 95

2000

Source: Authors’ own compilation based on Comin – Hobijn (2010).

The appearance of general-purpose technologies is accompanied by two phenomena: first, productivity gains are usually more muted when new technology is introduced. This is because new technologies are initially not user-friendly. Second, the reorganisation of economic processes and any additional investment in physical or human capital takes time (Brynjolfsson et al. 2017). This is an example of the productivity paradox proposed by Solow (1987), in other words, the effect of the age of information and communication on productivity growth will be felt with some delay. Digitalisation today and in the future will highlight the next wave of general-purpose technologies. However, nowadays, after automation and the smart devices of the Internet of Things, innovation focuses on technologies using artificial intelligence (advanced robotics, self-driving cars, data visualisation, machine learning) (McKinsey 2017). Future economic growth may be defined by productivity

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3 5 challenges of the future

growth related to artificial intelligence as a new input of production (Chart 3-13). Chart 3-13: Factors shaping the structure of production before and after the turn of the millennium

New energy and information based economy

Economy based on hydrocarbons

Artificial Intelligence

Productivity

Capital

Capital Labour

Labour

Economy output in the 21st century

Economy output until the 21st century

Source: Authorsâ&#x20AC;&#x2122; own compilation.

Nevertheless, the appearance of artificial intelligence and the abundance of data that can be analysed provides not only benefits to companies and the state but also poses challenges for them. Technological innovations affect the firms in the various sectors differently, therefore a technological breakthrough may transform the ecosystem of firms. The differences may appear not only across sectors but among countries too, widening the digital divide. The emergence of digital technologies put the concept of data in a new context, as data collection methodology has changed and data processing has also taken on a new form. This also highlights issues such as data ownership, data security and cyber protection. â&#x20AC;&#x201D; 76 â&#x20AC;&#x201D;

3.3 How to keep up with technology?

What are the challenges of technological progress on the geopolitical map? The innovations of the digital revolution will transform the ecosystem of firms, offering new opportunities to technology companies. In recent years, based on their revenues the Forbes “Global 2000” list ranking businesses was topped by companies from the financial and energy sectors (e.g. oil refining). The next period is expected to bring about the rise of technology firms, supported by the fact that Apple was in the top ten on the 2019 list (Forbes 2019). Tech giants generate 46 per cent of their revenue from IT (such as cloud services and data analysis). This is followed by consumer goods and communication services, and these companies have also ventured onto the market for financial products. In terms of geographical location, digital trailblazers are currently heavily concentrated. The home of new-wave technologies is the United States, but China is also making great strides to catch up. Besides the “Big Four” (Google, Amazon, Facebook, Apple) operating in the United States, Chinese tech giants (Alibaba, Baidu, Tencent) dominate the technology market (Chart 3-14.). Currently, the United States hosts 54 per cent of the world’s “unicorns” (start-ups valued at USD 1 billion or more). 23 per cent are in China, while Europe’s 10 per cent share suggests that it is lagging far behind (Bughin et al. 2019).

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3 5 challenges of the future

Chart 3-14: Tech giants

USAUSA

25,7 %

23,4 %

China Kína

22,0 %

Distribution of big technological firms’ subsidiaries (per cent)

Revenues of big technological firms by type of activity (per cent)

3.9 11.3

6.1

14.8 46.2 21.6

Infocommunication technologies Consumer goods Communication services Finance Other

2.3 13.8

42.9 37.0

Europe North America Asia and Oceania Latin America and the Caribic Africa and Middle East

Note: The tech giants include: Alibaba, Alphabet, Amazon, Apple, Baidu, Facebook, Grab, Kakao, Mercado Libre, Rakuten, Samsung and Tencent. Source: Authors’ work based on BIS (2019) and McKinsey (2019).

In Europe, the traditional web-based and mobile phone technologies as well as big data analysis are part of large enterprises’ operations in over 64 per cent of cases. However, in the case of artificial intelligence, the continent is lagging far behind (Chart 3-15.), which may be a major competitive disadvantage in the long run compared to the leading nations. Nonetheless, the roots of artificial intelligence development go back to Europe. The history of self-driving cars started in 1984 in a German Mercedes factory, and 35 per cent of deep learning models were developed in Europe too (Bughin et al. 2019). However, Europe’s leading role was short-lived, as European efforts are dwarfed by those — 78 —

3.3 How to keep up with technology?

of the United States and China. This is demonstrated clearly by the fact that the European Commission allocated EUR 2.6 billion for developing artificial intelligence and robotics, whereas China uses that amount to build a single technology park. Moreover, more than 50 per cent of the investments in start-ups focusing on artificial intelligence are implemented in China (McKinsey 2019). Chart 3-15: Digital technology adoption of large European companies, 2017 (per cent) Traditional-access web technologies

Wave 1: Access Mobile internet technologies

Wave 2: Analytics

Big Data

Smart robotics (eg, robotic process automation)

Wave 3: Analitical intelligence

Advanced neuronal machine learning (eg, deep learning)

3 10

Al tools (eg, virtual assistants, computer vision)

4 14

Other Al tools (eg, smart workflows, cognitive agents, language processing)

6 13

Using at scale across the entire enterprise Using at scale, but only for one function Piloting

Note: Chart may not sum to 100 per cent because of rounding. Source: Authorsâ&#x20AC;&#x2122; work based on Bughin et al. (2019).

With technological innovations, the capital using outdated procedures inevitably loses its value. This causes losses to the owners and users of the old technology and generates profits for the entrepreneurs â&#x20AC;&#x201D; 79 â&#x20AC;&#x201D;

3 5 challenges of the future

investing in new procedures (BrĂłdy 2010). According to Schumpeter (1942), as new combinations arise, earlier solutions and skills are crowded out and become redundant. He was referring to the process dismantling earlier structures that occurs in the innovation process of market economies as creative destruction. A prime example of this is the Internet. It helped produce new forms of communication, transform supplier chains and change consumer needs. It brought transparency into pricing, shattered former trade practices and rendered business models obsolete. Online booking systems reduced the significance of travel agencies, Amazon altered the whole structure of publication and book sales, while online music sharing platforms (Napster, iTunes) pulled the rug out from under music stores (Manyika et al. 2013).

Is data the new oil? An important issue is who collects the endless amount of data produced by the new data processing methods and who should own them. Should they be controlled by the consumer, the regulator, the current government, the service provider or the manufacturer? In addition, the platform economy of the future pays special attention not only to data ownership but also the access to data. Let us take the automotive industry as an example. Nowadays, several vehicle manufacturers and suppliers access lots of data on vehicles to fine-tune and enhance their cars and services. In the newly emerging ecosystem, many industry players have ample opportunities for sharing the data available to them with each other. A KPMG (2019) survey sought to find out who should own consumer data according to the buyers and managers they asked. One-third of the managers believed that the collected data should be managed by the manufacturer, and roughly the same share argued that they should be left in the hands of the consumer. Furthermore, managers increasingly claim that the manufacturers are the data owners, thereby fostering future profitability opportunities. There is a much more widespread consensus in the consumer base.

â&#x20AC;&#x201D; 80 â&#x20AC;&#x201D;

3.3 How to keep up with technology?

Almost half of consumers believe that the car owner is entitled to manage the collected data (Chart 3-16). Chart 3-16: The owner of data in the automotive industry based on managers’ and consumers’ opinion 50

Per cent

Per cent 47

45 40

35 30 25 20 15

30 29

50 45 40

2016

2017

2018

2019

Vehicle manufacturers

Owner of the car

Vehicle manufacturers

Owner of the car

20 15 10

Executive’s opinion

Consumer’s opinion

Source: Authors’ own compilation based on KPMG (2019).

The plethora of available information also increases risks related to data generation and storage. By managing these, companies can protect their reputation from being tarnished and avoid penalties or a decline in customer satisfaction (PwC 2018). According to a survey by Cooper – LaSalle (2016) covering 23 countries, 55 per cent of customers do not trust the way organisations manage their data. Meanwhile, consumers are increasingly conscious of data security, and 67 per cent regularly take action to protect their data. They change their passwords often and consciously cancel unused services. This result was confirmed by the participating companies too. More than half of the respondents admitted that they do not do everything they can to appropriately

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communicate how data are used. Companies need to make great efforts to restore customer confidence, as according to a SafeNet (2014) survey, two-thirds of consumers detest using the services of the firms that have misused data. A PwC (2018) study lists seven major risks related to data management (Chart 3-17). Businesses often have insufficient knowledge about data collection and storage, which may lead to incorrect decisions due to inaccurate data. To customers, it is sometimes unclear what their data are used for, which leads to seemingly unfair and unethical decisions. Companies may lose profits because, fearing the negative consequences, they do not make the most of the available data, or the reverse is also possible: inappropriate anonymity can lead to data being misused. Furthermore, firms also have to comply with constantly expanding national and international regulations. Chart 3-17: Major risks of data management

MAIN RISKS OF DATA MANAGEMENT Lack of knowledge of data generation and storage Possibility of data abuse Lack of transparency Decisions that seem unfair Wrong decisions due to "bad" data Conflict with global rules Data unavailability due to too cautious approach Source: Authorsâ&#x20AC;&#x2122; own compilation based on PWC (2018).

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Artificial intelligence instead of human intellect: Will robots take all the jobs? One of the most often cited challenges of technological progress is the increasing substitution of human labour for robots and the changing nature of human work in itself. While in the past machines replaced human muscle, “smart automation” can also replace intellectual work (PwC 2018). The studies published so far warn about major challenges. Owing to the new technologies, the labour market has become polarised in recent decades: both the share of high-skilled, high earners and low-skilled, low earners increased, while the demand for those in the middle of the wage scale slumped (Chart 3-18). Chart 3-18: Changes in employment shares in the US by income groups, 1980–2005

Change in employment share

0.4 0.3 0.2

Repetitive, routine tasks

0.1 0 Occupations with higher education, requiring creative, social skills

0.1 0.2

Difficult to automate, mainly service sectors 0

100

Percentile ranked by mean wage Source: Authors’ own compilation based on Autor and Dorn (2013).

Average-paying occupations typically include skilled industrial workers and office workers without a higher degree. Their work mostly comprises of routine tasks, so the activities involved are repeated and — 83 —

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their implementation is based on strict rules. As technology becomes affordable, robots will start to take on routine tasks, crowding out the workers performing them. With graduate jobs, robots will play a supplementary role rather than substituting workers, as technology makes those who were already earning higher wages more productive and their incomes will become even higher. The growing income of those at the top of the wage distribution allows demand to increase for the low-paying jobs mainly related to services. The tasks of those near the bottom of the wage scale are difficult to robotise, despite the fact that they do not require high skills. Robots cannot take over the jobs, or only with difficulty for the time being, that require complex communication skills (e.g. hairdresser) or constant adaptation, therefore the negative labour market effects do not directly impact labour-intensive services (Brynjolfsson and McAfee 2014). At the same time, the probability increases that those performing routine tasks will try to find a new job in this segment after losing their previous job. Besides the polarisation of the labour market, the survey by the Australian HR Institute (AHRI 2017) points out further relevant questions, and the mixed attitude towards technology suggests a lack of clear answers (Chart 3-19). According to hopes related to the labour market of the future, technology will play more of a supplementary role by transforming positions (78 per cent), and 87 per cent of respondents believe that they will be able to manage at their future workplace by acquiring new skills and knowledge. However, only slightly more than half of the respondents (51 per cent) assume that technology will not replace many jobs. Moreover, those who expect that robotisation and artificial intelligence will be able to create more jobs than they eliminate are in the minority (34 per cent), and another 45 per cent are unsure about the overall outcome. Even if on balance labour market effects are positive, the prolonged period of switching between workplaces may pose a great challenge. Besides, the increasing role of

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the sharing economy driven by digitalisation presents further labour market dilemmas. Chart 3-19: Attitude towards technology on the labour market

78%

Machines complement human workforce

87%

Acquiring new knowledge is crucial

51%

More moderate replacement of jobs

34%

Job creation of technology is stronger

69%

Duration of job search increases

43%

Concerns linked to the shared economy

Source: Authors’ own compilation based on AHRI (2017).

This is not the first time that technology has caused major advances on the labour market, however, it is the first time that even whitecollar jobs have been threatened. We are on the brink of a technological boom, which may entail unprecedented changes in the world of work. It will not affect all jobs and not all affected jobs will disappear, but jobs with unchanged characteristics will be the exception rather than the norm (Ernst & Young 2016). Machine automation is, for the time being, unsuitable for performing several activities requiring human skills. The remaining or newly emerging positions demand workers to have increasingly complex skills (problem solving, critical thinking, creativity). Digitalisation will fundamentally change people’s attitude towards work. The labour force means fewer and fewer employees in

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the traditional sense, with many people only being in virtual contact with the organisations they work for. The “constructive” and “destructive” effect of the new technology poses new questions for economic actors. Technologies transform the labour market and data becomes more important as it has a major impact on social welfare, which is detailed in Chapter 6.

References AHRI (2017): Future of Work: HR Hopes and Fears. Australian HR Institute, 2017. https://ahri. com.au/media/1205/future-of-work-report.pdf Autor, D. – Dorn, D. (2013): The Growth of Low-Skill Service Jobs and the Polarization of the U.S. Labor Market. American Economic Review, 103(5), pp. 1553–1597. BIS (2019): Annual Economic Report, Bank for International Settlements. https://www.bis.org/ publ/arpdf/ar2019e.pdf Bródy, A. (2010): Fejlődés vagy növekedés? (Development or growth?) Közgazdasági Szemle (Economic Review), Vol. LVII, Dec. 2010, pp. 1072–1086. Brynjolfsson E. – Rock D. – Syverson Ch. (2017): Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. NBER Working Paper Series, 24001 Brynjolfsson, E. – McAfee, A. (2014): The Second Machine Age. Work, Progress, and Prosperity in a Time of Brilliant Technologies. United States: W.W. Norton & Company, Inc. Bughin, J. – Seong, J. – Manyika, J. – Hamalainen, L. – Windhagen, E. – Hazan, E. (2019): Notes from the AI frontier: Tackling Europe’s gap in digital and AI. McKinsey&Company, Discussion Paper, February 2019. Comin, D. – Hobijn, B. (2010): An Exploration of Technology Diffusion. American Economic Review, 100(5), pp. 2031–2059. Cooper, T. – LaSalle, R. (2016): Guarding and growing personal data value. Accenture. Ernst & Young (2016): The Upside of Disruption: Megatrends Shaping 2016 and Beyond. Ernst & Young, 2016. https://cdn.ey.com/echannel/gl/en/issues/business-environment/2016megat rends/001-056_EY_Megatrends_report.pdf ILO (2008): Skills for improved productivity, employment growth and development. Report V. Fifth item on the agenda. International Labour Conference, 97th Session, Geneva. http://ilo.org/wcmsp5/ groups/public/@ed_norm/@relconf/documents/meetingdocument/wcms_092054.pdf

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3.3 How to keep up with technology? Jovanovic, J. – Rousseau, P. L. (2005): General Purpose Technologies. In: Handbook of Economic Growth, Volume 1B. eds.: Aghion, Ph. – Durlauf, S. N. Elsevier B.V.Jorgenson, D. W.-Stiroh, K. J. (1999): Information Technology and Growth. American Economic Review, 89(2), May 1999. KPMG (2019): Global Automotive Executive Survey 2019. KPMG Manyika, J. – Chui, M. – Bughin, J. – Dobbs, R. – Bisson, P. – Marrs, A. (2013): Disruptive technologies: Advances that will transform life, business, and the global economy. McKinsey Global Institute, May 2013. McKinsey (2017): What’s now and next in analytics, AI, and automation. McKinsey Global Institute, May 2017. McKinsey (2019): Twenty-five years of digitization: Ten insights into how to play it right. McKinsey Global Institute, May 2019. MNB (2017): Growth Report. Magyar Nemzeti Bank. PWC (2018): Mennyit ér az adat? Új szolgáltatások és bevételi lehetőségek nyomában (How much are data worth? Searching for new services and revenue opportunities). PWC, Hungary. PwC (2018): Will robots really steal our jobs? An international analysis of the potential long term impact of automation. PricewaterhouseCoopers, 2018. https://www.pwc.com/hu/hu/kiadvanyok/ assets/pdf/impact_of_automation_on_jobs.pdf SafeNet (2014): Global Survey Reveals Impact of Data Breaches on Customer Loyalty. SafeNet, July 30, 2014. Schumpeter, J. A. (1942): Capitalism, Socialism & Democracy. Taylor & Francis e-Library, 2003. Solow, R. M. (1987): We’d better watch out. New York Times Book Review, July 12, p. 36.

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3.4

Geopolitical challenges: long-term sustainable Eurasian growth Norbert Csizmadia

The most important geopolitical trend of the period following the hyperglobalisation that lasted until the 2008 economic crisis is multipolarisation, where new cooperation, new actors, new ways of thinking, new solutions and new value systems emerge. A feature of the transforming world order is the rise of cities and networks of cities. There are now 64 global urban regions and megaregions, which produce 80 per cent of the world’s economic output. New maps are needed for understanding the operation of the transforming world order. These network maps will be able to appropriately show the powers and major hubs of the 21st century. As Europe and Asia are ever more connected, the Eurasian supercontinent will become the most important cooperation in the world order. The Central and Eastern European region previously considered a buffer zone may become a gateway region, where two cities, Warsaw and Budapest are expected to stand out.

Who will be the winners in the 21st century? A new world order is dawning on us. While hyper-globalisation dominated in 1980–2010, new cooperation, new actors, new ways of thinking, new solutions and new value systems started to emerge in the aftermath of the 2008 economic crisis. In 2010, globalisation entered a new age of technology and knowledge (Cséfalvay 2018), and in 2013 it entered a Eurasian age based on long-term sustainable growth. — 88 —

3.4 Geopolitical challenges: long-term sustainable Eurasian growth

In these new times, geography and economic geography are on the rise, and geopolitical developments are being replaced by geo-economic ones, where the competition will be for markets rather than territory (Bernek 2010). We live in the age of networks and fusions. In this interconnected world, a complex approach is paramount (Castells 2005). The centre of gravity of the world economy is shifting towards the East again, marking the end of a 500-year Atlantic period. While the 19th century was the age of the British Empire, the 20th century was that of the US, and the 21st will be the century of Eurasia (Khanna 2019). Europe and Asia will become connected to form a new supercontinent, Eurasia, where China will play a leading role. And the Central and Eastern European region previously viewed as a buffer zone may become a gateway to the Eurasian continent. Chart 3-20: The shifting centre of gravity of the world economy between AD 1 and 2025, based on GDP

Source: McKinsey Global Institute, 2012.

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What can be expected in the age of the technological boom and geo-economics? By combining geography, geo-economics, geopolitics and the global economy, our world can be presented in a complex fashion. After the age of globalisation, the age of technology has arrived, and one of the most pressing questions is what role location will play in this technology-driven era. This is the geography of knowledge and fusions, or “Geofusions”, and geography becomes a meeting point in the age of networks. Technological progress has once again underlined the importance of geography (Csizmadia 2017). The 21st century is the century of knowledge and creativity, where unique ideas and innovations are the most important currencies, and the countries that do not have enough knowledge will have no choice but to buy it, even though it will become more and more expensive. When former Bank of England Deputy Governor Paul Tucker was asked in March 2016 at the Tacitus Lectures in London who would be the winning countries, nations, communities and leaders of the 21st century, his answer was telling: the countries that coordinate their financial or monetary policy, economic policy and geopolitics (Tucker 2016). In this new age of geofusion, data (big data) will be the raw material of the 21st century, and knowledge, creativity and experience will be its services. It will have new actors and new cooperation, where the small become the large, as demonstrated by the start-up firms, start-up cities and start-up nations (Moss 2011). This will be an age of fusions and networks, where the two most important buzzwords will be interconnectedness and complexity. A major geopolitical element of the 21st century is that the former unipolar world is turning into a multipolar world order. Geoeconomics determines the developments in the world economy by fusing economics, social sciences and geography. We are witnessing

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the rise of geo-economics, a competition in the language of trade but with the logic of war. Geopolitical competition transforms the global economy, the global balance of power and governance. Before the financial-economic crisis, geopolitics mostly played a role at the local level, however, nowadays the conflicts between the great powers have flared up again. Military action is replaced by economic sanctions, and military alliances are replaced by competing trade frameworks. The likelihood of a currency war is far greater today than that of annexation, and manipulating the prices of certain raw materials is a far more powerful weapon than the conventional arms race. Geoeconomics is simultaneously the antithesis and the greatest triumph of globalisation. The mutual dependency and connection between countries becomes so strong that exclusion from this system is considered as great a tragedy as war (Bernek 2010).

Why will global cities become the hubs of the new world order? In today’s world economy, 40 per cent of global GDP is produced by 147 global corporations, and around 700 companies generate 80 per cent of global GDP. These businesses cluster in cities around hubs, especially where a creative workforce is available. Besides nation states, strategic firms will undoubtedly be the new superstars of the 21st century (McKinsey 2018). Today, in the age of the rise of cities and networks of cities, there are 64 global urban regions and megaregions, which produce 80 per cent of the world’s GDP. If the five greatest global cities in the world (New York, Los Angeles, Tokyo, Paris and London) made up a country, this imaginary territory would be the third largest economy on the planet behind the US and China (McKinsey 2011). According to international forecasts, urbanisation will shift towards the east and the south by 2030 (UNDP 2018).

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Growth axes and regions start to form, with cities at their centre, from the Boston–New York–Washington axis to the New Hanseatic League in Europe to the Pearl River Delta in Asia (Hong Kong–Shenzhen– Guangzhou) to Singapore. In the new competitiveness rankings, the cities on the eastern coast of Asia are becoming increasingly important. When taking into account the new urban competitiveness factors, such as interconnectedness, creativity, knowledge, technology, innovation and participation in global trade, supplemented with welfare factors including security, liveability and the size of green areas, in all likelihood Singapore and Shanghai will top the list. City states also played an important role in history: they engaged in active trade, and functioned as financial, economic, educational and cultural centres, for example during the Renaissance. One only needs to think of Venice or the significance of Genoa, the most prominent factors of which were their locations, and their chief aim was to establish links to the world economy and world trade. Just like today, in the New Renaissance: there are roads, regions, cities, networks and centres (Khanna 2010). To understand the developments of this new age, new maps are needed, and the importance of maps is beyond doubt. They constantly change and evolve, but their meaning and significance remains unchanged. Maps help us think in new ways, because if we look at the world from another perspective, a new vantage point can be established. Our new maps are network maps with lines, and there are meeting points in the hubs that show the powers, major centres and cities of the 21st century. There are 1 million kilometres of submarine internet cables, 2 million kilometres of gas pipelines, 4 million kilometres of railway lines and 64 million kilometres of roads. These will be the most important lines on our maps. It is no coincidence that China’s long-term geostrategy focuses on how to shift the axis of the world economy back to the land from the oceans (Csizmadia 2017).

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3.4 Geopolitical challenges: long-term sustainable Eurasian growth

The New Silk Road or One Belt, One Road Initiative was launched by China in 2013. The essence of China’s long-term plan is to restore Eurasia’s historical, cultural, economic and trade significance by building a New Silk Road. The New Silk Road comprises railways, the development of sea and land-based ports, the construction of motorways and the establishment and development of logistic centres; in other words, networks that are realised in the form of economic corridors. Since the announcement of the programme in 2013, China has made ambitious financial investments and plans to turn the idea of the new economic region in Eurasia into reality (Eszterhai 2016). The main goal of the New Silk Road is to move the world economy’s axis back from the oceans to the land, and restore and reinforce Eurasia’s old economic, political and cultural role (Liu 1998). Chart 3-21: Railway links of the One Belt, One Road Initiative

Source: Deutinger & Chow, 2011.

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The New Silk Road is actually a complex network that can be expanded flexibly in both time and space. It is an alliance of state-owned and economic institutions and cities, a peaceful rise based on cooperation and a network of win-win relationships. The New Silk road connects the players who constitute the new phase of globalisation and represents 40 per cent of global GDP and 70 per cent of the Earth’s population (Eszterhai 2016). The One Belt, One Road Initiative (BRI) was announced by Chinese President Xi Jinping in September 2013, heralding in an infrastructural connection, political coordination, the removal of trade barriers, financial integration and human development. At that time, the BRI was joined by 64 countries, and by the spring of 2019, 125 countries and 29 international institutions had signed 170 agreements to the tune of USD 1,000 billion and started implementing them. The main hubs of the infrastructure networks built within the framework of the New Silk Road will reorganise the regions in terms of their significance, with new centres cropping up. The New Silk Road consists not only of infrastructure networks but also knowledge sharing, interpersonal relationships and cultural and financial cooperation. Since 2013, 3,673 trains have been running between 38 Chinese and 36 European cities, which has created over 180 thousand jobs. The Greek port of Piraeus can shorten maritime transportation by 20 days and the Xian–Duisburg railway reaches its destination in 24 days instead of the earlier 42. A new development axis is emerging, in East–West direction in the north, and NW–SE in the south, linking Piraeus to Rotterdam or the port of Hamburg. This creates a north–south region stretching from the Baltic Sea to the Adriatic and the Black Sea, and the 16+1 member states are an important connection to China. Two hubs are expected to emerge in the region, one in the north, with Warsaw as its centre, for transportation, logistics and energy investments, and the other in the south, with Budapest at its heart, for financial services and cultural and intellectual cooperation.

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References Bernek, Á. (2010): Geopolitika és/vagy geoökonómia – A 21. század világgazdasági és világpolitikai folyamatainak összefüggései (Geopolitics and/or geoeconomics – The interrelations between the world economy and world politics in the 21st century). In: Geopolitika a 21. században (Geopolitics in the 21st century), Vol. 1. No. 1., 31–64. Castells, M. (2005): A hálózati társadalom kialakulása (The Rise of the Network Society). Budapest, Gondolat-Infonia. Cséfalvay, Z. (2004): Globalizáció 2.0 (Globalisation 2.0). Budapest, Nemzeti Tankönyvkiadó, 311. Cséfalvay, Z. (2017): A Nagy Korszakváltás (TECHtonic Shifts). Kairosz Kiadó Csizmadia, N. (2016): Geopillanat – A 21. század megismerésének térképe (Geofusion – Mapping of the 21st Century). Budapest, L’Harmattan Kiadó, 408. Deutinger, T. – Chow, K. (2011): Iron Silk Road. http://www.td-architects.eu/projects/show/ iron-silk-road/ Eszterhai, V. (2016): Az Egy Övezet, Egy Út geopolitikai jelentősége a történelmi távlatban (The geopolitical significance of One Belt, One Road from a historical perspective). In: geopolitika.hu.https:// www.newsweek.com/new-world-order-map-72299 Gere, L. (2019): Városlendület index 2018 (City Momentum Index 2018). Geopolitika.hu http:// www.geopolitika.hu/en/2019/06/03/city-momentum-index-2018/ Khanna, P. (2010): Beyond City Limits. In: Foreign Policy, September/October, https://www. paragkhanna.com/home/beyond-city-limits Khanna, P. (2019): The Future is Asian. Simon & Schuster, 448. Kotkin, J. (2010): The new world order: A map. In: Newsweek. https://www.newsweek.com/ new-world-order-map-72299 Liu, Xinru (1998): The silk road: overland trade and cultural interactions in Eurasia. Washington D.C., American Historical Association, 42. Matolcsy, Gy. (2015): Amerikai birodalom – A jövő forgatókönyvei (American Empire – Scenarios for the Future). Budapest, Pallas Athéné Geopolitikai Alapítvány, 384. McKinsey Global Institute (2011): Urban world: Mapping the economic power of cities. https:// www.mckinsey.com/~/media/mckinsey/featured%20insights/urbanization/urban%20world/ mgi_urban_world_mapping_economic_power_of_cities_full_report.ashx McKinsey Global Institute (2018): ‘Superstars’: The dynamics of firms, sectors, and cities leading the global economy. https://www.mckinsey.com/featured-insights/innovation-and-growth/ superstars-the-dynamics-of-firms-sectors-and-cities-leading-the-global-economy Moss, I. (2011): Start-up nation: An innovation story. In: OECD Observer

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3 5 challenges of the future McKinsey Global Institute (2012): Urban world: Cities and the rise of the consuming class. June 2012. https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Urbanization/ Urban%20world%20Cities%20and%20the%20rise%20of%20the%20consuming%20class/MGI_ Urban_world_Rise_of_the_consuming_class_Full_report.ashx Tuckert, P. (2016): The Geopolitics of the International Monetary and Financial System. https://www. mnb.hu/letoltes/paul-tucker-eloadas.pdf UNDP (2018): World Urbanization Prospects 2018. https://population.un.org/wup/DataQuery/ World Bank (2018): Belt and Road Initiative. 29/03/2018 https://www.worldbank.org/en/topic/ regional-integration/brief/belt-and-road-initiative World Economic Forum (2018): The Global Competitiveness Report. http://reports.weforum.org/ global-competitiveness-report-2018/?doing_wp_cron=1562143355.3018579483032226562500

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3.5

Money in the digital age Gábor Horváth – Pál Péter Kolozsi

The financial system is facing a dramatic transformation, as the great economic, social, demographic and technological trends of our age are directly influencing the world of finance. The growing importance of sustainability issues, the steady build-up of debt deriving from the fiat money system, the increase in social and wealth inequalities and, particularly, digitalisation are all having a significant impact on finance. The world of finance is a natural fit for digital transformation, which poses a significant challenge in terms of both content and form, as it has not only brought about comfort functionalities and the transformation of banks’ background infrastructure, but has also facilitated the emergence of instruments challenging the boundaries of the current financial system, which are intended to fulfil certain money functions. Nowadays, the financial system needs to tackle several technological, economic, social and demographic challenges (Chart 3-22). Our economic and social environment and perspective is constantly and substantially changing for several reasons. The impact of the demographic trends and the transformations affecting the information society is huge both globally and locally, and its efficiency issues can be offset by automation and machine learning. The radically different fertility, demographic and educational patterns of emerging countries, as well as climate change and cultural globalisation could exert increasing pressure on the structure of society, which is already struggling with the weakening of its traditional pillars (Harari 2017). These together create an unprecedented and rapidly changing world.

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Chart 3-22: Megatrends established by the Bank of England

Shift to digital, big data, automation, machine learning Retail sales goes online, data wealth accumulates, jobs got automated

Platform- and app-based as well as gig and sharing economy Growing number of self-employed digital nomads and SME or retail mobile app users

Green economy, climate and demography related challenges, new institutional and regulatory frameworks Renewal of infrastructure, aging societies, climate migration may alter the world as we know it

New business models with cyber-risks involved Using cloud-based and developed IT solutions may also entail a growing global cyber-premium

Source: Bank of England.

One of the challenges faced by money and the financial system is26 that due to changing consumer habits, humanity can access huge amounts of data, which has both beneficial and negative consequences, and there are an increasing number of digital “nomads” and new, neverbefore-seen business models. Sustainability interests an increasing section of society, not only in terms of the macro-level environmental impact but also at the individual level, with respect to the number of years spent in good health. These could have a highly varied impact on finance, and not only does the banking system, which can now be “circumvented”, need a new supervisory/regulatory and central bank approach, but so do the changes on the capital market. New players may be granted access to the central bank’s balance sheet; furthermore 26

Huw van Steenis: The future of finance report. Source: Bank of England, 20 June 2019.

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3.5 Money in the digital age

revisiting the clearing systems, using cloud services, allowing smaller players to access payment systems, using artificial intelligence and settling the issues of digital regulation and cyber protection might all become warranted. Besides the above, the financial system also needs to face the fact that the fiat money system is based on growing outstanding debt, which may entail rising social inequality. In the economies based on a twotier banking system, money creation is performed by the system of commercial banks.27 However, the creation of new deposit money requires that debt continues to increase with no abating, which is why it is possible that despite the deleveraging after the financial crisis, global private debt28 relative to GDP is still higher after 10 years than in 2008. Although quantitative easing by the three large central banks (ECB, Fed, BoJ) eased financing costs as monetary conditions were relaxed, it had a significant impact in two related areas: government debt and asset prices surged, while income29 and especially wealth inequalities continued to widen in advanced countries. This may even erode the confidence in money, which may affect the operation of the entire financial system. This rapidly and fundamentally changing world also includes the proliferation of digitalisation, which is a major challenge for the financial system and money regarding both its form and substance. In the current financial system, money is created almost exclusively in the commercial banking sector, as central banks control the money creation process only indirectly, through monetary policy and, increasingly, macroprudential regulation. Money appears more and

Ábel, István – Lehmann, Kristóf – Tapaszti, Attila: A pénz és a bankok ellentmondásos kezelése a makroökonómiában (The controversial treatment of money and banks in macroeconomics). Source: Financial and Economic Review, 2016/2. 28 IMF: New data on global debt. Source: IMF, 2 January 2019. 29 Chad Borgman: After The Fall: Income Inequality and the Great Recession. Source: Harvard Political Review, 3 December 2018. 27

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more in digital form (Chart 3-23),30 and, although its significance is declining, it is still available in physical form as cash. The world of money is a natural environment for digitalisation, because in the case of deposit money, which constitutes the overwhelming share of money used in transactions, digital technology has been used already. However, the digital revolution entailed not only the comfort features related to bank accounts and the transformation of banksâ&#x20AC;&#x2122; back office, but also the appearance of instruments that are pushing the limits of the current financial system and seek to fulfil certain functions of money. Chart 3-23: Distribution of global money by monetary aggregates and the forms of money

USD 90,400 billion

REPO

USD 29,568 billion

USD 7,232 billion

Source: MNB.

This has changed considerably, as it is mostly the financial infrastructure based on private-sector actors and using digital solutions that faces the sweeping digital revolution of the recent decades, which could present 30

Globally, 90 per cent of money already exists in digital form.

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challenges for two reasons. First, the proliferation of digitalisation may crowd out cash from transactions, which not only means saying goodbye to a familiar form of money but also that there will be no state-issued money in the financial system. Second, a change in content may also occur, as more and more digital money substitutes appear that are not issued or backed by the state, potentially at the expense of the money related to the state monetary system, with all its economic and social risks. Therefore, on account of digitalisation, the current financial system already differs from the one from a couple of decades ago, and as regards the prospects, challenges and future risks, the change is even more prominent. With respect to the form of money, it is crucial to see that in digitally advanced countries digital technology’s proliferation is an uninterrupted one, and the use of cash and thus its macroeconomic significance is on a declining path. Salaries and pensions are received almost exclusively on bank accounts, and in certain Nordic countries even government offices have started pondering the gradual phasingout of “inconvenient” cash, which, incidentally, the state should always provide. The use of electronic deposit money is spreading continuously even in the remotest geographical locations and in large swathes of society, which is well demonstrated by the fact that, for example, in Sweden, which is making great strides towards achieving a cashless society, even church donations, which used to be collected in money boxes, can now be made with a bank card, and often even street beggars accept help by bank card. Over time, younger generations will grow up using digital solutions, rendering the use of cash as “obsolete scraps of paper” in payments almost inconceivable. China already has a messaging and money transfer service that has over 1 billion users (WeChat), crowding out not only cash yuan but also bank cards that slowly become outmoded. Retail sales also increasingly take place on online platforms (Amazon, AliExpress), which entails the continued increase in the popularity of electronic payment solutions.

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Besides the change in form, a turnaround in substance may also be experienced due to the digitalisation of money having taken shape in the appearance of privately issued electronic money or cryptocurrencies. Despite not completely fulfilling the functions of money, this threatens to fundamentally question the current financial system. Although in the case of digital money transfer services, it is often “classic” deposit money that switches hands, therefore ultimately payments are backed by more traditional bank instruments, privately issued cryptocurrencies have also appeared,31 without any collateral. It is an exaggeration to refer to cryptocurrencies as money, since these instruments can hardly fulfil the basic functions of money: an instrument with highly volatile prices can hardly perform the standard of value or medium of circulation functions, people do not buy everyday things with it, and those who purchase it spend their savings on a quasi-stock market bubble based on an obscure technology. Cryptocurrencies are unable to become the global standard not only due to financial considerations but also on account of technological constraints, and there have also been major cases of fraud32 with these instruments. Moreover, operational risks33 may be posed by the concrete technological implementation (distributed ledgers). This means that there are major obstacles to the establishment of long-term trust, which ultimately means that these are “crypto-investment” vehicles with significant financial and cyber risks, operating with an energy-wasteful process, but they could still pose an enormous challenge to the financial system. Nevertheless, having been spawned by the loss of confidence after the financial crisis and digital progress, this phenomenon cannot be ignored, and by virtue of its widely known nature it affects our concepts about the financial system, shaping the related thinking and attitudes as well.

The better-known include Bitcoin, Ethereum and Ripple, but in 2019 there were almost 2,000 cryptocurrencies in circulation. 32 Emily Stewart: If bitcoin is so safe, why does it keep getting hacked? Source: VOX, 8 May 2019. 33 “Forks” in the code. 31

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3.5 Money in the digital age

Another major development in the relationship between money and digitalisation may be that the tech giants34 that have a huge user base have also appeared on the market of digital currencies. The most recent and perhaps most prominent example for this is Libra,35 based on Facebook’s network and a wide range of companies, which claimed the right to be the new global currency in the summer of 2019. In Asia, the payment service of Alipay is widely used, and Amazon has also become able to manage supplier credit flexibly, in effect disintermediating SME loans from banks36 and sufficiently replacing the working capital lending business in the case of the companies that are suited for this. However, the appearance of the tech giants in payments entails considerable risks, precisely due to the widespread nature and popularity of these firms: consumer confidence is high, while consumer protection, privacy, money laundering and financial stability issues are not resolved.37 Regulators often lag behind at the inception of ambitious plans, as apparently they do not lead but follow innovation, attempting to close the gaps punctured by the innovators from the private sector. Moreover, a key threat of digitalised finance is cyber risk, which has had futurists, sociologists and military experts interested since the advent of the Internet. From phishing to cyber manipulation to attacks on digital banks/payment systems/central banks (e.g. in Bangladesh in 2016 and in India in 201838), the near future holds numerous risks from unexplored sources.39 Especially the FAANG companies: Facebook, Apple, Amazon, Netflix and Alphabet behind Google. 35 For more on the concept, see: Libra White Paper. Source: Libra Associations Members, 18 June 2019. 36 Jon Frost, Leonardo Gambacorta, Yi Huang, Hyun Song Shin and Pablo Zbinden: BigTech and the changing structure of financial intermediation. Source: BIS, 8 April 2019. 37 Jerome Powell, the chair of the US Federal Reserve (Fed) argued at his hearing by the Financial Services Committee of the US House of Representatives in July 2019 that the Libra project cannot progress until the severe consumer protection, privacy, counterfeiting and financial stability issues are not resolved. 38 Sudarshan Varadhan: India bank hack ‘similar’ to $81 million Bangladesh central bank heist. Source: Reuters, 19 February 2018. 39 Geopolitikai Közhasznú Alapítvány: A virtuális tér geopolitikája (Geopolitics of virtual space). Source: OSZK, 2016. 34

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3 5 challenges of the future

The value of money in the last decades and currently is determined by confidence rather than its underlying physical content; the common belief that the scrap of paper held in our hands or the digital signs on our bank account will also be valued and accepted by the other economic actors (VirĂĄg 2019). This confidence also includes that in the case of a disturbance in the financial system, the central bank will intervene, hammering out the problems. But what would happen in a system dominated by cryptocurrencies? In the 2008/2009 crisis, the central banks, armed with the function of lender of last resort, were able to avoid a complete meltdown, but who will cryptocurrency owners be able to turn to in the next downturn? The challenge is great, but all in all in the digital age central banks will surely respond to the transformation and renewal of money itself and how money is used. This is illustrated well by the fact that although the central bank digital currency has not been introduced anywhere, an increasing number of central banks all over the world are researching this topic (Chart 3-24). Chart 3-24: Central banks researching the topic of central bank digital currency

Source: MNB.

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References Ábel, I. – Lehmann, K. – Tapaszti, A. (2016): A pénz és a bankok ellentmondásos kezelése a makroökonómiában (The controversial treatment of money and banks in macroeconomics). Source: Financial and Economic Review 2016/2. Borgman, C. (2018): After the Fall: Income Inequality and the Great Recession. Source: Harvard Political Review, 3 December 2018. Frost, J. – Gambacorta, L. – Huang, Y. – Shin, H. S. – Zbinden, P. (2019): BigTech and the changing structure of financial inter-mediation. Source: BIS, 8 April 2019. Geopolitikai Közhasznú Alapítvány (2016): A virtuális tér geopolitikája (Geopolitics of virtual space). Source: OSZK, 2016. IMF: New data on global debt. Source: IMF, 2 January 2019. Libra White Paper. Source: Libra Associations Members, 18 June 2019. Steenis, Huw van (2019): The future of finance report. Source: Bank of England, 20 June 2019. Stewart, E. (2019): If bitcoin is so safe, why does it keep getting hacked? Source: VOX, 8 May 2019. Virág, B. (2019): Elefántok a homokozóban (Elephants in the sandbox). Világgazdaság, VG-páholy. 17/07/2019.

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Ecological sustainability â&#x20AC;&#x201C; Green growth

4.1

Green growth framework Róbert Mátrai

Green growth takes into account ecological sustainability considerations and ensures economic growth in the present by making sure that the natural resources and environmental services that are vital for human welfare are available to future generations as well. To this end, consumer behaviour needs to change, and investments and innovations need to be encouraged in such a way that they improve the efficiency of using environmental and natural resources spanning their whole life cycle while maintaining the conditions for growth. The achievement of green growth is jeopardised by several factors. The population growth seen in recent centuries coupled with the continuous scientific and technological innovations has entailed the massive exploitation of natural resources. Human activities (e.g. urbanisation, agriculture, transportation, mining) gravely threaten the resources of land, soil, forests, freshwater reserves and wildlife that are pivotal in satisfying our economic needs and which also provide free-time and recreational opportunities. The sustainable functioning of the economy and the provision of natural resources and environmental services that are crucial for welfare entail several advantages. The positive physiological effects (e.g. the drop in the number of pollution-related diseases) not only increase welfare in themselves but also mitigate the economic sacrifice caused by negative externalities. Greater innovation and the transformation of consumer behaviour create jobs and new business opportunities and thus also affect growth. Green growth has several sources. The enhancement of productivity improves the management of resources, whereby it helps economic activities to be realised — 109 —

4 Ecological sustainability – Green growth

in the areas where their long-term social utility is the greatest. Innovations allow environmental problems to be addressed using new methods, contributing to the separation of the pace of growth and the use of natural resources. New markets can contribute to green growth by fostering demand for green technologies and goods and services while creating new jobs. Growing investor confidence could help sustain the conditions of growth through the improving predictability and stability of environmental policy measures.

What are the conditions for green growth and which factors threaten it? When green growth is achieved, economic development moves along a path that guarantees the conditions for the present growth, while at the same time enabling, in an ecologically sustainable way, that the natural resources and environmental services vital for humanity’s welfare be available for satisfying the needs of future generations. Green growth improves resource productivity through the whole life cycle, from the extraction and use of resources to waste management, thereby mitigating the risks arising from their scarcity and the imbalances in natural systems while promoting the transition to a cyclical economy. To achieve green growth, the change in consumer attitudes and investments and innovations that pave the way for the sustainable transformation of production and consumption should be fostered and accelerated by various regulatory instruments (e.g. taxes, subsidies), awareness-raising and the creation of new economic opportunities (OECD 2011, OECD 2017a).

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4.1 Green growth framework

Chart 4-1: Green growth framework

Source: OECD (2017a).

The conditions of green growth are jeopardised by several factors. Since the beginning of industrialisation, humanity has experienced unprecedented development. Population growth and the scientific and technological innovations resulted in the large-scale exploitation of natural resources, and consumption growth entailed a major negative environmental impact. In the past 100 years, while the Earth’s population has increased fourfold and real GDP per capita has risen sixfold, human land use has almost doubled, freshwater use is up fivefold and forested areas have shrunk by over 10 million square kilometres.40 This entailed biodiversity loss and the accelerated the extinction of species, the rate of which may now be a thousand times greater than at the beginning of human activity (De Vos, Jurriaan et al. 2015). According to the OECD (2017a), the most threatened natural resources are land, forests, freshwater and biodiversity. 40

According to Our World in Data (https://ourworldindata.org/) online database.

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4 Ecological sustainability – Green growth

Land and soil resources are a dominant part of the natural resources of the economy and the ecosystem. They are critical from the perspective of the production of food and other elements of biomass, provide recreational opportunities as well as the physical basis of all economic activities. The way land is exploited impacts the whole natural environment from biodiversity to the ecosystem (e.g. erosions, floods) to water and air quality to greenhouse gas emissions. The greatest challenge related to land use is to maintain the economic, social and environmental balance, which can only be attained if growth is predominantly achieved without increasing the use of green areas and if it ensures that the role of land and soil in the ecosystem is protected. This can be carried out through regulatory constraints (e.g. the establishment of protected areas) or economic mechanisms (e.g. by withdrawing financial support from agricultural activities that harm the environment). Forests are among the Earth’s most diverse and varied ecosystems. Through their use, they provide timber and fulfil cultural and free-time functions. They also play a central role in maintaining other ecosystems (soil, air, water) and protecting biodiversity, and they act as “carbon dioxide depositories”. Human activities considerably influence forested areas, particularly their growth and natural regeneration. Currently, a significant share of forested areas are threatened by excessive logging, fragmentation and conversion to other types (e.g. agricultural land). The greatest hurdle is to establish sustainable forest management, which provides the resources necessary for human activities (e.g. timber and recreational opportunities) without leading to excessive logging or deterioration.

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4.1 Green growth framework

Chart 4-2: Forest area as share of land area, 2015

Source: Bing © GeoNames, HERE, MSFT, Microsoft, Navinfo, Wikipedia

Forest area share of land area (2015) 0%

99%

Source: ourworldindata.org, FAO.

Freshwater reserves have a crucial environmental and economic significance in every region on Earth. However, the existing water reserves are threatened by various factors from over-abstraction of water to pollution caused by human activities (agriculture, industry, and households) and climate change to the appearance of invasive species. Among these, the over-abstraction of water can lead to low water flows, decreasing groundwater levels, deteriorating water quality, the disappearance of wetlands and desertification, which may entail social and economic consequences that threaten food security as well as economic productivity. The greatest challenge related to water reserves is the establishment and maintenance of sustainable water management, which ensures the amount of water necessary for economic activities and human use, without the over-abstraction of water and the deterioration of water quality and threatening aquatic and other ecosystems.

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4 Ecological sustainability â&#x20AC;&#x201C; Green growth

Biological resources (terrestrial, aquatic, and marine) not only provide raw materials for several economic sectors, but also represent the basic elements of ecosystems and environmental capital, and their diversity is vital from the perspective of subsistence and safeguarding the quality of life. The protection and sustainable use of biological diversity (biodiversity) is essential at both the national and global level. Biodiversity conservation, however, is threatened by various dangers arising from human activities, ranging from the physical (e.g. transformation and fragmentation of habitats due to a change in land use), to the chemical (e.g. poisoning, acidification, oil spills) and the biological (e.g. change in the dynamics of the population or the composition of the species by the introduction of exotic species or the overexploitation of game). The chief impediment to the conservation of biodiversity is ensuring the sustainable exploitation of biological resources, which includes strengthening the protection of habitats and species, the elimination of illegal exploitation and trade as well as the overhaul of the environmental subsidy, taxation, usage fee and limitation systems (OECD 2017a).

Has progress been made in the efficiency of the exploitation of natural resources? The previous subchapter showed that the sustainable use of natural resources and curbing the overexploitation of land, forests, water and biological resources are indispensable for green growth. Under these conditions, economic development can only be sustained if the efficiency of using natural resources, i.e. environmental productivity increases. According to the OECD (2017a), environmental productivity has improved in several respects. CO2 emissions increased at a slower rate than real GDP, today raw material use creates greater economic value than in 2000, and major progress can be seen in recycling waste. However, despite the efficiency gains, environmental risks are still

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substantial: CO2 emissions continue to climb, the energy mix is still dominated by fossil fuels and the share of renewables is still low. At the same time, while the global economy’s demand for raw materials continues to be high, many valuable materials end up on landfills without being recycled. The CO2 released from burning fossil fuels and biomass amounts to 90 per cent of the Earth’s total greenhouse gas (GHG) emissions, therefore it is pivotal in the initiatives combating global warming. Coordinated national and international action aimed at structural and technological changes is important in halting the rise in GHG concentrations. Global climate change and the resulting increasingly frequent extreme weather events exert a massive negative impact on ecosystems, human settlements and agriculture. Climate change heavily influences people’s quality of life as well as economic and social activities, which also affects the total output of the global economy. Green growth can only be achieved by increasing the efficiency of CO2 emissions and reducing global carbon intensity. CO2 emissions on Earth are steadily rising, with their levels up by 58 per cent in 2014 as compared to 1990. Although in OECD countries CO2 emissions dropped relative to GDP between 1995 and 2014, they surged in the BRIICS countries (Brazil, Russia, India, Indonesia, China and South Africa). Even among OECD countries, many were only able to cut their emissions relative to real GDP, as in absolute terms, CO2 emissions did not fall in half of the OECD countries. However, several countries show a different picture if not only the direct (production-based) CO2 emissions are taken into account but also the embedded (demand-based) emissions, which were cut in merely 12 OECD countries (e.g. Denmark and Germany) between 1995 and 2011. Most OECD countries are “net CO2 importers”, as their CO2 emissions related to the production of products and services behind domestic consumption exceeds the CO2 emissions of domestic production. This is partly attributable to three

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4 Ecological sustainability – Green growth

factors: (1) the relocation of energy-intensive production to non-OECD countries, (2) the rise in imported products and services (3) and the greater “carbon footprint” of imported goods. Chart 4-3: Correlation between CO2 emissions and economic growth Demand-based CO₂ vs GDP, 1 5 to 2011

Production-based CO₂ vs GDP, 1 5 to 2014

150

Change in demand-based CO₂ emissions, , 1 5 2011

Change in production-based CO₂ emissions, , 1 5 2014

200

45° line

200

BRIICS 1

100 50 OECD

HUN 50

100

200

300

400

Change in GDP, , 1 5 2014

45° line

150 BRIICS

100 50 OECD HUN

0 50

100

200

300

400

Change in GDP, , 1 5 2011

Source: OECD (2017a), IEA (2016), OECD (2015).

Energy is essential for all economic activities. The energy supply and the efficiency of energy use of a country are major factors in its environmental performance and economic development, therefore they are key in green growth, too. The environmental impact of energy supply and use may, depending on the energy source, increase greenhouse gas emissions and local and regional pollution and influence water quality and land use. The ecosystem may face risks from the disposal of nuclear fuels and the extraction, transportation and use of fossil fuels. The use of renewables and low-carbon fuel technologies is important in managing global climate change and establishing energy security. Energy productivity can be improved by employing energy-

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4.1 Green growth framework

efficient production technologies and processes and increasing the share of energy-efficient products and services within consumption. Green growth and the achievement of environmental and climate objectives (e.g. Paris Agreement) require lower energy consumption, both relative to economic output and in absolute terms. Since 1990, the energy consumption of OECD countries has slightly increased and stabilised at 5 billion tonnes of oil equivalent. In the same period, energy use in the BRIICS countries doubled, to around 5 billion tonnes of oil equivalent. This growth is mainly attributable to the services and transport sectors in OECD countries and to industry in the BRIICS countries. In terms of energy efficiency, although there are still huge differences, most countries have made considerable progress in the past over two decades, however, several large energyhungry countries (e.g. Russia and China) continue to exhibit low energy efficiency. With respect to energy sources, even though the proportion of renewables has increased since 1990, they still constitute a small proportion of the energy mix. More than 80 per cent of the energy supply is based on fossil fuels, mainly oil and gas, however, coal use also increased sharply in BRIICS countries. In their case, half of the energy supply is coal-based.

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Chart 4-4: Composition of global primary energy consumption 100 90 80 70

Per cent

12%

11%

17%

18%

20%

21%

22%

23%

24%

43%

38%

37%

35%

10 0

80 70 50 40 30

30 20

60 50

100

25%

27%

26%

25%

24%

28%

30%

29%

28%

1980

1985

1990

1995

2000

2005

2010

2015

2017

Coal Natural gas Solar Wind Nuclear

20 10 0

Crude oil Traditional biofuels Hydropower Other renewables

Source: ourworldindata.org, MNB.

The material resources, which form the physical basis of the economy, are varied as regards their physical and chemical features. The use and processing of raw materials have large environmental, economic and social effects. Improving their productivity and ensuring the sustainable management of material resources are also key in respect to supply security and the environment. The greatest challenge entailed by their use is to ensure efficiency across the whole life cycle (extraction, transport, manufacturing, consumption, recycling, and waste management) and supply chain. This helps avoid the squandering of resources, reduces adverse environmental effects and mitigates the demand for primary natural resources.

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4.1 Green growth framework

Raw material consumption continues to increase all over the world, which calls into question the efficiency of their use. Globally, extraction has grown more than threefold since 1980. Most of this growth came from the extraction of non-metal raw materials (e.g. construction material and minerals), which was up more than fourfold. In certain cases, the surge in use was coupled with uncertainties surrounding supply and price fluctuations. With respect to the efficiency of use, a somewhat decreasing consumption per capita and rising productivity can be seen in OECD countries, however, in BRIICS countries per capita use is rising sharply, while productivity is stagnating. The sustainability of the agri-food systems is a central issue of green growth, the main elements of which include food security considerations, the use of nutrients (nitrogen and phosphorus) and fertilisers and how they enter the food chain together with the pesticide residue runoffs into surface water and groundwater. Farming also contributes to climate change, it may impair soil, water and air quality and lead to habitat and biodiversity loss. These environmental changes affect agricultural production and hamper the sustainability of agriculture. At the same time, agricultural activities contribute to capturing greenhouse gases, to preserving biodiversity and the landscape as well as to the prevention of floods and landslides. The greatest challenge is to gradually ensure that the negative consequences of agricultural production are reduced while its environmental benefits increase. This makes ecosystems and the growing global populationâ&#x20AC;&#x2122;s food security sustainable. In OECD countries, the use of nutrients declined relative to agricultural output: whereas the latter rose by 55 per cent in real terms, nitrogen and phosphorus use were down by 16 per cent and 43 per cent, respectively. By contrast, in BRIICS countries, nitrogen and phosphorus use climbed by 36 per cent and 48 per cent, respectively, and plant production expanded by 143 per cent in real terms, therefore the efficiency of use was up here as well, but it still lags far behind the OECD average (OECD 2017a). â&#x20AC;&#x201D; 119 â&#x20AC;&#x201D;

4 Ecological sustainability – Green growth

What are the benefits of green growth for humankind? The sustainable functioning of the economy and the provision of natural resources and environmental services that are crucial for humanity’s welfare entail several social and economic advantages. The positive physiological effects boost welfare in themselves, but by reducing the decline in productivity due to air pollution and cutting the currently growing healthcare spending, the growth sacrifice caused by growth is mitigated. Moreover, by fostering innovation and expediting the transformation of consumer behaviour, jobs and new business opportunities are created. Nowadays, air pollution is one of the greatest environmental risks to people’s health, causing millions of deaths around the world each year. A major part of the deaths could be avoided by lowering the emission of pollutants and mitigating the effect of pollution on people. 91 per cent of the world’s population lives in places where the air quality guidelines of the World Health Organisation (WHO) are violated. The reduction of air pollution could bring down the frequency of strokes, heart disease, lung cancer and chronic and acute respiratory diseases (including asthma). The lower levels of air pollution exert a positive effect on cardiovascular and respiratory health (WHO 2018). In Europe, air pollution is mostly caused by transport, trade, energy production and distribution, industry, agriculture and waste management (EEA 2018). The reduction of air pollution could be best supported by shifting to clean fuels, increasing the share of clean industries, cutting down on consuming polluting products and the use of cleaner technologies in general, which also requires the adaptation of people’s behaviour, attitudes and lifestyle (OECD 2017a).

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4.1 Green growth framework

According to the OECD’s (2016) estimate, the annual number of deaths related to air pollution globally could increase from the current figure that stands at approx. 3 million to 6–9 million by 2060, and the welfare loss related to premature deaths could rise from USD 3 trillion to USD 18–25 trillion in the absence of a major tightening in energy policy. Moreover, the diseases and suffering caused by air pollution may cause a welfare loss of USD 2.2 trillion each year. The social and economic costs of air pollution also entail a growth sacrifice: due to the falling labour productivity, growing healthcare spending and falling crop yields, global annual GDP could diminish by 1 per cent by 2060. However, the territorial distribution of the growth sacrifice is uneven, exceeding 2 per cent in Eastern Europe. Sustainable green growth could help avoid the further deterioration of air quality, thereby reducing the negative effects of air pollution on people’s health and mitigating the growth sacrifice arising from the pollution thus helping to improve people’s quality of life and welfare. Chart 4-5: Death rate from ambient particulate air pollution, 2017

Szolgáltató: Bing © GeoNames, Hrer, MSFT, Microsoft, NavInfo, Wikipedia

Death per 100,000 individuals 8

Source: ourworldindata.org, IHME.

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110

4 Ecological sustainability – Green growth

The lack of safe water supply and sanitation could also have severe healthcare implications, contributing to the spread of diseases and the rise in the mortality rate. This not only has a major impact on welfare and freshwater ecosystems but also hampers economic growth by reducing labour productivity and rising healthcare spending. In developing countries, the greatest challenge is posed by the extension of water supply and sanitation to rural and poorer, underdeveloped regions, whereas in advanced countries the main issue is the upgrading and modernisation of the existing, often old infrastructure. A mature infrastructure helps countries provide high-quality water supply and sanitation, even if the natural water supply is uncertain on account of the changing population numbers and the global climate change. Among OECD countries, the proportion of those who are connected to the local sewage treatment networks has grown from 60 per cent in 1990 to 80 per cent today. However, the distribution is highly varied. There are countries that have reached the economic and technological limits of expanding the sewage network. They only need to find solutions for the sanitation of small, isolated areas, while in other countries the coverage of the sewage network can still be considerably expanded (OECD 2017a). A precondition for sustainable growth is curbing global climate change entailing a rise in average temperatures. The Paris Agreement signed by 195 countries at the 2015 UN Climate Change Conference sought to keep global warming under 1.5–2 C compared to pre-industrial levels. The Intergovernmental Panel on Climate Change (IPCC) believes that to meet the 1.5 C target, relative to 2010, net global CO2 emissions caused by human activities need to be reduced by 45 per cent by 2030, then cut to zero by 2050. Even to meet the 2 C target, annual CO2 emissions should be reduced by 25 per cent by 2030 (IPCC 2018). Such decarbonisation is inconceivable without overhauling the infrastructure of the sectors causing the greatest greenhouse gas

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4.1 Green growth framework

emissions (mainly energy supply, manufacturing, agriculture, transport and construction). With the currently available technologies, this would mean a radical shift away from the use of fossil fuels to technologies with lower carbon intensity. However, the spread of technologies with lower carbon intensity presents not only risks but also business opportunities for companies. The transition requires that government and private infrastructure investments be stepped up and the sources of finance be rechannelled towards low-emission technologies. According to the OECD (2017b), even if climate objectives are disregarded, sustainable development can be achieved only if infrastructure investments to the tune of USD 95 trillion over 15 years, i.e. USD 6.3 trillion on average annually, are implemented globally in energy, transport, water and telecommunications. Compared to the achievement of the 2 C target set by the Paris Agreement, infrastructure investments worth another USD 0.6 trillion would be required each year. This is 1.5–2 times the current USD 3.4–4.4 trillion. Among the estimated necessary investments, the transport and the energy sectors represent the greatest portion, with a share of 39 per cent each. 60–70 per cent of the necessary investments are linked to developing countries. The financial implications of the investments made to achieve climate protection goals can be partially offset in time by the estimated savings of USD 1.7 billion in fuel costs by 2030 if the investments are implemented. Another positive result may be the economic stimulus provided by the necessary investments. The investments that integrate climate objectives could raise GDP by 1 per cent in four years, and they may entail GDP growth of 4.7 per cent by 2050 (OECD 2017b).

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4 Ecological sustainability – Green growth

Chart 4-6: Annual infrastructure investment needs and fuel savings for sustainable development according to climate goals 8 7

USD trillion 6.3

USD trillion 6.9

8 7 6

6 4.7

5 4

5 3.0

4 3

Sustainable growth in case of no climate goal

Sustainable growth in case of scenario 2°C

Transport Power and electricity T&D Fuel use Water & sanitation

Sustainable growth in case of no climate goal

Sustainable growth in case of scenario 2°C

Primary energy supply chain Telecoms Energy demand

Source: OECD (2017b).

What are the sources of green growth? Green growth provides a framework suitable for tackling economic and environmental challenges by creating new growth opportunities, the sources of which are, according to the OECD (2011), improving productivity, innovations, new markets, investor confidence and a stable macroeconomic environment.

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4.1 Green growth framework

Chart 4-7: Sources of green growth

Source: OECD (2011), MNB.

Productivity is a major source of economic growth, whether environmental considerations are taken into account or not. Green growth strategies explicitly acknowledge the dual role of environmental capital in the production of marketable assets and the provision of environmental services (for individuals and society as a whole). With the appropriate incentive and institutional system, green growth strategies improve resource management, enhance productivity and help economic activities be realised in the areas where their longterm social utility is the largest. On the markets with a large number of participants, market efficiency is established by the equilibrium between supply and demand, however, when environmental capital is used, resource allocation does not fully reflect the value of environmental capital. Thus the appropriate pricing of natural resources, taking into account their impact on the various ecosystems, is crucial for improving efficiency that supports green growth.

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Making use of innovations is key in green growth. The current level of technology and consumer behaviour can sustain development only up to a certain point, but beyond that the depletion of natural resources has serious negative consequences for growth. At present, it is not always known where this point lies, but in the absence of innovation, reproducible capital can replace the (depleted) environmental capital only to a limited extent. Innovations allow environmental problems to be addressed using new methods, contributing to the separation of the pace of growth and the use of natural resources. Innovations also boost the other sources of green growth, especially productivity. The establishment of new markets could contribute to green growth by fostering demand for green technologies and goods and services and thus creating new jobs. Government bodies play a crucial role in creating new markets, through designing measures that stimulate demand and influencing consumer behaviour. They can also contribute to the development of green markets and the proliferation of new products and services by stipulating the conditions of public procurements. The shaping of industry standards is also an important tool in the hands of the government and professional organisations that may help form a critical mass of users necessary for the economical proliferation of green innovations. The greening of growth may also promote the development of the labour market through the growing labour demand as the green innovative activities spread. Growing investor confidence may help sustain the conditions of growth through the improving predictability and stability of environmental policy measures. The regulatory environment must be strict enough to encourage innovation; stable enough to engender confidence in investors; flexible enough to stimulate genuinely new solutions; targeted enough to support policy objectives, and it must also foster continuous innovation. Clear and consistent

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environmental policy measures are needed, to engender long-term confidence in strategic and financial investors for green growth projects. A more stable and balanced macroeconomic environment could contribute to the establishment of the conditions for green growth by falling price volatility, a review of the composition and efficiency of government spending and accommodative fiscal consolidation that entails taxing pollution and putting a price tag on it (OECD 2011).

References De Vos, Jurriaan et al. (2015): Estimating the normal background rate of species extinction. Conservation Biology. 29 (2): 452–462. https://onlinelibrary.wiley.com/doi/abs/10.1111/ cobi.12380 EEA (2018): Air quality in Europe — 2018 report. European Environment Agency, Luxembourg. https://www.eea.europa.eu/publications/air-quality-in-europe-2018/at_download/file IEA (2016): CO2 emissions by product and flow (Edition 2016). IEA CO2 Emissions from Fuel Combustion Statistics (database). http://dx.doi.org/10.1787/data-00430-en IPCC (2018): Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. World Meteorological Organization, Geneva, Switzerland. https://www. ipcc.ch/sr15/ OECD (2011): Towards Green Growth. OECD Publishing, Paris, http://dx.doi. org/10.1787/9789264111318-en OECD (2015): Carbon dioxide embodied in international trade. OECD Structural Analysis Statistics: Input-Output (database). http://stats.oecd.org/Index.aspx?DataSetCode=IO_GHG_2015 OECD (2016): The Economic Consequences of Outdoor Air Pollution. OECD Publishing, Paris, https://doi.org/10.1787/9789264257474-en OECD (2017a): Green Growth Indicators 2017. OECD Publishing, Paris. http://dx.doi. org/10.1787/9789264268586-en

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4 Ecological sustainability – Green growth OECD (2017b): Investing in Climate, Investing in Growth. OECD Publishing, Paris. http://dx.doi. org/10.1787/9789264273528-en WHO (2018): Ambient (outdoor) air quality and health (fact sheet). World Health Organization, Geneva. https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-qualityand-health

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4.2

Regulatory opportunities fostering ecological sustainability Gábor Gyura

As we have seen in the previous chapters, the negative environmental externalities entailed by economic growth necessitate regulatory intervention. However, designing this is a major economic and public policy challenge. While ecological problems are pressing, a massive and sudden intervention in the functioning of the economy carries its own risks and usually entails a sacrifice in growth. The optimal regulatory mix needs to be found with the various instruments, which are partly administrative, and partly based on market-mechanisms, and which have either direct or indirect effects. In the national and international environmental and environmental protection regulations, certain principles became clear in the second half of the 20th century, mainly thanks to the supranational forums similar to the Earth Summit, first held in Rio de Janeiro in 1992. While, as presented below, the regulatory instruments themselves included new solutions as time progressed, the main principles remained basically the same. For example, the European Union regulation rests on four pillars: precaution,41 prevention, rectifying the problem at source and the “polluter pays” principle (European Parliament 2019). Of course, these principles seem to be very broad, so the question immediately arises how an “appropriate” environmental regulation could be formulated that would be able to take these into account. In other words, what are the features of effective environmental 41

As long as no there is no scientific certainty about a given activity but the risk of environmental harm is real, constraints should be imposed.

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regulation? There are widely acknowledged criteria and principles for this that are summarised in Chart 4-8. Chart 4-8: Expected characteristics of environmental regulation

Likely to achieve environmental goals

Cost-efficient

Flexible, lends itself to changes

Needs few governmental resources

Incentivises technological innovation

Source: Author’s own compilation based on Office of Technology Assessment (1995).

Taking the above into account, what type of regulatory solutions are possible? The various and sometimes completely different approaches are best classified based on two aspects, the directness of the regulation (whether it directly affects the polluter or pollution) and the mechanism (whether it is market- or government-driven) (Chart 4-9).

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Chart 4-9: Range of possible environmental regulation approaches

Direct Taxes

Bans and limits

Subventions

Licensing requirements

Emission trading Standards Liability rules

Market based

Administrative

Eco-labels Direction via the financial system

Diclosures

Education, provision of in-formation

Indirect

Source: Authorâ&#x20AC;&#x2122;s own compilation.

In theory, the advantage of the approaches that are as much marketbased as possible is that they minimise the intervention in the functioning of the economy, i.e. the distortion of competition, but their disadvantage is of course their doubtful effectiveness. Very direct regulation theoretically promises better results due to its targeted nature, but its enforcement usually requires more money and resources, and the risk often arises that it is circumvented and the polluting activity is transferred to players that are outside the scope of the regulation. The most administrative (authorities-driven) and most direct interventions traditionally include bans, directives and sanction systems â&#x20AC;&#x201D; 131 â&#x20AC;&#x201D;

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on polluting activities and products. An important criticism levelled at the methods that are referred to in the literature as command-andcontrol approaches is that their uniform requirements do not take into account companies’ compliance costs. Overall, this means a less optimal outcome, since certain players are burdened with disproportionately and unnecessarily high costs. In other words, the given reduction in environmental impact is achieved with a greater sacrifice than necessary (Stavins 2003). A more flexible variation on this approach is goal-oriented regulation, whereby only a final objective is determined for economic actors (for example the total amount of emissions) but companies can act at their own discretion in achieving the given objective. This does not specify the method of adaptation and the opportunity of technological innovation, which may cut the costs of compliance with the regulation, i.e. the growth sacrifice (Office of Technology Assessment 1995). This principle was enhanced with the market-based approach of regulation that increasingly used market mechanisms. Actually taxation (see the previous subchapter) can also be classified here, but the most market-based approach was introduced with carbon trading. The essence of the approach that was first introduced in the 1970s and 1980s in the US to curb air pollution and considered very innovative back then is that it integrates (or more precisely brings back) the focus on profits. Wellperforming companies, which emit below the emission cap, are allowed to sell their remaining quota, so they are encouraged to step up their game on environmental issues. Ideally, environmentally friendly technological investment can be partly financed from their allowance receipts. The common element of taxation and the emissions trading solutions is that they put a price tag on pollution, while economic actors can make a profit-maximising, rational decisions on whether to cut their emissions or pay. This makes them the least costly to society, as they encourage the firms that can achieve the greatest cuts in emissions at the least cost to “undertake” that. However, in theory, according to the famous Coase — 132 —

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theorem, carbon trading can lead to a socially more efficient outcome than taxation (Mariotti 2015).

But do these theories work in practice? Although each country has had different experiences in respect to each harmful substance, and they are not necessarily constant in time, most empirical analyses confirm the greater efficiency of market approaches. One of the most comprehensive studies in the United States found that regulations using the administrative, command-and-control approach to curb air pollution was 22 times more expensive than the market alternative. For example, Anderson (1999) estimated that over a two-year time horizon, cost savings amounting to 2 per cent of GDP could be achieved if the government attained the same environmental “results” with market-based regulation. Recent analyses in China also show that market-based regulation and government subsidies are effective in reducing CO2 emissions and in improving energy efficiency, while in the case of direct and prescriptive regulations these positive results cannot be demonstrated, or only to a very limited extent (Zhao et al. 2015). Although marketbased approaches are more effective overall, Pigouvian taxes have not been widely introduced in this category. An important factor that hindered the latter is that setting the right tax rate is difficult on account of information asymmetry (Hahn–Stavins 2010). There are also mixed experiences with the regulation on selling emission rights (quotas) and emission fees, as they do not always tally with the theory. For example, emission fees are sometimes better able to create sources of finance than to reduce pollution. (It must be noted that sometimes actually regulators’ intentions also remain unclear in this respect.) This relative ineffectiveness is linked to the fact that emission fees are often not high enough (R. W. Hahn 2000, Kerekes 2007). With respect to the carbon trading market, the largest, real-world experiment, — 133 —

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the European Union’s greenhouse gas emission trading scheme, also shows that even a theoretically sound environmental regulation framework can be very difficult to apply in practice. Box 4-1 Carbon trading in practice: the case of the EU ETS

The European Union’s Emissions Trading System (ETS) established in 2005 was created to foster the cost-effective and efficient reduction of greenhouse gas emissions. The ETS’s main principle is to limit the amount of greenhouse gases that can be emitted by capping it and lowering the cap over time. For companies (power plants, airlines and other players from energy-intensive sectors), these allowances are allocated (initial allocation) and they can also be purchased. However, experience from the past almost 15 years shows that the EU ETS has not been able to effectively encourage the reduction of emissions and the innovations necessary for a low-carbon economy. According to relevant analyses, this could be attributable to several reasons, the most important of which was a quite straightforward development: emissions were down on account of the economic crisis that started in 2008 (which is, of course, positive in itself), but this also stifled demand for emission rights (carbon quotas). Therefore allowances accumulated in the system, and market prices became persistently lower (Chart 4-10). The slump in prices posed problems in the short term for the development of the market, but it also jeopardised the achievement of the European Union’s climate objectives (European Commission 2015). Another problem was that certain companies simply relocated to outside the EU and thus also outside the scope of the ETS, so in these cases the reduced emissions presented in the EU data did not entail a cut in greenhouse gas emissions globally (the so-called carbon leakage issue).

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Chart 4-10: Development of carbon allowance prices in the EU ETS (EUR) 35

Euro

2019

2018

2017

2016

2015

2014

0 2014

0 2013

2013

2012

2011

2010

2009

2008

Source: sandbag.org.uk

Experience showed that regulation had to be overhauled. Auctions were introduced and thus, while the amount of allowances continuously diminishes, the emission rights are acquired by companies through an increasingly transparent and competitive process. And the so-called market stability reserve automatically corrects the annual amount to be sold in the auction if the number of emission allowances in circulation exceeds a predetermined range. The most important factor, however, is that the annual decline of total allowances is accelerated. Thanks to the measures, the EU ETS carbon prices started rising sharply, therefore it would be too early to dismiss the viability of the cap-and-trade approach.

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At the other end of the range of regulatory interventions, indirect solutions and those mainly based on market mechanisms can be found. Several environmental regulations rest on disclosures and transparency, following the logic that if the information asymmetry is reduced and the costs of acquiring information sinks, the core stakeholders among economic actors, the customers, the owners or even the lenders, will provide the necessary pressure and incentive to companies. However, the publication of the information that has an environmental impact means a genuine limit only if the stakeholders of the given company themselves consider it as important to protect the natural environment, and that is why they take into account ecological factors in their consumer decisions and during their shareholder voting. Consumer attitude is also a major factor in eco-label regulatory solutions. The essence of these is that the regulators themselves determine qualitative criteria based on which the products and services with favourable qualities (e.g. with respect to the materials used or the production method) can be readily identified by the consumers. In such cases, the regulation fosters the transparency of the products rather than the firms themselves. However, the effectiveness of these market-driven solutions demands an environmentally aware approach from both customers and stakeholders. The latter requires education policy, the public’s education and awareness-raising as indirect regulatory instruments. However, it must be borne in mind that simply passing on information is not enough, since several paradox phenomena appear in connection with green attitudes.

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Box 4-2 Paradoxes surrounding “green” attitudes

Numerous studies have pointed out that there is a major contradiction between the attitudes towards the environment, the declared importance of protecting nature and actually taking action, whether this concerns consumer decisions, voting in elections or the government drafting laws. Without attempting to be exhaustive, here are some contradictions that underscore how difficult it is to create effective regulation: – In economically more advanced countries, environmental awareness is greater (mainly among higher earners), but going forward the ecological footprint is forecast to grow (Lenzen et al. 2007). – At the micro level, there is also a wide gap between individual decisions. According to a large-scale Hungarian study by Csutora (2014), neither the ecological footprint nor the carbon footprint differed significantly in the case of “green”, “average” and “brown” consumers. – Public awareness of climate change has increased in recent years in most countries, and more and more people consider it a disturbing, threatening danger. However, this does not necessarily entail the logically related consequences. For example, based on a recent US survey, while a very high proportion of Americans are concerned about global warming, only a fraction of them believe that it will actually affect their lives (Marlon et al. 2018).

Overall, taking into account ecological problems, it would be hard to argue that recent and present environmental rules are effective. That is why new and innovative approaches need to be found all the time.

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For instance an innovative approach would be based on financial intermediation. The main point of the market-driven approach based on transparency and the (at least hopefully) increasingly green attitude of the public and investors is that the funds allocated by banks, wealth managers and other financial organisations should be channelled into an environmentally more sustainable direction. A logical argument behind this method is that the financial sector provides the lifeblood of the economy, therefore the whole economy or at least a great many economic players could be affected by relatively few actors. Today it is unclear what the prevailing approach will be in the regulations currently pondered and put into place by financial supervisors and central banks. According to a conservative estimate by financial regulators, at best, financial supervisory authorities require financial organisations to measure environmental risks more accurately, and this in itself may lead to fewer or more expensive resources allocated for environmentally harmful activities. Other, more ambitious proposals claim that financial regulation needs to guide loans and investments towards green projects decisively and in a targeted manner. The international dialogue on this is still taking place. The stakes are high, because the funds allocated by the banking, capital and insurance market far exceed the fiscal capacity of governments.

What else might be necessary to take into account, besides the regulatory factors providing sufficient economic incentives and people’s attitudes, i.e. limited rationality? The key issue of the present seems to be international cooperation. Some environmental anomalies are completely local, which means that the harmful activities exert their negative impact in a relatively limited area. Some have a regional impact (e.g. pollution of rivers). However, climate change is a far cry from this from a geographical perspective: greenhouse gases emitted anywhere on Earth contribute to climate — 138 —

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change on the whole planet. In fact, there is often an inverse relationship between emissions and the impact suffered: the countries most exposed to climate change are those that, usually on account of their low level of development, have barely contributed to the emergence of the anomaly over the course of history. Box 4-3 Game theory issues with combating climate change

It is easy to recognise game theory situations in the international efforts to curb or rein in climate change. As pointed out by, among others, Nordhaus (2018), the free-rider problem arises in two ways: first, in the form of the countries that would like to avoid the costly climate measures (but nevertheless gladly enjoy a stable climate) and second, when interpreting the opposition across generations, the current generation is also enjoying a free ride, as it continues its greenhouse gas emissions at the expense of future generations. Since a stable climate is a kind of public good, the topic also offers examples of the tragedy of the commons: there is no appropriate collective interest in avoiding pollution. Similar to the well-known basic game theory situations, the outcome of the decisions by individual nations regarding climate protection measures (in other words the success of climate protection) depends heavily on the decisions of other nations, and the latter, the honouring of the climate protection promises, is not known in advance. The “payoff matrices” of the countries very much depend on how costly it is for them to curb emissions and how vulnerable they are to the consequences of climate change. Accordingly, the prisoner’s dilemma, the game theory situation of the stag hunt or game of chicken, can be traced in the various relations between countries. It is generally true, and so far experience also shows, that in the global climate protection “game”, the countries (or most of them) that act fully in their own national selfinterest do not achieve optimal outcomes for the common good, or even for themselves.

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Therefore environmental (and especially climate protection) regulation needs to be not only efficient and well-planned at the national level but also stand the test of diplomatic and geopolitical games.

Does international cooperation work in environmental regulation? The intergovernmental conferences organised under the auspices of the UN have produced mixed results from this perspective. There are clear success stories (for example, the Montreal Protocol that helped the recovery of the hole in the ozone layer), more or less successful efforts (including the Kyoto Protocol, under which international carbon allowance trading was established and the Paris Agreement that set out a common goal and negotiation process), but in light of the seriousness of climate change, even partial successes are failures. Adopting international regulations is therefore essential, without, to complicate matters, a central regulator. For example, the above-cited Nobel laureate Nordhaus proposed a Climate Club, with appropriate incentives for avoiding free-riding. In his concept, the “members” of the club would pay their dues in emission abatement, while nonparticipants would be penalised (and encouraged to join) with tariffs. The tariffs would, of course, be set in line with the target carbon price (Nordhaus 2018). To sum up, significant progress has been made in the past 50 years in regulations on curbing and preventing environmental anomalies. The traditional command-and-control administrative approaches have been partly replaced and partly supplemented by market-driven, indirect solutions, while raising green awareness has also come into the focus of environmental and education policy. However, it seems that environmental regulations have been unable to keep up with the much faster Great Acceleration presented in Chapter 3 and the exponential growth of the population and the economy. Thus long— 140 —

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term sustainable economic growth requires a globally consistent environmental regulatory framework that is difficult to circumvent, conducive to innovations and more efficient than before, especially in climate change. The optimal mix of this framework should definitely entail green taxes, which will be presented in detail below.

References Anderson, R. C. (1999): Economic Savings from Using Economic Incentives for Environmental Pollution Control. USA Environmental Protection Agency Research Inventory. Csutora, M. (2014): Összegződnek-e az egyéni törekvések? A cselekvés és az eredmény közötti szakadék problémája (Can individual efforts be aggregated? The problem of the action-impact gap). Közgazdasági Szemle (Economic Review), Vol. LXI, May 2014 (pp. 609–625). European Commission (2015): Impact assessment accompanying the document Proposal for a Directive of the European Parliament and of the Council amending Directive 2003/87/EC to enhance cost-effective emission reductions and low-carbon investments. Brussels, 15.7.2015. SWD(2015) 135 final European Parliament (2019): Environment policy: general principles and basic framework. Available at: http://www.europarl.europa.eu/factsheets/en/sheet/71/environment-policy-generalprinciples-and-basic-framework. Downloaded: 04/07/2019. Hahn, R. W. (2000): The Impact of Economics on Environmental Policy. Journal of Environmental Economics and Management Volume 39, Issue 3, May 2000, Pages 375–399. Hahn, R. W - Stavins, R.N. (2010): The Effect of Allowance Allocations on Cap-and-Trade System Performance. M-RCBG Faculty Working Paper Series | 2010-03 Mossavar-Rahmani Center for Business & Government. Kerekes, S. (2007): A környezetgazdaságtan alapjai (Foundations of Environmental Economics). Budapest, Aula könyvkiadó. 238 p., ISBN 978-963-9698-25-3. Lenzen, M. et al. (2007): Forecasting the ecological footprint of nations: A blueprint for a dynamic approach. Sydney University–SEI, Sydney–Stockholm. Marlon et. al. (2018): Yale Climate Opinion Maps 2018. Available at: https://climatecommunication. yale.edu/visualizations-data/ycom-us-2018/?est=discuss&type=value&geo=county#downsca ling-panel-about. Downloaded: 5 July 2019. Mariotti, C. (2015): Theory and Practice of Emissions Trading in the European Union: Some Reflections on Allowance Allocation in Light of the DK Recycling Case. European Papers, Vol. 1, 2016, No 3, European Forum, Insight of 22 December 2016, pp. 1153–1170. ISSN 2499-8249 - doi: 10.15166/2499-8249/94

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4 Ecological sustainability – Green growth Nordhaus, W. (2018): Climate Change – the Ultimate Challenge for Economics. Nobel Lecture in Economic Sciences. December 8, 2018. Office of Technology Assessment (U.S. Congress) (1995): Environmental Policy Tools: A User’s Guide, OTA-ENV-634 (Washington, DC: U.S. Government Printing Office, September 1995) Stavins, R. (2003): Experience with market-based environmental policy instruments in Robert Stavins (eds.), Handbook of Environmental Economics, vol 1, Elsevier Zhao, X. – Yin, H. – Zhao, Y. (2015): Impact of environmental regulations on the efficiency and CO2 emissions of power plants in China. Applied Energy. Elsevier, vol. 149(C), pages 238–247.

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4.3

The growing use of green tax Róbert Hausmann – András Bese Kolok

The reduction of pollution requires economic policy measures, the instruments of which include green taxation. The costs of exhaustion of some environmental resources, such as clean air and oceans, are not passed on to the polluter but are distributed widely across society. Therefore, the price of the polluting activity will be lower than the price that takes into account social costs as well, which leads to overproduction (or consumption) and an excessive environmental impact. Green taxes are instruments that help restore the overall balance of supply and demand in society disrupted by pollution. The economic effect of green taxes takes effect in the long run: they assist in preventing pollution from curbing future growth and indirectly improve public health. Green tax revenues relative to GDP are currently low. The use of green taxation in the form of turnover taxes may promote a shift in the tax regime’s structure towards strengthening competitiveness, if the taxes on labour and capital are reduced as green taxes are levied. Levying and raising turnover taxes on polluting activities allows the taxes on labour (e.g. personal income tax) to drop, which makes production for exports cheaper, thereby improving countries’ external competitiveness. There are more and more good practices for using green taxes. One example of the reduction of emissions is the European Union’s Emissions Trading System, and some American states also employ similar instruments. The Nordic countries and Germany, exhibiting international good practice, are spearheading the introduction of deposit systems. Sweden is attempting to halt soil acidification by introducing a nitrogen oxide tax, while the United Kingdom curbs the amount of waste on landfills with a landfill tax.

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How can environmental sustainability be integrated into economic decisions? The natural environment can also be seen as a resource that is used, among other things, for pursuing economic production and service activities as well as daily life. The world’s population currently uses one and a half times more resources than the Earth can produce with its regenerative capacity. This is demonstrated by the world population’s ecological footprint. The ecological deficit has become so large that 1.7 Earth’s resources would be necessary to satisfy the needs of the planet’s total population. A report 1972 titled “The Limits to Growth” commissioned by the Club of Rome, which first drew attention to the sustainable economy, considered it a fact that environmental resources are finite (Meadows et al. 1972). Some natural resources have a mature market, however, others can be accessed practically free of charge, and this is partly the reason for their overexploitation. A part of our natural environment, such as arable land, forests and minerals have long been considered resources generating income and have long formed a part of advanced market economies. The ownership rights to them is straightforward, their users pay for them and their prices develop in accordance with market conditions. In contrast, other parts of the natural environment, such as clean air, the ozone layer surrounding Earth and, somewhat more abstractly, nature’s regenerative capacity are fundamentally outside the purview of market economies, their ownership rights and thus also their usage costs are not clearly defined. The consumption of environmental resources does not pose a problem as long as they can be regenerated in sufficient quantity and quality. However, they are finite, or their regeneration takes time.

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The natural environment is beset by the so-called tragedy of the commons. This demonstrates that if everyone accesses a certain resource (in this case a common grazing ground), it will be overexploited. This is because individually it is worth it to put some more animals on the common, even if the available food is so scarce that the quality of the total stock out there (or for example the total milk yield of the cows) declines. Generally, the goods accessible by everyone (but available in a limited amount) are referred to in economics as public goods. This includes several elements from the natural environment. For example, at the individual level, environmentally harmful emissions seem to be worth increasing, even if at the national economy or global level this is detrimental. The problem may be easier to solve if a market price is assigned to use. From an economic perspective, the other important feature of the exploitation of the natural environment is that its cost is not usually borne by the person who caused it and benefits from it (which is referred to as externality). Economics textbooks usually illustrate externalities by polluting activities, for example a factory that excessively pollutes water or the air, decreases the quality of life of those living nearby, while this does not mean extra costs for the polluter, and it may even be more profitable than a less polluting procedure using advanced technology. In contrast, under appropriate market conditions, all consequences caused by the producers should be reflected in their costs. By the same logic, negative externalities (and excessive demand) can arise on the consumer side, too, when the price of something is lower than its broader social costs (disposable plastic products, fuel-guzzling vehicles). Here, too, the economic problem is the disproportionate distribution of prices and costs.

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Chart 4-11: Change of the ecological footprint of the world population

1.8

Resources consumed, Earth=1 unit

1.8

1.6

1.4

1.2

1.0

0.8

0.6 0.4 0.2

Ecological deficit

Ecological reserve

0.0

0.6 0.4 0.2

1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

0.0

Ecological footprint of the world population Biocapacity of the Earth Note: On the chart the green line shows the maximal available ecological capacity (biocapacity) of the Earth, the red line shows the ecological footprint of the world population. The unit of measurement is based on how much of the Earth would be needed to satisfy all needs. Source: Global Footprint Network.

Regulatory action is needed against the overexploitation of environmental resources and pollution, and one potential tool for this is taxation. As demonstrated, the reasons behind the overexploitation of the natural environment can be deduced and explained from an economic perspective as well, therefore economic policy tools can contribute to its solution. The UN’s Brundtland Commission dealing with environmental and economic convergence linked the concepts of economic growth and environmental sustainability in their report “Our Common Future” 30 years ago, creating and defining the concept of sustainable development, and ascertaining that well-targeted measures were needed for protecting environmental resources, at the level of politicians, economic actors, civil society and individuals (UN 1987). — 146 —

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Countries are making ever greater efforts to foster regulatory action against pollution, and the regulations may cover a wide range of measures. Pollution can be reduced by legal and financial regulatory instruments. Financial regulation is designed to increase the price of the resource and thus cut pollution. One such form of financial regulation is the levying of taxes on polluting activities or products. Green taxes are formulated to represent the cost of the environmental impact in producer or consumer prices, thereby mitigating the environmentally harmful activity. The example of public goods and externalities showed that the cost of the polluting activity perceived by the polluter (or consumer) is lower than its total social cost. Therefore pollution (and consumption) will be greater than desirable. Individually, many people believe that they benefit, but, mainly on account of those who only share in bearing the costs rather than sharing in the consumption and the profits, the total social utility will be lower than the greatest total social benefit that can be achieved with a regulatory instrument. To attain the optimal balance, the higher cost of pollution should be borne by the beneficiaries. A straightforward solution for this is to levy taxes on production or consumption. Such Pigouvian taxes42 that seek to offset the negative social impact of an activity raise the market price of environmental resources, thereby lowering the polluting activity and the consumption of environmentally harmful products and restoring the balance between total social supply and demand. As the balance is restored, social welfare starts growing again.

Tax type named after British economist Arthur Pigou.

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Chart 4-12: Microeconomic effects of imposing green (Pigouvian) taxes

Note: Values denoted with an asterisk are the result of the introduction of the green tax. Source: MNB.

One feature of green taxes is the double dividend effect, i.e. the diverting effect and the surplus revenue effect. Levying green taxes entails an activity determining effect and a revenue effect, with the latter causing a restructuring of the tax regime, which changes the proportion of taxes within the tax system. The activity determining effect can be seen from the fact that the green tax nudges economic actors to reduce the polluting activity and use more environmentally friendly solutions. The revenue effect simply refers to the surplus revenues from green taxes. These can be used to cut the deficit or reduce other tax types while maintaining the level of the government deficit. If this entails the lowering of the taxes on labour and capital, it has a beneficial impact on competitiveness. The activity determining and revenue effects together are sometimes referred to as the double dividend effect (Williams 2016). — 148 —

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Chart 4-13: Aims and consequences of green taxation

Source: MNB.

The effectiveness of the taxes on environmentally harmful activities depends on how flexibly the producers engaged in the harmful activity and the consumers respond to the levying of the tax. If they are flexible, they will change their activities. This reduces the environmental impact but generates little government revenue (as the tax base contracts). By contrast, if their behaviour is not flexible, the activity changes only slightly, but the government revenue will be higher due to the tax levied on it. In 2012, the International Energy Agency modelled how the structure of the United States’ electricity production would be transformed by the levying of various amounts of carbon taxes. According to the results, if no carbon tax is levied, carbon’s 40 per cent proportion would not decrease considerably in American electricity production. If a 15-dollar carbon tax was introduced, it would fall to 16 per cent in 30 years, and if a 25-dollar tax was imposed, it would drop to 4 per cent (US Energy Information Administration 2012). Supply

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and consumer demand adjust differently to the setting of different tax rates. Chart 4-14: Double dividend effect concerning green taxation

Source: OECD (2006), Williams (2016).

In the interest of economic and environmental sustainability, green taxes need to play a bigger role. According to a study by Van Ruijven et al. (2019), the global energy need could rise by 11–27 per cent in the case of a moderate warming, or by 25–58 per cent in the case of a more vigorous warming. Producing this amount of energy will have a major additional impact on the environment, and the pollution cannot be expected to stop at the border, therefore economic policymakers need to promote energy efficiency using green tax instruments and guide economic actors and households alike towards the use of environmentally friendly energy sources.

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Chart 4-15: Estimated change in energy consumption (2016–2040, million tonnes of oil equivalent)

Source: International Energy Agency (2017).

The impact of green taxes on growth The impact of the introduction of green taxes on growth mainly takes hold in the long run, through the improvement of sustainability. In itself, this impact mitigates the effect of the factors that in the long run curb and slow down growth rather than accelerate it, therefore it helps sustain economic growth. The effect on the economic environment and human resources can be distinguished. It is important, however, that a tax shift based on green taxes could boost the economy and competitiveness even in the short term. The most straightforward is the effect on environmental sustainability. Pollution’s effects hamper growth and increase costs in several fields. The impact is seen directly, for example, in agriculture as the proportion of areas that have become completely arid, and the costs — 151 —

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of the instruments mitigating the effects of global warming (e.g. air conditioning) are considerable. If these negative environmental developments are halted by reducing the environmentally harmful activities, the obstacles to future growth are also eliminated. The decrease in negative environmental effects also has a beneficial effect on labour productivity. Green taxes reduce pollution by making it more expensive to burden the environment, which leads to healthier life conditions and more hours worked through the improved health of the workforce. In 2017, 153 billion working hours were lost due to heat caused by global warming, which was more than double the figure lost in 2000 (64 billion) (Watts et al. 2018). According to a Chinese study, raising energy taxes could lift GDP by 0.06–0.16 per cent through improving public health (Wang et al. 2018). The strengthening of green taxation in the form of turnover taxes may promote a shift in the tax regime’s structure towards bolstering external competitiveness, if the taxes on labour are reduced as green taxes are levied. Increasing the turnover taxes on polluting activities and the reduction of taxes on labour at the same time could lead to a more efficient tax structure (Matolcsy–Palotai 2018). This improves competitiveness by making labour and production for exports cheaper, while reducing polluting activities and the consumption of harmful, often imported, products. This approach can be interpreted in a way that you pay after pollution rather than work (former British Chancellor of the Exchequer and Conservative Party MP George Osborne expressed this in a speech as follows: “Pay as you burn and not pay as you earn.”). In the case of a fiscal adjustment, the tax shift by increasing green taxes distorts the functioning of the economy less than increasing taxes on labour (Barrios et al. 2013). This is because the taxes on labour and capital set back employment and production more than turnover and production taxes, where green taxes belong. The tax base of green taxes, a type of the turnover taxes, is usually larger, therefore the same

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revenues can be collected with a lower tax burden than with the taxes on labour and capital. The beneficial effect is doubled if the revenues from the green taxes are spent directly on environmental objectives. For example, the Irish Environmental Fund established in 2001 uses the environmental tax revenues directly. The receipts from the levies on plastic bags and landfills are paid to the Fund, which uses it for supporting measures related to waste (general systems or producer initiatives), preventing/ reducing the production of waste and the implementation of waste management plans (Government of Ireland 2001). The drop in the use of plastic bags may also help mitigate the expansion of the 150 million tonnes of plastic waste polluting the world’s oceans, which is currently growing by 8 million tonnes per year (World Economic Forum 2016). Chart 4-16: Ocean pollution by plastic waste

Source: Pixabay.com, Needpix.com

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Nonetheless, increasing turnover taxes may entail temporary inflationary effects, therefore green tax rates have to be carefully considered during budgeting. The taxation of polluting activities can lead to price hikes in two ways. First if the polluting product or resource is taxed directly, and second, indirectly, if production is taxed. Using polluting technologies is usually cheaper than environmentally friendly solutions. As a result of the activity determining effect, the consumption of environmentally friendly but more expensive products may also drive up inflation. The introduction of green taxes encourages firms to innovate, and the revenues from the environmental taxes can also be spent on innovation. The introduced environmental taxes may push economic actors to switch from the increasingly expensive polluting activities to other, less polluting ones. Therefore, companies need innovation as well as the human capital capacities, infrastructure and capital that are necessary for innovation. Furthermore, the revenues from green taxes can be spent by governments either directly on promoting innovation to develop environmentally friendly technologies or indirectly through subsidising firms. The positive effect of green taxes on innovation is confirmed by the OECD’s analysis (OECD 2010).

Types of green taxes Green taxes can be classified in several ways. They may be proportionate to value (VAT) or itemised (excise duty), and from a territorial perspective they may be international or domestic. Moreover, they may be punitive, i.e. paid after a given environmentally harmful activity, or they may act as incentives in the form of tax credits. Producer taxes are introduced to curb polluting production technologies or encourage the switching to less polluting ones. The taxes directly

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payable by the producer include the environmental load charge that can be imposed on air pollution, water pollution or soil pollution. This is based on the amount of emitted pollutant or the land area used. The same group includes carbon tax and carbon dioxide allowances (which are not taxes in the narrow sense but behave as taxes in several respects). A third tax type payable by the economic actor performing the activity is the tax on the waste deposited in landfills (household, construction, industrial waste etc.) – the landfill tax – and wastewater fee. Usually, different rates apply to the different materials and pollution levels. Consumer taxes seek to make production less polluting by making consumption more expensive. By raising the taxes and thus the prices of the products the production of which entails greater pollution makes the alternative, less polluting products more attractive. These taxes include the excise duty on fuels, which cuts fossil fuel consumption and could encourage people to use renewables. The setting of the motor vehicle tax and road tolls by environmental classification also serves to curb the polluting effect of transport. The deposits payable by consumers act as a social incentive. Besides taxes, governments also use benefits to involve environmental aspects in economic actors’ decisions. If certain conditions are met on the producers’ side, the government seeks to promote environmental aspects with corporate tax credits. On the consumer side, the same objective can be seen in the tax allowance for the registration of electric and hybrid cars and other measures supporting the use of electric cars (e.g. free parking, subsidised charging).

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How widespread is green taxation nowadays? Compared to other widely used taxes, green taxes are still new. The first version of the personal income tax appeared in antiquity, then it was first introduced in its modern form in the United Kingdom in 1799. The US first taxed corporate profits in 1909, while VAT appeared in Germany and France during the First World War. However, green taxes started cropping up later, in the late 1980s and early 1990s (although Norway introduced a tax on the sulphur content of oil in 1971). Economics started to focus on the taxes for curbing pollution much later than on other tax types. Chart 4-17: Income from green taxes relative to GDP (2016)

4.5%

Note: In the case of missing values, complemented with data from the previously available year (2014, 2015). Source: OECD.

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Green taxes are continuously spreading, but the proportion of revenues relative to GDP is still low. Green taxes amount to merely 5.3 per cent of total tax revenues in OECD countries, representing an amount equivalent to the 1.6 per cent proportion of GDP on average (OECD 2017). To put this into perspective, income taxes and social security contributions were over 17 per cent of GDP, while consumption taxes were over 11 per cent (OECD 2018). In Europe, environmental tax revenues are higher than in the other parts of the world. The top ten countries with the highest proportion are typically European. The world’s economic powerhouses usually have lower shares, for example in the US green tax revenues are less than 0.7 per cent relative to GDP, in China they represent 0.7 per cent, in Japan 1.4 per cent and even in Germany a mere 1.9 per cent. In 2017, the total of the environmental taxes collected by the 28 Member States of the European Union amounted to 2.4 per cent of the EU’s GDP. This amount (over EUR 68 billion) is over the OECD average and represented 6.1 per cent of total EU tax receipts. In the Community, Greece has the highest share of environmental tax revenues relative to GDP at 4 per cent, followed by Denmark and Slovenia with 3.7 per cent. The lowest ratio was in Luxembourg with 1.7 per cent, but it was below 2 per cent in another six EU countries (Lithuania, Romania, Spain, Germany, Slovakia, and Ireland).

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Chart 4-18: Income from environmental taxes relative to all government incomes (2017)

11.2%

Source: Eurostat.

Among green taxes, energy tax revenues are by far the greatest, followed by transport tax receipts. The former amount to three quarters of green tax revenues, while the latter amount to one-fifth. Tax revenues from the environmental impact are usually low; in EU countries they amount to 1 per cent of green tax receipts and resource taxes amount to just 0.3 per cent, and even combined they are a fraction of the other two. However, in some countries, including Hungary, the proportion of environmental load and resource taxes is relatively large. In this respect, the Netherlands tops the list in the European Union with 13.1 per cent, followed by Hungary and Estonia with 10.7 and 10.1 per cent, respectively. In Hungary, this is the result of the air pollution, water pollution and soil pollution charges. — 158 —

4.3 The growing use of green tax

Chart 4-19: Green taxes by sectors (EU28, 2017)

Energy taxes Pollution and resource taxes

Transport taxes Not classified

Source: Eurostat.

Box 4-4 How to tax green?

i) The European Union’s Emissions Trading System The EU undertook to reduce greenhouse gas emissions by 40 per cent relative to 1990 levels by 2030. This is supported by the EU’s Emissions Trading System (ETS), which was established in 2005 and pertains to emissions from industrial activities. Emissions trading systems are not strictly tax measures, but they can be considered tax-type measures. The receipts from the sale of allowances are due to the Member States, and Eurostat, the statistical office of the European Union also classifies these revenues among environmental taxes. The EU ETS, which covers almost 11 thousand heavy energy-using installations and airlines, was the first such system in the world, and it is still the biggest. It sets a cap on carbon dioxide emissions, under which companies can pollute the air in exchange for carbon dioxide allowances, and they may trade the unused

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allowances as they see fit (this is the so-called cap-and-trade system). An allowance entitles the polluter to emit one tonne of carbon dioxide or equivalent greenhouse gas. In the third, current phase between 2013 and 2020 (Directive [EU] 2018/410), a common EU level total allowance was determined rather than the earlier national allowance. This total quota, i.e. the number of allowances issued by the EU, diminishes annually at a predetermined rate (linear reduction factor). The stipulated reduction is 1.74 per cent each year for 2013–2020, totalling 38 million allowances, then from 2021, 2.2 per cent annually, i.e. 48 million allowances. Chart 4-20: The European Union’s Emissions Trading System

Source: Elekházy (2019).

88 per cent of the auctioned allowances are allocated among countries in proportion to their emissions in 2005 or 2005–2007 on average (whichever is higher). Another 10 per cent goes to the ten countries with the lowest income, and the revenues from that need to be spent on reducing their country’s emissions and adaptation to climate change. The remaining 2 per cent of the allowances is also called the ‘Kyoto bonus’, and it is distributed among the countries that by 2005 decreased their greenhouse gas emissions by 20 per cent relative to their own base year or period. These are Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania and Slovakia. Member States need to spend at least 50 per cent of the revenues from selling allowances on climate and energy purposes (in 2015, 71 per cent of all revenues went towards these purposes) (European

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Commission 2017). The money received by the countries from selling the allowances may be a substantial source of extra revenue, and it also has an activity determining effect. Compared to 1990, the EU emitted approximately 22 per cent less greenhouse gases in 2016. Greenhouse gas emissions were over 5.7 billion tonnes per year in the early 1990s, which, after minor fluctuations, dropped to around 5.2 billion by 2005 when the ETS was introduced, then it contracted to 4.4 billion tonnes by 2016. The EU plans to reduce emissions by 21 per cent by 2020 relative to the establishment of the ETS, i.e. 2005, and by 40 per cent by 2030 relative to 1990 (a 36-per cent decrease relative to 2005). The Emissions Trading System helped reduce emissions in EU Member States, although its efficiency was sometimes called into question (when allowance prices were low and there was a significant amount of surplus, but this now belongs to the past, and allowance prices reached historic highs in early 2019). The EU’s allowance trading system is the world’s oldest functioning and most widely used emissions trading system. ii) Deposit refund system in Finland Pollution by product packaging can be effectively mitigated by a wellfunctioning deposit system. A prime example of this is Finland where the deposit on PET bottles, glass bottles and metal beverage cans helped achieve a 95-per cent return rate on metal beverage cans by 2015. The deposit is set by the government, and it ranges from EUR 0.1 to EUR 0.4, depending on the type of packaging, and in the case of a return, consumers get back the deposit paid upon purchase. The system rests on the very close cooperation between the food industry, the retail sector and the government (Ettlinger 2016). The deposit system was supplemented with a beverage packaging tax in 1994 (EUR 0.51 per litre), with an allowance for the packaging companies participating in the deposit system. Although the return rates were high in Finland to begin with, the improvement was remarkable in the year after the deposit was introduced: the return rate of disposable metal beverage cans rose from 59 to 79 per cent, reaching 95 per cent in 2015. After the introduction of PET bottles in 2008, the return

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rate increased from 71 to over 90 per cent in two years, while in the case of glass bottles this proportion has always been over 80 per cent, standing at 89 per cent in 2015. Chart 4-21: Functioning of the Finnish deposit scheme

Source: PALPA.

The deposit system also functions spectacularly in other countries, for example in Germany. Germany also achieved a similarly high return rate (according to the packaging market research society, the Gesellschaft für Verpackungsmarktforschung or GVM, it was 93.5 per cent for PET bottles in 2015) with the introduction of the deposit, which is a flat EUR 0.25 for all disposable plastic bottles. Refillable bottles and glasses are charged a preferential deposit of 8- or 15-cent, depending on their size and material. iii) Nitrogen oxide tax in Sweden Among other measures, the Swedish government sought to reduce soil acidification, an increasingly pressing issue, by levying a tax on nitrogen oxide emissions of stationary combustion facilities in 1992. The measure

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included a reimbursement mechanism that favoured those who emitted less. Partly owing to the tax amounting to SEK 40 per kilogram when it was first introduced (and raised to SEK 50 in 2008), nitrogen oxide emissions in Sweden diminished by 30–40 per cent between 1992 and 2014 (Pedersen 2016). iv) Plastic bag levy in Ireland By introducing a levy on plastic bags in 2002 (EUR 0.15 per bag at first, then from 2007 EUR 0.22 per bag), Ireland managed to cut the share of plastic bags relative to total discarded waste from 5 per cent in 2001 to 0.1 per cent in 2015, and the amount of plastic bags in marine litter decreased from 5 per cent to 0.2 per cent. The charge also transformed the public’s shopping habits, so the measure can be considered as being extremely successful (Anastasio and Nix 2016). v) Landfill tax in the United Kingdom The United Kingdom introduced the tax in 1996 to reduce waste and encourage recycling. The currently effective landfill tax is GBP 2.65 per tonne in the case of non-hazardous waste and GBP 84.4 per tonne in the case of biodegradable waste. As a result of the measure, the amount of waste that ended up in landfills shrank from 50 million tonnes to 12 million tonnes between 2001 and 2015 (Elliott 2016). The landfill tax proved to be a similar success in other parts of the world, for example in South Korea.

References Anastasio, M. – Nix, J. (2016): Plastic Bag Levy in Ireland. Institute for European Environmental Policy https://ieep.eu/uploads/articles/attachments/0817a609-f2ed-4db0-8ae0-05f1d75fbaa4/IE%20 Plastic%20Bag%20Levy%20final.pdf?v=63680923242 Barrios, S. – Pycroft, J. – Saveyn, B. (2013): The marginal cost of public funds in the EU: the case of labour versus green taxes. Európai Bizottság Taxation Papers WP N. 35. Elekházy, N. (2019): Az Európai Unió kibocsátás-kereskedelmi rendszere (The European Union’s Emissions Trading System). Infojegyzet, Országgyűlés Hivatala (Information Note, Office of the National Assembly). https://www.parlament.hu/documents/10181/1789217/ Infojegyzet_2019_9_EU_kibocsatas-kereskedelem.pdf/5582ab18-4c8b-c53b-067c-1d2c195b2022

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4 Ecological sustainability – Green growth Elliott, T. (2016): Landfill Tax in the United Kingdom. Institute for European Environmental Policy https://ieep.eu/uploads/articles/attachments/e48ad1c2-dfe4-42a9-b51c-8fa8f6c30b1e/UK%20 Landfill%20Tax%20final.pdf?v=63680923242 UN (1987): Report of the World Commission on Environment and Development (Brundtland Report), 4 August 1987, https://sswm.info/sites/default/files/reference_attachments/UN%20 WCED%201987%20Brundtland%20Report.pdf Ettlinger, S. (2016): Deposit Refund System (and Packaging Tax) in Finland. Institute for European Environmental Policy. https://ieep.eu/uploads/articles/attachments/9d526526-d22b-4350-a5906ff71d058add/FI%20Deposit%20Refund%20Scheme%20final.pdf?v=63680923242 European Commission (2017): Analysis of the use of auction revenues by the Member States https://ec.europa.eu/clima/sites/clima/files/ets/auctioning/docs/auction_revenues_ report_2017_en.pdf European Commission (2018): Report on the functioning of the European carbon market https://ec.europa.eu/clima/sites/clima/files/ets/docs/com_2018_842_final_en.pdfCommission Regulation (EU) No 1031/2010. https://eur-lex.europa.eu/legal-content/EN/TXT/ PDF/?uri=CELEX:32010R1031&from=IT Decision (EU) 2015/1814 of the European Parliament and of the Council. https://eur-lex.europa. eu/legal-content/EN/TXT/?uri=CELEX%3A32015D1814 Directive (EU) 2018/410 of the European Parliament and of the Council. https://eur-lex.europa. eu/legal-content/EN/TXT/HTML/?uri=CELEX:32018L0410 Government of Ireland (2001): Environmental Fund. https://www.dccae.gov.ie/en-ie/ environment/topics/environmental-protection-and-awareness/environmental-fund/Pages/ default.aspx Matolcsy, Gy. – Palotai, D. (2018): A magyar modell: A válságkezelés magyar receptje a mediterrán út tükrében (The Hungarian model: Hungarian crisis management in view of the Mediterranean way). In: Financial and Economic Review, Vol. 17, Issue 2, pp. 5–42, June. https://en-hitelintezetiszemle. mnb.hu/letoltes/fer-17-2-st1-matolcsy-palotai.pdf Meadows, Donella H. – Meadows, Dennis L. – Randers, J. –Behrens, William W. (1972): The limits to growth, Universe Books, New York. http://www.donellameadows.org/wp-content/userfiles/ Limits-to-Growth-digital-scan-version.pdf International Energy Agency (2017): World Energy Outlook. https://www.iea.org/weo2017/ OECD (2010): Taxation, innovation and the environment, 2010. https://read.oecd-ilibrary.org/ environment/taxation-innovation-and-the-environment_9789264087637-en#page1 OECD (2017): Green Growth Indicators. https://read.oecd-ilibrary.org/environment/greengrowth-indicators-2017_9789264268586-en#page1 OECD (2018): Revenue Statistics 2018, Tax revenue trends in the OECD https://www.oecd.org/ tax/tax-policy/revenue-statistics-highlights-brochure.pdf

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4.3 The growing use of green tax Pedersen, A. B. (2016): NOx and SO2 taxes in Sweden. Institute for European Environmental Policy https://ieep.eu/uploads/articles/attachments/272d334d-c78b-4da6-8e39-f3259a6e8058/SE%20 NOx%20SO2%20Tax%20final.pdf?v=63680923242 van Ruijven, B. J. – De Cian, E. – Wing, I. S. (2019): Amplification of future energy demand growth due to climate change. Nature Communications, 24 June 2019. https://www.nature.com/articles/ s41467-019-10399-3 US Energy Information Administration (2012): EIA projections for the effect of carbon tax on sources of United States electrical generation. World Economic Forum (2016): The New Plastics Economy. Rethinking the future of plastics. http:// www3.weforum.org/docs/WEF_The_New_Plastics_Economy.pdf Wang, B. – Liu, B. – Niu, H. – Liu, J. – Yao, S. (2018): Impact of energy taxation on economy, environmental and public health quality. In: Journal of Environmental Management. Vol 206., pp. 85–92, January 2018. https://www.sciencedirect.com/science/article/pii/ S0301479717310149?via%3Dihub#! Watts, N. et al. (2018): The 2018 Report of the Lancet Countdown on health and climate change: shaping the health of nations for centuries to come. November 2018. https://www.thelancet.com/journals/ lancet/article/PIIS0140-6736(18)32594-7/fulltext?code=lancet-site Williams, Roberton C. (2016): Environmental taxation. NBER Working Paper 22303, June; https:// www.nber.org/papers/w22303.pdf.

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4.4

Investments and green financing Zsolt Mihálovits – Éva Paulik – Attila Tapaszti

89 thousand billion dollars, that is, more than four times America’s GDP of 2018. According to World Bank estimates, an infrastructural investment of this amount would be necessary in the coming decades to meet the target set in the Paris Agreement on Climate Change, i.e., to remain at a maximum increase of 2 Celsius degrees of average temperature. Climate change is one of the biggest challenges facing mankind, the financial dimensions of which also raise extremely complex questions: what incentives, methods and new frameworks would be necessary for the timely materialization of green investments? This chapter will examine financial solutions that are considered novel. Government action is touched upon only in the context of the support for market-based initiatives in the form of regulations and other incentives. Why is it important to emphasise what we are discussing are market solutions? With regards to the huge investment need, many only consider the related costs, which is one of the major arguments against the required intervention. This argument appears one-sided, since costs for one party are revenues for another. Therefore, boosting green investments automatically results in economic growth in the short term. However, efficient capital allocation ensuring the long-term financial sustainability of projects raises more doubts. Markets may have a greater role here, but it necessitates the adjustment of the short-term profit-oriented character of the market mechanism. This is what the new trends are about, aiming at the simultaneous achievement of financial, social and environmental sustainability. Of course, the supply side of green projects and investments is also undergoing significant developments. Due to technological improvements, recent years have seen the increasing competitiveness of renewable energy, posing an ever— 166 —

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growing business challenge for the traditional energy sector. This is also true for other economic sectors, where environmentally sustainable technologies are needed. Renewable energy is only a part of this story. However, it must be understood that the total global economy operates in a given structure, which is mainly built on carbon-based energy, the changing of which exceeds the limitations of simple business mathematics. Therefore, new and competitive technologies do not necessarily spread rapidly. New market trends may have a key role in the latter, from the acceleration of innovation to the proliferation of their market application at the appropriate speed.

Sustainable financial trends in capital markets Can the markets and profit-oriented actors driven by market mechanisms (also) support sustainable growth? It is evident that government action is key in creating the conditions for sustainable growth. Apart from direct intervention (including, e.g., green investment by the state), this would also include market regulation. Therefore, the “external” configuration of the market capital allocation framework may help to channel the funds towards more sustainable economic activities. In addition to this, there are market-based initiatives, which actually encourage the “internal” transformation of the market mechanism targeting an operation which is sustainable and profitable in the long term. It is important that these capital market trends fit perfectly into traditional market frameworks, and basically optimise in the traditional risk-return space. Therefore, these aim at combining the efficiency of the market allocation mechanism with a wider approach taking social and environmental factors into account too. All this in the hope that a situation can be established in the long term that is advantageous for the environment, society and market actors as well, and that the market mechanism, which is often short-term and narrowly-focused, can be improved, too. These trends could be important supplements for state interventions, while market participants and regulators can often establish generally accepted standards together. — 167 —

4 Ecological sustainability â&#x20AC;&#x201C; Green growth

In what follows, two important capital market trends pointing towards sustainable finances will be briefly presented, one being green bonds and the other the ESG (Environmental, Social, Governance) approach. The reasons underlying the trend are multifold. On the one hand, the expected surge of environmental risks and the significant increase in related costs simply force the actors to change: managing climate change risks is also essential for purely financial reasons. On the other hand, the rapid development of green technologies may lead to major business opportunities, although their utilization would take place too slowly due to the huge capital stocks invested in already existing capacities (so called vested interest). Green finance43 may catalyse this change. Apart from these reasons, another important factor is that private citizens, either as investors or as consumers, place ever-growing emphasis on environmental and social factors going beyond short-term profit objectives. Therefore companies, investment funds, and trusts should definitely take the preferences of their clients into account. Last but not least, research to date suggests that the taking of environmental and social factors into account does not lead to under-performance in respect to profitability in the long term, and that this approach would not require altruistic sacrifices. It is important to highlight the increasingly active communication on more sustainable operations between companies and their investors. This is mainly the case for shareholders (e.g., in the form of shareholder resolution) but this can be observed in the case of other financial instruments too. Recent experience suggests that these capital market trends stay permanent and become much more standardised and fundamental. However, the future is full of challenges too. Quite a lot of work and 43

By green finances, we mean financial intermediation based on private resources, fundamentally on a market basis, in which financial, investment and insurance services are - without damaging the principles of risk management - dedicated to environmental sustainability, typically through the financing of investments and projects.

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development is needed to make sure that taking environmental and social factors into account in market decisions goes beyond being a mere marketing trick or an administration burden to be filed obligatorily but without effect.

Green finances – Why and what? Why are green finances needed?

The examination of the operation of the market mechanism is the key to understanding the bases of new market trends. This process contains an assessment from an ethical and philosophical perspective, facilitating an understanding of the interactions between the market, society and the environment. Naturally, the question emerges immediately whether it is a faulty assumption at all to regard the market (the economy) separately from society and the environment. Could this approach not become the cause of the problem itself? The separation of the economy as well as society and the environment resulted in the belief that the single objective of the operation of a company is the generation of profit and an increase in the price of shares while limitations set by society and the environment are only external factors. As stated by Milton Friedman in 1962: “… there is one and only one social responsibility of business, to use its resources and engage in activities designed to increase its profits so long as it stays in the rules of the game” – this is the so-called shareholders’ principle. The rules of the game of course refer to laws and other regulations establishing the relationship between companies and society (employee’s rights, product safety, working environment-related standards, etc.) and the environment (prohibition of pollution, payment of costs, etc.). In such a reflective framework, companies internalise operational externalities only under an external force. If there is no such limitation, then they are not bound to act in this way, and, what’s

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more, it would be unethical to take other factors into consideration than the interests of investors. The so-called stakeholders’ principle (Freeman, 1984) is, in a way, the opposite. It would not deny the profit objective of the company, however, it considers the company itself to be an entity vindicating the interests of a wider group. The group of company stakeholders cannot be determined exactly, of course. In a narrower sense, it usually includes suppliers, customers and employees but, in a wider sense, local society, the environment and all effectively concerned parties belong here. The problem is that even the determination of the relevant stakeholder group is difficult, not to mention the way they can be involved in each decision affecting the company. Who represents each stakeholder group and at which fora? Who can vote at general meetings of the company, with what kind of voting rights, and what is the weight of a party when participating in the decisions? Disregarding these practical obstacles and examining the issue from a theoretical perspective, we can see that operational limitations of the company are determined by the dynamics of the internal groups (Rönnegard et al, 2013). This principle can be considered more democratic – whoever is concerned by the issue should decide – and would envisage a situation which is more advantageous for society and the environment (having a higher total benefit), but its critics highlight the eventual deterioration of the company’s financial performance as an expected disadvantage. The main counterargument is that this deterioration of efficiency would result in an economically less advantageous situation which, in the longer term, would be disadvantageous for the whole of society too. According to the advocates of the “shareholders’” principle, as indicated above, social and environmental effects (advantages and disadvantages) in society should be allocated through political processes, which should be based on a just and sustainable social contract. Therefore, company decision-makers should not reflect on these questions, but only on the profit objectives. The chart below briefly sums up the above reasoning: — 170 —

4.4 Investments and green financing

Chart 4-22: Shareholder vs. Stakeholder

Source: MNB.

The two above-mentioned viewpoints reflect two very divergent opinions. Of course, in reality companies operate combining these to some extent. The main question is whether the two viewpoints can be integrated. Can business efficiency be maintained in an environmentally and socially sustainable way? The two market-based initiatives, that is, green finances and the ESG concept, to be presented by us is an attempt to respond to this challenge. Basically, what we are talking about here is an investorâ&#x20AC;&#x2122;s approach where the taking of environmental and social factors going beyond narrow and short-term profit and asset price maximisation in business decisions is encouraged. It is a very important point that this is not an altruistic approach but is based on the expectation that social and environmental effects will be priced in the long term and influence the value of the company, so, on the whole, the taking of these effects into account will also result in a more advantageous financial situation.

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How does it look in practice? What are the main approaches? The integration of a sustainable approach to the investment process is one of the most important aspects, requiring the highest caution and a detailed analysis. So far, there is no perfect solution to this, but there are several approaches with significant differences between them, regarding implementation. There are three main trends and, within them, several solutions for integration into the investment process44: 1) Socially Responsible Investing (SRI) is the earliest approach that excludes certain industries and activities from the investment universe (negative screening), and therefore not ethically questionable or clearly harmful investments are made, e.g., harmful for people’s health or the environment. 2) The Environmental Social Governance (ESG) based investment approach was formed at the beginning of the 2000s, it does not apply exclusion like SRI, and it does not approach the issue on a moral basis either. The ESG investment approach is based on the recognition that these factors also influence the financial results of the companies concerned. This is already a data-based approach, built on the detailed analysis of several criteria from which it is always the factors relevant for the given industry or company to receive the greater emphasis. There are significant differences between ESG rating agencies with regard to methodology, and it very much depends on the investors what they consider as really important. Ratings are not absolute value judgements. They are more useful for relative ratings within an industry, to identify companies that are laggards or leaders, and make it possible to monitor the changes 44

World Economic Forum, 2014: Impact Investing: A primer for family offices

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in ESG performance for each company. Thus, companies with improving/deteriorating performance can be identified. 3) The impact investing (e.g., green bonds) philosophy differs from the two methods described above. Apart from financial performance, it is expected that the investment in question would have a positive influence on the environment and/or society, and it is increasingly emphasised that this influence should be measurable. For example, the reduction in greenhouse gas emissions is one of these indicators, which can be relatively easily quantified. For the identification and measurement of the positive effect, the UN’s sustainable development goals are often used, that is, examining the realisation of which goals is promoted by the company or investment in question. Chart 4-23: Methods of the practical application of the system of sustainable approach

SOCIALLY-RESPONSIBLE INVESTING ESG INTEGRATION INCREASING IMPACT INTENT, MEASUREMENT, AND REPORTING

„IMPACT INVESTING”

Source: World Economic Forum, Impact Investing: A Primer for Family Offices 2014.

All three approaches can be illustrated by several examples. So far, negative screening (SRI) dominates regarding the quantity of assets under management, partly because this is the most traditional one — 173 —

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and partly because this is perhaps the easiest to introduce. It is less data intensive than ESG, no ESG ratings are required, and the related value-based approach can also be easily explained to investors. At present 25 to 30 per cent of investment takes SRI or ESG factors into consideration to some extent globally, and growth is dynamic. It is important that the three approaches do not exclude each other but rather build upon one another. This is illustrated by the above chart too. Following the value-based exclusion, the ESG rating can be quantified, and the goal could be either an improvement in the overall ESG rating of a certain portfolio or the improvement in specific factors, e.g., an increase in the environmental or social scores could be emphasized. Following this, the goal could be a reduction of some concrete environmental indicators, e.g., the emission of greenhouse gases of the whole portfolio, or the support of some sustainable development goal (SDG). These can be managed within the framework of the optimisation of a portfolio, with several alternative solutions possible. Optimisation should be performed again from time to time since parameters tend to change over time. This approach can be applied for bond and equity portfolios as well. Chart 4-24: The integration of the system of sustainable approach into the investment process

EXCLUSION (SRI)

ESG RATING

IMPACT INVESTING

Based on etichal value

• • • • • • •

Tobacco Alcohol Guns GM plants Pornography Gambling Animal fur

• Exclusion of the worst ESG-rated companies

•

Mitigation of CO2

•

SDG

• Does ESG-rating improve?

•

Other positive impact

• Selection of ESG criteria

Source: MNB.

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What is a green bond and what standards should be met for this? What makes an issued bond green?

The increase in environmental risks and their coming into the focus of economic policy placed new instruments, including mainly green bonds, on the investment map. In the case of green bonds, the relevant funding is spent on a determined investment, which is useful in respect to environmental and energy efficiency. Green bonds facilitate the channelling of capital into environmentally friendly investments, reduce the cost of funding, and create awareness of financial risks related to the environment (Mihálovits–Tapaszti 2018). Since green bonds are only allowed to finance a defined scope of utilization, both the processes are therefore intended to ensure that and the specific utilization of the resources are clearly defined and documented. This provides additional information to the investors on the competency of the given company in control, auditing and project management, which may also support the assessment of the credit risks of the bond. On the other hand, the issuers incur additional costs because of the issuing framework of the green bond, project control, the need to develop and operate internal processes, which is intended to be offset by several positive factors45. The establishment of green bond standards was an important step towards the promotion of green financing. Green bonds had already been issued earlier, from 2007, however, this process was given a major impetus by standardising the requirements of the “green label”. In 2014, the ICMA (International Capital Market Association) established the green bond framework (Green Bond Principles46), which then led to Green Bonds: Country experiences, barriers and options – G20 Green Finance Study Group http://unepinquiry.org/wp-content/uploads/2016/09/6_Green_Bonds_ Country_Experiences_Barriers_and_Options.pdf 46 Green Bond Principles, 2018: Voluntary process guidelines for issuing green bonds, ICMA 45

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a significant increase in green-labelled bond issuance. The green label is intended to ensure that the funds obtained via the bond should only finance specific activities related to environmental protection, and the fight against climate change. The UN “Sustainable Development Goals” programme (SDG) identifies 17 key areas which are indispensable for global sustainable growth (Chart 4-25). The programme includes global challenges like climate change, environmental deterioration, sustainable cities, the protection of waters and the land, and the issue of poverty. There are several areas among these, where green bonds could provide the necessary funding to establish the projects. Chart 4-25: Sustainable development goals as determined by the United Nations

Source: United Nations.

The dynamically growing green financing sphere provides significant capital for the support of SDG areas. Funds raised via the green bond market can be categorised according to the purpose of the investments. The majority of the green bond market is dedicated to the funding of green energy projects, while the second largest category is the funding of — 176 —

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low carbon-emission buildings and transport. Projects funded by green bond issuance also include clear water and wastewater management as well as energy efficiency. So funding from green bond issuance may be utilised in several areas. The next chart published by S&P Global Ratings47 illustrates these project categories and their shares. Chart 4-26: Project categories financed by green bonds 8% 9%

47%

14%

22%

Green energy Green buildigns Water Transport Energy efficiency Source: S&P Global Ratings.

Green bond issuance has started to increase dynamically in recent years. The annual volume of rated green bond issuance grew from USD 1 billion to almost USD 170 billion between 2011 and 2018 (Chart 4-27). Cumulative issuance has been worth USD 521 billion since 2007. The biggest green bond issuers are the US, China and France according to geographical location. Although these instruments represent only a fraction of the whole global bond market, experts see huge upside potential, supported by ever-growing environmental awareness and the 47

Green Finance = Sustainable Finance? – Abhishek Dangra, 30 November 2017 S&P Global Ratings

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fight against climate change. So this trend may continue in the future as well. Chart 4-27: Green bond issuing USD billions

USD billions

180

180 +90%

160

140

120

100

100 +100%

60 +220%

0 2011

2012

2013

2014

2015

2016

2017

2018

Source: Climate Bonds Initiative.

Green finance has become a quasi-permanent topic of international conferences, economic policy meetings and fora in recent years. Green bonds proliferate widely and nowadays the market and state actors both recognise the role these bonds can play in the promotion of sustainable economic development. With increasing environmental risks, the environmental sustainability-related approach of central banks is gaining more traction. Due to these risks, new considerations appear in reserve management, and the scope of investment opportunities has expanded with new instruments. This process may involve an increase in the role of green bonds and the expansion of the ESG approach.

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What are the advantages of green financial products? The example of the green bond There is a growing range of financial products for green purposes and they have extremely colourful parameters. Among these, green bonds are now highlighted due to their standardised character and their history of more than ten years. Therefore, it is worth examining what the advantages and disadvantages are in the application of green bonds as opposed to traditional bonds, from the perspective of issuers and investors. It is an advantage for both that, to a certain extent, green bonds have the capacity to manage climate change-related risks. As we saw previously, the issuing of green bonds forces the given company to examine its operations in light of climate change-related risks, and to continuously reflect on this topic methodically. Apart from this, it is a natural phenomenon that green projects themselves are more resistant to climate change, and that their financial performance correlates positively with the growth of the intensity of climate risks. Similarly to issuers, investors should identify methodically assessed risks, monitor impact reports and, where applicable, communicate more actively with the issuer, etc. What’s more, the performance of green bonds may offset the performance of other portfolio elements exposed to the consequences of climate change. For this purpose, the full ESG profile of the issuing company should be known (e.g., this effect is not realised in the case of “greenwashing”48). Further advantages for issuers are, the wider investor base – green funds are usually considered “buy-and-hold”49 investors – and the soTo perform bogus environmental activities in a misleading way, only for PR and marketing reasons. For example, when a company issues a single green bond and almost the whole activity of the company is related to contamination, without any plan to change it. 49 Investors optimising for the long term who usually keep the given securities until their expiry. 48

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called halo effect, meaning that other non-green bonds of the issuer may be assessed more positively due to the authentic representation of an environmentally conscious approach. As opposed to corporate social responsibility brochures which, in many cases, play only PR roles, the issuing of green bonds demonstrates a more tangible commitment. In certain cases, the so-called “greenium” phenomenon appears, meaning an issue yield somewhat lower in some cases as compared to traditional bonds, which can result in interest savings upon issuing. In addition, green bond issuance improves the ERP (Enterprise Resource Planning) system– for the operation of the previously described GBP (Green Bond Principles) and CBI (Climate Bond Initiative) framework, a more developed and conscious corporate management approach is necessary. Of course, marketing, and the PR effect can also be cited which, optimally, is not the main purpose of issuing. As a disadvantage, high initial fixed costs can be mentioned, resulting from the costs of green bond ratings and the organisation of the internal team who manage the whole process. Another disadvantageous aspect is the possibility of “green default”, that is, risking that the given green projects financed later turn out not to be green, or the raised funds are not used for green purposes etc. It is important to highlight that the “green default” does not automatically imply legal and financial consequences according to the present regulation, however, this could also be detrimental to the credit rating of the given company. As regards the investors, in addition to the advantages described above, that information about the given issuer not available so far becomes public knowledge and, what’s more, this information is mandatorily updated on a regular basis. This may improve the assessment of the traditional credit risk too. Of course, the above detailed phenomena of “greenium” and eventual “green defaults” are disadvantages. The table below sums up the above:

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INVESTORS PERSPECTIVE

ISSUERS PERSPECTIVE

- Instrument providing hedge against climate change risk - More data, comprehensive information about the given company, active dialogue – it could help in traditional credit risk management as well - Changing attitude among the clients – (GEN Y and younger generation are active in this area) - Marketing, „signaling effect”

- Instrument providing hedge against climate change risk - Increasing the investor base – green funds, dedicated buy and hold investors - Halo-effect - Possible „greenium” - Encouraging climate risk awareness that has impact on the whole operation of the company – it means real reputational risk, there is „skin in the game” - Improving the internal processes, corporate governance, ERP - Marketing effect

- Possible „greenium” - Reputational risk, „green default” risk

- Because of the relative considerable initial fix costs (eg.: external reviews, building internal teams, ERPs) economies of scale matters – it makes no sense to issue only one green bond - Reputational risk, possible „green default”

CONS

PROS

Table 4-1: Green bond: Pros and Cons

Source: MNB.

On the whole, it can be said that green bonds have characteristics that are the same as or close to those of traditional bonds with regard to financial performance, but it can still be considered a smaller, less liquid market due to the relative novelty of the instrument. In the near future, certain events (e.g., the “green default”) may well test the viability of the market but market actors have already prepared for this due to increasingly accurate standards and rating obligations.

What are green bond standards and rating agencies good for? Is continuous development the key? In the case of dedicated green investments, it is of fundamental importance to ensure that funds raised with a given instrument (e.g., green bond issuing) only be used for green objectives. Therefore, those activities should be identified first which, given the present — 181 —

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technological development level, qualify as ones with green objectives. This mainly includes activities positively contributing to the fight against climate change, however, there may be objectives which are not directly related to the emission of greenhouse gases but the underlying environmental intent supplements it or goes beyond it. From among these, it is worth highlighting sustainable water management, the support of the circular economy, waste management, pollution reduction and so on. In general, green activities can be categorised along two lines: the degree to which they reduce or mitigate environmentally harmful effects and the degree to which they increase adaptation or resilience to the inevitably changing environmental effects. This latter is a category that is more difficult to grasp since while mitigation can be relatively well spotted and measured by the CO2 reduction effect of the given activity, adaptation can be determined by defining the expected negative effects and the appropriate responses to them. Therefore, adaptation greatly depends on the location and the context, shifting the focus of the necessary analyses to a somewhat qualitative direction. The following table lists those climate risks that require adaptation from the actors (EU Taxonomy, 2019). The table classifies physical risks in two dimensions – chronic (slow process) and acute (extreme, disastrous): Furthermore, any activity can have green business objectives which, albeit indirectly (e.g., an industrial patent which can be used for an activity meeting the above criteria), contributes to the above purposes. As highlighted above, the first step is to determine a list of green activities accepted by the economic and social actors, elaborated according to a methodology approved by the technological experts in the given area. The aim is to achieve the most objective taxonomy, but naturally these can have political aspects and, of course the experts do not necessarily agree on everything. So consensus-based decisions may not be satisfying for all (for example, one such controversial issue is the assessment of nuclear energy). — 182 —

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Table 4-2: Classification of climate change physical risks

ACUTE

CHRONIC

TEMPERATURE

WIND

WATER

SOLID MASS

- Changing tempera- - Changing wind ture patterns - Heat stress - Temperature variability - Permafrost thawing

- Changing precipitation patterns and types - Precipitation and hydrological variability - Ocean acidification - Saline intrusion - Sea level rise - Water stress

- Heat wave - Cold wave - Wildfire

- Drought - Heavy precipitation - Flood - Glacial lake outburst

- Avalanche - Landslide -Subsidence

- Cyclone, hurricane, typhoon - Storm - Tornado

Coastal erosion Soil degradation Soil erosion Solifluction

Source: EU Taxonomy, 2019.

There are different taxonomies on the market (e.g., the list of the Climate Bond Initiative50, and the EU taxonomy), which describe activities qualifying as green in a quantifiable way, broken down by sector in detail. For example, sectoral breakdown means seven sectors and 67 different economic activities in the case of EU Taxonomy, for which requirements were elaborated one by one. It is very important to point out that the path of ensuring the transition to the “low carbon” economy is also extremely important. Therefore, it is not only zeroemission activities that can qualify as green but also low-emission activities that could lead to zero-emission eventually. Recent standards (e.g., EU taxonomy) try to cover the whole life cycle of the given activity, setting basic social requirements (especially those relating to the conditions of the workers), which actually amount to a kind of ESG screening. Besides this, the so-called “do no significant harm” – DNSH principle has considerable weight in the EU taxonomy, being an important 50

https://www.climatebonds.net/standard/taxonomy

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filter for the assessment of the activities, since it implies a valuation from a higher perspective. We can easily recognise its importance: let us assume that a solar power plant is built in the habitat of a protected animal or in another nature conservation area. Such an investment would hardly qualify as green, although the targeted metrics (CO2 reduction) could be achieved. Therefore, the DNHS principle ensures that not a single environmental or climate change-related objective and activity contradicts another, serving as a kind of “mortar” in the taxonomy which, otherwise, is very diverse. The chart below illustrates the reflection framework (EU Taxonomy Technical Report), which serves to guarantee the principles detailed above: Chart 4-28: Process of prior screening (DNSH) DUE DILIGENCE

DOES THE ACTIVITY PASS DNSH? NO

DOES NOT PASS THE TAXONOMY

YES

DOES THE ACTIVITY PASS MINIMUM SOCIAL SAFEGUARDS? NO

DOES NOT PASS THE TAXONOMY

YES

✔

Source: EU Taxonomy, 2019.

The next important question is what are the internal and external processes to ensure that funding raised for green purposes is invested only according to the pre-set objectives. In the case of green bonds, the most common standard to be considered as a starting point is the GBP being the framework elaborated by industrial actors under the auspices of the ICMA. Green bond issuers adapting the GBP commit themselves to follow the guidelines in a transparent and documented way in their internal processes. The framework elaborated by the CBI — 184 —

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would supplement the GBP with the necessity to use an external rating agency, after which an official CBSB (Climate Bonds Standard Board) green bond rating is issued. The table below describes the main points of the two frameworks. Table 4-3: Main parameters of GBP and CBI frameworks THE GREEN BOND PRINCIPLES

CLIMATE BONDS INITIATIVE

Proceeds can be exclusively applied to sustainable green projects – this should be appropriately described in the documentation. („use of proceeds”)

The sustainibility of GBP is zero condition

The process by which the issuer ensures the + external, independent review is necessary compliance with the framework, sustainability objectives („evaluation & selection”) The framework should enable to track the + sector specific criteria (low carbon & proceeds and verification. („management of climate resilient) proceeds”) Issuer should make and keep readily available information on the use of proceeds („reporting”)

+ independent Climate Bonds Standard Board certificate

Source: GBP and CBI.

The proposed EU green bond framework is virtually the same as the CBI. Naturally it differs in that it is based on the EU taxonomy and not on the CBI taxonomy, and there is one more important difference: it is expected that only EU-accredited rating agencies will be allowed to perform the rating process. Rating agencies may consider several aspects and depths of the green bond “life cycle” and therefore the industry is segmented into various actors and tasks. The main task is to ensure credibility, which can involve every detail from the assessment of the internal processes, through the general ESG rating of the issuer to the exhaustive evaluation of each project. On the whole, the aim of the extensive range of green taxonomies, green bond frameworks and external ratings is that funding raised by the — 185 —

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given bond serves a green purpose to the utmost certainty. One of the most important tasks of the forthcoming period will be to ensure the integrity of the green bond market.

ESG – A financial approach useful for both society and the environment? What is the aim of the ESG approach?

The ESG (Environmental, Social, and Governance) approach means that factors going beyond the traditional financial analytical framework are taken into consideration during the investment process. ESG is the analysis of the way a given company influences its environment (water, raw materials, energy use, waste production, recycling) and the community of its location (treatment of employees, suppliers, consumers) during its operation, and what its corporate management practice is like (transparency, management structure, composition of the board of directors, manager’s compensation, etc.). ESG is basically a market-based approach, that is, its main purpose is Chart 4-29: Main pillars of the ESG approach

Environmental, Social, Governance

• resource-use • emissions • innovation

• workforce • human rights • community • product responsibility

Source: MNB / MSCI.

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• management • shareholders • CSR strategy

4.4 Investments and green financing

to determine opportunities and risks with economic advantages and disadvantages. Therefore, the examination of ESG factors can allow for the improvement of market effectiveness. The main pillars are broken down into the most tangible and quantifiable aspects. Each category is taken into consideration with a different weight when determining the ESG score, so the process is similar to credit rating, its final result being an ESG rating. The aim of the sustainable business model is that the company does more than merely follow the other market participants in a changing environment. It should also be able to anticipate new consumer demand and regulatory challenges, and be more successful in business, through this. It can be demonstrated that share prices of leading ESG companies perform better than those lagging behind. So the mainstreaming of ESG criteria within the company is more than just a marketing label. ESG integration is a complex process with higher data and analysis needs that have undergone dynamic improvement in recent years and which is continuously developing and changing. It has detectable financial advantages, it reduces risks and therefore it can be expected to proliferate globally and become an organic part of the investment process. And those companies that are late in integrating it into their investment process will lag behind. It is only the beginning to take ESG ratings into consideration in a practical application; investorsâ&#x20AC;&#x2122; preferences determine the ESG factors that are the most important for them beyond this. Due to major differences between ESG ratings, they often take several ratings into consideration. It can also be the case that investors buy only the raw data from the rating agencies to develop the ESG rating of each company according to their own preferences. Ethical investment aims at avoiding companies that would harm the moral policies of investors. Such ethical aspects appear in the ESG approach, too, but the basic principles of ESG investing go beyond â&#x20AC;&#x201D; 187 â&#x20AC;&#x201D;

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the mere exclusion of companies that act unlawfully. Investors try to assess risks and opportunities presented by environmental, as well as social and corporate management considerations. Therefore, it is often called sustainable investment.

Objective, quantifiable, measurable or subjective? The standard issue. There are still significant differences among ESG ratings both in their methodologies and in measurement and weighting issues. In general, ESG rating agencies and data providers try to stress objective and measurable indicators. However, compared to green bonds, the ESG concept is less standardised, and has no generally accepted minimum standards. This carries major risks for the investors since the mere application of ESG on some level would not reveal much about the attitudes of the given company or investment fund related to environmental, and social risks and opportunities. This would require a comprehensive context-depending on the examination of the given ESG framework. Therefore, many institutional investors buy only data produced by certain rating agencies to produce the rating themselves according to their own values and investment criteria. Aware of the above challenges, the rating agencies try to deliver their opinions using the most exact procedures possible. The main pillars as described in the previous chapter are broken down into hundreds of raw ESG indicators on a case-by-case basis. These can be both qualitative and quantitative, and the aim is to examine the given ESG topic from as many perspectives as possible. For example, indicators of the Natural resources sub-point of Environment as a main pillar can be data related to water management, e.g., whether the company operates at a geographical location rich in or lacking water, its related water consumption, the efficiency of its water use in proportion to production, the method of cleaning, etc. It can also include indicators related to biodiversity (whether the company poses a risk in this regard, whether â&#x20AC;&#x201D; 188 â&#x20AC;&#x201D;

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it pays attention to this, whether it has disputes or legal cases) or to raw material acquisition principles (whether the company takes into consideration how sustainable the source of the production of a given raw material is, what kind and amount of quantifiable contamination it produces, etc.). It is important that the topics mentioned are broken down into as subtle and tangible units as possible. This would make up as many as one thousand raw indicators applied by certain rating agencies. Indicators are weighted according to the principle of materiality to be discussed later. This means the selection and ranking of criteria exerting the highest influence on the financial performance of the given company. The question of timescale is another factor to be pointed out. Certain rating agencies outweigh those effects which have the potential to influence the operation of the companies in the relatively short term, including within two or three years. Ratings produced from raw indicators mean a relative position within the industry. Contrary to credit ratings, a given rating can be interpreted only within a given sector. E.g., a high rating in the oil industry cannot be compared to the possible lower rating of a sustainable energy company. Naturally, the latter is probably much less harmful environmentally, but it could be the case that it does not pay so much attention to waste management as other companies within the industry. So the ESG rating is of companies which “behave in the best way” within the sector. It cannot be interpreted in an absolute sense, across sectors. It is this very feature thanks to which the ESG approach is often combined with the full exclusion of certain sectors from the investment universe. The exclusion of whole sectors is contradicted by the fact that almost all industries are necessary for the smooth realisation of the transition into the carbon-free economy. E.g., Investors who integrate ESG can play a very important role even in the expansion of the sustainable operation of the best oil companies. Exclusion, if it is progressive in time, is supported by the argument that certain sectors may fully disappear during the transition to a carbon-free economy. So the gradual reduction of exposure towards companies, the assets of which are expected to devalue, is key for financial reasons too. — 189 —

4 Ecological sustainability â&#x20AC;&#x201C; Green growth

In the future, the development of the market and the achievement of a real, additional positive effect will possibly necessitate a certain level of standardization in ESG standards, including the setting the minimum requirements. Industry and science are developing extremely quickly and, due to the huge quantity of available data and those to be processed, the emergence of the big data51 and AI (artificial intelligence) methods could bring about revolutionary progress. However, a sharp increase in the quantity of data does not automatically mean that the quality of decisions would improve.

How does the ESG approach support a more efficient capital allocation? The concept of efficient capital allocation can be interpreted on several levels and in various temporal dimensions. According to the advocates of the ESG theory, apart from an allocation which is absolutely shortterm focusing only on profit and asset price increase, the application of ESG indicates increasing efficiency both on an economic and social level. It is important to point out that the ESG approach could improve not only the quality of investment allocation decisions among companies, but also the allocation decisions within companies. In the long term, the two aspects may meet since investors applying ESG will prefer companies where available resources are distributed among the projects by the management according to ESG criteria. The basic assumption of the ESG model is that a higher quantity of more detailed data will lead to better decisions, a more sustainable operation and a better risk profile, involving the improvement of efficiency (Clark et al 2015). This would necessitate well-structured authentic data from various sources, which is supported by a growing number of company publications and reports becoming increasingly standardised. The other supporting factor is the development of big 51

A technology allowing for the efficient processing of complex data of high quantity.

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data / AI which allows for the management of data that are available in huge quantities, not structured and not published by the given company (e.g., satellite data, data of sensors, media news etc.). Naturally, there are relevant but unavailable data, however, their quantity is expected to reduce in the future. However, the other important question is what can be considered to be relevant data to be monitored with the given company, for a given asset category? The starting point and also one of the central elements of ESG analyses is the question of materiality (relevance), that is, which are those from among the huge quantity of available data that should be integrated into the decision. The most common market approach is the application of the socalled financially material data which emphasises the market-based character of this approach, that is, the ESG would not go beyond the market framework, with the financial incentives being unchanged. But what can be considered material? To sum up: each and every factor that has a significant effect on the market price, the value of the given instrument or what is expected to exert such an effect. For this purpose, so-called “materiality maps” that are widely accepted and considered objective were formulated, to serve as compasses for investors and companies. Materiality maps usually depict financially relevant factors broken down by sectors (e.g., ESG criteria that are relevant for an oil company or an IT company are very different). The following table illustrates factors that are highly important for each sector in the case of the SASB52 (Sustainability Accounting Standards Board):

https://materiality.sasb.org/

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4 Ecological sustainability – Green growth

Table 4-4: Examples of SASB sector materiality map INDUSTRY

TOPIC

METRIC

Real Estate

Energy Efficiency of Buildings

Energy consumption intensity of portfolio

Airlines

Environmental Footprint of Fuel Use

Total fuel consumed, percentage renewable

Oil & Gas

Reserves Valuation & Capital Sensitivity of reserves to Expenditures carbon pricing, estimated emissions embedded in reserves

Automobiles

Fuel Economy & Usephase Emissions

Sales-weighted average passenger fleet fuel economy, consumption, or emissions, by region

Banking & Insurence

Vulnerability of Assets to Climate Change

Amount and percentage of lending and project finance that employes integration of sustainability factors

Source: SASB53

The major reason for applying the ESG approach is to explore risks and opportunities arising from market failures, that is, the insufficient pricing of external costs, by expanding ESG criteria used for the decision. However, the focus on financial materiality also implies the assumption that the market will still be able to price such risks appropriately in the long term. Therefore, these highlighted factors should be monitored because this will influence the profitability of the company and its share/bond prices. Historical data support this assumption to the extent that a significant part of the research work suggests that the application of the ESG approach has exerted a positive or neutral effect on the development of asset prices, that is, it does not sacrifice the yield, which is one of the most important arguments for the application of the ESG approach.

Getting ready for SASB: A deep dive into SASB’s Industry-specific sustainability standards, 2016

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But if only the priced ESG criteria, which have a financially material effect, are taken into consideration by the investor/corporate manager even now, how would the quality of capital allocation improve as compared to the present status in respect to the environment and society? What is the added value of ESG? ESG promises to create “win-win” situations that are mutually beneficial. This means that something that is good from a financial perspective is good from an environmental/social perspective too, subject to the consistent application of ESG. So what can improve capital allocation? On the one hand, it may happen that the market prices environmental/social effects, but far from being of adequate depth, while the taking into consideration of ESG criteria, which are available in better and better quality and quantity, may increase the value of the “ESG premium”. On the other hand, the proliferation of ESG also implies a self-fulfilling prophecy effect: the more people apply it and enforce its usage, the more it would appear in prices, which would lead to over-performance as regards investment/corporate effectiveness. It is important to stress that the application of the ESG concept in itself is far from being sufficient for managing risks related to climate change and social problems. It could fundamentally facilitate the making of additional regulations, if other ESG data that are not material from a financial perspective but are available in better and better quality and in an increasing quantity, for the fine-tuning of the framework. This could also improve the correct pricing of external costs and their more just redistribution within society too. Therefore, the ESG approach and data have much potential in the context of capital allocation and traditionally interpreted financial efficiency, but its application could result in improved efficiency in a wider sense too.

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Green investments, ESG: what does the future hold? Climate change is one of the greatest problems of the 21st century and market solutions are given an ever-increasing role in the fight against it. Recent years have seen several initiatives to internalise the risks of environmental destruction and climate change into the financial system. Green bonds and the ESG approach have started to proliferate globally to a significant extent. Nowadays, both the market actors and the regulatory authorities recognise the role of these instruments in the promotion of sustainable economic growth and the exploitation of market opportunities. Several initiatives have been launched to support the expansion of the market, with the potential to be combined in a generally accepted framework. The determination, quantification and harmonisation of the standards have only just begun. Parallel to this, more thorough and more accurate analyses can be expected thanks to the development of information technology. Regarding green bonds and the ESG alike, one of the indicators of a successful future operation is the number of investments realised which, otherwise, could not have been financed and therefore could not have been realised or only partially (“additionality”). That is, such concepts bear real added value only if they help to create additional green and socially advantageous projects. Apart from this, investments that have environmentally and socially significant negative effects should be examined that have not been materialized due to the new approaches. As we can see, such success criteria cannot be measured inherently, but the knowledge of this factor would already improve investor decisions. It may be a vital issue in the decades to come how such green investments can be spread and permanently stay in investor’s focus and the extent to which they can contribute to the solution of climate related challenges.

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Box 4-5 The Green Agenda of The Magyar Nemzeti Bank

The Magyar Nemzeti Bank (the Hungarian Central Bank or MNB) started a comprehensive green programme to facilitate the reduction of risks related to climate change and other environmental problems, and the enhancement of green financial services in Hungary, widening the related Hungarian and international knowledge base, and further reducing financial participantsâ&#x20AC;&#x2122; and its own ecological footprints. The programme consists of three pillars: first, various initiatives cover the financial sector, second, the development of the social and international relations of the Magyar Nemzeti Bank and, third, the further greening of its own operations. In the first pillar, the Magyar Nemzeti Bank as a supervisory authority prepares impact assessments on the possible effects of climate change and the transition to a climate-friendly operation of the economy on financial markets. The majority of such effects have not yet been explored. Based on the analyses, the MNB will provide guidance to financial institutions, if necessary, by issuing recommendations in order to reduce existing risks. The Bank will also encourage the greening of Hungarian financial institutions and their products. By taking regulatory and marketbuilding actions, the Magyar Nemzeti Bank makes efforts in order to increase the volume of green lending and investments and to encourage the proliferation of dedicated green financial products on the market. Regulatory incentives are supplemented by actions such as the Green Finance Award granted to Hungarian financial institutions by the Magyar Nemzeti Bank in 2019. This is based on the extent to which environmental considerations appear in the business policy and operations of the market participants applying for the Award. Within the framework of the Green Programme, under the second pillar, the central bank undertakes a role in the development of education and awareness-raising related to climate-friendly finances. Therefore, green

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finance appeared not only in the financial expert training provided by the Budapest Institute of Banking but also in the educational and research activities of several Hungarian universities. The Magyar Nemzeti Bank also takes an active part in the work of Hungarian and international forums dedicated to the reduction of environmental risks through the use of financial instruments. As the first Central European member, the central bank therefore joined the international organisation established to green the financial system (Network for Greening the Financial System, NGFS) in January 2019. The NGFS was established by several of the world’s leading central banks more than a year ago to promote funding and investment programmes to foster environmental sustainability and to map out the effects of risks associated with climate change. Under the third pillar, the Magyar Nemzeti Bank takes measures to further reduce its own ecological footprint, and improve its own transparency related to environmental issues. The central bank is externally audited at present, operating a developed eco-management and auditing system. Moreover the bank has recently obtained the Green Office qualification and wishes to maintain it.

Green Bond Portfolio As part of the Green Programme, the Magyar Nemzeti Bank was one of the first central banks to establish a dedicated green bond portfolio within its foreign exchange reserves in July 2019 and has already started to build up the portfolio. The mitigation of the negative impact of climate change and adaptation to changes are forecast to be two of the most important tasks facing the international community. The establishment of a dedicated green bond portfolio supports the development of the market, is in accordance with the recommendation of the most important relevant central bank forum of

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4.4 Investments and green financing

which the Magyar Nemzeti Bank is a member (NGFS) and it also indicates the commitment of the Magyar Nemzeti Bank towards international cooperation. As a result of this decision, the Magyar Nemzeti Bank would be one of the first central banks to mainstream sustainability aspects in their reserve management by establishing a dedicated portfolio. The portfolio will hold bonds that meet international green standards and the traditional reserves management principals bearing the so-called ‘green label’, where the issuer uses the funds raised to finance specific ‘green’ investment projects that bring environmental benefits. The decision to create a dedicated green bond portfolio is in line with the social responsibility and environmental strategy objectives of the central bank. Although the portfolio will include only foreign securities, the Magyar Nemzeti Bank attaches particular importance to the development of green finance in Hungary. The central bank published its regulatory plans aiming at the expansion of financial products supporting environmental sustainability in July 2019. These may also help launch the Hungarian green bond market.

References CFA Institute / PRI, 2018: Guidance and case studies for ESG integration: Equities and fixed income. EU Technical Expert Group on Sustainable Finance: Taxonomy. Technical Report, 2019. Freeman, R. E. (1984): Strategic Management: A stakeholder approach. Boston, Pitman Series in Business and Public Policy. Gordon L. Clark – Andreas Feiner – Michael Viehs, (2015): From the stockholder to the stakeholder: How sustainability can drive financial outperformance. University of Oxford & Arabesque Asset Management. Mihálovits – Tapaszti (2018): Zöldkötvény, a fenntartható fejlődést támogató pénzügyi instrumentum (Green bond, a financial instrument that supports sustainable development), Pénzügyi Szemle. Sherwood, W. M.– Pollard, J. (2019): Responsible Investing, an introduction to environmental, social and governance investments. Routledge NY. Rönnegard, C. (2013): Shareholders vs. Stakeholders: How liberal and libertarian political philosophy frames the basic debate in business ethics. Business & Professional Ethics Journal, 183–220.

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4 Ecological sustainability – Green growth World Economic Forum (2014): Impact Investing. A primer for family offices, http://www3.weforum. org/docs/WEFUSA_FamilyOfficePrimer_Report.pdf Internet sources (downloaded on June 2019): https://www.thebalance.com/a-short-history-of-socially-responsible-investing-3025578 https://www.forbes.com/sites/georgkell/2018/07/11/the-remarkable-rise-ofesg/#4e72bfa51695 https://www.cfainstitute.org/en/about/press-releases/2019/new-report-highlights-bestpractices-in-esg-integration-across-emea https://www.unpri.org/investor-tools/guidance-and-case-studies-for-esg-integration-equitiesand-fixed-income/3622.article https://www.climatebonds.net/standard/taxonomy https://www.icmagroup.org/green-social-and-sustainability-bonds/green-bond-principlesgbp/ https://mnbtanszekblog.hu/2018/11/23/tarsadalmi-es-kornyezeti-hatasu-befektetesek-esgures-hivoszavak-vagy-szuksegszeru-valtozasok/ https://www.msci.com/documents/10199/123a2b2b-1395-4aa2-a121-ea14de6d708a https://materiality.sasb.org/ https://www.un.org/sustainabledevelopment/sustainable-development-goals/ https://www.climatebonds.net/resources/reports/green-bonds-state-market-2018 https://us.spindices.com/indexology/esg/a-look-inside-green-bonds-combining-sustainabilitywith-core-fixed-income https://www.morganstanley.com/ideas/green-bond-boom https://www.worldbank.org/content/dam/Worldbank/document/Climate/ FinanceClimateAction_Web.pdf

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Demographic changes in the world

5.1

Economic challenges of ageing populations Emese Kreiszné Hudák

The two most important megatrends of global demographic processes are the increase in the global population and population ageing. In the decades to come, the increase in life expectancy and the gradual decrease in the fertility rate may result in historically unprecedented demographic changes. The world’s population may increase to a peak reaching 10 billion in the middle of the century, however, population dynamics is expected to show significant differences from one continent to another. The greatest population increase is expected in Africa, where the population may double between 2015 and 2050. Europe may be the only continent where population will decrease in the coming decades. Population ageing can be observed in every part of the world. In the future, the number and proportion of elderly persons may increase significantly on every continent. The unprecedented growth in the number of the elderly population is a global challenge: between 2015 and 2050, the number of those aged 60 and over in the world may increase from 900 million to 2 billion. Demographic processes may have significant economic consequences: transform the labour market, affect labour productivity, change consumption and savings rates and reorganise the production structure, these may increase the impact on the environment. However, less developed countries with an increasing population and those that are economically developed but more seriously affected by the population ageing face different challenges. It will be a challenge in developing countries for people of working-age to get proper jobs in the coming decades while in countries with decreasing populations, the management of labour shortages may require appropriate economic policy measures while long-term increase of productivity may become a priority. In the long term population ageing may have unfavourable effects on growth opportunities in several respects. However, proper economic policy preparation — 201 —

5 Demographic changes in the world

may mitigate such effects and ageing may offer opportunities that can be potentially utilised in certain economic areas.

For how long and in what way might the Earth’s population increase? One of the most important megatrends of global demographic processes is the increase in the global population. The population of the world may continue to increase in the decades to come, but divergent trends are expected from one continent to another.54 Global population may increase by 2 billion between 2019 and 2050 and may approach 10 billion in 2050. However, the rate of population growth could decrease in the coming decades: while the population grew by an average of 1.2 per cent between 2010 and 2015 annually, the annual average growth rate may decrease to below 1 per cent in the first half of the 2020s while it could be close to 0.5 per cent in the second half of the 2040s (UN 2019a). Based on the UN’s population forecast (2019), the world’s population could continue to increase until 2100 to reach its maximum value of 11 billion people at the end of the century (UN 2019b). From among the continents of the world, population is expected to grow the most dynamically in Africa due to the high fertility rate and the increase in life expectancy. The population of Africa may expand from 1.2 billion to 2.5 billion between 2015 and 2050 and exceed 3 billion in the first half of the 2060s. By comparison, in Asia the population may increase to a lesser extent, from 4.4 billion in 2015 to 5.3 billion. Europe may be the only continent where the population could decrease: Europe’s population may fall below 700 million in the second half of the 2050s from 743 million in 2015, due to the low fertility rate.

We present the expected development of global demographic trends based on the findings of the 2019 UN Population Prospects (UN 2019a).

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The fall in the fertility rate is a global trend, albeit with significantly differing fertility rates from region to region. The average number of children by one woman was around 5 in 1950 to 1955, but this rate decreased to 2.5 by 2010 to 2015 (Chart 5-1). This means that 100 women would give birth to 250 children during their lifetimes to maintain this fertility level. In regions of higher income, that is, Europe and North America, the fertility rate does not reach 2.1, the value necessary for the reproduction of the population. The proportion of countries wishing to increase the level of the fertility rate with government measures is the highest in Europe (66 per cent) (UN 2017a). As opposed to this, 83 per cent of African governments introduced measures targeting the reduction of fertility rate. According to UN forecasts, the average number of children by one woman may decrease from the present 4.7 to below 3 in the first half of the 2050s in Africa (UN 2019a), as a result of which the growth rate of the population may gradually decrease in several decades. Chart 5-1: Fertility rate in the regions of the world, 1950â&#x20AC;&#x201C;2055 7

Children per woman

World

Africa

Asia

Europe

2050 2055

2045 2050

2040 2045

2035 2040

2030 2035

2025 2030

2020 2025

2015 2020

2010 2015

2005 2010

2000 2005

5 2000

1 0

0 1

1 85 1

1 80 1 85

1 75 1 80

1 70 1 75

1 65 1 70

1 60 1 65

1 55 1 60

1 50 1 55

North America

Note: Data are available for five-year periods. The chart contains factual data until 2015. Source: UN (2019a).

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Experience suggests that fertility rate decreases in tandem with economic development as a result of the so-called demographic transition. During the demographic transition, the reduction in the mortality rate from a high level can be typically observed first, followed by the decrease in the fertility rate within a few decades (Lee â&#x20AC;&#x201C; Reher 2011). During this period the working-age population increases more quickly than that of the dependent population, since the number of children decreases due to the reduction in the fertility rate. This is the time when the demographic dividend can be utilised. Demographic dividend means that the change in the age structure of the population, that is, the increase in the working-age population and the reduction in the proportion of the dependent population presents the possibility to achieve higher economic growth. Due to demographic developments, the labour force involved in production increases, partly because of an increase in the number of active-age people and partly because the labour market participation of women can also increase with a lower fertility rate. Fewer dependent people allows for an increase in household savings, which, in turn, may result in the expansion of the capital stock. Fewer children per household means that parents can spend more resources on education, and improvement in levels of education increases productivity (Bloom et al. 2003). Certain regions of the world are in different phases of the demographic change: fertility is already low in developed countries, while the number of children per woman is decreasing in developing countries. Examining the relationship between regions at different development levels and the fertility rate, we can see that a country is able to stay above the replacement-level fertility threshold (2.1 children) until GDP per capita is lower than USD 12 thousand, while a higher income per capita would mean that the fertility rate is not enough to sustain population levels any more (Chart 5-2).

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Chart 5-2: The development of the fertility rate and GDP per capita, 2017 6 5 Total fertility rate

Low income 4 Lower middle income

Middle income 2

Upper middle income

High income

1 0

10,000

20,000

30,000

40,000

50,000

60,000

GDP per capita PPP (USD) Source: World Bank.

After reaching a critical level of development, the fertility rate typically would not decrease any further, or it may even increase, but in the majority of the developed countries it is below 2.1. However, it must be taken into account that several other factors can affect the fertility rate other than economic development (e.g., the culture of the country, quality of healthcare, the participation of women in the labour market or the level of family benefits). The other megatrend of global demographic processes is population ageing, caused by the reduction in the fertility rate and the increase in life expectancy. Between 2015 and 2050, the number of those aged 60 and older in the world may undergo an unprecedented increase, from 900 million to 2 billion. The proportion within the population of the old may increase from 12 per cent of 2015 to 21 per cent by 2050, however, ageing may be present to different extents in the various regions. Europe may remain the continent with the oldest population in the coming decades. The proportion of the elderly within the population â&#x20AC;&#x201D; 205 â&#x20AC;&#x201D;

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may increase to 35 per cent by 2050 (Chart 5-3). At present Africa has the youngest population, and the proportion of those aged 60 and above within the population is low, reaching only 5 per cent in 2015. The proportion of those aged 60 or above may increase to 9 per cent in African countries by 2050. At the same time, the number of the elderly may increase to more than three times the present value in Africa, supported by the increase in life expectancy too. Similar to Africa, Asia may see a possible doubling in the proportion of those aged 60 or older by 2050. The highest number of elderly people is expected to be seen in Asia in 2050, and their number may increase from 511 million to 1.3 billion between 2015 and 2050. Chart 5-3: Proportion of the population above 60 in certain continents of the world in 2015 and 2050 (in per cent of the whole population) 35% 29%

24%

21%

24% 12% 9% 5% 25% 11%

21% 12%

23% 16%

2015

2050

Source: UN (2019a).

Population ageing may entail a rise in the ratio of the old and the younger generations and thus, with every other factor being unchanged, a growing burden on the economically active population. The old-age dependency ratio55 may almost double globally between 2015 and 55

The old-age dependency ratio is the ratio of the population above 65 to the workingage population (15-64 years).

â&#x20AC;&#x201D; 206 â&#x20AC;&#x201D;

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2050: it may increase from 13 per cent to 25 per cent by 2050. This means that while in 2015 there were 13 elderly people per 100 working-age people, there will already be 25 in 2050. There are significant regional differences between the average values. The old-age dependency ratio may increase to the highest extent in Europe: In 2015, there were 26 elderly people for every 100 persons of working-age in Europe (so 4 working-age people for 1 elderly person), while in 2050, there will be 49 elderly people for every 100 working-age people (2 people of working age caring for 1 old person).

How might the number of the working-age population develop as a result of demographic changes in the coming decades? Demographic changes show significant differences in certain regions of the world, and therefore each continent faces different labour market challenges. In regions where the number of workingage people will increase in the coming decades, there is a potential to utilise the labour force surplus if such countries can properly adapt to demographic changes. In regions where the number of working-age people will decrease, the reduction in the labour supply may have an unfavourable effect on economic growth, with every other factor staying the same.

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Chart 5-4: Change in the working-age population in each continent of the world between 2015 and 2050 (change percentages) Percentage change between 2015 and 2050 Countries of the World 27%

10%

-18%

13%

136%

17% 38%

Source: UN (2019a).

The working-age population is expected to increase in every region except for Europe by 2050 (Chart 5-4). Globally, the number of people between 15 and 64 was 4.8 billion in 2015 which could increase by 27 per cent, that is, to 6.1 billion by 2050. In tandem with this the proportion of active-age people within the population is expected to decrease in every continent except for Africa since the number of people in older generations will grow more quickly than that of any other age group as a result of population ageing. The number of working-age people may increase the most in Africa. This number could be more than twice the 2015 value by 2050, increasing to almost 1.6 billion. In Africa, the proportion of children within the population was very high (41 per cent), while the proportion of working-age people within the population (55 per cent) is below the values of other regions of the world (Chart 5-5). In the coming decades, high numbers of young people will reach working age in â&#x20AC;&#x201D; 208 â&#x20AC;&#x201D;

5.1 Economic challenges of ageing populations

Africa, in tandem with the expected reduction in the fertility rate and the total dependency rate. The continent is in a stage of demographic transition when it could benefit from the significant increase in the number of the working-age population, and this will also promote economic convergence. The annual growth rate of GDP per capita could be higher by 0.5 percentage points in Africa in the next 50 years as a result of the demographic dividend (Bloom et al. 2016). Nevertheless, comprehensive economic policy preparation is necessary to utilise this: Access to education and healthcare should be extended among the young and it must be ensured that these age groups of high numbers are able to find jobs in the labour market (UN 2019b). Moreover, productive investment (e.g., infrastructure), as well as the increased labour-market participation of women could also contribute to successful economic convergence.

2015 56

2050

2015 2050

Northern America

2015

2050

15 10

2050

2015

2050

2015

Europe

Asia

World

Africa

Chart 5-5: Distribution of the population by age group in each continent of the world in 2015 and 2050 (per cent)

67 28

57 20

Population ages 0 14 Population ages 65 and over

Source: UN (2019a).

â&#x20AC;&#x201D; 209 â&#x20AC;&#x201D;

Population ages 15 64

100

5 Demographic changes in the world

Of the continents of the world, Europe may be the only region where the working age population will decrease in the coming decades. The number of active-age persons may decrease from 495 million in 2015 to 407 million by 2050 in Europe, amounting to an 18 per cent decrease (UN 2019a). As a result of the lower fertility rate that can be observed as compared to previous decades, the number of persons reaching working age will be lower as compared to the number of older age groups. The reduction in the labour force affects each European region to a different extent. The working-age population may decrease to the highest extent in Eastern and Southern Europe. In Eastern Europe, the number of the labour force below 35 may fall by 24 per cent between 2015 and 2050, in which the migration of younger workers to Western Europe also has a role alongside unfavourable demographic processes (IMF 2019, Sinnott and Koettl-Brodmann 2015).

How do demographic changes influence the labour market? Demographic processes influence the labour market through several channels. On the one hand, the number of the working-age population fundamentally determines the development of the labour force supply, that is, the number of employees that can be potentially involved in production. On the other hand, the change in the age composition of the working-age population may also influence the development of labour productivity. Thirdly, population ageing could also transform labour demand, and demand for employees with higher skills may rise. The reduction in the number and proportion within the population of working-age persons may have unfavourable effects on economic growth in the long term. Based on the growth accounting, the growth rate of GDP per capita can be divided into the increase in output per worker and the development of the proportion of jobseekers within the population. With the age-specific behaviour unchanged, the ageing of society may result in a lower economic growth. Based on this division, â&#x20AC;&#x201D; 210 â&#x20AC;&#x201D;

5.1 Economic challenges of ageing populations

Bloom et al. (2010) stated that the economies of the OECD countries would grow only by 2.1 per cent on average instead of 2.8 per cent between 1960 and 2005 if the demographic processes followed the path estimated for the coming decades. In the coming decades, in tandem with the strengthening of the demographic constraints and rapid technological development the demand for a skilled labour force may increase. Digitalisation and automation may well result in the transformation of labour markets, strengthening the importance of a labour force equipped with a proper education and appropriate skills. In the European Union, more than 100 million new workplaces may be created between 2013 and 2025 based on the projections of the OECD and the EU (2016), thus the significance of the attraction and keeping of the skilled workforce will strengthen. On the other hand, consumersâ&#x20AC;&#x2122; demands may transform in ageing countries in the long term to which the production and employment of each sector should adapt too. Consumption habits of the elderly are different from those of working-age people in several respects: they prefer different products and services, they have more leisure time and, generally, their state of health may be less favourable. Due to population ageing, the structure of the economy may change in a way that demand for products and services consumed to a higher extent by the elderly may increase. Consumption demand may shift from consumer durables (e.g., car purchase) towards services (e.g., healthcare) (OECD 2019a). As a result of the increase in the proportion of the elderly within the population, the proportion of workers employed in social services may increase. In tandem with this, the proportion of those employed in agriculture, industry and mining may decrease (Siliverstovs et al. 2011). The transformation of the economic structure may influence the development of the labour demand of each sector in the future, which might necessitate labour force flow between certain sectors. Preparation for this could be facilitated by supporting the mobility of employees between sectors and regions and by increasing their participation in further training and retraining programmes. â&#x20AC;&#x201D; 211 â&#x20AC;&#x201D;

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How could the unfavourable economic effect of the reduction in the number of the labour force be offset? With regard to sustainable economic growth, the possibility that the reduction in the number of working-age persons may mitigate the growth rate of GDP through a decrease in the labour supply represents a challenge. The unfavourable economic effect of the reduction in the number of working-age persons can be mitigated by several measures. These include an increase in the activity rate, the encouragement of longer active careers and an increase in productivity in the short term, while measures designed to foster an increase in the fertility rate may help in stabilising the labour supply in the long term. In addition to demographic processes, the development of the labour supply is substantially influenced by the activity rate, that is, the proportion of economically active people as compared to workingage people. In Eastern European countries, the labour market effects of the decrease in the working-age population could be partially reduced by further increasing the activity rate of groups in a more disadvantageous labour market situation. Young employees, those almost reaching the retirement age, low-skilled people and mothers with small children typically have a lower activity rate. In the VisegrĂĄd countries, significant labour market reserves can be identified among young employees (aged 15 to 24) and low-skilled people as compared to the European Union average (Chart 5-6).

â&#x20AC;&#x201D; 212 â&#x20AC;&#x201D;

5.1 Economic challenges of ageing populations

Chart 5-6: Activity rates in different social groups in the V4 countries, in 2008 and 2018 (per cent) 60

Per cent

Low educational attainment

2008

Persons before reaching retirement age (ages 60 64 years) 2018

Slovakia

Poland

Hungary

10 Czechia

10 Slovakia

Poland

Hungary

Czechia

Slovakia

Poland

Hungary

Czechia

The young (ages 15 24 years)

EU28 average (2018)

Source: Eurostat.

The utilisation of these reserves can be facilitated, among others, by targeted tax credits, since such groups react more sensitively to financial incentives during their decisions related to their entry into the labour market (Palotai – Virág 2016). The activity rate of those almost reaching retirement age significantly increased in the period following the economic crisis in which the change of retirement rules also played a major role. There is an international trend parallel to the increase in life expectancy, that is, the increase in the length of active careers. The employment rate of 55 to 64 year-old persons increased almost by 10 percentage points on average in OECD countries between 2005 and 2018 (Chart 5-7). Nevertheless, there are significant differences between the average values. The employment rate of old people increased to an extent exceeding 20 percentage points in Austria and Italy, as well as in the — 213 —

5 Demographic changes in the world

VisegrĂĄd countries. During the same period, the effective retirement age, being 65 on average in 2017 for men, albeit with significant differences between the countries, increased almost by 2 years during the same period both for men and women (OECD 2019b). Retirement age increases as announced in certain countries played a significant role in this since the old-age pension age is approximating 65 in more and more countries. The restriction of the opportunities of early retirement also contributed to the increase in the effective retirement age (OECD 2017). Due to retirement age increases that have already been introduced in certain countries to enter into force in the future, the coming decades might see a further prolongation of active careers, which could partly mitigate the labour market effect of the reduction in the number of the active age population. The labour market participation of the elderly could also be incentivised by the taxation system and pension rules awarding later retirement. Employment beyond the age limit has several advantages for employees, employers and the government budget. A longer career means that employees can reach a higher starting pension in several countries, and employment in old-age may also help people to stay healthy for longer. Employers could also benefit from retaining employees with more experience. Chart 5-7: The employment rate of age group 55 to 64 years in OECD countries between 2005 and 2018 (per cent)

2005 51.6% 2018 61.4%

Source: OECD (2019c).

Managing the labour shortage could also be facilitated by the further proliferation of automation. Automation could be spread in several areas of life in the near future (see the Box on the experiences of Japan). â&#x20AC;&#x201D; 214 â&#x20AC;&#x201D;

5.1 Economic challenges of ageing populations

The number of orders placed for industrial robots increased by five times between 2001 and 2017 and further dynamic expansion can be expected in the coming years (OECD 2019a). In the recent period, the countries most affected by ageing were leading in the extension of automation and were able to avoid economic losses due to ageing by using new technologies (Acemoglu – Restrepo 2017). One of the reasons for this was that the productivity of industries using automation was able to expand more quickly and to a greater extent as compared to other sectors (Acemoglu – Restrepo 2017). The increase in productivity could be facilitated by lifelong learning, continuous further training and improvement in people’s state of health. In the long term, a permanent increase in the fertility rate could also contribute to the stabilisation of the number of working-age persons, but its positive economic effects appear only with a lag of several decades, when the generation of more children enters the labour market.

How does the ageing of employees affect productivity? In developed countries, the gradual ageing of the labour force may impact productivity. In the countries of the European Union, every fifth employee will be older than 55 in 2030 according to the forecast of the International Labour Organisation. The proportion of those above 55 within the total labour force may increase especially significantly in certain countries. This proportion may increase from 16 per cent in 2015 to 25 per cent by 2030 in Italy, and by 8 percentage points in Spain (Chart 5-8). In the coming decades, the population structure of certain European countries will increasingly come to approximate that of Japan, due to the acceleration of ageing, while the proportion within the labour force of those older than 55 may reach the Japanese value in such states (e.g., in Italy and Spain) by 2030. The median age of the labour force may grow close to 43 in Europe and Eastern Asia by 2030, this being the highest value throughout the regions of the world. Population ageing may have several labour market implications. On the one hand, — 215 —

5 Demographic changes in the world

it takes typically longer for older employees to find a new job, should they become unemployed, and on the other, a smaller proportion of them attend further and retraining programmes. Therefore, the increase in the average age of the labour force may slow down the adaptation of the labour market which follow economic shocks (ILO 2018a). Chart 5-8: Distribution of the population by age in certain regions and countries of the world in 2030 (per cent) 3,3

1,3

24,6

4,9

22,6

Italy

3,6 19,3

European Union

13,5

21,7

Spain

22,8

Germany

6,1

9,1

Japan

5,2

15,1

14,7

12,3

North America

Asian and Pacific Region

Latin America and Caribic

15–24 25–54

55–64

3,7 8,3

Africa

65+

Source: ILO.

The increase in the proportion of older employees may have an unfavourable effect on productivity through several channels (Chart 5-9). On the one hand, the literature suggests that the labour productivity of individuals typically descends in a reverse U curve, that is, it increases following finding a job in the labour market, then it reaches its peak in the 40s, to show a decrease during the remaining career (Aiyar et al. 2016). Due to the different productivity of age groups, the increase in the proportion of older employees may result in a decrease in aggregate productivity. This can be related to the fact that the physical and mental skills of older employees deteriorate with time, and their knowledge formerly obtained in the educational — 216 —

5.1 Economic challenges of ageing populations

system may become outdated. Therefore, the role of lifelong learning and further training programmes could appreciate in tandem with population ageing. Chart 5-9: Ageing of the labour force and aggregate productivity

Declining physical and mental capacities

Ageing of labour force

More difficult adoption to new technologies Previously acquired knowledge deteriorates

Less potential young inventor

Lower innovation potential

Decline in aggregate productivity

Declining creativity and risk taking willingness Less new enterprise

Source: Own edition based on the related statements of the literature.

On the other hand, older employees find it more difficult to adapt to new technologies, and the innovation potential and the number of new enterprises may reduce with population ageing. Innovation activity supports the growth of productivity. The age distribution of those coming up with significant technological innovations reaches a peak at the end of the 30s; inventors produced the most technological innovations at this age in the 20th century (Jones 2010). Based on Feyrer (2008), the median age of those coming up with innovations was 48, and the age distribution of inventors reached its peak in the mid-40s age group in the United States, based on the data of patents registered between 1975 and 1995. Accordingly, Feyrer (2008) anticipates that the decrease in the number of younger employees in their 30s or 40s also reduces the number of potential inventors, which can limit innovation activity and the increase in productivity. Innovations typically appear in relation to the establishment of new enterprises, while skills and conditions necessary for entrepreneurâ&#x20AC;&#x2122;s activities (e.g., creativity, risktaking willingness, energy) decrease with the progress of age, so the â&#x20AC;&#x201D; 217 â&#x20AC;&#x201D;

5 Demographic changes in the world

growth in the proportion of older employees may slow down the rate of company establishment (Liang et al. 2014). Macroeconomic studies based on regression results identify a clearly negative relationship between the ageing of the older labour force and productivity (e.g., Aiyar et al. 2016, IMF 2017, IMF 2019). Based on the estimated result related to the data of the 28 European Union Member States between 1950 and 2014, an increase in 1 percentage point of the proportion of the age group of 55 to 64 could reduce the output rate per employee by 0.7 percentage points (Aiyar et al. 2016). The economic structure can also affect how the change in age composition influences the development of aggregate productivity in the long term. Veen (2008) assigned industrial sectors into three categories depending on how the ageing of the labour force affects productivity: 1) productivity reduces with the progress of age (e.g., blue-collar workers, construction industry); 2) age has no influence on the development of productivity (e.g., bank officials, service sector); 3) ageing results in the growth of productivity of the individual (e.g., doctors, lawyers). In the Member States of the European Union and in economically more developed countries, labour productivity is not expected to decrease significantly despite ageing based on economic structure-related features. On the one hand, the service sector, where productivity does not decrease with the progress of age, contributes significantly more to the increase in GDP in economically more developed regions as compared to less developed countries. Both in the countries of the European Union and in North America, the proportion of the employees in the service sectors exceeded 70 per cent in 2018 which is considerably higher than that in other countries and especially than that in African and Asian countries (Chart 5-10).56 On the other hand, the proportion of those with tertiary education is high, and their productivity may well increase in tandem with ageing. 56

In the database of the World Bank, employees of the service sector include workers employed in trade, the hospitality sector, transport, communications, the financial sector, the property sector and community services.

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5.1 Economic challenges of ageing populations

Chart 5-10: Number of workers employed in various economic sectors in proportion to all employees in certain regions of the world (per cent), 2018 100

1 19

100

4 24

80 55

60 40

26 11

72 49

40 20 0

North America

European Union Services

World Industry

East Asia

Sub-Saharan Africa

Agriculture

Source: World Bank.

It is not clear, even taking other aspects into consideration, whether population ageing will reduce productivity. On the one hand, this is due to the greater accumulated experience of older employees and, on the other, to the greater opportunity to invest in human capital. Börsch-Supan and Weiss (2016) examined the relationship between the employees’ age and their individual productivity according to their data related to the production processes of an automotive assembly factory in Germany. The individuals’ productivity was measured by the frequency and seriousness of errors committed by the employees. Their results contradict macroeconomic conclusions since the productivity of the employees covered by the examination gradually increases until age 65, which is made possible by the accumulated experience of the employees. On the other hand, Lee and Mason (2010) found that the standard of living can even increase if less productive cohorts of high numbers are replaced by more productive (more highly educated) employees of less numbers (Lee – Mason 2010). The reduction in the — 219 —

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fertility rate observed in recent decades has increased educational attainment: the fewer children there are in a family the more resources parents can spend on the education of a child. On the whole, the literature includes more studies according to which the ageing of employees will reduce aggregate productivity in the long term. Its effect can be reduced through several measures. For example, one such measure could foster an increase in the educational attainment level, the retention of highly trained employees, further improvement in peopleâ&#x20AC;&#x2122;s state of health, the dissemination of lifelong learning, supporting innovation activity, grants supporting young inventors and scientists, as well as the further proliferation of automation. Labour market mobility may also be increased, with regard to the fact that the labour demand of certain sectors may undergo significant restructuring in the future. Box 5-1 The experiences of Japan

Preparation for demographic changes can be facilitated by understanding the example of Japan, where the process of an ageing population started decades ago and is happening more quickly than in other developed economies. Of all the countries of the world, the oldest population lives in Japan. The proportion of those above the age of 65 within the population more than doubled between 1990 and 2015, increasing from 12 per cent to 26 per cent, and may further increase in the coming decades. In comparison, ageing is on a lower level in the countries of the European Union since the proportion of those above 65 within the population was around 19 per cent on average in 2015, that is, every fifth inhabitant was older than 65. Looking ahead, the rate may reach 26 per cent, which is now observable in Japan, and will be the case in EU countries in the second half of the 2030s (Eurostat 2019). Within the population, the number of working-age persons has significantly decreased in recent decades, while in other developed

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countries it stagnated or even increased during the same period (Chart 5-11). The number of active-age persons reached its peak in Japan in 1995, compared to which it reduced by 11 per cent by 2015. However, the number of employees reduced by a significantly lesser extent (ILO 2019). The reason for this is that although the number of people in younger age groups has become smaller in recent years labour market participation has significantly increased among those over 65 and among women. Japanese data clearly show the role of demographic processes in economic growth. Although production per employee increased in a similar way as in other developed countries in the last 25 years, aggregate GDP could increase only at a substantially slower pace. The reason for this is that gradually fewer and fewer people were of a working age in proportion to the whole population, and more and more people were retired. Basically this was the reason for the increase in the Japanese GDP substantially slowing down in the 1990s, and why it lagged behind the average of the OECD countries by almost 1.5 percentage points (Chart 5-12). This happened despite the fact that GDP per working-age person, which can be interpreted as one of the indicators of productivity, increased in Japan at the same rate as in the OECD countries at all times, furthermore, it has been increasing significantly quicker than that since 2012. Therefore, experience suggests that the economic effects of negative demographic changes could not have been offset even by an increase in productivity in Japan. In the last two decades, GDP produced during one working hour significantly grew in the country, which is an indicator highly monitored for changes in productivity. Its value has increased almost by 50 per cent in Japan since 1990 which is just below the 53 per cent value of the United States and is significantly higher than, for example, data related to France or Italy. Dynamic expansion of GDP per hour worked means that the ageing of the labour force has not limited the growth rate of productivity in Japan, despite the findings of the literature. At the same time, GDP per capita could not have reached the average growth rate of OECD countries although productivity grew at a rate exceeding that of other developed countries.

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Chart 5-11: Change in the number of working-age persons and old persons in G7 countries between 1995 and 2015 (per cent) 100

Per cent

100

0 20

Population ages 15 64

USA

Canada

Germany

France

Italy

Japan

United Kingdom

Population ages 65 years and over

Source: UN (2019a).

The Japanese government announced several measures in the last decade designed to boost economic growth and to limit the effects of ageing. It included an increase in the employment rate of old people, which significantly rose between 2012 and 2018. In 2012, the government announced that companies are obliged to employ those employees until they reach 65 who wish to work longer than the lower retirement age limit of 60.57 In addition, the retirement age limit will be increased: it will be gradually increased to 65 for men between 2013 and 2025, and from 60 to 65 years for women between 2018 and 2030 (OECD 2018). 57

The Japanese pension system has two pillars: one of them is the Employeesâ&#x20AC;&#x2122; Pension Insurance Programme from which pension payments may be requested from the age of 60, and the other one is the National Pension Programme from which pension payments can be requested any time between the ages of 60 and 70 but the amount of the pension depends on the age at payment (pension payment below 65 implies a sanction while above 65 a bonus) (Bloom et al. 2018).

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Due to its particular demographic situation, Japan is in the lead in elaborating solutions and answers to ageing. The two most important objectives are the increase in the employment rate, and the substitution of the labour force of decreasing numbers by automation, which also increases productivity per capita. Chart 5-12: The development of real GDP, GDP per capita and GDP per working-age person in Japan and in OECD countries (per cent) 2.5

Per cent

2.5

2.0

1.5

1.0

0.5

0.0

7 2011 2012 2018 1 Real GDP

7 2011 2012 2018 1 GDP per capita Japan

7 2011 2012 2018

0.0

GDP per workingage population

OECD

Source: OECD (2019).

As regards the exploitation of labour force reserves, it is a significant result that the employment rate of age groups from 55 to 64 increased from 65 per cent to 75 per cent between 2012 and 2018, which is one of the highest values in OECD countries. Reaching this was mostly due to the increase in the relatively low retirement age of 60 years, on the one hand, and the structural changes in the labour market, on the other. For an ageing society, it is favourable that the proportion of jobs with physical demands is decreasing while the number of tasks requiring high skills is increasing (OECD 2019d). In addition, improvement in people’s general health also expands the labour supply in older age groups.

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Chart 5-13: Development of GDP per hour worked in the G7 countries, between 1990 and 2017 (per cent change compared to 1990) +53%

+40%

+49%

+19%

+52%

+48%

+39%

Source: OECD.

In order to substitute the decreasing labour force, the big corporations of the country have a leading role in the development of automation and robots of industrial use (Schneider et al. 2018). Japanâ&#x20AC;&#x2122;s aim is to establish the so-called Society 5.0 where social groups are to be joined and social challenges solved using various innovations (like robots, artificial intelligence, big data). For example, in healthcare, the dissemination of telemedicine and home carer robots was indicated as a target together with the building up of online systems monitoring health, which can reduce the burdens upon healthcare workers and younger age groups who perform care and help less mobile old people in accessing care. In the area of transport, the target is to develop and disseminate self-driving means of public transport and to monitor transport nodes with sensors and robots (Japanese government 2019). Such solutions could result in tensions or even in an increase in unemployment in countries with an extensive labour supply, but in Japan where the number of the workingage population is decreasing, their effect could be positive in solving social and economic problems.

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How does population ageing affect consumption and saving habits? The ageing of society can affect the development of consumption and savings rates due to the change in the proportions of age groups and longer life expectancy. Based on the life-cycle hypothesis, individuals smoothen their consumption over their lifetimes, and their propensity to consume and save depends on age. The consumption rate of young and old people is higher and their savings rate is lower than that of middle-aged persons. With the age structure shifting, determining factors of economic growth, that is, consumption and savings are changing depending on the life cycle the most individuals will be in. Chart 5-14: Development of labour income per capita and consumption per capita by age in France in 2011 45

Thousand euro

Labour income

Consumption

Note: Average values per capita. Source: Database of national transfer accounts, Lee â&#x20AC;&#x201C; Mason (2011).

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Children and old people consume more than they produce. The majority of their consumption is produced by the employees who consume less than their income (Chart 5-14). With population ageing, the proportion of employees producing consumable incomes within the population will decrease in most of the developed countries, while the proportion of older people with a higher consumption rate is expected to increase (Lee and Mason 2017). On the whole, this may result in a higher consumption rate with the increase in the proportion of older persons in the long term. According to Lee and Mason (2017), the shifting of the age structure will reduce the sum of consumable incomes, to which adaptation is possible by limiting individual consumption or by increasing the labour supply (longer active career). The older age pyramid would reduce the savings rate and increase consumption. In their regression model, Erlandsen and Nymoen (2004) explain the development of the consumption rate with the proportion within the population of middle-aged persons (between 50 and 66) in addition to the macroeconomic variables (income, real interest rate). The age group of those between 50 and 66 is highlighted in the study since they are close to the retirement age limit and, due to their preparation for their pensioner years, their propensity to consume is substantially less than that of the young age groups, while their income is higher than that of the other middle-aged age groups. According to their results, the increase in the proportion within the population of middle-aged persons implies a reduction in consumption. Mason and Tryon (1990) found a positive relationship between the total dependency ratio and consumption: an increase of 1 percentage point of the total dependency ratio would increase the consumption rate by almost 0.1 percentage point.

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Chart 5-15: Effects of ageing on consumption and savings Young population Lower consumption rate Higher savings rate

Working-age population

Higher consumption rate Lower savings rate

Old population

Rise in life expectancy

Higher aggregate consumption rate Lower aggregate savings rate

Behavioural effect

Higher aggregate savings rate

Source: Own edition based on the related statements of the literature.

Population ageing may result in the rearrangement of consumption expenditure in the long term. With the increase in age, for example, demand for healthcare and energy consumption increases, while expenditure spent on other products and services (e.g. car purchase, fuel, education) typically decreases (Martins et al. 2005). The consumption of old-age individuals shows different paths in countries of different economic development. Based on the report of the UN, consumption per capita shows a decrease in old age in countries with low or middle income, and lags behind the average consumption level of younger age groups. By contrast, in countries of high income affected by ageing, the average value of consumption per capita may exceed the consumption of the young by as much as 30 per cent in old age (UN, 2017b). This means that in less developed countries, in the absence of pension systems with wide coverage, older people cannot properly smoothen their consumption over their lifetimes.

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The relationship between the savings rate and the composition of the population involves similar drives than the relationship between the consumption rate and the composition of the population. The savings rate and demographic processes can be connected through the lifecycle theory: the savings rate is lower in the case of young and old people than in that of middle-aged persons, so the age composition of society can affect the savings rate as well. Based on estimates in the literature, the increase in both the youngage and the old-age dependency ratio reduces the savings rate. So the lifecycle theory is working: there is no such income in young age to save from while in old age, the savings of previous periods are typically consumed (Aiyar et al. 2016), so the increase in the total dependency ratio has a negative effect on the development of the savings rate. According to Lindhâ&#x20AC;&#x2122;s findings (1999), the age group of 0 to 14, and those above 65 have a significantly negative effect on the savings rate. The panel regression results of Martins et al. (2005) suggest that the increase in the proportion within the population of the 25 to 59 years old would increase the savings rate of households while the increase in the proportion of those above 60 would significantly reduce it. As opposed to the long-term reduction in the savings rate to be assumed based on the lifecycle theory, other aspects suggest that the savings rate will increase. The long-term reduction in the savings rate could be limited by the adaptation of economic agents. Younger age groups may choose a higher savings rate as compared to former generations due to the increase in life expectancy and a longer old age, or if the economic actors suppose the reduction in the care level of the social security care systems until reaching old age (NRC 2012). Therefore, the savings propensity of the young and, especially, of the middleaged may increase on the whole due to the preparation for old age. On the one hand, this process may reduce real interest rates in the long term, and it may increase investments on the other, which, in the case of productive investments, it could also support an increase in

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productivity. Encouraging individuals to save long term is a serious challenge for economic policy, aiming at the maintenance of a proper standard of living in ageing societies despite the gradually increasing life expectancy. The interest rate may also influence the long-term development of consumption and savings rates. According to Juselius and TakĂĄts (2018), the increase in the proportion of the dependant population (that is, the total dependency ratio) would reduce the savings rate and increase the balanced real interest rate while the increase in life expectancy exerts the opposite effects. Following the economic crisis, real interest rates decreased and demographic processes suggest that they may stay low in the long term too. Most studies conclude that ageing results in lower real interest rates in the long term (Aksoy et al. 2015, IMF 2017; Bielecki et al. 2018). Persistently low real interest rates would make presentday consumption relatively cheap as compared to future consumption which, in turn, can result in an increase in consumption and a reduction in savings.

How should we finance pensions in ageing societies? Due to population ageing, the developing and the developed countries will face different challenges in the financing of old-age pensions. In developing countries, the coverage of pension systems is low as yet, so preparation for demographic changes may make it necessary to further increase coverage to ensure appropriate living conditions for the old. In developed countries, the coverage of pension systems is high but population ageing and the reduction in the number of working-age persons may make the financial sustainability of pension systems difficult. In addition, finding the balance between financial sustainability and decent pensions will be a challenge for such countries (ILO 2018b).

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There are significant differences in the coverage of pension systems from one country to another. (Chart 5-16). Globally, 68 per cent of old people above the legal retirement age limit receive a pension (ILO 2018b). In highly developed regions, like North America and Western Europe, the coverage of the pension systems is close to 100 per cent, that is, all the old people reaching the legal retirement age limit can expect a pension. In contrast, in countries of Sub-Saharan Africa, 23 per cent of old people above the retirement age limit received a pension.58 Chart 5-16: Coverage of the pension systems in each country of the world (latest available data)

0 20 40 60 80 100 Note: Effective coverage shows the proportion of those receiving pension from among old people who already reached the legal retirement age limit. Source: ILO (2018b).

Data of each country in the ILO database relate to different years, containing the most up-to-date data available. The latest available data of the examined countries typically relate to the period between 2009 and 2016, containing mainly data for 2014 in the case of European countries.

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In low-income countries, coverage has started to increase in recent years but, despite this, less than 20 per cent of old people receive a public pension so they are highly dependent on financial assistance within the family (ILO 2018b). At the same time, children will be less and less able to take care of their parents the latter becoming old with the gradual reduction in the fertility rate and the spread of urbanisation (Grandolini 2016) which can also justify a further increase in coverage. Whatâ&#x20AC;&#x2122;s more, the proportion of those working in the informal sector and thus not being able to count on an old-age pension is high in developing countries. In order to support themselves in old age, a significantly higher proportion of the older population works in African countries than those living in developed countries (Chart 5-17). The proportion of those participating in the labour market was 52 per cent in Africa and 10 per cent in Europe among men older than 65 in 2015 (UN 2017b, ILO). 60 to 69 year-old people living in developing countries covered 56 per cent of their consumption expenditure by income from work in the 2000s (UN 2015), and the average consumption expenditure of those above 60 is typically lower as compared to younger age groups. Chart 5-17: The labour market participation rate of men older than 65 in certain regions of the world (per cent) Europe: 10% Oceania: 21% North America: 23% World: 30% Asia: 30% Africa: 30%

Source: ILO.

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In developed countries, ageing will challenge the financial sustainability of social security care systems and the maintaining of the budgetary balance. Population ageing may affect budgetary revenues and expenditure in a negative way. On the revenue side, the reduction in the working-age population may result in the reduction in tax and contribution revenues related to wages, subject to an unchanged regulatory environment and activity rate. On the expenditure side, the increase in the number of old people may result in the increase in pension expenditure, healthcare-related public expenditure and expenditure related to old-age patient care. The increase in the proportion within the state budget of expenditure items sensitive to demographic changes may force productive government expenditure (like research and development, education, infrastructure) out, which, in turn, can have a negative effect on growth potential. In the absence of concerted measures, the reduction in the number of working-age people and the increase in the proportion of those above 65 is expected to result in an increase in GDP-proportionate public pension expenditure. In pay-as-you-go pension systems, it is mainly the current contribution payments of workers that cover the pensions of old people. The amount of public pension expenditure simultaneously depends on several factors, including mainly the parameters of the pension system in the short term (old-age retirement age limit, length of service, replacement rate of new pensions, indexation of the awarded care), and the demographic processes to which rules affecting the pension system are adapted in the long term. In European countries with a higher old-age dependency rate, generally a higher GDPproportionate pension expenditure can be observed (Chart 5-18). This gives a static illustration of the fact that negative demographic processes may result in an increase in expenditure in the absence of measures.

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Chart 5-18: GDP-proportionate public pension expenditure and old-age dependency rate in European countries in 2016

Public pension expenditure as % of GDP, 2016

20 EL

18 FR

16 14 PL

12 10

BE HU

UK RO

EU HR

CZ MT EE NL LT

4 2 0 20

Old-age dependency ratio, 2016 Source: European Commission (2018).

According to the results of the 2018 report of the European Commission (EC 2018), GDP-proportionate pension expenditure may increase from 11.2 per cent (2016) to 11.7 per cent by 2050 in the countries of the European Union. The majority of the increase in expenditure is related to the increase in the old-age dependency rate. In tandem with this, the gross replacement rate is expected to decrease in EU countries, from 45 per cent to 40 per cent. This means that the income replacement capacity of pensions may reduce in EU countries in the coming decades. Ageing societies may improve the long-term sustainability of the pension system in several ways. In the recent period, several countries

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decided to increase the old-age retirement age limit59, and the retirement age limit approximates 65 in more and more countries (OECD 2017). The increase in the age limit in proportion to the increase in life expectancy may serve two contradictory targets of the pension system, that is, financial sustainability and guaranteeing the security of an income for old people. The restriction of early retirement options may contribute to the approximation of the effective and the legal retirement age limit. Another solution could be offered by the introduction of positive incentives awarding work above the age limit, and the option of a flexible retirement above the minimum age limit. Measures to increase the activity rate may partly counterbalance the fact that revenues of the pension systems are expected to decrease due to the reduction in the number of the working-age population. A further important target could be to encourage people to save for pension-related purposes. However, measures designed to increase active years can bear results only if there is a demand for those staying in the labour market. Chart 5-19: Challenges of pension systems due to ageing in the 28 EU Member States 2015

2050

Old-age dependency ratio

29.6%

50.4%

Public pensions as % of GDP

11.2%

11.7 %

Number of pensioners

128 million people

163 million people

Average age at retirement

63.5 years

65.4 years

Source: European Commission (2018).

For example, the old-age retirement age limit will increase from 65 to 68 in Denmark by 2030 (OECD, 2017).

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What challenges and opportunities do healthcare systems face? In the coming decades, the increase in life expectancy will result in a significant increase in the number and proportion within the population of old people which is expected to increase demand for healthcare. As regards the regions of the world, life expectancy at birth shows the lowest values in Africa: while it used to be 50 in the first half of the 1980s, it exceeded 60 by the first half of the 2010. However, this value continues to be significantly lower than life expectancy in the developed regions which was around 77 to 79 from 2010 to 2015 (Chart 5-20). At 30 years the difference between countries with the shortest and the longest life expectancy values is significant. In Japan, life expectancy at birth is 84, while it is below 55 in certain African countries (e.g. Nigeria) (UN 2019). In the coming decades, the difference in life expectancy between developing and developed countries may diminish, but inequalities might remain. The number of life years to be expected at 65 is 18 in the case of women and 16 in the case of men. By 2050, the number of life years remaining at 65 may increase by a further 2-3 years as compared to the values observed in the second half of the 2010s in every region (UN 2019). It is an important question whether the further increase in life expectancy will be in tandem with the increase in healthy life years. If the additional life years are spent in good health, ageing may provide potential opportunities for society, e.g., through the opportunity of longer active careers. If the increase in life expectancy does not result in the occurrence of illnesses at a later age, then demand for healthcare may increase to a significant extent (WHO 2015). Based on the findings of the literature, no clear conclusion can be drawn as regards the relationship between the increase in life expectancy and healthy life years. The theory assuming the shortening of illness periods (“compression of morbidity”) suggests that illness periods may shorten in tandem with the increase in life expectancy, should chronic — 235 —

5 Demographic changes in the world

illnesses start later (Fries et al. 2011). Prevention and healthy lifestyle may play an important role in this, but a higher educational attainment and technological development could also contribute. According to others, the increase in life expectancy results in the increase in years spent in illness since the increase in life expectancy is caused by the reduction in mortality rates related to illnesses and the patients stay alive for a longer time subject to proper treatment. Certain studies examining the data of developed countries suggest that the frequency of occurrence of serious illnesses requiring care slightly decreased among those older than 65, while according to other studies the frequency of chronic illnesses increased with the frequency of serious illnesses being unchanged (WHO 2015). Demand for old-age patient care and the related healthcare expenditure will increase in the coming decades as a result of ageing. Chart 5-20: Life expectancy at birth in certain regions of the world (2010 to 2015) and the level of increase in life expectancy to be expected by 2055 +7 years

+10 years

+5 years

+6 years 60.2 years

72.8 years

77.2 years

74.4 years +7 years

77.4 years

79.2 years

80 +5 years

Source: UN (2019a).

The long-term forecast related to the healthcare expenditure of the Member States of the European Union suggests an increase in expenditure due to ageing (EC 2018). The scenario examining the effect of demographic changes on healthcare public expenditure assumes age-specific illness rates remain unchanged, that is, that additional life years due to the increase in life expectancy may be spent in bad health. Based on such assumptions, GDP-proportionate health-related â&#x20AC;&#x201D; 236 â&#x20AC;&#x201D;

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public expenditure may increase by 1.1 percentage points on average as compared to the 6.8 per cent in 2016 in the Member States of the European Union by 2070 (Chart 5-21). However, such results may underestimate the actual future growth of healthcare expenditure, since these suppose that the increase in healthcare expenditure follows the growth rate of the national income. Based on empirical findings of the literature, healthcare expenditure increased to an extent exceeding the increase in GDP per capita in recent decades. However, the future dynamics of healthcare expenditure may be limited by improvements in people’s health. Chart 5-21: The estimated development of GDP-proportionate healthcare public expenditure in EU Member States, 2016–2070 10

Per cent

10 9

CY LV LU LT IE RO PL HU EL BG HR EE CZ SK MT SI ES PT BE FI NL IT EU28 DK SE AT DE FR UK

2016

2016 2070

Note: The Chart shows the results of the demographic scenario. Source: EC (2018).

Demand for healthcare is influenced by people’s state of health, as well as by an increase in individual and national income, and access options to care, apart from the age structure of the population (EC — 237 —

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2018). However, technological development has a significant role on the supply side (IMF 2010). In developed countries, only one quarter of the increase in GDP-proportionate healthcare public expenditure was caused by ageing between 1980 and 2008, the remaining part being the result of the other factors (IMF 2010). Breyer et al. (2010) also concluded that the increase in life expectancy contributed to a significant increase in healthcare expenditure observed in recent decades only to a small extent. It was rather technological development, the increase in income levels and the extension of health insurance that played a role (Breyer et al. 2010, Felder 2013). In the long term, the cost pressure on healthcare systems could be offset by an increase in the role of prevention, and the early recognition of illnesses. Physical activities and healthy nutrition can also contribute to an increase in the number of healthy life years. However, healthcare systems also have to prepare for the fact that the increase in the number of old people may result in greater demand. Due to ageing, further capacities should be built into healthcare (including especially the area of old-age patient care), and the number of healthcare staff should also be adapted to the increasing demand. The Japanese example shows that telemedicine and the monitoring by online systems of the health of patients could mitigate the pressure on care systems. However, the increase in life expectancy provides an opportunity for the old to perform new activities subject to being in the appropriate state of health, including travelling, professional further training, and more active participation in household work and childcare. In ageing societies, the development of health tourism and the manufacturing of medical devices could offer breakthrough opportunities.

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References Acemoglu, D. – Restrepo, P. (2017): Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation. American Economic Review, Vol. 107/5, pp. 174–179. Aiyar, S. – Ebeke, C. – Shao, X. (2016): The Impact of Workforce Aging on European Productivity. IMF Working Paper WP/16/238. Aksoy, Y. – Basso, H. S. –Smith, R. P. – Grasl, T. (2015): Demographic Structure and Macroeconomic Trends. Banco de Espana Working Paper No. 1528. https://ssrn.com/abstract=2669321 or http://dx.doi.org/10.2139/ssrn.2669321 Bielecki, M. – Brzoza-Brzezina, M. – Kolasa, M. (2018): Demographics, monetary policy and the zero lower bound. Narodowy Bank Polski Working Paper No. 284. Bloom, D. E. – Canning, D. – Fink, G. (2010): Implications of population ageing for economic growth. Oxford Review of Economic Policy, Volume 26, Number 4, 2010, pp. 583–612. Bloom, D. E. – Canning, D. – Sevilla, J. (2003): The Demographic Dividend. A New Perspective on the Economic Consequences of Population Change. Bloom, D. E. – Kirby, P. – Sevilla, J. – Stawasz, A. (2018): Japan’s age wave: Challenges and solutions. 03 December 2018. https://voxeu.org/article/japan-s-age-wave-challenges-and-solutions Bloom, D. E. – Kuhn, M. – Prettner, K. (2016): Africa’s Prospects for Enjoying a Demographic Dividend. NBER Working Paper No. 22560. Börsch-Supan, A. – Weiss, M. (2016): Productivity and age: Evidence from work teams at the assembly line. The Journal of the Economics of Ageing Vol. 7 (2016) pp. 30–42. Breyer, F. – Costa-Font, J. Felder, S. (2010): Ageing, health, and health care. Oxford Review of Economic Policy. Vol. 26 (4), pp. 674-690. Erlandsen, S. K. – Nymoen, R. (2004): Consumption and population age structure. Norges Bank Working Paper No. 2004/22. European Commission (2018): The 2018 Ageing Report. Economic and Budgetary Projections for the 28 EU Member States (2016-2070). Institutional Paper No. 079, May 2018. Eurostat (2019): Population and social conditions database, Demography and migration, Population: Structure Indicators. Proportion of Population aged 65 years and more. Felder, S. (2013): Managing the health care system – The impact of demographic change on health care expenditure. CESifo DICE Report, 1/2013. https://wwz.unibas.ch/fileadmin/wwz/ redaktion/health/dicereport113-forum1.pdf Feyrer, J. (2008): Aggregate Evidence on the Link Between Age Structure and Productivity. Population and Development Review, March 2008, vol 34, pp. 78-99.

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5 Demographic changes in the world Fries, J. F. – Bruce, B. – Chakravarty, E. (2011): Compression of Morbidity 1980-2011: A Focused Review of Paradigms and Progress. Journal of Aging Researhc, Volume 11, Article ID 261702, 10 pages. International Labour Organization (2018a): World Employment Social Outlook: Trends 2018. International Labour Organization (2018b): Social Protection for Older Persons: Policy Trends and Statistics 2017-19. Social Protection Policy Papers No. 17. International Monetary Fund (2017): Regional Economic Outlook. Asia and Pacific: Preparing for Choppy Seas, May 2017. International Monetary Fund, European Department (2019): Demographic Headwinds in Central and Eastern Europe. European Departmental Paper Series. No. 19. Japan Government (2019): Realizing Society 5.0. https://www.japan.go.jp/abenomics/_userdata/ abenomics/pdf/society_5.0.pdf Jones, B. (2010): Age and Great Invention. The Review of Economics and Statistics, MIT Press, Vol. 92(1), pp. 1-14. Juselius, M. – Takáts, E. (2018): The Enduring Link between Demography and Inflation. BIS Working Paper No. 722. https://ssrn.com/abstract=3175848 Lee, R. – Mason, A. (2010): Fertility, Human Capital, and Economic Growth over the Demographic Transition. European Journal of Population, Vol. 26, Issue 2, pp. 159-182. Lee, R. – Mason, A. (2011): Population Aging and the Generational Economy: A Global Perspective Cheltenham, UK: Edward Elgar. www.ntaccounts.org Lee, R. D. – Reher, D. S. (2011): Introduction: The Landscape of Demographic Transition and Its Aftermath. Population and Development review Vol. 37. pp. 1–7. Lee, R. – Mason, A. (2017): Cost of Aging. Finance and Development, March 2017, Vol. 54, No. 1. https://www.imf.org/external/pubs/ft/fandd/2017/03/pdf/lee.pdf Liang, J. – Wang, H. – Lazear, E. P. (2014): Demographics and Entrepreneurship. NBER Working Papers No. 20506. http://www.nber.org/papers/w20506 Lindh, T. (1999): Medium-term Forecast of Potential GDP and Inflation Using Age structure Information. Submitted as working paper at Sveriges Riksbank. http://www.riksbank.se/ Upload/Dokument_riksbank/Kat_publicerat/WorkingPapers/WP_99.pdf Martins, J. O. – Gonand, F. – Antolín, P. – Maisonneuve, C. – Yoo, K. Y. (2005): The Impact of Ageing on Demand, Factor Markets and Growth. OECD Economics Department Working Papers No. 420. https://doi.org/10.1787/18151973 Masson, P. R. – Tryon, R. W. (1990): Macroeconomic Effects of Projected Population Aging in Industrial Countries. IMF Working Paper, No. 90/5.

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5.1 Economic challenges of ageing populations National Research Council (2012): Aging and the Macroeconomy: Long-term Implications of an Older Population. Committee on the Long-Run Macroeconomic Effects of the Aging U.S. Population. Board on Mathematical Sciences and their Applications, Division on Engineering and Physical Sciences, and Committee on Population, Division of Behavioral and Social Sciences and Education. Washington, D.C.: The National Academies Press. OECD és EU (2016): Recruiting Immigrant Workers: Europe 2016. OECD Publishing, Paris. http:// dx.doi.org/10.1787/9789264257290-en OECD (2017): Pensions at a Glance 2017: OECD and G20 Indicators. OECD Publishing, Paris. https://doi.org/10.1787/pension_glance-2017-en OECD (2018): Working Better with Age: Japan, Ageing and Employment Policies. OECD Publishing, Paris. https://doi.org/10.1787/9789264201996-en OECD (2019a): OECD Employment Outlook 2019: The Future of Work. OECD Publishing, Paris. https://doi.org/10.1787/9ee00155-en OECD (2019b): Ageing and Employment Policies - Statistics on average effective age of retirement. https://www.oecd.org/els/emp/average-effective-age-of-retirement.htm OECD (2019c): Employment rate by age group (indicator). https://data.oecd.org/emp/employmentrate-by-age-group.htm OECD (2019d): OECD Economic Surveys: Japan 2019. OECD Publishing, Paris. https://doi. org/10.1787/fd63f374-en Palotai, D. – Virág, B. (2016): Versenyképesség és növekedés. Út a fenntartható gazdasági felzárkózáshoz. Magyar Nemzeti Bank, 2016. Schneider, T. – Hong, G. H. – Le, A. V. (2018): Land of the Rising Robots. Finance and Development Vol. 55. No. 2. June 2018. https://www.imf.org/external/pubs/ft/fandd/2018/06/japan-laborforce-artificial-intelligence-and-robots/schneider.pdf Siliverstovs, B. – Kholodilin, K. A. –Thiessen, U. (2011): Does Aging Influence Structural Change? Evidence from Panel Data. Economic Systems, Vol. 35, No. 2, 2011. Sinnott, E. – Koettl-Brodmann, J. (2015) Aging with Growth in Central Europe and the Baltics: what’s next for old Europe?. Washington, D.C.: World Bank Group. http://documents.worldbank.org/ curated/en/559001468000582442/Aging-with-growth-in-Central-Europe-and-the-Baltics-whats-next-for-old-Europe United Nations, Department of Economic and Social Affairs, Population Division (2017a): Government policies to raise or lower the fertility level. Population Facts No. 2017/10. https://www. un.org/en/development/desa/population/publications/pdf/popfacts/PopFacts_2017-10.pdf United Nations, Department of Economic and Social Affairs, Population Division (2017b): Population ageing and sustainable development. Population Facts No. 2017/1. June 2017. https://www. un.org/en/development/desa/population/publications/pdf/popfacts/PopFacts_2017-10.pdf

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5 Demographic changes in the world United Nations, Department of Economic and Social Affairs, Population Division (2019a): World Population Prospects 2019. https://population.un.org/wpp/DataQuery/ United Nations, Department of Economic and Social Affairs, Population Division (2019b): World Population Prospects 2019: Highlights. https://population.un.org/wpp/Publications/Files/ WPP2019_Highlights.pdf Veen, S. (2008): Demographischer Wandel, alternde Belegschaften und Betriebsproduktivität. München, Rainer Hampp Verlag, 2008. World Health Organization (2015): World Report on Ageing and Health. https://www.who. int/ageing/events/world-report-2015-launch/en/

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5.2

Inequalities and growth in the 21st century Géza Rippel – Judit Várhegyi

Income and wealth inequalities have increased in the overwhelming majority of countries since the 1980s, making it one of the hottest topics of our time. There has been an intense debate among economic policy makers and researchers on the relationship between economic growth and inequalities for decades. It became a central issue again following the global economic crisis. The period chosen, the group of countries involved in the examination and their level of development all influence empirical results, which reinforces the fact that the relationship between economic development and inequalities is nonlinear. In addition to the effects of the crisis, the development of inequalities is also influenced by global megatrends like globalisation and technological development. Globalisation has resulted in the redistribution of income, with the emerging Chinese middle class and the high-income groups of developed economies being the real winners. Technological development has contributed to the increase in productivity for centuries, however, the introduction and proliferation of new technologies has broken the balance between those receiving capital and labour income – so it may widen income inequalities. As a result of globalisation and technological progress, jobs requiring medium qualifications have been terminated, but at the same time, demand for a highly-skilled workforce has increased significantly. The skill premium reinforced income inequalities. Inherited factors while path dependent has also played a role in the evolution and permanence of inequalities, because intergenerational income mobility greatly depends on parental background (income, educational attainment). There is no universal silver bullet to support inclusive growth and deal with inequalities, however, the ensuring of wider access to education and healthcare, the introduction or extension of job guarantees, and the reinforcement of financial regulation and surveillance could be appropriate

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means. The support of lifelong learning from early childhood provides an opportunity for adaptation to rapidly changing demands and greater social mobility, while job guarantees provide living through job opportunities, contributing to the stability of economic cycles as well.

How does income inequality influence the rate of economic growth? The relationship between economic growth and inequality has been at the focus for economists and economic policy makers for a long time. There is a lively debate ongoing nowadays, too. The identification of the causal link and the empirical proving of theoretical links is often difficult. According to Kuznets (1955), inequalities tend to increase in the early stage of economic development, to mitigate after a certain development level. Although empirical estimates were not able to prove the existence of the reverse U curve clearly, this theory still serves as the foundation for presenting economic development and the evolution of income inequality. In the same decade, Kaldor (1955, 1957) found that income inequalities lead to greater investment activity and economic growth, justified by the typically higher savings rate of those with higher incomes. Followers of this theory stress the existence of a tradeoff between growth and inequalities. The debate on the relationship of economic growth and inequalities has been active in recent decades, too. There is still no clear consensus on empirical estimates. The period chosen, the group of countries involved in the examination and their level of development all influence the results. Based on the Benhabibâ&#x20AC;&#x2122;s model (2003), the relationship between economic growth and inequalities is non-linear: the increase in inequalities first accelerates economic development and then (with the further widening of inequalities) the rate of growth decreases.

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Inequalities may support growth since they can provide innovation and enterprises with incentives (Lazear – Rosen 1981) and create opportunities for starting enterprises and participating in education in the developing countries – at least for a certain social group (Barro 2000). Nevertheless, the other camp is convinced that inequalities could limit economic development. A poor population has no opportunity to preserve its health and invest in human capital, which limits the potential performance of the economy (Galor – Zeira 1993, Aghion et al. 1999). Moreover, inequalities generate instability in economic policy which, in turn, limits investment (Alesina – Perotti 1996). The topic has been particularly focused in the post-crisis period. According to Rajan (2010), inequalities contributed to the overheating of the financial cycle while Stiglitz (2012) emphasised the influence of the rich on economic policy, all of which could have contributed to the emergence of the crisis.

What drives the changes in inequality? Despite differences in economic structures and economic policies, income inequality within countries typically increased in recent decades. In the USA, the top 1 per cent almost doubled its income share while the portion of the lower 50 per cent continuously decreased. The difference is spectacular if we examine income inequality in another developed region, namely, Western Europe. In 1980, the share of the top 1 per cent and the lower 50 per cent was essentially the same in the USA and Western Europe. The proportions changed only to a limited extent in Western Europe, the portion of the top 1 per cent increasing only by 2 percentage points. In China, Russia and India, inequalities significantly increased within countries as a result of economic opening and liberalisation. In countries like Brazil, South Africa or the economies of the Middle East, income inequalities are at extremely high levels.

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The extensive increase in the income share of rich people supports the fact that inequality is one of the hottest topics of the 21st century. The position within the income distribution (deciles) and share of economic prosperity is a contentious issue. The famous “elephant curve” of Lakner – Milanovic (2015) presents an increase in real income along the global income distribution. Based on their analysis, three main groups determined the evolvement of the so-called global growth incidence curve in recent decades: the top 1 per cent, the rising Chinese (and Indian) middle class, and the “Western” lower middle class. The most striking development is the substantial gain of the rich from the income increase of recent decades. Between 1980 and 2016, 27 per cent of real income per adult growth was received by the top 1 per cent, while the lower 50 per cent was responsible for only 12 per cent of this increase (Chart 5-22). The top 1 per cent of global distribution consists of mainly billionaires from the developed countries but the group also includes an increasing number of wealthy Chinese, Indian and Russian families, too. The rising Chinese and Indian middle classes also had an important effect on the shape of the curve. The top Chinese urban income group was at the 68th percentile of global distribution in 1988 but in 2008, they reached the 83th percentile, thus “jumping over” 15 per cent of the global population – almost 900 million people. The “biggest losers” of recent decades were the lower middle classes of developed economies. The German median employee increased his real income only by 7 per cent in 20 years while the same was negative in Japan.

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Chart 5-22: Global growth incidence curve (1980–2016)

Total real income growth per adult between 1980 and 2016 (%)

250

Bottom 50%

Top 1%

12% of total growth

27% of total growth

200 150 100 50

100.0

99.9

99.1

90.0

80.0

70.0

60.0

50.0

40.0

30.0

20.0

10.0

Income group (%) Source: MNB based on Piketty et al. (2018).

I) Global economic crisis

After 2008, the global economic crisis had fundamentally influenced the factors determining households’ incomes. The majority of the economies fell into recession, with the unemployment rate increasing substantially, encouraging governments to take action. Thus, the tax and transfer systems have changed over the last decade. Since the global economic crisis, income inequality has not changed essentially in most developed and emerging economies (Chart 5-23). In Iceland, the sharp increase in inequality resulting from the crisis has been reduced in recent years, while income inequality also decreased in Russia and Uruguay, but their levels are still significant. In larger Latin-American countries (Brazil, Chile, Mexico), income inequality is still expressly high, while it has increased overall in the USA since 2008. Since World War II, it has been typical in the USA that the top 10 per cent of society skims off a growing share of the boom cycles. Economic — 247 —

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upswings have not been inclusive since the 1980s in the USA, and over 70 per cent of income increase was gained by the richest 10 per cent in the last four growth periods (Tcherneva 2015, 2017). Chart 5-23: Income inequalities by country in 2008 and 2015 50 BR

Income inequality in 2015 (Gini index)

Increasing inequality CL

30 HU DK 25

IS Decreasing inequality

Income inequality in 2008 (Gini index) Note: those economies are positioned along the 45° line where income inequality has not changed from 2008 to 2015. SI=Slovenia, DK=Denmark, SK=Slovakia, HU=Hungary, IS=Iceland, US=USA, RU=Russia, UY=Uruguay, CL=Chile, MX=Mexico, BR=Brazil. Source: UNI-WIDER World Income Inequality Database.

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5.2 Inequalities and growth in the 21st century

Dobbs et al. (2016) examined the factors behind the changes in disposable income of median households for the period between 1993 and 2005 as well as between 2005 and 2014 (Chart 5-24). Their analysis found that the decrease in the growth rate of income is explained mainly by falling demand (the 2008 crisis and the 2012 Eurozone debt crisis). This is augmented by the general decline in population in developed countries. In the last decade, demography could have been an effective limit for the increase in income in the surveyed countries. Following the crisis, labour markets also changed radically. The slowdown in the growth rate of disposable income (or its decline) is influenced by the decreasing wage share, that is, wages and benefits paid to employees from the national income, to which the different wage dynamics in various income segments also contributes. In the United Kingdom and the USA, the earnings of high-income households increased while that of middle- and low-income ones significantly fell. Part-time work, which has become popular after the crisis, also contributed to this, particularly in medium- and low-skilled jobs. In Sweden, high trade union coverage helped to maintain jobs and the purchasing power of wages. Following the crisis, tax and transfer measures by the government have somewhat mitigated the declining income dynamics explained by market factors, while the estimated effect of the capital income was typically very limited in the case of median households.

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Chart 5-24: Factors determining the changes in disposable income 30

Per cent

Sweden

Tax and transfer abour market Demand

USA

France

2005 2014

3 2005 1

2005 2014

3 2005 1

2005 2014

1 UK

3 2005

2005 2014

3 2005

10 2005 2014

10 3 2005

Italy

Capital income Demography Changes in disposable income

Source: MNB based on Dobbs et al. (2016).

II) Globalisation

The distribution of income and wealth between and within countries has fundamentally been influenced by megatrends spanning decades or centuries. Globalisation and technological development are long-term structural processes, which both impact global income distribution, in addition to the growth rate of global GDP and world trade. From a historical perspective, experts typically identify two waves of globalisation. The first started during the 19th century and its end was marked by World War I, while the globalisation wave prevailing up to now started after World War II. Recently, almost one quarter of global production was exported while foreign input has a significant role in the economic activity of certain countries. The recovery of world trade supported economic expansion to a high extent in recent decades (Romer – Frankel 1999, Alcalá – Ciccone 2004), but globalisation resulted

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in the redistribution of income. Owing to the reduction of consumer prices and the widening range of available products, the aggregated impact of globalisation on consumers is positive on the whole, however, the stronger linkages in world trade resulted in the loss of jobs in certain regions. As a result of the new wave of globalisation, global value chains expanded (Baldwin 2012). Several new countries joined the network of world trade, commercial turnover multiplied in the case of intermediate (production inputs) and final products in recent decades as well, and the mobility of capital also increased substantially. According to an analysis by Basco – Mestieri (2019), capital stock and real wages increased in developed countries, while middle-income economies typically benefited less from globalisation, which could also have resulted in a declining share of the industrial sector and Rodrik’s (2016) “premature deindustrialisation” in certain countries. At the same time, the biggest winner of this period is China. In 1980, China was responsible for 3 per cent of global income (in purchasing power parities), which increased to 19 per cent in line with the dynamic economic expansion of recent decades by 2016, thus exceeding the share of the European Union or the USA and Canada (Piketty et al. 2018). During this period, the Chinese average income increased almost nine times, which significantly contributed to the mitigation of income inequalities between countries. On the other hand, the increasing share of high-income groups in China resulted in widening inequality within the country. Lang – Tavares (2018) also cited that typically it was the high-income groups that benefited from globalisation, while lower income groups hardly benefited from it at all, despite the fact that globalisation resulted in a substantial reduction of poverty in developing countries.

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5 Demographic changes in the world

Global wealth keeps on being accumulated typically in developed countries, but China now ranks second in the wealth hierarchy of the world. The Asian country was responsible for only 3.2 per cent of global wealth in 2000, which expanded to 16.4 per cent by 2018. Following the USA, the second highest number of dollar millionaires live there (Credit Suisse 2018). But wealth is still very much concentrated. The USA holds 31 per cent of global wealth and is home to 41 per cent of dollar millionaires (China ranks second with 8 per cent). The compilation by Forbes (2019) also supports this, since there are 16 American, 3 Chinese, 2 French and only 1 German, Indian, Mexican and Spanish citizens among the 25 richest people of the world. In developed countries, it is mainly those with a high income who have benefited from globalisation. The increasing foreign trade activity of China and emerging countries created fiercer competition for those on lower incomes. Acemoglu et al. (2016) argues that the Chinese import competition substantially contributed to the reduction of manufacturing employment in the USA before the crisis. The merchandise exports of the Asian country covered 2.5 per cent of GDP in 1970 which, following the policy of opening up, had increased almost 10 fold by 1990. The export performance picked up especially following the 2001 WTO accession. In 2006, the GDP share of merchandise exports exceeded 43 per cent. In tandem with this, manufacturing employment decreased by almost 4 million people in the USA between 2000 and 2008 (Chart 5-25). However, Magyari (2017) believes that jobs lost as a result of outsourcing and cost reduction were compensated for by new jobs created in higher wage categories and services (R&D, engineering, design), even within the same company. According to the results of the author, companies better exposed to Chinese competition created more jobs on the whole.

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Chart 5-25: Merchandise exports of China and US manufacturing employment 50

Per cent

Million

2000 2008

2014

2012

2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

1978

1976

1974

1972

1970

Chinese merchandise export/GDP US manufacturing employment (right-hand scale) Source: MNB based on Fouquin – Hugot (2016) and FRED.

Financial flows expanding as a result of financial globalisation (FDI, portfolio investments) increased income inequalities in developed and developing economies (Dabla-Norris et al. 2015). Financial globalisation and deregulation contributed to the fact that the financial sector has become one of the most quickly expanding sectors among developed economies and that the wages and wealth of its employees have substantially increased. III) Technological development

Besides globalisation, technological progress has contributed to the increase in productivity and the expansion of global GDP. Innovations like steamboats, telephones, PCs, MRI, mobile phones and artificial intelligence created and create new markets and jobs. Mokyr et al. (2015) confirm that new technological achievements have facilitated

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5 Demographic changes in the world

the development and proliferation of new products since the time of the Industrial Revolution. Although technological development promises long-term economic prosperity, the transition periods may bring about the reshaping of labour markets and the non-equal gains of social groups. Based on the lessons of history, the development of technology has resulted in an immediate increase in productivity and income per capita, followed only later by the increase in real wages. The process that took place in the United Kingdom in the age of the Industrial Revolution has been called the “Engels’ pause” by Allen (2009) (Chart 5-26,, left panel). New technological achievements (the steam engine, steamboat etc.) led to the expansion of productivity and the acceleration of economic growth, chiefly benefiting “the owners of technology” (capitalists). The break-up of the balance between the owners of capital and work led to the widening of income inequality in the period following the introduction of new technologies and innovations. In the decades following World War II, productivity and wages were developing in close alignment in the USA, both doubling between 1948 and 1973. At the same time, productivity and real wages have substantially been decoupling since the 1970s, which is more striking in the case of median wages. Private sector productivity more than doubled between 1973 and 2014, while average real wages increased by 44 per cent and median real wages by only 9 per cent (Chart 5-26, right panel). The gap between productivity and average wages was a consequence of the decrease in the wage share (the decline in the ratio between labour and capital income) and from price effects (different evolution of consumer, producer prices and the terms of trade). The decoupling of average and median wages could be explained by the changes in the wage distribution, that is, inequality among employees significantly increased in recent decades (Bivens – Mishel 2015, Stansbury – Summers 2017). USA trends are explained by rapid technological development, the increase in unemployment and health insurance transfers, the decreasing mobility of the labour force, — 254 —

5.2 Inequalities and growth in the 21st century

the reduction of the bargaining position of trade unions and the noninclusive educational system. Chart 5-26: Productivity and real earnings in the UK (left panel) and in the USA (right panel) 0

150

Engels pause

125

1 48 1 73

110

150

100

GDP/employee Real earnings

2018

8 1

1 88

1 78

2008

USA

50 1 68

United ingdom

1760 1770 1780 17 0 1800 1810 1820 1830 1840 1850 1860 1870 1880 18 0 1 00 1 10

100

200

1 73

1 58

250

1760

1 48

300

Output per hours worked Average real compensation per hour Median real compensation per hour

Source: MNB based on Allen (2009), Bank of England (2018), Bivens – Mishel (2015) and FRED.

IV) Skill premium: Technological progress and globalisation led to the polarisation of jobs by qualification in developed economies, where it was mainly the highly qualified who benefited from the increase in income. The employment structure of the USA have gradually shifted from jobs requiring medium qualifications (and paying medium wages) towards higher and lower ones since the 1980s (Acemoglu – Autor 2011). This phenomenon can be identified in Europe as well, where the proportion of employment paying medium wages decreased from 47 per cent to 38 per cent from 1993 to 2010 (Goos et al. 2014). The labour markets have been transforming as a result of globalisation and technological development: demand for capital and a skilled — 255 —

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labour force have increased, but jobs have been lost due to growing automation, typically affecting medium-skilled occupations (Acemoglu 1998). Besides the highly qualified, technological development and automation increase the employment of workers with low qualifications. The outflow of labour from lost medium-skilled jobs may lead to higher wage categories by retraining or flow into non-automated low-skilled jobs requiring a personal presence and communication skills (hairdresser, cleaner). This is the skill “U curve” (Autor – Dorn 2013), which is resulting in the increase of income inequality through job polarisation. Based on OECD (2011), technological development increased income inequalities are mainly the case in the developed countries, which explained almost one-third of the difference in wage increases of the 90th and 10th income percentiles. From the beginning of the 1990s until the crisis, the wages of the high-skilled typically increased at a higher rate than those with basic qualifications in the USA. The skill premium (wage premium for higher qualifications) of those with the highest school attainment gradually increased until 2009 and then it has decreased overall since the crisis (Chart 5-27). On average the medium-skilled earn 55 per cent more than those with only a basic education in the USA. Moreover, an MA/MSc degree increases wages by more than two times while a PhD degree by three times.

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Chart 5-27: Earnings relative to those with a basic education and the evolution of income inequality (USA) 600

Per cent

Gini-index 2009

0.40

0.38

400

0.36

300

0.34

200

0.32

100

0.30 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

500

Gini (right-hand scale) MA/MSc

Secondary educated PhD

Source: US Census Bureau, OECD.

V) Intergenerational income mobility

In addition to individual decisions, talent, effort and luck, inherited factors also play an important role in the evolution of inequality, thus the development of income inequality is also characterised by path dependence. When examining income inequalities, the literature mainly presents the difference between outcomes, but the inequality of opportunity is being given more and more attention, mainly as a result of the work of Sen (1999, 2001).

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The theory emphasises the freedom of choices regarding the way of life they would like to live. Within this framework, the objective is not the equalisation of income, but rather the determining power of inherited factors on which we have no influence but limit our opportunities: gender, race, parental background, the educational and healthcare system and access to subsistence factors. Equal opportunities are provided by such a society, where living is not determined by circumstances and the freedom of choice is not limited for anyone. Naturally, there is a correlation between inequality of opportunity and income inequality: in countries where the access of individuals to subsistence factors as well as their decisions are more limited, income inequality is also typically higher. In countries examined by the EBRD (2016), these being mainly emerging countries of Eastern, Southern and Central Europe, 30 to 50 per cent of total income inequality can be related to path dependence. Two countries can be highlighted as examples: Income inequality is relatively low in Slovenia (its Gini coefficient being 0.26), of which only a small proportion (around 30 per cent) is explained by the inequality of opportunity. But in Estonia, income inequality is higher (its Gini coefficient being 0.35), almost 50 per cent of which can be related to inherited factors (Chart 5-28). Based on the analysis, inequality of opportunity is expressly determined by parental background (school attainment of parents) and gender, while urban/rural origin or belonging to a majority or minority explains only a smaller part of inequalities.

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Chart 5-28: Income inequality and the decomposition of the inequality of opportunity 0.20

Gini-index

Higher inequalities

Lower inequalities

0.5

0.15

0.4

0.10

0.3

0.05

0.2

0.00

TR RU BG RO HU GR

Ethnic (minority/majority) Gender Income inequality (right-hand scale)

0.1

Birthplace (urban/rural) Parental background

Source: EBRD (2016).

In the group of countries examined by EBRD, inequality of opportunity is typically lower in Western Europe, while the value for the USA is typically two times higher, more than three times in India and significantly higher (almost ten times) in Brazil. Bourguignon et al. (2005) estimated for Brazil that inherited factors (race, place of birth, school attainment and occupation of parents) explain almost onequarter of the differences between earnings. Intergenerational mobility in the US society was examined by Chetty et al. (2014). Pop culture often characterises the USA as the “land of opportunities”, but the authors found that there are significant differences in respect to the influence parental background has on

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the income situation of children. In the South-eastern United States, mobility is low, while children of low-income families in central regions have a higher probability to rise higher in the income distribution. Mobility is mostly impacted by parental background, nevertheless, racial segregation, participation and achievement in education as well as social networks (religion, local civic organisations) also influence it. A study by Palomino et al. (2018) on US data between 1980 and 2010 confirms that parental background has a determining role in intergenerational mobility. The analysis found a U-shaped relationship between the income situation of parents and children, thus, the situation of parents has the highest explanatory power at the bottom and top of the distribution. Naturally, intergenerational mobility is related to the level of income inequalities, which is known as the Great Gatsby curve (Krueger 2012, Corak 2013). Intergenerational mobility is typically more limited in countries with higher income and wealth inequality (Chart 5-29). In Finland and Denmark, low income inequality goes hand in hand with higher social mobility, while in bigger Latin-American countries and the USA, mobility is lower in line with significant income inequalities. So, it is less probable that those from poorer families get to the top of the income hierarchy. Borella et al. (2019) produced a striking finding when examining the income inequality of American society. The white, less educated generation born in the 1960s is in a worse situation than those born in the 1940s, which is also explained by low wage dynamics, the remarkably growing healthcare costs and decreasing life expectancy.

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Chart 5-29: Income inequality and intergenerational earnings mobility 0.7

Intergenerational earnings mobility (coefficient)

Lower mobility ZA

0.6

CL BR

0.5 MX 0.4

0.3

PT GR

CH DE

0.2

IE NL AT SI

GB ES IT

Higher inequality 0.1 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Income inequality in 2010 (Gini-index) Source: UNI-WIDER World Income Inequality Database, EqualChances.org

What are the possible economic policy responses to address inequality? Within country inequality and intergenerational mobility is a contentious issue for economic policy makers in both developed and emerging countries (Piketty 2014). However, just like in the case of the relationship between economic growth and income inequalities, opinions are diverse regarding the role of government redistribution. Meltzer – Richard (1981) found that higher inequalities may encourage higher redistribution since the majority of citizens may vote for equalisation policy in order to mitigate their economic disadvantage. At the same time, this can be counterbalanced by the higher political influence of the rich (Benabou 2000, Stiglitz 2012). Examining direct — 261 —

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channels, Okun (1975) argued that higher taxes and subsidies limit employment and investment incentives, and thus reduce the rate of economic growth. Nevertheless, Berg et al. (2012) and Ostry et al. (2014) believe that (in non-extreme cases) redistribution goes hand-in-hand with higher economic growth rates. It is worth noting the non-linear relationship between economic growth (development) and inequality, which can shape economic policy and its respective toolset as well. Measures improving economic competitiveness support the transition to a knowledge-based society and an efficient and productive company ecosystem. Inclusive growth strategies focus on education and vocational training, healthcare, labour market reforms and the mitigation of tax avoidance, among others. Adaptation to changing global demands can be ensured by the modern vocational training system and the widely accessible education and healthcare. Besides, living through work opportunities and the access to labour market reserves can also contribute to inclusive economic growth. I) Education and healthcare

Education and healthcare play an especially important role (Mincer 1958, Dabla-Norris et al. 2015, OECD 2017). The increase in access to education and healthcare widens opportunities and decisions which, in turn, can contribute to a better life for individuals. The proportion of those participating in primary education typically exceeds 90 per cent, while life expectancy at birth is around 80 per cent in developed European and North American countries. This is much lower in several African, Asian and Latin-American countries, which relates to the nonequal starting opportunities of individuals. Besides national economy averages, the distribution of access is also determining. There is only a small difference in the proportion of higher education graduates in respect to the top and bottom income groups in Ireland, Denmark and Sweden, while the gap is substantial in France, Poland and Hungary (Chart 5-30). Although 85 per cent of the top income group graduated from higher education in Mexico, opportunities and thus the results of the bottom income quintile are substantially limited. â&#x20AC;&#x201D; 262 â&#x20AC;&#x201D;

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Chart 5-30: Share of higher educated in top and bottom quintile and life expectancy at birth 100

Per cent

Years

Egypt

Kenya

India

Nigeria

Indonesia

Italy

Columbia

Czechia

Hungary

Germany

Sweden

40 Switzerland

0 Finland

Portugal

Poland

Denmark

France

Ireland

Mexico

Top quintile Bottom quintile Life expectancy (right-hand scale) Source: World Bank WDI, UNESCO WIDE.

Higher education attainment provides access to a wide range of job opportunities and higher earnings, while also serving as an indicator of better skills and higher productivity. Investment in education may provide young people with new opportunities, so it is extremely important in addressing income inequality. Ahmed et al. (2017) found that the educational gap (differences in the years spent in education between 20 to 24-year-olds and those between 60 and 64) decreased in the developed countries in the 2000s, which could imply that these two generations achieved approximately the same educational level. At the same time, the young tend to spend more time in education in developing and emerging countries, which can lead to the transformation of global labour force distribution and a more significant role for emerging economies.

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Aizenman et al. (2017) highlights the importance of vocational training. Examining the data of the USA and Germany, they found that wellresourced and well-targeted vocational training can be the right solution for the loss of jobs in the manufacturing industry. Although the average school attainment of US manufacturing workers is higher than their peers in Germany, the research suggests that the vocational training system of Germany is better adapted to the changing needs of manufacturing. It is important in both developed and developing economies to increase educational attainment, to develop educational infrastructure and to mitigate financial barriers, so that a growing proportion of society has the skills necessary in a rapidly changing and globalising world. It is of special importance that learning, and the development of skills start at a young age and are lifelong. Research supports that cognitive and social/emotional skills developed in the first years of our lives determine the basis of future potential (OECD 2017). Supporting access to early childhood schooling and healthcare is fundamental for economic policies while, in the most disadvantaged regions, the involvement of parents in the programmes may support childrenâ&#x20AC;&#x2122;s later success in life. II) Job guarantee

Universal basic income and job guarantee often emerges as an economic policy response addressing income inequality. There is an extensive debate in the literature on the applicability and estimated effects of these tools. Nevertheless, ensuring a standard of living that is accessible and appropriate for all can be the key to an inclusive society. Regarding universal basic income, there are few available results to cross-check (Box 1), but job guarantee can help to address income inequality (Atkinson 2015, Tcherneva 2018).

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Box 5-1 Universal basic income as an economic policy tool?

As a result of increasing income inequality, economic policy discourse often includes the topic of basic income. Rapidly changing technology and globalisation can be a challenge for the low- and medium-skilled and disadvantaged groups, so one of the theoretical tools ensuring their social welfare is basic income, namely a direct financial support from the government. Although certain middle-income economies (India) attempted to introduce this measure, it is rather the developed countries that provide us with examples in this case. In Finland, the programme introduced in January 2017 provided 2 thousand participants with EUR 560 monthly, which just exceeded one-quarter of the median income of households. In France, there have been pilot initiatives to introduce certain variants of the basic income. In the USA, locally organised innovative initiatives are related to the framework of the basic income, but all of these would affect small groups only. A universal (provided unconditionally for a wide group of society) basic income could theoretically ensure that no one is left without support in society. At the same time, this idea would imply significant fiscal burdens, while the possible benefits are hard to quantify. This measure is not targeted, so it would serve as a major counter-incentive for employees with regard to performance at their full potential. OECD (2017) highlights the importance of focussed policies, because universal basic income would result in less advantageous outputs than the starting one in the case of disadvantaged groups formerly receiving higher transfers. There are examples of the pilot introduction of the theoretical basic income, but not all details are known about these initiatives and the estimate of their economic and social effects is also uncertain.

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Job guarantee is a voluntary but permanent and widespread employment network, which is designed to manage the issue of unemployment on a local level. The programme ensures basic welfare through job opportunities, so it can improve the lower social segmentâ&#x20AC;&#x2122;s share of income growth. According to this idea, the government creates an employment reserve with employment programmes for a permanently high number of persons, thus ensuring the stability of economic growth cycles. Inflation stability is also ensured by the linking of wages and productivity. As opposed to universal basic income, job guarantee provides living through job opportunities and helps address mental problems (criminality) arising from long-term unemployment. Together with on-the-job training and learning, the programme provides an opportunity for participants to transform their skills to match changing demands and, in the case of a successful transition, to find a job on the market. Most successful examples of job guarantee include the WPA (Work Progress Administration) programmes launched during the New Deal, financing almost 8 million jobs between 1935 and 1943. In India, there is a programme for those employed in agriculture based on similar principles (covering a large number of people), while several European countries (including Hungary) actively use certain elements of the job guarantee framework. According to a survey by McElwee et al. (2018), this programme is more and more popular in the USA, and especially among the young, low-income and non-white groups of society. III) Taxation and financial regulation: In addition to high-quality and accessible education as well as healthcare, and permanent labour market participation, taxation policy is also important to address income inequality (Atkinson 2015). There are intense debates ongoing between economic policy makers on the features of an optimal taxation system. Laffer (2004) found that the increase in tax rates would initially raise tax revenues, but after a certain value, the increase in the tax rates

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is counterproductive (Chart 5-31). The Laffer curve is a theoretical construction, but it helps to make clear the non-linear relationship between the tax rate and the tax revenues. Efficient taxation can help to limit tax avoidance among both companies and individuals. Chart 5-31: The theoretical Laffer curve Tax income

Laffer curve

Tax rate

100 %

Source: MNB based on Laffer (2004).

Differences in the taxation systems and regulation between countries has contributed to the creation of tax havens. Not all dimensions of global financial flows are covered by deep and reliable databases, but Zucman et al. (2016) estimate that, on a global level, 8 per cent of the financial wealth of households is kept in tax havens. Offshore wealth exceeds USD 1,200 billion in the USA and Asia, nevertheless, it is less than 5 per cent of total financial wealth (Chart 5-32). Offshore wealth in proportion to total financial wealth is estimated to exceed 50 per cent in the Gulf States and in Russia. Tax evasion is rife among companies too, with 55 per cent of foreign profit of American companies being held in tax havens.

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Chart 5-32: Offshore financial wealth in major economies (2015) 3,000

USD Billions

Per cent

500

Russia

Canada

1,000

Africa

Latin America

1,500

Gulf countries

USA

2,000

Asia

Europe

2,500

Offshore wealth In percentage of total financial wealth (right-hand scale) Source: MNB based on Zucman et al. (2016).

Tax evasion amounted to USD 200 billion globally in 2015 (Zucman et al. 2016), and thus requires globally coordinated measures. The authors believe that one solution could be the global registering of financial wealth, where owners of shares and bonds would be displayed. Both Piketty and Zucman suggest a solution to mitigate the income gap between top and bottom income groups, which requires significant international cooperation. The coordination of taxation policies and regulation suggested by them would require serious sacrifices from national economies.

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References Acemoglu, D. (1998): Why Do New Technologies Complement Skills? Directed Technical Change and Wage Inequality. Quarterly Journal of Economics 113 (4): 1055–89. Acemoglu, D. – Autor, D. (2011): Skills, Tasks and Technologies: Implications for Employment and Earnings. In Handbook of Labor Economics, 4:1043–1171. Acemoglu, D. – Autor, D. – Dorn, D. – Hanson, G. H. – Price, B. (2016): Import competition and the great US employment sag of the 2000s. Journal of Labor Economics 34: S141-S198. Aghion, P. – Caroli, E. – Garcia-Penalosa C. (1999): Inequality and Economic Growth: The Perspective of the New Growth Theories. Journal of Economic Literature, Vol. 37(4), pp. 1615–1660. Ahmed, S. A. – Bussolo, M. – Cruz, M. – Go, D. S. – Osorio-Rodarte, I. (2017): Global Inequality in a More Educated World. Policy Research working paper 8135, World Bank. Aizenman, A. – Jinjarak, Y. – Ngo, N. – Noy. I. (2017): Vocational Education, Manufacturing, and Income Distribution: International Evidence and Case Studies. NBER Working Paper No. 23950 Alcalá, F. – Ciccone, A. (2001): Trade and productivity. Economics Working Papers 580, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2002. Alesina, A. – Perotti, R. (1996): Income Distribution, Political Instability and Investment. European Economic Review, Vol. 40(6), pp. 1203–28. Allen, R. C. (2009): Engels’ pause: Technical change, capital accumulation, and inequality in the british industrial revolution. Explor. Econ. Hist. (2009). Atkinson, A. B. (2015): Inequality – What Can Be Done?. Harvard University Press, Cambridge, Massachusetts, 2015. Autor, D. – Dorn, D. (2013): The Growth of Low-Skill Service Jobs and the Polarization of the U.S. Labor Market. American Economic Review 103(5), 1553‒1597. Baldwin, R. (2012): Global supply chains: Why they emerged, why they matter, and where they are going. CEPR discussion paper 9103. Bank of England (2018): A millennium of macroeconomic data. Research datasets. https://www. bankofengland.co.uk/statistics/research-datasets Barro, R. J. (2000): Inequality and Growth in a Panel of Countries. Journal of Economic Growth, Vol. 5(1), pp. 5–32. Basco, S. – Mestieri, M. (2019): The world income distribution: the effects of international unbundling of production. Journal of Economic Growth, Springer, vol. 24(2), pages 189-221, June. Benabou, R. (2000): Unequal Societies: Income Distribution and the Social Contract. The American Economic Review, 90(1): pp. 96-129. Benhabib, J. (2003) The Tradeoff Between Inequality and Growth. Annals of Economics and Finance, Vol. 4(2), pp. 491–507.

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5 Demographic changes in the world Berg, A. – Ostry, J. D. – Zettelmeyer, J. (2012): What Makes Growth Sustained?. Journal of Development Economics, 98(2): 149–166. Bivens, J. – Mishel, L. (2015): Understanding the Historic Divergence between Productivity and a Typical Worker’s Pay: Why It Matters and Why It’s Real. Washington DC: Economic Policy Institute. Borella, M. – De Nardi, M. – Yang, F. (2019): The Lost Ones: The Opportunities and Outcomes of White, Non-College Educated Americans Born in the 1960s. NBER Working Paper no. 25661. Bourguignon, F. – Ferreira, F. – Menendez, M. (2005): Inequality of Opportunity in Brazil? World Bank.Washington, DC. Chetty, R. – Hendren, N. – Kline, P. – Saez, E. (2014): Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the US. NBER Working Paper 19843 Corak, M. (2013): Income Inequality, Equality of Opportunity, and Intergenerational Mobility. Journal of Economic Perspectives, 27 (3): 79-102. Dabla-Norris, E. – Kochhar, K. – Suphaphiphat, N. – Ricka, F. – Tsounta, E. (2015): Causes and Consequences of Income Inequality; A Global Perspective. IMF Staff Discussion Notes 15/13, International Monetary Fund. Dobbs, R. – Madgavkar, A. – Manyika, J. – Woetzel, J. – Bughin, J. – Labaye, E. – Huisman, L. – Kashyap, P. (2016): Poorer than their Parents? Flat or Falling Incomes in Advanced Economies. McKinsey Global Institute, July 2016. https://www.mckinsey.com/~/media/McKinsey/ Featured%20Insights/Employment%20and%20Growth/Poorer%20than%20their%20parents%20 A%20new%20perspective%20on%20income%20inequality/MGI-Poorer-than-their-parents-Flator-falling-incomes-in-advanced-economies-Full-report.ashx EBRD (2016): Transition Report 2016-17. Transition for all: Equal opportunities in an unequal world. European Bank for Reconstruction and Development, 04 Nov 2016. https://www.ebrd.com/ news/publications/transition-report/transition-report-201617.html Forbes (2019): The World’s Billionaires. https://www.forbes.com/billionaires/list/#version:static Fouquin, M. – Hugot, J. (2016): Two Centuries of Bilateral Trade and Gravity Data: 1827-2014. CEPII Working Paper 2016- 14, May 2016, CEPII. Galor, O. – Zeira, J. (1993): Income distribution and macroeconomics. Review of Economic Studies, 60 35-52. Goos, M. – Manning, A. – Salomons, A. (2014): Explaining Job Polarization: Routine-Biased Technological Change and Offshoring. American Economic Review 104 (8): 2509–26. Kaldor, N. (1955): Alternative Theories of Distribution. Review of Economic Studies 23(2), p. 83-100. Kaldor, N. (1957): A model of economic growth. Economic Journal 67, 591-624. Krueger, A. (2012): The Rise and Consequences of Inequality in the US. Speech at the Center for American Progress, Washington D.C. on 12 January.

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5.2 Inequalities and growth in the 21st century Kuznets, S. (1955): Economic growth and income inequality. American Economic Review 45(1), 1-28. Laffer, A. (2004): The Laffer Curve, Past, Present and Future. Backgrounder, no. 1765. Heritage Foundation. Lakner, C. – Milanovic, B. (2015): Global income distribution: from the fall of the Berlin Wall to the Great Recession. World Bank Economic Review 30(2): 203-232. Lang, V. F. – Tavares, M. M. (2018): The Distribution of Gains from Globalisation. IMF Working Paper 18/54. Lazear, E. P. – Rosen, S. (1981): Rank-Order Tournaments as Optimum Labor Contracts. Journal of Political Economy, Vol. 89(5), pp. 841–64. McElwee, S. – McAuliffe, C. – Green, J. (2018): Why Democrats Should Embrace a Federal Jobs Guarantee. The Nation, March 20. Mincer, J. (1958): Investment in Human Capital and Personal Income Distribution. Journal of Political Economy 66 (2): 281-302. Magyari, I. (2017): Firm Reorganization, Chinese Imports, and US Manufacturing Employment. Working Papers 17-58, Center for Economic Studies, U.S. Census Bureau. Mokyr, J. –Vickers, C. –Ziebarth, N. L. (2015): The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different?. Journal of Economic Perspectives 29, 31–50. Nino-Zarazúa, M. – Roope, L. – Tartp, F. (2017): Global Inequality: Relatively Lower, Absolutely Higher. Review of Income and Wealth, Series 63, Number 4, December 2017. OECD (2011): Divided We Stand: Why Inequality Keeps Rising. Paris: OECD Publishing. OECD (2017): Bridging the Gap: Inclusive Growth 2017 Update Report. Ostry, J. D. – Berg, A. – Tsangarides, C. G. (2014): Redistribution, Inequality, and Growth. IMF Staff Discussion Notes 14/02, International Monetary Fund. Palomino, J. C. – Marrero, G. – Rodríguez, J. G. (2018): One size doesn’t fit all: a quantile analysis of intergenerational income mobility in the U.S. (1980-2010). Journal of Economic Inequality 16(3): 347-367. Piketty, T. (2014): Capital in the twenty-first century. Cambridge Massachusetts: The Belknap Press of Harvard University Press. Piketty, T. – Saez, E. – Zucman, G. (2018): World Inequality Report 2018. https://wir2018.wid. world/ Rajan, R. (2010): Fault Lines: How Hidden Fractures Still Threaten the World Economy, Princeton: Princeton University Press. Rodrik, D. (2013): Unconditional Convergence in Manufacturing. Quarterly Journal of Economics, Volume 128, Issue 1, pp. 165–204.

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5 Demographic changes in the world Romer, D. H. – Frankel, J. A. (1999): Does Trade Cause Growth?, American Economic Review, American Economic Association, vol. 89(3), pages 379-399, June. Sen, A. (1999): Development as freedom. Anchor Books. Sen, A. (2001): Ten theses on globalization. New Perspectives Quarterly, Vol. 18 No. 4, pp. 9-15. Stansbury, A. M. – Summers, L. H. (2017): Productivity and Pay: Is the link broken?. NBER Working Papers 24165, National Bureau of Economic Research, Inc. Online: Stiglitz, J. (2012): The Price of Inequality: How Today’s Divided Society Endangers Our Future. W. W. Norton & Company. Tcherneva, P. R. (2015): When a Rising Tide Sinks Most Boats: Trends in US Income Inequality. Economics Policy Note Archive 15-4, Levy Economics Institute. Tcherneva, P. R. (2017): Inequality Update: Who Gains When Income Grows?. Economics Policy Note Archive 17-1, Levy Economics Institute. Tcherneva, P. R. (2018): The Job Guarantee: Design, Jobs, and Implementation. Economics Working Paper Archive wp_902, Levy Economics Institute. Zucman, G. – Fagan, T. L. – Piketty, T. (2016): The Hidden Wealth of Nations. University of Chicago Press Economics Books, University of Chicago Press, number 9780226422640, June.

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Social effects of the development of technology

6.1

Changes in the labour market in regard to the development of technology Levente Erdélyi – Gábor Dániel Soós

Technology is one of the most important factors determining the future of the labour market. A large number of jobs may be lost as a result of automation and the widespread use of Artificial Intelligence (AI) but new technologies could also create jobs. The jobs created by innovation will play a key role in the future to maintain a high level of employment following robotization. However, robotization and innovation make the labour market even more polarized. In addition to automation, digitalization will bring changes to workflow as well: flexibility in space, time and the working environment will gain more importance in the future. The changes regarding the place and time of work are reflected in the boom in the social economy that offers greater freedom compared to traditional forms of work. Virtual work is a flexible option, and the number of people working in the digital space (digital nomads) is growing. New technologies accelerate the change in the skillset expected by employers – jobs in the future will require creativity, critical thinking, and advanced social skills (communication, cooperation). Employees will have to update and upgrade their knowledge to have a competitive edge on robots. This will ensure that employment will continue to be a key factor of growth in the long term.

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Do robots really take our jobs away? Section 3.3 shows that many fear that new technologies such as robots and AI will terminate their jobs in the coming years and decades. The effect of the development of technology on the labour market is a popular field of study within economics. Several research papers have investigated how automation effects employment and wages. Conclusions drawn from the past may help to understand how the changes in technology affect the labour market. But we need to see how today’s changes differ from the ones in the past. Technological revolutions in the past affected only a narrow segment of the economy and as such the loss of jobs was concentrated. The first industrial revolution saw the mechanisation of agriculture, and labourers who lost their jobs moved to the manufacturing industry. The next wave of automation channelled workers from the manufacturing industries to the services sector. As negative labour market developments were gradually balanced by the new jobs created in the new industries, the increase in unemployment proved to be temporary and the phenomena of permanent technological unemployment did not occur. New technologies brought about fundamental changes in the economy and employment, but unemployment levels did not rise as a result of structural changes (Chart 6-1). The fluctuations of unemployment were mainly caused by economic cycles – for example the Great Depression (1929–1933) led to an unemployment rate of 20 per cent.

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6.1 Changes in the labour market in regard to the development of technology

Chart 6-1: Share of the main sector of the US labour market 100

Per cent

90 20

80 70

60 50

40 30

Agriculture Services

2015

2010

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

1950

1945

1940

1935

1930

1890

1840

10 0

Manufacturing Unemployment rate (right-hand scale)

Source: Herrendorf et al. (2014), Groningen Growth and Development Centre (GGDC), Lebergott (1964), Coen (1973), Romer (1986), BLS, FRED.

The current industrial revolution is widely regarded as another cycle of creative destruction, similar to the earlier ones. However, an important difference is that AI and the new phases of automation will affect every segment of the economy and not just a distinct one (Ford, 2015). In the past machines replaced manpower, but smart automation is set to replace intellectual labour (PwC 2018). Expert predictions for the future are varied – some papers outline a world without human labour, but the latest studies contradict this narrative. Based on US data, Frey and Osborne (2013) estimate that in the coming decades significant automation will put around 47 per cent of current workplaces at risk. According to the World Bank, in just 20 years 57 per cent of the positions will be filled by robots (World Bank 2016). McKinsey outlines a scenario of a more heterogeneous automation process where only 1 per cent of workplaces are fully automated, with 60 per cent of workplaces up for partial automation — 277 —

6 Social effects of the development of technology

(Manyika at al. 2017a). In the event of partial automation, at least 30 per cent of tasks will be performed by machines. Arntz et al. (2016) used a similar methodology and came to the conclusion that 9 per cent of the jobs will be terminated due to robotization in the OECD countries. Nedelkoska and Quintini (2018) claim that 14 per cent of workplaces will be eligible for large scale (at least 70 per cent) robotization in the future. The methodology used in recent calculations anticipates a more moderate effect because when the forecast is made for the subtasks involved and not for the position itself, the probability of full automation of the position is smaller (Chart 6-2). Chart 6-2: Range of automation estimates for current workplaces 70

Share of automatable jobs (%)

Arntz et al. (2016)

Nedelkoska & Quintini (2018)

Manyika et al. (2017)

Frey & Osborne (2013)

World Bank (2016)

Source: MNB.

It is important to note that estimates concern only the automation possibilities of existing workplaces, and do not take into consideration new jobs or any other conditions of the actual implementation of automation. The automation process does not exclusively depend on technical feasibility. Other factors involve the cost of the new

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technology, the amount and cost of the workforce available, the financial viability of the investment and very importantly the social acceptance of automation (Manyika et al., 2017b). Taking these factors into consideration, the most probable scenario is that use of human labour will be transformed but not replaced by robotization. The possible extent of automation differs for each position. The automation of subtasks depends on two conditions. The first question is to what extent the job contains routine tasks. The second, to what extent the job requires skills that are hard to / not yet possible to robotize (for example social skills or creativity and critical thinking). So the general fear of new technologies has not faded since studies on the effects of automation on the labour market currently draw contradictory conclusions regarding both aggregated employment and individual jobs. As new technologies transform everyday life faster than previous industrial revolutions, forecasts necessarily become more uncertain. A large number of jobs may be lost as a result of automation and the widespread use of Artificial Intelligence (AI) but new technologies may also create new jobs. Acemoglu and Restrepo (2016) draw attention to the dual nature of technology â&#x20AC;&#x201C; automation processes terminating jobs and innovative processes creating jobs are both present in the economy at the same time (Chart 6-3). Within the framework presented by the authors, simple tasks are performed by capital (machines) while more complex tasks are performed by humans.

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Chart 6-3: The connection between automation and innovation

Tasks performed by capital

Tasks performed by labour

Capital

Labour

Artificial intelligence (automation)

Least complex tasks

New tasks (innovation)

Labour

More complex tasks

Source: Authors’ own compilation based on Acemoglu – Restrepo (2016).

New technologies change the structure of the economy. Demand for jobs that are easy to automate decreases. As a result of innovation, obsolete jobs will be replaced by new jobs in the economy where human labour will still have an advantage over machines. With the development of the economy, labour intensive tasks will be automated and AI, as a new production factor, will take over tasks from employees. Employees will win in the introduction of new technologies in the economy if the number of new jobs created as a result of innovation balances negative labour market trends. This means that besides the negative effects of technology its innovative role also needs to be investigated. The significant importance of new professions is also justified by historical data. Acemoglu and Restrepo (2016) analysed US data and came to the conclusion that there is a positive connection between the ratio of innovation-based new jobs, that previously did not exist, and the expansion in employment and GDP growth. In sectors, where the

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6.1 Changes in the labour market in regard to the development of technology

ratio of new jobs was higher by 10 per cent, employment grew 5 per cent faster in the following decade. Based on their calculations, during the 30 years preceding the crisis (1980â&#x20AC;&#x201C;2007) half of the expansion in employment occurred in branches where new professions came into being. 18 per cent of professions existing today did not exist at all before 1980 (Lin 2011). For instance, as computers appeared, new tasks required employees in new positions thus system administrator, developer and other IT professions came into being. Innovation has created numerous new professions in the last 10 years too. Some of these are illustrated in Box 6-1. Box 6-1 New technologies create new professions in the labour market

If the open positions available in the labour market are considered professions that did not exist a decade ago can be observed. (WEF, 2016a). Rapid changes in technology create new positions for employees from mobile app (application) development to being a Generation Z expert. The advent of iPhone in 2007 marked the start of the age of smart phones. Today nearly half of the adult population of the world have such a device. Customers install and use a growing number of apps on their phones and this increasing demand made the profession of mobile app developer extremely popular. Although self-driving cars will probably make most taxi drivers redundant, new technologies have also created new jobs in this sector. The production, development and maintenance of self-driving cars will require special mechanics, software developers (autonomous system IT experts), and engineers (autonomous vehicle control engineers). The advent of the Internet and social media created professions such as social media manager and vlogger (YouTube content creator). Companies

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take on Generation Z experts to manage recruitment. This is the first infocommunication native generation to enter the labour market. It is anticipated that the technological revolution will make the role of new professions even more important – 65 per cent of the children starting school today will probably have a profession that does not exist today.

100 150 200 50 0 −200 −150 −100 −50

Per cent change in employment growth by decade

Chart 6-4: Connection between the extension of employment and the proportion of new professions

Share of new job titles at the beginning of each decade 1980–1990

1990–2000

2000–2007

Source: Acemoglu – Restrepo (2016).

The jobs created by technological innovation will play a key role in the future in maintaining a high level of employment following robotization. Countries with a high innovation indicator have low unemployment figures in the long term (Vicini 2016) and considering all channels the effect of new, higher productivity technologies can be neutral on aggregate employment (Autor – Salamons 2017).

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In summary, automation and the use of robots will decrease the number of jobs available while innovation will create new jobs, but these will not have a balanced effect on the labour market. Most studies predict an increasing polarisation in the labour market, i.e. the U-shaped connection between the destructive force of technology and the level of education of the workforce will become wider and deeper. Nedelkoska and Quintini (2018) present a slightly different scenario in which the advent of AI will put jobs requiring lower qualification at risk. This paper also mentions jobs requiring a stronger skillset as an exception, but overall less skilled workers are the most vulnerable to automation. The more skilled the employee is the lower the risk of automation. There are several probable scenarios to describe how robotization will affect employment in the various segments of the labour market in the future. Moreover, besides data collection and communication enhancing technologies and robots, several other factors will also shape the labour market of tomorrow. Beyond the new technologies global megatrends will also have an effect, such as the problem of aging societies, urbanization, the new phase of globalization and the changing energy mix (MNB 2018). As a summary of the effect of automation on employment, based on historical data and forecasts, the job creation and termination processes of technology may achieve a balance, but on the level of individual employees more significant differences can be expected based on individual characteristics (for example skills).

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How does digitalization change the world of work? Besides automation, the widespread use of new technologies will affect numerous other characteristics of work. The digital economy will change the labour market significantly and both companies and employees will be forced to adapt. Flexibility regarding space, time, and working environments will gain more importance (Chart 6-5). Chart 6-5: Effect of the development of technology on the characteristics of work

Workplace

FLEXIBILITY Form of work

Working time

Source: de Groen et al. (2017).

The place of work will be more flexible as employee mobility increases. Infocommunication devices and technologies will enable us to work from more places (hotels, home, while travelling). The number of tasks that can be performed outside of the office will increase and consequently the time spent with mobile work will also increase. In the European Union (on average) the current proportion of remote workers is 17 per cent (Eurofound-ILO 2017). Although the frequency â&#x20AC;&#x201D; 284 â&#x20AC;&#x201D;

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of mobile work may differ among countries and positions, the flexibility of the place of work is one of the most important innovations of new technologies. Digitalization also effects the duration of work. For example, 9 to 5 jobs will become less common. Naturally, flexibility of work in time is connected to flexibility in space. Employees can work at different times because they can perform their tasks at home or while travelling. The changes regarding the place and time of work are reflected in the boom of the social economy that offers greater freedom regarding the form of work compared to traditional types of jobs. There are various concepts of the social economy, all with different names, such as temporary economy or economy on demand. From a labour market perspective, these mean practically the same thing â&#x20AC;&#x201C; social economy enables workers to work anywhere and anytime, virtually without restrictions. Workers will schedule their own time and they will usually be assigned tasks through an online service provider, i.e. a platform. This will make working from home a significant source of motivation. The number of individuals working in the virtual space is growing steadily. They refer to themselves as digital nomads as they do not have a regular place of work. In recent years, social economy companies have appeared in numerous sectors in the world (transportation, commerce, tourism etc.), but still form a minority compared to traditional market players. The social economy has a large growth potential and will probably generate many new jobs. PwC (2015) forecasts that the overall income of platforms will grow from USD 26 billion to USD 335 billion by 2025. That would mean an approximately 50 per cent market share in the affected sectors.

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Chart 6-6: Projected income growth of social economy

Source: OECD (2016), PwC (2015).

The current size of the workforce employed in the social economy is uncertain. Official statistics probably underestimate it. One of the reasons for this is that activities carried out on the platforms are generally not regarded as work and consequently are not reported in labour market surveys (Coyle 2016). However, different surveys show that platform workers have some common characteristics: individuals active in the digital labour market are generally younger and more commonly live in cities compared to traditional, offline employees (De Groen â&#x20AC;&#x201C; Maselli 2016). As new generations enter the labour market, an increasing number of workers will be able to find jobs in the social economy. Although platforms pave the way for the globalization of the labour market, the extent to which jobs created in the social economy will have a supplementary or replacement effect on typical forms of employment is an open question. The digital labour market is characterized by low intensity, meaning that the number of individuals spending longer periods on the online labour market regularly is low. The low number of work hours is in proportion to the income gained. At the moment, most employees use platforms as a part time opportunity that can add some extra amount to the income they receive from other sources. According to the latest survey of the European Commission, â&#x20AC;&#x201D; 286 â&#x20AC;&#x201D;

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only half of individuals working in the social economy spend at least 10 hours per week working on the platforms, and only a quarter of them said that this was their main source of income (Pesole et al. 2018). Platforms resemble clusters, where groups show significant differences in income and working conditions. De Groen and Maselli (2016) argue that the various categories share the common feature that the market is not homogenous, primarily based on place of service and type of work required (Chart 6-7). The situation of workers largely depends on the segment of the on-demand economy where they find work. Chart 6-7: Online service providers (platforms) based on place of service and type of work required

Low-/medium -skilled

High-skilled

Virtual/global services

Source: de Groen â&#x20AC;&#x201C; Maselli (2016).

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Physical/local services

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Based on the place of work, a platform job can be virtual or connected to a physical location. The virtual option is more flexible as these tasks can be performed anywhere in the world with the use of the respective infocommunication devices. These jobs include designer and developer tasks where the only criterion is to be able to perform the task in the digital space. In contrast to this, the labour market of the social economy has a segment that requires physical availability at a certain location. Such platform jobs offer transport services or a market alternative to household chores. Another important condition is the skillset required to perform the jobs. Local jobs generally do not require highly qualified individuals with custom skills. Virtual services, however, generally require higher qualifications and longer professional experience. The more unique the work required for the service the stronger the position of the skilled worker who is able to perform the requested task. Through digitalization, more flexible and diverse tasks will be provided by the social economy for the labour market. However, there is a growing fear that with the gradual shift from traditional work contracts the boundary between work and free time will diminish. Online platforms go to great lengths to avoid any control over workers thus evading the legal responsibility of employment. Most workers on the digital labour market are sole proprietors or freelancers. A growing number of companies with a traditional business model are turning to the platforms to outsource tasks. This changes the scope of participants in the labour market and their relationships (Chart 6-8). Based on the latest experience and studies, the nature of the boundary between digital and traditional employers is subject to debate. The social economy increased the flexibility of the characteristics of work, and as a result, platforms define themselves as employment agencies rather than employers.

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Chart 6-8: The changing relationships of the participants in the labour market

Online m

Self-employed

Employers

Employees

Source: de Groen et al. (2017).

The state must implement controls proactively so that the new, alternative forms of employment do not have an adverse effect on employees. The criteria of the European Commission (2016) make it clear that the flexible conditions of work relations of the social economy appear to be new only due to the lack of regulation. A platform has an employment relationship with the individual if they have to perform a service in line with the instructions of the platform in return for a wage, and the task performed generates economic value. If appropriate regulation is implemented, the new work opportunities provided by digitalization may offer better wages. In spite of increased flexibility, online labour does not result in lower wages and more insecure terms of employment.

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What skills will workers need in the labour market of the future? As automation reforms jobs and digitalization changes the characteristics of work, the skills required from workers also change. The labour market is changing rapidly and certain skills become more important than others. The quality and continuous development of human capital is even more important than it was in the industrial revolutions of the past in order to maintain the comparative advantage of human resources. However, this is not reflected in the current system of education and adult training. In fact, education has not changed much in the last 100 years. Education is still carried out within the framework created for industrial societies (Manyika et al. 2017a). Retraining for a knowledge economy has unfavourable trends – in recent decades, public spending on workforce training has decreased throughout the world (Chart 6-9). Chart 6-9: State subsidy spent on employee training

0.2

Percentage point change in percentage of GDP, 1 5 2017

0.2

0.1

0.0

0.2

0.3

0.4

0.5

0.6

0.7

Source: OECD.

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FR DE SE FI O D

0.2

AU ES AT BE IT PT CA GR IE

0.1

I C R CH C P S US U U P HU

0.1

6.1 Changes in the labour market in regard to the development of technology

Lower education spending is also disadvantageous because high levels of education play an important role in the mitigation of automation risks (PwC 2018). A well-trained workforce adapts to new technologies more easily, making human work more efficient. On the other hand, employees who spend less time with learning are less successful in keeping their jobs or finding a new job. For this reason, every participant in the labour market (including the Government, companies and employees) should introduce measures to ensure that the working age population maintains its knowledge-based competitive edge on robots. To ensure that the labour supply meets the labour demand, it is important to list the skills that employees will need in the future (also). The pace of the change in skills deemed important by employers is accelerated by new technologies. In his research McKinsey found (Bughin et al. 2018) that in the coming decades the demand for technology skills will grow at the highest rate. This demand includes both basic IT skills and higher-level ones (for example developers). Along with the demand for high level digital literacy, skills that can only be automatized in the long term will also be sought after. Jobs in the future will require creativity, critical thinking, and advanced social skills (communication, cooperation). Surveys generally agree on the skillset that will be required in the coming years regarding the jobs created or modified by the development of technology. According to the Deloitte Global Human Resources Trends survey (Agarwal et al. 2018), human skills such as complex problem solving, cognitive or social skills (Chart 6-10) will be in great demand in the future. The World Economic Forum (WEF 2016b) confirms this stating that the most important skills for the future will be complex problem solving, critical thinking (processing skills) and creativity (cognitive skills).

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Chart 6-10: Expected changes in demand for workforce skills Per cent Technical skills Complex problem solving Cognitive abilites Process skills Resource management Social skills Content skills Sensory abilities Psychomotor abilities Physical abilities 0 Source: Deloitte (2018).

Increase

Stay the same

100

Decrease

In general, there will be a decrease in demand for skills where machines are in competition with humans, while demand will increase for skills where human work is preferred due to technological or other constraints (OECD 2017). The working age population must continue to possess fine basic knowledge (reading, writing, and mathematics) because however rapidly technology and the required skills change, the success of learning and training is established where these are concerned. In order to be successful in work situations changed by automation and digitalization, employees must be open to learning, either from colleagues, on the job or autodidactically (OECD 2019b). The ability to quickly adapt to changing skill requirements is a decisive factor for getting reemployed. If it takes too long for individuals to find a new job, this can have a negative effect on the labour market and unemployment. According to the experts of McKinsey (Manyika et al. 2017b), two conditions must be fulfilled to maintain high employment levels: 1) the number of jobs terminated and created due to automation must be in balance and 2) individuals must be â&#x20AC;&#x201D; 292 â&#x20AC;&#x201D;

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reemployed quickly. Simulations show that the majority of individuals need to find a new job within a year to keep the unemployment rate low (Chart 6-11). Chart 6-11: Unemployment based on time required to find a job US unemployment rate

Range of unemployment scenarios 2000

2016 Baseline Reemployment within 1 year

2030

Low (25%) Medium (50%) High (66%) Full (100%)

Source: Manyika et al. (2017a).

Every participant in the economy must make great efforts to mitigate negative labour market developments. Governments can play a leading role through the development and transformation of the education system. For the sake of the whole of society, education must focus on meeting the demand for higher level skills required by innovative sectors and companies (Vicini 2016). Beyond the transformation of the education system, continuous, life-long learning must become the norm and this is predominantly the responsibility of individuals, although, companies must play a supportive role in training (PwC 2017). Technology may make certain professions obsolete and employees must be prepared for this by training, as well as strengthening the skills â&#x20AC;&#x201D; 293 â&#x20AC;&#x201D;

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that make them more flexible and more resistant to the adverse effects of technology. Effective adult education will be essential to meet the challenges of the labour market of the future (OECD 2019a). Employees must use the advantages of new, digital technologies and will have to update and upgrade their knowledge to have a competitive edge on robots. This will ensure that employment will continue to be a key factor of growth in the long term.

References Acemoglu, D. – Restrepo P. (2016): The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment. NBER Working Paper No. 22252. Agarwal, D. – Bersin, J. – Lahiri, G. – Schwartz, J. – Volini, E. (2018): AI, robotics, and automation: Put humans in the loop. Deloitte 2018 Global Human Capital Trends. Arntz, M. – Gregory, T. – Zierahn, U. (2016): The Risk of Automation for Jobs in OECD Countries. OECD Social, Employment and Migration Working Papers, No. 189. Autor, D. – Salomons, A. (2017): Does Productivity Growth Threaten Employment? A tanulmányt bemutatták az “ECB Forum on Central Banking” rendezvényen, 2017. Bughin, J. – Hazan, E. – Lund, S. – Dahlström, P. – Wiesinger, A. – Subramaniam, A. (2018): Skill Shift: Automation and the Future of the Workforce. McKinsey Global Institute Discussion Paper, May 2018. Coen, R. M. (1973): Labor Force and Unemployment in the 1920s and 1930s: A Re-Examination Based on Postwar Experience. The Review of Economics and Statistics, 55(1): 46–55. Coyle, D. (2016): “The Sharing Economy in the UK”. http://enlightenmenteconomics.com/beta/ wp-content/uploads/2016/01/210116_TheSharingEconomyintheUKTPDC.docx1111.docx.pdf De Groen, W.P. – Maselli, I. (2016): The Impact of the Collaborative Economy on the Labour Market, CEPS Special Report No. 138. De Groen W.P. – Lenaerts K. – Bosc R. – Paquier F. (2017): Impact of digitalisation and the on-demand economy on labour markets and the consequences for employment and industrial relations, Employers’ Group of the European Economic and Social Committee, Brussels. Ernst & Young (2016): The Upside of Disruption: Megatrends Shaping 2016 and Beyond. Ernst & Young, 2016. https://cdn.ey.com/echannel/gl/en/issues/business-environment/2016megat rends/001-056_EY_Megatrends_report.pdf

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6.1 Changes in the labour market in regard to the development of technology Eurofound and the International Labour Office (ILO) (2017): Working anytime, anywhere: The effects on the world of work. Publications Office of the European Union, Luxembourg, and the International Labour Office, Geneva. European Commission (2016): A European agenda for the collaborative economy. COM/2016/0356 final. Ford, M. (2015): Rise of the robots: technology and the threat of a jobless future. Frey, C.B. – M.A. Osborne (2013): The Future of Employment: How Susceptible are Jobs to Computerisation? University of Oxford. Herrendorf B. – Rogerson R. – Valentinyi A. (2014): Growth and Structural Transformation, Handbook of Economic Growth Vol. 2B. Lebergott, S. (1964): Manpower in Economic Growth: The American Record since 1800. New York: McGraw-Hill. Lin, J. (2011): Technological adaptation, cities, and new work. Review of Economics and Statistics, volume 93, number 2. Magyar Nemzeti Bank (MNB) (2017): Growth Report. https://www.mnb.hu/letoltes/novekedesijelentes-2017-hu-web.pdf Magyar Nemzeti Bank (MNB) (2018): Growth Report. https://www.mnb.hu/letoltes/novekedesijelentes-2018-digitalis.pdf Manyika, J. – Lund, S. – Chui, M. – Bughin, J. – Woetzel, J. – Batra, P. – Ko, R. –Sanghvi, S. (2017a): Jobs Lost, Jobs Gained: Workforce Transitions in a time of Automation. McKinsey Global Institute Report, December 2017. Manyika, J. – Chui, M. – Miremadi, M. – Bughin, J. – George, K. – Willmott, P. – Dewhurst, M. (2017b): A Future that Works: Automation, Employment and Productivity. McKinsey Global Institute Report, January 2017. Nedelkoska, L. – G. Quintini (2018): Automation, skills use and training. OECD Social, Employment and Migration Working Papers, No. 202, OECD Publishing, Paris. OECD (2016): OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris. http://dx.doi.org/10.1787/sti_in_outlook-2016-en OECD (2017): The Next Production Revolution: Implications for Governments and Business, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264271036-en OECD (2019a): OECD Employment Outlook 2019: The Future of Work, OECD Publishing, Paris. https://doi.org/10.1787/9ee00155-en OECD (2019b): OECD Skills Outlook 2019: Thriving in a Digital World, OECD Publishing, Paris. https://doi.org/10.1787/df80bc12-en

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6 Social effects of the development of technology Pesole, A. – Urzí Brancati, M.C – Fernández-Macías, E. – Biagi, F. – González Vázquez, I. (2018): Platform Workers in Europe. EUR 29275 EN, Publications Office of the European Union, Luxembourg. PwC (2015): Sharing or paring? Growth of the sharing economy. PricewaterhouseCoopers, https:// www.pwc.com/hu/en/kiadvanyok/assets/pdf/sharing-economy-en.pdf PwC (2017): Workforce of the future: the competing forces shaping 2030. https://www.pwc.com/ gx/en/services/people-organisation/workforce-of-the-future/workforce-of-the-future-thecompeting-forces-shaping-2030-pwc.pdf PwC (2018): “Will robots really steal our jobs? An international analysis of the potential long-term impact of automation.” https://www.pwc.com/hu/hu/kiadvanyok/assets/pdf/impact_of_ automation_on_jobs.pdf Romer, C. (1986): Spurious Volatility in Historical Unemployment Data. Journal of Political Economy, University of Chicago Press, vol. 94(1). Vicini, A. (2016): Technological Innovation and the Effect of the Employment on the EU Countries. World Bank (2016): World Development Report: Digital Dividends. Washington, DC: The World Bank. World Economic Forum (WEF) (2016a): 10 jobs that didn’t exist 10 years ago. https://www. weforum.org/agenda/2016/06/10-jobs-that-didn-t-exist-10-years-ago/ World Economic Forum (WEF) (2016b): The Future of Jobs, Employment, Skills and Workforce: Strategy for the Fourth Industrial Revolution.

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6.2

Information (data) is the new oil Mihály Hajnal – Katalin Kis

Today’s digital revolution is shaped by three major trends. The first, the increased performance of computers, and the second, the increasing flow rate of data, which provide the base for the third trend that involves the enhanced collection, storage and use of digital information in various forms. Information is the driving force of the digital transformation – data is the new resource of the world. The emergence of digital technologies gave a new context to the concept of data, the methodology of data collection changed and the third revolution of informatics brought about a new format of data processing. Today 75 per cent of our personal data are digital. Personal data collection and the widespread use of AI can be beneficial for both companies and customers. For customers it may offer products selected on the basis of individual preferences, bigger discounts and a more comfortable shopping experience. As for companies, new channels are available to reach customers, firms can produce more innovative and customized products and it may provide easier access to new markets. Big data analysis may support company, decision-maker and customer decisions, solve global challenges, lead to disruptive new technologies, provide real time information and improve the consumption of resources to facilitate long-term sustainability. Besides these benefits the large amount of data available pose risks related to data ownership, creation and storage. To ensure sustainable use of data and implement inclusive digitalization issues have to be solved on an enterprise and regulator level.

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How does the digital revolution change the role of data? “The data-driven world will be always on, always tracking, always monitoring, always listening and always watching – because it will be always learning.” DAVID REINSEL—JHON GANTZ—JOHN RYDNING

011 10100011 101101011011 101101011010010 4.1 billion Internet users 0011010010101100 in the world at December 2018 1010110101110010 1110111011101101 0110101101001101 1.94 billion websites in the world at December 2018 11101110

Over 5 billion

Over 500 million

Google searches are made every day

tweets are sent every day

Over 4 million

blog posts are published on the Internet every day

The digital revolution based on the development of technologies is influenced by three major trends. The increase in computing capacities, the growing speed of communication as well as the information flow rate and the exponentially growing amounts of data provide ever more possibilities. Computing capacity growth was well predicted by Moore’s law of 1965. According to this principle the number of transistors in a dense integrated circuit doubles about every 18 months, making an accurate prediction of the performance increase of computers. The law is a result of observation, and the capacity enhancement it describes increased the performance of computers with a dramatic reduction in costs. This was also reflected in consumer prices and helped to spread the use of computers (WTO 2018). The second trend of technology is the creation of modern communication networks as the globalization of the 21st century is characterized by international data flow. Today all international transactions have digital — 298 —

6.2 Information (data) is the new oil

components. Goods shipped by container carriers are ordered in web shops, shipping is tracked using digital codes and payment is made electronically (Manyika et al. 2016). Based on Gilder’s Law (2000) bandwidth grows three times faster than computer power. In other words, bandwidth doubles every 6 months. International bandwidth grew 45 times between 2005 and 2014 with the contribution of the dynamic growth of the developing region (Chart 6-12). Chart 6-12: Bandwidth change

Source: Created by MNB based on Manyika et al. (2016).

Similar to Moore’s Law growing bandwidth resulted in a substantial fall in telecommunication costs and contributed to the increased use of Internet and mobile phone networks (WTO 2018). Regional ICT device penetration data shows that developing countries are falling behind (Chart 6-13). In the developed region more than 80 per cent of homes had a computer and used the Internet in 2018. As for developing countries, despite a 3 digits growth computer and Internet penetration is below 50 per cent. The number of mobile phone subscriptions shows the greatest convergence. In 2005 22.9 per cent of the population had a mobile phone subscription in the developing countries, while in 2018 — 299 —

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average mobile phone subscription penetration was 100 per cent (ITU 2018). Chart 6-13: Rate and changes of ICT use between 2005 and 2018

140 120 100 80

Per 100 person

+43%

+56%

+58%

+137%

+349%

+488%

+75%

+215%

+224%

140 120 100 80

2005 2018 Households with a computer Developed countries

2005 2018 Mobile-cellular telephone subscriptions

2005 2018 Individuals using the Internet

Developing countries

World

Source: MNB, based on ITU (2018).

Digital transformation means not only the use of new technologies and new devices, as these could not work efficiently without the intelligent use of data covering all areas of life. Bojár (2018) argues that the first information revolution started with the advent of Cro-Magnons, the “wise man”, as it introduced the ability of speech that enabled the exchange of complex information. Humanity had the ability to transfer information, but it was only a few tens of thousands of years later that the ability to store information was developed – writing, which is considered to be the second information revolution. Although the library of Alexandria had a collection of half a million volumes 2 thousand years ago, the fact that it is practically impossible to understand and process such large amounts of information became apparent only after the development of printing in the 15th century.

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6 thousand years after the development of writing the third information revolution and also the third trend of technology enabled humanity to utilize all the information collected and stored in a digital format, using the tools developed by the first two trends (computers and telecommunication networks) (Bojár 2018, Manyika et al. 2016). Information is the driving force of the digital transformation. In the age of the scarcity of data humanity developed hypotheses to understand the mechanisms of nature, collecting and analysing data to confirm these hypotheses. Hypotheses are often built using the theories of natural and social sciences, and seek answers to the questions of “why”, trying to find causal relationships. As opposed to this model big data and the abundance of information helps us to switch to a data driven world, i.e. one that focuses on “what” instead of “why” and concentrates on the patterns in data (Mayer-Schönberger – Cukier 2014). Until recently, data collection, storage and analysis were complicated and it was difficult and expensive to extract value. Economists of the classical era did not mention the utilization of data in their analysis of the production factors (land, work and capital). Nowadays, however, most of the limits of data collection have been eliminated (MayerSchönberger – Cukier 2014). The emergence of digital technologies gave a new context to the concept of data, the methodology of data collection changed and a new format of data processing emerged (Chart 6-14).

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Chart 6-14: The analogue and digital data processing process

DIGITAL

ANALOG Face-to-face

Face-to-interface

COLLECTION

Consumer data is collected primarily through direct surveys, interviews and focus groups.

Data is collected via different tracking technologies, such as sensors, GPS and website cookies.

Sample-based

Individual-based

AGGREGATION

Data is segmented into groups, usually by socioeconomic characteristics (e.g., income level, demographics). It is difficult to combine data in different formats.

Data is analyzed on an individual basis, with standardized formats helping to build a 360-degree profile of each consumer.

ANALYSIS

MONETIZATION

STORAGE

DISPOSAL

Retrospective

Predictive

Basic levels of historical analysis are used to identify needs of certain groups from sample-based data.

Companies use more advanced statistical modelling, such as predective analytics, to build a fuller consumer profile and predict future purchases.

Indirect

Direct

Revenue is generated indirectly by using insight into customer needs to develop new products and services.

Data has intrinsic value and can be sold to third parties (in anonymized format).

Physical

Virtual

Storage is physical (e.g., in files) and space-consuming. Retrieval of data is often costly and inconvenient.

Users can now access data anywhere with an internet connection and at low cost.

Single-step

Multi-step

Permanent deletion of data involves destroying the single physical device on which the data is stored.

To permanently delete data, numerous platforms and databases must be targeted individually.

Source: Cooper - LaSalle (2016).

The scope of personal data is increasingly large. In the past, if customers were asked about their personal data they mentioned their address, illnesses or social security number. Today 75 per cent of our personal data are digital. It includes Internet browsing data, friends and followers in the social media, comments, blogs, mobile phone contacts, location data or health data recorded by a smart watch. Today you do

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not need a personal meeting to collect data, and paper-based surveys are a thing of the past. It is enough to follow people’s digital footprints (Cooper – LaSalle 2016). Data collection is usually carried out with a certain goal. However, the cost of digital storage dropped by 50 per cent every second year in the last decade, making it easier of reuse data. Consequently, it is possible to extract more and more value from data, and it can be used for multiple purposes that fosters an understanding of the immense value of information in the age of big data (Mayer-Schönberger – Cukier 2014).

What are the opportunities of data utilization? Companies can use different channels to realize the advantages that data extraction offers. These include different customer, product and market related innovations. In a survey 77 per cent of CEOs cited the use of personal data as an advantage, mainly for providing a better user experience and more personalized services (Chart 6-15). In the Chinese market Alibaba analysed the previous purchases of customers and offered complete carts to make a record profit (Cooper – LaSalle 2016). Personalized services help to customize marketing activities to meet personal preferences and offer special sales for customers. Furthermore, 50 per cent of CEOs think that data analysis may help companies to find new markets and offer more innovative products.

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Chart 6-15: Possible benefits of using personal data, according to executives (per cent) 41

Increased profitable revenue

Special discounts and sale schemes

More innovative products Advertising that is more targeted to individuals’ interests

Ability to uncover opportunities in new markets

52 53

Enhanced customer loyalty

Better customer experiences/personalized services 0

Source: MNB, based on Cooper – LaSalle (2016).

The value of benefits that can be extracted with the use of data and AI is different in each sector. Manyika et al. (2011) studied the opportunities provided by big data analysis with regard to the productivity changes in the various sectors of the US economy. Their results show that the IT, electronics, and infocommunication sectors have enjoyed a significant increase in productivity in recent years due to being firmly embedded in global value chains, and further utilization of data could increase productivity even more. The financial and insurance services as well as government services sectors were characterised by a more modest increase in productivity, but these sectors have the largest amount of data. As for skilled professionals, besides scientific research financial and insurance services have the most appropriately qualified workforce to utilize data. Box 6.2 provides a detailed overview of the role of big data in banking.

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The following sections give some quantified examples for the possibilities that data and AI provides, from some sectors. As per the estimate of Manyika et al. (2011) the utilization of the data available in the healthcare system of the US would enable savings of more than USD 300 billion through the areas of surgical interventions, method of payment and pricing as well as R&D. 66 per cent of the savings would come from an 8 per cent saving on nursing costs. Furthermore, this estimate does not contain the potential advantages of real time data analysis based on web search results that could also be used for a real time evaluation of flu trends. The utilization of this huge amount of data could promote transparency in the public sector and could help to increase the efficiency of public procurement processes and the level of government services. It could also help to decrease running costs, errors and fraud, and help to increase the transparency of the sector and provide more effective information for citizens. More modern methods of tax collection could also help to significantly reduce tax evasion (Cavanillas et al. 2016). An OECD (2013) study found that the use of big data can reduce the administration costs of the sector by an average of 15 to 20 per cent. Big data could also increase productivity and efficiency in retail and wholesale, and increase the operating profit of retailers by 60 per cent. Data analysis could facilitate retail such as in store behaviour analysis, selection optimization, product placement and pricing. It also supports warehousing, supplier negotiations, and can devise new business models facilitating the extension of Internet sales (Cavanillas et al. 2016). According to a recent estimate by McKinsey (2019) the use of AI provides a wide range of advantages in operation and profitability. Most profitable opportunities related to utilization of the abovementioned

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technology are in marketing, sales and wholesale. As for hospitals and healthcare, patient data confidentiality currently limits the use of data by AI technologies. AI significantly improves the performance of companies, especially in the sectors that employ a highly qualified workforce and produce intangibles. This means that tech companies can realize the highest profit from the use of AI. Based on Burghin et al. (2019) the use of AI could increase the growth of the European economyâ&#x20AC;&#x2122;s economic performance by 19.4 per cent by 2030, which means an economic surplus of EUR 2.7 billion. The positive effect of AI technologies comes from various factors (Chart 6-16). 75 per cent of gross growth comes from improved productivity supported by automation and innovation from the supply side. With the help of AI innovation is a powerful driver of GDP growth, generating an approximately 0.5 per cent increase. As for demand, an increase in productivity leads to increased income for consumers and a higher level of consumption. Moreover, the openness of European economies adds to the positive effects. Nevertheless, it is important to note that in the case of an AI based growth path respective costs amount to 40 per cent of the potential growth covering technology development, introduction and the negative externalities of the transition.

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Chart 6-16: The income surplus generated by the use of AI by 2030 in the EU (per cent)

Wealth creation

3.7

Connectedness

3.8

Innovation

7.5

33.2

6.7

Implementation costs

7.1

Negative externalities

Substitution 14.5

Augmentation 3.7

TOTAL NET

TOTAL GROSS

19.4

Source: MNB based on Burghin et al. (2019).

Box 6.2 Big Data in banking

Banks increasingly use big data solutions to process large quantities of data. It enables them to get to know their clients better and potentially offer products that better fit their needs. Big data can include customer data collected from web sites, social media, Internet browsing history, smartphone use or data generated by card payments. Additionally, bank transactions carried out by the client and their financial decisions are also included in the data available and usable (McKinsey 2013). The use of big data by the banks may offer several advantages for the users of financial services, but risks are also present. As for advantages, big data enables banks to offer personalized products and services to customers. For example, this technology enables financial institutions to connect customer social media data with the financial data of their savings. This information can be used to understand the savings and investment

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behaviour of customers. Big data use can also help banks to fight fraud. For example, if someone tries to carry out an unauthorized electronic payment from abroad, the bank can identify the location of the account holder using a location services app and block the payment if necessary. The availability and use of data from a wider source facilitates easier access to financial services and helps to increase financial penetration using alternative creditworthiness assessments.

Use of big data to assess residential creditworthiness The most significant risk and challenge with regard to big data use and the connected machine learning solutions are the issues resulting from faulty data use such as false connections or over alignment. For example, if a customer working night shifts applies for credit, they may be assigned with a worse credit rating because night time activity is associated with an unhealthy life style. Creditworthiness assessment is carried out to decide the repayment probability of a loan and the losses suffered in the case of non-payment. Credit institutions generally use their proprietary systems to perform the creditworthiness assessment. Traditional assessment primarily concentrates on the comparison of the ratio of income and credit protection against the repayment. The credit history of the applicant is also analysed, if available. Big data and machine learning opened up the opportunity to use alternative creditworthiness assessment methods. These alternative methods analyse customer data from sources that have not been used before, for example, social media data, company customer data, publicly available location data, mobile and web data. These sources enable banks to measure such qualitative characteristics as area of interest, customer habits or a responsible way of living that can predict responsible payment behaviour (Hurley â&#x20AC;&#x201C; Adebayo 2017).

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Usage of big data enables swift processing of large amounts of data and may facilitate an extended access to financial services due to the fact that scoring can be carried out even for those who previously had no access to the credit market due to their restricted visibility (lack of a tax return stating income, lack of any credit history) (EBA 2018). Time will tell if the use of big data technology for creditworthiness analysis provides better results compared to the use of legacy scoring systems. This technology will be especially beneficial for creditworthiness assessment in developing countries where credit penetration is low and where there are limited possibilities to carry out creditworthiness assessment using traditional methods. In countries with an advanced banking system appropriate regulations must be implemented to avoid potential risks.

Dig data analysis may support company, decision-maker and customer decisions, solve global challenges, lead to disruptive new technologies, provide real time information and improve the consumption of resources to facilitate long term sustainability. During the typhus epidemic of 2015 in Uganda data collected from the hospitals were analysed using an interactive data visualization method that helped to identify infected areas and the spread of the disease. This made the distribution of medicine and the mobilization of medical teams more efficient. Big data contributes to sustainability and also helps to measure it. Research conducted in Ruanda found a significant pattern connecting mobile phone use with the consumption of certain foodstuff (vitamin rich vegetables, meat, grain), that was in correlation with the poverty statistics for the region. The number of daily and weekly searches performed in Google’s systems correlate with certain economic indicators that can help to make short-term economic forecasts. Other nations are also interested in the opportunity to utilize these data, and several governments are thinking of a “national big data strategy”. Singapore and the United States appointed a head researcher responsible for big data research. China cooperates with the Development Community of the UN within the framework of the “Big

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Data Joint Laboratory in China” project. The first result of the project is an application to measure electric waste reuse (UNCTAD 2018).

How to manage the risks of a data-based economy? Besides the potential benefits the advent of AI and the abundance of data available for analysis is also a challenge for companies and the state. As we have seen in the part of Chapter 3 dealing with technology, new technologies have a different effect on companies active in the various sectors of the economy, and a disruptive technology may have an effect on the ecosystems of companies. Differences may be present not only on the level of sectors but also on the level of countries leading to a wider digital divide that can redraw the geopolitical map of the world. Furthermore, the emergence of digital technologies gave a new context to the concept of data, the methodology of data collection changed and a new format of data processing emerged. This raises fundamental questions about the ownership of data, data security and cyber protection. As this chapter gave a detailed analysis of the opportunities opened up by data utilization, when it comes to the potential answers to challenges the focus will still be on data management. A valid question is how companies can mitigate the risk of personal data utilization. The literature (Cooper – LaSalle 2016, WEF 2013) uses different categorizations, but there are closely related principles that need to be observed. With regard to this we will use 4+1 criteria (Chart 6-17).

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Chart 6-17: Digital responsibility basics Digital accountability, compliance with the law

Digital equality

Digital inclusion

Digital transparency

Digital empowerment

Source: MNB, based on Cooper â&#x20AC;&#x201C; LaSalle (2016) and WEF (2013).

(1) Digital diligence, legal conformity: business management, customers and regulating authorities all expect responsible data handling. Data handling related legal requirements must be observed and the ecosystem of the company must be developed. Continuous training of the employees and the appointment of a data protection officer helps to prevent data theft and to reduce the resulting costs. (2) Digital transparency: companies must provide more detailed information for customers and other organizations on the use and storage of their data. (3) Digital empowerment: customers must be enabled to update their stored data; moreover, the analysis of their data may help them in their own decisions. It enables companies to produce more personalized products and diversify their income.

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(4) Digital equality: companies must share data benefits with customers. Companies facilitate closer connections with customers by offering financial incentives (for example sales) for customer data. (+1) Inclusive digitalization: companies that collect data can provide considerable help for organizations dealing with sustainability. Data can help in areas such as healthcare, city planning and food security. In 2014 Twitter shared tweets with researchers within the framework of the project “Data Grants” to help map gastrointestinal diseases in Jakarta. Research using data can also help regulator decisions. Based on a study by Cooper – LaSalle (2016) involving nearly 600 companies 22 per cent of the companies interviewed met all five criteria of digital responsibility and had a data protection officer. The ratio was 11 per cent for SMEs. It is probably more difficult for SMEs to cover the costs of data management. The level of data responsibility is also different in the various sectors. IT companies are the most advanced in respect to data protection (36 per cent), while company digital responsibility criteria are fulfilled by 22 per cent of the companies in the financial sector, by 15 per cent in the telecommunication sector, and by only 14 per cent in healthcare (Chart 6-18). As an example, Blackphone has been encrypting the calls, e-mails and internet browsing data of customers since 2014. For an annual fee Personal.com offers its customers a data protection level that is identical to the one used by the US Army. However, looking ahead, companies will have to adopt a proactive approach to achieve a sufficient level of data protection.

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6.2 Information (data) is the new oil

Chart 6-18: Proportion of companies that meet the digital responsibility criteria by sectors (per cent) Health & public service

Telecommunications & media 15 17

Retail/wholesale

Financial services

Products

Resources

Manufacturing

IT & technology 0

Source: MNB, based on Cooper – LaSalle (2016).

International organizations and national governments introduce measures to implement a sufficient regulatory framework. In 1993 only four countries had data security related legislation. It took more than 20 years from the introduction of the Internet for the number of countries with national data protection laws to reach 100 in 2013 (Accenture 2016). The legislation of the European Union on the protection of personal data came into force in May 2018. The General Data Protection Regulation or GDPR establishes the right of the recursive deletion of customer data. Data protection must be a part of the planning phase of new IT products. The regulation provides precise rules on obtaining customer consent and selling their data. Breaking GDPR rules is penalized with heavy fines (PWC 2018). Besides regulation there are new technologies that focus on a higher level of security. Blockchain is a shared database that creates a ledger of transactions by connecting the various data blocks. Anyone can — 313 —

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initiate and verify transactions. Data blocks must be verified by multiple persons and once the block has been added to the chain it cannot be modified. A blockchain is a “trust machine” that eliminates the need for a central agent that verifies all transactions. It also uses a series of encryption technologies that make it more resistant to cyberattacks compared to normal databases. As a result of the enhanced security, efficiency and traceability of the system the number of blockchain related patents grew threefold in 2017. Its widespread use is expected to be worth USD 3 trillion by 2030. Today blockchain primarily serves as the technology behind crypto currencies, but in the future it could be used in a number of areas. Blockchain is suitable for carrying out property and stock exchange transactions and for identifying the owner of stolen goods, and as such contributes to the fight against crime and to long term sustainability (WTO 2018). Companies, states and other organizations often use their current computers to solve optimization tasks such as finding a more efficient distribution of resources, appropriate scheduling or search in large databases. However, the capacity of traditional computers is limited. Searches will probably be accelerated considerably by the use of quantum computers. Quantum informatics uses the results of quantum mechanics, computer technology and mathematics, and appeared four decades ago to create faster and more secure computers, but this technology is not yet ready for everyday use. Quantum computers use cryptography to encrypt data. The aim of cryptography is to encrypt information so that only the permitted parties have access. Technology enables more secure communication, money transfers, and electronic signing. This can enhance data security for financial and state services (Wolf 2017).

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References Bojár G. (2018): Negyedik ipari vagy harmadik informatikai forradalom? (Fourth industrial or third information technology revolution?) Az információ sok ezer éves hatalma (The millennials long power of information). Magyar Tudomány, 179(1), pp. 37-46. Bughin, J. – Seong, J. – Manyika, J. – Hamalainen, L. – Windhagen, E. – Hazan, E. (2019): Notes from the AI frontier: Tackling Europe’s gap in digital and AI. McKinsey&Company, Discussion Paper, February 2019. Cavanillas, J. M. – Curry, E. – Wahlster, W. (2016): New Horizons for a Data-Driven Economy. A Roadmap for Usage and Exploitation of Big Data in Europe. Springer International Publishing AG Switzerland. Cooper, T. – LaSalle, R. (2016): Guarding and growing personal data value. Accenture. EBA (2018): Report on the prudential risks and opportunities arising for institutions for fintech. https://eba.europa.eu/documents/10180/2270909/Report+on+prudential+risks+and+opportunities+arising+for+institutions+from+FinTech.pdf EDPS (2019): The History of the General Data Protection Regulation. https://edps.europa.eu/dataprotection/data-protection/legislation/history-general-data-protection-regulation_en Flynn, G. – Griffin, J. (2015): Big data: The BIG factor driving competitive advantage. KPMG International Cooperative. Switzerland. Gilder, G. (2000): Telecoms: The World After Bandwidth Abundance, Touchstone edition, New York: Simon and Schuster. Hurley, M. – Adebayo, J. (2017): Credit scoring in the era of big data. Yale Journal of Law and Technology, 18 (1), pp. 148-216. https://digitalcommons.law.yale.edu/cgi/viewcontent. cgi?article=1122&context=yjolt ITU (2018): 2018 global and regional ICT estimates. International Telecommunication Union. Switzerland. https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx Manyika, J. – Chui, M. – Brown, B – Bughin, J. – Dobbs, R. – Roxburgh, C. – Hung Byers, A. (2011): Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, May 2011. Manyika, J. – Lund, S. – Bughin, J. – Woetzel, J. – Stamenov, K. – Dhingra, D. (2016): Digital globalization: The new era of global flows. McKinsey Global Institute, March 2016. Mayer-Schönberger, V. – Cukier, K. (2014): Big data – Forradalmi módszer, amely megváltoztatja munkánkat, gondolkodásunkat és egész életünket (Big data – A Revolution That Will Transform How We Live, Work, and Think). HVG Könyvek, Budapest. McKinsey (2013): New credit-risk models for the unbanked. https://www.mckinsey.com/businessfunctions/risk/our-insights/new-credit-risk-models-for-the-unbanked?reload

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6 Social effects of the development of technology McKinsey (2017): What’s now and next in analytics, AI, and automation. McKinsey Global Institute, May 2017. McKinsey (2019): Twenty-five years of digitization: Ten insights into how to play it right. McKinsey Global Institute, May 2019. OECD (2013): Exploring Data-Driven Innovation as a New Source of Growth: Mapping the Policy Issues Raised by “Big Data”, OECD Digital Economy Papers, No. 222, OECD Publishing, Paris. PWC (2018): Mennyit ér az adat? (What is the worth of data?) Új szolgáltatások és bevételi lehetőségek nyomában (Finding new services and income possibilities). PWC, Hungary. Reinsel, D. – Gantz, J. – Rydning, J. (2018): The digitization of the world – From edge to core. Data age 2025. IDC, USA. https://www.seagate.com/files/www-content/our-story/trends/files/ idc-seagate-dataage-whitepaper.pdf UNCTAD (2018): Technology and innovation report 2018. Harnessing frontier technologies for sustainable development. United Nations Conference on Trade and Development. Switzerland. Wolf, R. (2017): The Potential Impact of Quantum Computers on Society. https://arxiv.org/ pdf/1712.05380.pdf WTO (2018): World Trade Report 2018 – The future of world trade: How digital technologies are transforming global commerce. World Trade Organization, Geneva. https://www.wto.org/english/ res_e/publications_e/world_trade_report18_e.pdf

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6.3

How to convert economic growth into social well-being Kristóf Lehmann – Gábor Neszveda

Standard economics does not give an exact, utility function based definition of consumption. According to the generally accepted approach if an individual consumes more they also have higher utility and as such higher income, which in turn also results in higher utility. However, subjective satisfaction measurements and experimental economics provide results that contradict or supplement the presumptions of the generally accepted approach. Wealthier societies are typically happier, but this is a result of several factors. Satisfaction studies show that an increase in the income per capita does not result in an increase in the level of satisfaction in society. International comparisons indicate that at lower income levels there is a correlation between income and happiness, but beyond a certain income level this correlation disappears. The feeling of satisfaction is distorted by several factors both within society and at the level of the individual. Individuals get used to a given higher income level and compete, meaning they measure their income against their environment. Living in a big city decreases the level of happiness because the individual has a more limited community life. Level of education studies provide contradictory results. Current research results show that the development of technology and the resulting economic growth do not necessarily lead to an increase in the wellbeing of society. Although the development of technology may improve people’s quality of life, several other factors involved present risks. Robotization may increase social differences, while new communication technologies and social

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media offers a more limited scope of real social experience. The digital society may even decrease the level of individual happiness. Standard economic models suggest that decision-makers have their own utility function, and that potential utility is gained from an increase in consumption. This theoretical approach is generally accepted and very hard to challenge as it enables a wide selection of approaches and does not define consumption or the shape of the utility function. Consequently, a holiday or making a donation can theoretically be categorized as consumption if it changes the utility of the decision-maker. However, further assumptions are needed to draw more specific conclusions from this general format. Therefore, these models still use the intuitive and easily acceptable assumption that more consumption is better and it is possible to monetize consumption as the amount of money spent. This means that if someone spends HUF 100 thousand more compared to the previous month, the person has larger consumption in the given month and has larger utility. These general assumptions then lead automatically to one of the most generally accepted and most important conclusions of standard economics, namely that higher income necessarily means higher utility and as such a higher level of happiness because individuals have more opportunities to spend their money on whatever they want to spend it on, and this results in higher consumption and therefore higher utility.

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Box 6-3 How to measure well-being and happiness

Several approaches exist to measure well-being and happiness. Happiness is very hard to define, and quantifying it is another challenge.60 The literature offers the following methods to solve this problem. The Questionnaire Method basically asks participants how happy, sad or even depressed they have felt recently. These questions are designed to evaluate how participants feel, which can be quantified later. In the Day Reconstruction Method participants have to recall their day and their experiences, and evaluate how positive and negative these experiences were for them (Kahneman et al. 2004). The Experience Sampling Method aims to follow the activities, feelings and mood of participants in real time. Finally, advanced technology enabled researchers to use brain activity sensors to measure happiness, such as FMRI, which provides feedback on the subjectsâ&#x20AC;&#x2122; emotion.

Are wealthy societies satisfied societies? Contrary to convincing theories the results of empirical research are significantly more controversial in regard to whether or not a higher income automatically makes people happier and more satisfied. The first and best known criticism of this theory came from Richard A. Easterlin in 1974 with his Easterlin Paradox, which states that although income did grow steadily in Western societies following World War II this did not result in an increase in satisfaction in the same societies.

Lehmann (2014) gives a detailed overview of the methods.

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(Easterlin 1974) This is clearly detectable in later periods for example in the US (Lehmann 2014). Chart 6-19: Real GDP per capita (left axis, USD) and mean happiness (right axis) in the USA between 1973 and 2009 45,000

3.0 2.8

40,000

2.6

35,000

2.2 2.0

30,000

1.8

Index point

US dollar

2.4

1.6 25,000

1.4 1.2

20,000 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

1.0

Real GDP per capita

Mean happiness (right-hand scale)

Source: World Happiness Database, USDA.

In the period that followed, several studies were conducted to investigate this topic and provide a more general picture of the problem. For example, Inglehart and Klingemann (2000) and Graham (2005) found that the level of satisfaction in developing countries is clearly lower compared to that of developed countries. These results were aligned with the assumption by Marmot (2004) that at lower income levels there is a correlation between income and happiness, but beyond a certain income level this correlation disappears. Data justify this assumption as shown in the following chart. Consequently it is safe to say that the difference in happiness between societies may be explained by income level differences.

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Based on Chart 6-19 the assumption above is still detectable after 15 years. Beyond a certain level of nominal income per capita any additional increase in income does not have any significant effect on happiness. It is important to note though that there are countries that deviate significantly from the dotted line, i.e. the level of happiness expected based on the level of income. Countries of the Caribbean and Latin America are typically happier than their income level (for example: Guatemala and Jamaica). Countries suffering a serious crisis are significantly less happy than expected based on their wealth and international trends (for example: Greece and Italy). Chart 6-20: Average of social happiness (0–10) and national income per person in 2017 (USD) 9 GT

Average happiness

CO 7

US R2 =0.7371 JP

6 IT HU

GR 4

20,000

40,000

60,000

80,000

100,000

Nominal GDP per capita * Note: Social happiness averages are based on the latest World Values Survey data available. Source: World Development Report (2010) pp. 378–379, World Values Survey and UN National Accounts Database.

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Researchers also came up with some important results within societies. Results that indicate that the increase in the income of households leads to an increase in required income are in conflict with the assumptions of economics. (Layard 2010) This also means that individuals get accustomed to higher income levels. Consequently, the conclusion drawn from the utility function is not valid based on the answers given by US citizens in the social questionnaire over four decades.

1987

US dollar

1985

1983

100 1981

100 1979

110

1977

110

1975

120

1973

120

1971

130

1969

130

1965

140

1967

140

1963

150

1961

150

1959

160

1955

160

1957

170

1953

170

1951

US dollar

Chart 6-21: Framework of actual and necessary income based on the General Social Survey of USA (1952â&#x20AC;&#x201C;1987)

Required real income (right-hand scale) Actual real income Source: Layard, 2010, p. 148.

According to the standard models and rationale of economics, economic growth in a country inevitably increases social well-being because higher economic output provides higher income levels and this leads to a higher level of happiness. However, research on happiness and well-being shows that this correlation is more complex and suggests

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that if negative social processes prevail economic growth might even decrease the level of satisfaction in a society.

What are the conditions of converting wealth into social well-being? Several papers show that a simple increase in income does not necessarily lead to an increase in happiness and well-being. Consequently we need to know which factors have an effect on the happiness and well-being of individuals. Research results show several interesting patterns. Individuals do not measure their income and financial situation independently of other factors as they get accustomed to any new situation easily. This can have a negative effect on individuals – they can buy a new car or a bigger house, but they get accustomed to the new situation quickly and they do not particularly appreciate it any longer. However, this can also have a positive effect as it enables individuals to find happiness again despite having suffered grave financial or physical losses (Gerhart et al. 1994). Furthermore, individuals generally evaluate their status compared to the status of others, so an increase in nominal wealth may be unappreciated if their environment enjoys an even more significant increase in income (Solnick – Hemenway 1998). If individuals evaluate income not as an absolute value but in relation to the income of their environment, increasing income differences may make them more unhappy even if their personal income grows. This was confirmed by the research conducted by Oishi and Kesebir (2015) in connection with the Easterlin Paradox. Results suggest that general happiness levels did not increase in countries where economic growth was accompanied by increasing social differences. On the contrary, if

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social differences did not grow, economic growth was able to facilitate the growth of general social happiness. Another well-known connection is that individual levels of happiness may increase if the individual is able to help others, for example by giving a donation (Liu – Aaker 2008). In line with this, several papers show that a fair and generally beneficial distribution of wealth is important for people (Fehr – Schmidt 1999). Humans are social beings and as such happiness and well-being strongly depend on being a useful member of a community. Services in which we can involve others result in a lot more happiness compared to spending the price of this service on ourselves (Caprariello – Reis 2013). Finally, our self-image and identity have a very important impact on happiness. Anything that is able to reinforce this self-image and identity increases our happiness and well-being. For example, products that people can identify with invoke significantly greater happiness compared to other similar products (Carter – Gilovich 2012). An interesting question is how does urbanization (one of the most significant social phenomenon of economic growth) affect social wellbeing. Berry and Okulicz-Kozaryn (2011) found that in the US not living in an urban environment had a clearly positive effect on happiness. One of the main reasons for this is that communities are significantly stronger in smaller towns and this is important for well-being and happiness. All the results cited above suggest that economic growth may serve as a means to increase social satisfaction and happiness, but this by no means happens automatically. The system of education is among the most important social institutions from the perspective of social processes as it provides knowledge and

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social patterns for society. Consequently, it is important to investigate how and to what extent it can influence social well-being and happiness. General results show that the higher the level of education attained by an individual the higher the income they enjoy, but as we have seen earlier this does not automatically guarantee a higher level of well-being and happiness. Consequently, studying the connections between qualifications and happiness offer an interesting opportunity to understand the mechanisms that are at work deciding how a certain factor affects social well-being and happiness. In general the higher the level of education attained by an individual the higher the well-being and happiness they enjoy (for example Florida et al. 2013). Based on the data analysed Cunado and Gracia (2012) identified two main mechanisms in connection with the positive effects of qualifications. Firstly, higher qualifications lead to a higher income and a higher social status, and secondly individuals with higher qualifications have a stronger positive self-image and more confidence. Clark and Oswald (1996) found, however, that a higher qualification may lead to a lower level of well-being. According to their results this has two main reasons. On the one hand a higher qualification means higher expectations with respect to jobs/positions. On the other hand income differences are more marked among highly qualified individuals and this inequality may have a negative impact on well-being. These results are in line with the research conducted in other areas showing that the main connections between happiness and well-being are not dependent on income only. In fact the importance of income is usually overshadowed by numerous other factors, for example relative financial position, personal expectations or the individualâ&#x20AC;&#x2122;s self-image and identity.

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How does social well-being change in the digital age? In light of the results we have seen so far, it is an interesting question to investigate the effect of todayâ&#x20AC;&#x2122;s incredible technological development on social well-being and personal happiness. The development of technology is among the most important drivers of economic development and growth, but it also shapes our society in several different ways, and some of these effects may prove to be negative. Even though technological advancement has a positive effect on economic growth and income, it has had a negative effect on our lives and happiness for decades. The reason for this is that the use of tech devices takes away time from all the activities that bring more happiness even today, changes the labour market, brings uncertainty and reinforces negative trends and human traits, including the information bubble and envy. Chart 6-22: Connection between average happiness and number of hours spent with certain activities weekly 2.15

Mean happiness

2.10 2.05 2.00 1.95 1.90 1.85

Social Media Texting

1 2

3 5 6 10 1 20 2 Number of weekly hours Internet Video chat

Source: Twenge, Martin, and Campbell, 2018, p. 10.

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Gaming

30 3

40+

6.3 How to convert economic growth into social well-being

The proliferation of “screen” addiction is a source of increasing concern for parents and society trying to protect children and young people. These concerns are justified by Twenge et al. (2018) whose paper shows that activities involving screen use such as browsing, gaming and social media clearly decrease the well-being of pupils as opposed to non-screen activities (sports and personal interaction) that increase wellbeing (Chart 6-22). This is a very old question as the investigation of the development of technology and its consequences has been present since the beginnings of civilization. The issue became more and more pressing with the extremely fast technological advancement of the last 100 years. Studying the decades following World War II Rescher (1979) expresses doubts if the development of technology really contributes to social wellbeing. Based on an opinion poll carried out as early as 1949 (Rescher, 1979) found that although 70 per cent of the responders thought that healthcare and general knowledge of the world had increased during the previous 30 years, only 21 per cent of them thought that there had been positive changes in regard to personal happiness and spiritual well-being within the same period. A fundamental question is how the development of technology affects social well-being based on the research results of modern psychology. The first positive effect of the development of technology is that it makes our lives more comfortable. You can travel faster and more comfortably, it is easier to communicate over large distances and there are more entertainment opportunities than ever. However, as we have seen earlier we tend to get accustomed to these changes. Consequently these positive changes do not increase our well-being and happiness in the long term. However, technological advancement and robotization bring radical changes in social conditions and as such may increase social differences in income (Jaumotte et al. 2013). This widens the gap between computer literate and non-literate employees. There are a number of jobs where — 327 —

6 Social effects of the development of technology

a human workforce is not even employed any more. This increases social inequality leading to a decrease in well-being and consequently more unhappy people. The financial position of employees working in areas affected by robotization have clearly deteriorated in the last decade both in the short and long term (Jansson – Karabulut 2019). The development of technology and urbanization also challenge human altruism (Wilson – Baldassare 1996). In small, tightly knit communities people knew each other well and there was a stronger tradition of helping each other, while today’s society is increasingly alienated. Offering donations and helping still have a positive effect on us today, but it is conducted in an increasingly impersonal manner and it plays a less important role in our everyday lives This also raises the question of issues regarding information bubbles. Active, organically cooperating communities force us to know and acknowledge many contradicting opinions. In today’s society this is less typical. The development of technology provides many cheap sources of information. This makes it possible for individuals to only be exposed to news and opinions that they agree with. Flaxman et al. (2016) conducted an investigation of the web habits of 50 thousand US citizens and he concluded that social media indeed widened the average gap of ideology among participants. This means that although new technologies seem to open the way for diversity, in reality they lead to the formation of information bubbles. Finally, there is controversy regarding the link between the development of technology and social interaction. On the one hand the development of technology makes communication easier and cheaper. This has a clearly positive effect on our lives and happiness. On the other hand new forms of communication, such as social media, do not provide a genuine social experience (Pittman – Reich 2016) and as such these have a markedly negative effect on social well-being.

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Consequently, the rise of online social media has a wide range of negative effects on our lives. One of the most marked characteristics is that the use of online social media, which makes us feel that others have a better quality of life and that they are considerably happier. With it comes the feeling that life is not just and we get less of it than others do (Chou – Edge 2012). In summary, current research results show that the development of technology and the resulting economic growth do not necessarily lead to an increase in the well-being of society. Moreover, based on the majority of papers a negative social systems and economic approach may mean that growth has a markedly negative effect on social well-being. For this reason it is important that economic growth does not become an end in itself – but must rather promote happiness and well-being.

References Berry, B. J., & Okulicz-Kozaryn, A. (2011): An urban-rural happiness gradient. Urban geography, 32(6), 871-883. Caprariello, P. A. – Reis, H. T. (2013): To do or to have, or to share? Valuing experiences over material possessions depends on the involvement of others. Journal of Personality and Social Psychology,104(2), 199–215. Carter, T. J. – Gilovich, T. (2012): I am what I do, not what I have: The differential centrality of experiential and material purchases to the self. Journal of Personality and Social Psychology, 102(6), 1304–1317. Chou, H. T. G., – Edge, N. (2012): They are happier and having better lives than I am: the impact of using Facebook on perceptions of others’ lives. Cyberpsychology, Behavior, and Social Networking, 15(2), 117-121. Clark, A. E. – Oswald, A. J. (1996): Satisfaction and Comparison Income. Journal of Public Economics, 61, 359–381. Cuñado, J. – de Gracia, F. P. (2012): Does education affect happiness? Evidence for Spain. Social indicators research, 108(1), 185–196.

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6 Social effects of the development of technology Easterlin, R. A. (1974): Does economic growth improve the human lot? Some empirical evidence. in P. A. David – M. W. Reder (ed.) Nations and Households in Economic Growth (pp. 89–125), New York: Academic Press. Gerhart, K. A. – Koziel-McLain, J. – Lowenstein, S. R. – Whiteneck, G. G. (1994): Quality of life following spinal cord injury: Knowledge and attitudes of emergency care providers. Annals of Emergency Medicine, 23(4), 807–812. Graham, C. (2005): Insights on globalization from a novel approach. World Economics, 6(3), 41-55. Fehr, E. – Schmidt, K. M. (1999): A theory of fairness, competition, and cooperation. Quarterly Journal of Economics, 114(3), 817–868. Flaxman, S. – Goel, S. – Rao, J. M. (2016): Filter bubbles, echo chambers, and online news consumption. Public opinion quarterly, 80(S1), 298-320. Florida, R. – Mellander, C. – Rentfrow, P. J. (2013): The happiness of cities. Regional studies, 47(4), 613-627. Lehmann, K. (2014): Subjective well-being in the European Union. (Doctoral dissertation, Budapesti Corvinus Egyetem). Liu, W. – Aaker, J. (2008): The happiness of giving: The time-ask effect. Journal of Consumer Research, 35(3), 543-557. Kahneman, D. – Krueger, A. B. – Schkade, D. A. – Schwarz, N. – Stone, A. A. (2004): A survey method for characterizing daily life experience: The day reconstruction method. Science, 306(5702), 1776-1780. Inglehart, R. – Klingemann, H. D. (2000): Genes, culture, democracy, and happiness. Culture and subjective well-being, 165–183, Cambridge, MIT Press. Jansson, T. – Karabulut, Y. (2018): Do Robots Increase Wealth Dispersion? (August 13, 2018). Available at SSRN: https://ssrn.com/abstract=3229980 Jaumotte, F. – Lall, S. – Papageorgiou, C. (2013): Rising income inequality: technology, or trade and financial globalization? IMF Economic Review, 61(2), 271-309. Marmot, M. (2004): Status syndrome: How your social standing directly effects your health and life expectancy. London: Bloomsbury. Oishi, S. – Kesebir, S. (2015): Income inequality explains why economic growth does not always translate to an increase in happiness. Psychological Science, 26(10), 1630-1638. Pittman, M. – Reich, B. (2016): Social media and loneliness: Why an Instagram picture may be worth more than a thousand Twitter words. Computers in Human Behavior, 62, 155-167. Rescher, N. (1979): Technological progress and human happiness. Philosophic Exchange, 10(1), 2.

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6.3 How to convert economic growth into social well-being Solnick, S. J. – Hemenway, D. (1998): Is more always better?: A survey on positional concerns. Journal of Economic Behavior & Organization, 37(3), 373-383. Suls, J. (2003): Contributions of social comparison to physical health and well-being. In J. Suls, & K. Wallston (Eds.): Social psychological foundations of health and illness (pp. 226–255). Malden, MA: Blackwell Publishers. Wilson, G. – Baldassare, M. (1996): Overall “sense of community” in a suburban region: The effects of localism, privacy, and urbanization. Environment and Behavior, 28(1), 27-43.

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The future of money and the money of the future

7.1

Challenges of the digital era Gábor Horváth – Pál Péter Kolozsi – Annamária Sipos-Madarász

In this subchapter the challenges stemming from the increasing digitalisation of money are described. Through examples from the past and different theoretical approaches we shall examine how social trust forming the basis for the operation of the financial system in the digital era can be interpreted, and what challenges the digital transformation of money poses in this context. We shall see how the collateral underlying the digital era’s money may develop, considering that data has become the “new gold” and digital economy relies heavily on energy. We shall assess the impact of the digital transformation of money on cash, notably regarding the potential risks that the decline of cash – which is the state’s ultimate means of payment – may impose. In the following we shall present what money of the future may look like on a global and local scale, addressing, in particular, the question whether a privately issued currency can become world currency. So far, the main question has been whether the dollar would remain the only global currency in the world, or other national currencies (especially the euro and the Chinese renminbi-yuan) would catch up with the US currency. Digital economy, however, may easily result in a situation where instead of state currencies, privately issued means of payment would dominate the world, which may present a novel and significant challenge for monetary authorities. This subchapter concludes by examining the role central banks may play in issuing digital currencies, and the possibilities and challenges that the potential introduction of central bank digital currency may present. In many ways, the digital era will constitute a new situation for the financial system, while in the changing environment central banks will have to fulfil the same two functions as presently: they need to participate in money creation in the digital era and — 335 —

7 The future of money and the money of the future

they need to regulate money creation taking place beyond central banks. This may imply that central banks would have to be able to compete with the private currencies of large technological companies, and their regulatory function may also change substantially, while cooperation between the state and the central bank may become closer than what has been seen in recent decades.

What might become the most important pillar supporting money of the digital era? All well-functioning financial systems are based on extensive social trust. On the one hand it is essential to trust that the general acceptance of the asset functioning as money will be ensured, i.e. that payments can be made via such assets. On the other hand, it is also important to trust that the financial system will ensure financial and price stability and will be able to realise transactions, and the value of money will remain stable. Without social trust no asset can function as money. The simplest and most difficult question in finance is what is actually meant by money. There are many answers to this question, but the commonality in all definitions is that there is no money without social trust. Money can be viewed, inter alia, as collective fiction (Harari 2017), debt (Borio 2018), technology (Levine 2019), a share of the net present value of the assets produced by society (Bossone-Costa 2018), or a social convention (Carstens 2018a), but all these presuppose that trust exists on the part of the members of the community. Historical experience also shows that although the functions of money can be fulfilled by a variety of means, successful currencies have always been characterised by broad acceptance, adequate supply and stability ensured by institutions (especially the central bank and financial supervision). The value of money is based on the fact that the accepting party can trust that others will also accept its money – and this trust needs to be built up and constantly maintained –, which constitutes the primary task and social function of the system of financial institutions, including the statutory framework and formal institutions. — 336 —

7.1 Challenges of the digital era

The system of institutions ensuring cash flow, the value of money and the long-term preservation of price stability and financial stability is the prerequisite for trust in money. Money can also be understood as an implicit contract concluded between the individual and the given community, according to which the individual can have access to money under a previously determined mechanism, and society guarantees that this asset (money) will be exchangeable for value in the future too. In this regard money is a commitment, i.e. debt undertaken by society towards the individual. If money is debt (Graeber 2011, Borio 2018), then the debtor (society) bears obligations such as the appropriate operation of the financial system, which is therefore the state’s responsibility. This stands for deposit money and for central bank money (cash), as the latter is issued by the state representing society. The state has an outstanding role and significance in the financial system, as ultimately one of the state’s important functions is to draw up and ensure compliance with the implicit contract mentioned above, and to set up the necessary institutional framework. It is also important to create and maintain trust in certain non-state actors of the financial system (banks). 61 From many aspects, money is permanent, still it has seen significant development in past millennia and centuries. The functions fulfilled by money are stable, but the evolution of the financial-technical solutions provided by money has been striking starting from ancient coins, through the first Chinese paper notes issued in the 9th century, Arabian cheques (Sakks) and banking in medieval northern Italy, all the way to modern money. In respect of trust in money, significant changes were represented by the demonetisation of gold and the development of the currently existing financial system, in which a substantial share of money in circulation is created by commercial banks, not central banks, in the course of their lending process. Digital development has brought an even more significant change (Lagarde 2018c) as the fintech revolution calls into question the very existence of the forms of money known so far and the role of the state at the same time. 61

On the historical aspects of trust in banks see: Kolozsi (2017).

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Digital transformation has also brought about a substantial change in the financial system, but without trust money of the digital era cannot function. Digital assets include several substantially different assets, such as – according to the taxonomy used by BIS – commercial bank deposits, central bank deposits, virtual money and cryptocurrencies,62 which have become widely known in recent years (Chart 7-1). From the aspect of trust the latter category bears outstanding significance, first of all because they do not impose obligations on any economic operators, and they ensure the possibility of peer-to-peer transactions, i.e. without the participation of a central clearing house, which is a significant difference as compared to “traditional” digital currencies, such as bank deposits. Chart 7-1: Classification of money types Central bank-issued

Digital

Virtual currency

Widely accessible

Fed

P2P

Central bank reserves and settlement accounts Central bank deposited currency accounts

Bank deposits

Central bank digital currencies (wholesale)

Central bank digital currencies (retail)

Cryptocurrency (permissioned DLT)

Commodity money

Cryptocurrency (permissionless DLT)

Cash

Source: Bech, M. – Garratt, R. (2017).

Cryptocurrencies have three main elements: the rules underlying the transactions (protocol), the ledger where transactions are recorded, and the network of the participants, which uploads, stores and inspects the ledger according to the rules of the protocol. See: BIS (2018).

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The main technical challenge is to prevent the multiple spending of digital money. The solution is provided by the permanent registration of the transaction, which, at the same time, is ensured by a decentralised network, rather than by a central institution.63 According to Levine (2019), the current financial system is based on an appropriate regulatory environment, which restricts money creation and thus guarantees that the scarcity and the value of money is maintained, thus inspiring trust in money. In the case of cryptocurrencies, it is not centralised state control, but a decentralised IT solution, i.e. a computer algorithm, that keeps money creation on track. Due to the nature of money, in the digital era as well the most significant challenge remains how to reach social consensus, considering that building trust is a long process which can quickly be destroyed. On the basis of historical experience, no financial system can be envisaged in which there is no need for trusted state or market institutions. It is uncertain whether the technology underlying cryptocurrencies can be considered as a sufficient guarantee, besides appropriate transparency, for inspiring trust among wide layers of society. Although cryptocurrencies do offer the potential for this, it is doubtful whether the operation of the financial system can be envisaged without state control ensuring the functioning of the assets used in past millennia, or whether the state should control it at all or how it should respond to the challenges of the digital era. Is it enough to just rephrase the rules, or should the state become an active participant of the financial sector? Christine Lagarde, chairperson of the International Monetary Fund between 2011 and 2019, is of the opinion that besides appropriate control and a statutory institutional system, digital currencies may contribute to increasing the diversity of financial services (Lagarde 2018b). AgustĂn Carstens, serving as general manager of the Bank of International Settlements since 2017, finds that 63

In the case of the distributed private ledger system trust is tied to selected participants, while in the case of the distributed public ledger system there are no such participants, so in respect of social trust the latter technology represents a challenge.

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the challenge arising in respect of maintaining trust in money can be handled through education (Carstens 2018b). In the case of cryptocurrencies brought about by digitalisation several factors make it difficult to gain social trust. In the centralised ledger system representing the current financial system, elaborate institutional frameworks built upon centuries of experience, first of all the central bank and supervision, and related legislation can be regarded as the basis for trust, while in the case of distributed ledger systems the only elements of trust available are either difficult to understand, not sufficiently known, or are based on trust in certain non-state actors. Cryptocurrencies that Carstens (2018b) refers to as the alchemy of the age of innovation have come into the focus of attention because they proclaimed that institutional trust could be replaced by trust in a decentralised system and in a technological solution. In the case of cryptocurrencies, several factors make it difficult to gain social trust as (1) the efficiency of cryptotechnology is questionable, (2) abusive practice is substantial and common, with the black economy playing a significant role (Lagarde, 2018a), (3) price volatility is contrary to the stability expected from money, and no participants are interested in stabilising money. Chart 7-2: What exists in each type of ledger system to ensure trust in money?

Source: Authorsâ&#x20AC;&#x2122; own compilation based on BIS (2018).

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Throughout history, typically the collateral underlying money also strengthened social trust in money, and in the digital era data and energy may also become collaterals. From a historical perspective, gold or state tax, or, in the case of commercial bank deposit money, loans also functioned as collaterals. It is uncertain, however, what could become the “collateral” of the digital era, presuming that money continues to have a collateralised nature. The collateral ensures that in the case of non-payment, i.e. when money becomes useless, there is the possibility to “escape” into an asset, the help of which claims can be restructured, and liabilities can be reduced. The question is therefore which asset has a direct value in the digital era besides gold – which is still potentially relevant in crisis periods due to its historical background – and taxation power. If we accept that data has become the “new gold”, or that energy is the key resource of the digital economy, then these two factors can be definitely added to the group of possible collaterals (Chart 7-3). Chart 7-3: Potential collaterals underlying money

Source: Authors’ own compilation.

What may the digital transformation of money entail and what risks does it pose? In recent decades the role of cash in transactions reduced significantly in many developed countries. The proportion of cash to the entire money stock has significantly reduced in several developed countries — 341 —

7 The future of money and the money of the future

(Chart 7-4). For example, in Sweden while in 2010 only 40 per cent of society considered themselves cash users, by 2018 this proportion had fallen to 13 per cent.64 This trend may intensify over time, as new generations that are born during this era appearing increasingly digital cash will become an incomprehensible and outdated asset. This tendency will make most central banks think hard, as the existence of cash is a condition for ensuring the security of the two-tier banking system. The reason for this is that deposit money is basically a private bank liability relating to cash, a means of payment guaranteed by the state. Besides prudent lending by banks and deposit guarantee schemes, the security of deposit money is ensured by trust in cash. Chart 7-4: Development of the proportion of cash in certain countries 20

Per cent

United Kingdom Sweden

2019

6 2018

2 2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

16 14

Euro area USA (right-hand scale)

Note: the proportion of cash within the M1 monetary aggregate. Source: central bank databases.

Stefan Ingves: The e-krona and the payments of the future. Source: Riksbank, 11 November 2018

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Cash can be pushed out of a country’s financial system in several ways: (1) via dollarisation, (2) due to the increasing popularity of bank deposit money and (3) by means of private but not controlled issue of money (cryptocurrencies). – The suppression of a state’s own currency due to dollarisation (when a legal tender outside a given economy is used without a formal agreement or accession) is accompanied by the unintended surrender of monetary sovereignty. This is substantially different from joining the euro area, as a dollarised country does not have the roles fulfilled by EA member states that are involved in the conduct of the policy of the European Central Bank. – Besides appropriate economic, financial, infrastructural and social conditions, bank deposit money may push cash out from everyday circulation.65 – The cryptocurrencies that have emerged so far could be regarded as risky investments rather than real alternatives to money, because of their deficient functions. In the following, we shall focus on the second scenario, i.e. we shall examine the effects the diminishing role of cash – resulting from digital technology – has had and the challenges that it has posed. The exclusive spreading of commercial bank deposit money and the disappearance of cash may present a number of challenges. Although electronic deposit money has indisputable advantages in the field of efficiency and transparency, it is still not completely reassuring if the state permanently loses its privilege to issue money.66 In times of natural or financial disasters commercial banks can hardly be expected to restore the payment network or to fully comply with their 65 66

The case of Sweden is an example for this. Hannah Armelius: CBDCs could protect citizens from e-currency abuse, official says. Source: Central Banking, July 4, 2019

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obligations, as their money is mainly backed by long-term loans or by securities potentially losing much of their value in the case of a crisis. But this would be even more difficult or even practically impossible to ensure, if the given country’s currency did not have a form that could be used as a means of escape in the case of a panic shaking the entire bank system. Furthermore, even without panic, privately owned institutions could hardly be forced to provide services at places where it would not be economically viable for them. Taxpayers enjoy the benefits and bear the costs of cash. The profit resulting from deposit money goes to the banks, while its costs – both under normal conditions and in the case of crisis – are borne by the entire society. If the bank deposit money system became unique, this would create a monopoly for the banking system. If a private business alone dominates a market, it enjoys substantial freedom in determining prices. Antitrust legislation and competition regulations all over the world seek to prevent this unfavourable situation for members of society. If cash disappeared from the economy, this would result in a natural monopoly for the banking system in the payment system. At the same time, the role of money in social and economic functioning has become almost as important as that of drinking water. Similarly to a significant European Union initiative67 launched against the privatisation of drinking water with hundreds of thousands signing the petition, the complete privatisation of money and the payment system would also present a significant regulatory challenge for politicians serving at any given time. Ever since the very first civilisations, money issued by the state has guaranteed the preservation of central power and the performance of tasks of the state. Economists sometimes recall68 that Aristotle or Adam Smith, in their discussions on (barter) economies based on barter trade, demonstrated how essential the institution of money was, and how strange and unreal it would have been to live in a barter economy. Harari, in his summary European Commission: Water and sanitation are a human right! Water is a public good, not a commodity! Source: EC, 2019 68 Ilana Strauss: The Myth of the Barter Economy. Source: Atlantic, 26 February 2016 67

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on money,69 also links the birth of money to the cradle of civilisations and to the beginning of writing. Mints, mining rights and coins played a central role in medieval state finances, and monarchs’ portraits are often known only from the coins issued by them. The maintenance of monetary sovereignty and the operation of the two-tier banking system may be hindered, if the right of issuing money was completely moved beyond the state, as it would result in the loss of the elaborate practices and experience based on the foundations of the central bank, banking regulations and deposit guarantee. It may also result in entire regions or social groups becoming inaccessible, and those not having bank accounts may be pushed out of economic activity. The total abandonment of cash may be problematic, for example, because of those members of society who have language difficulties or other disabilities (even age-related limitations) when it comes to the use of digital tools.70 In disadvantaged settlements there may be civilizational barriers to the introduction of sophisticated solutions. Although the existence of cash does facilitate the functioning of the black economy, it is not clear how and by what the black economy would attempt to replace cash – besides the benefits resulting from the diminishing of illegal activities – and its unintended effects. The role of cash as the state’s ultimate means of payment may become more significant in crises. Just imagine the delicate geopolitical situation when the payment network of a bank owned by a foreign country operates in your country, and it obviously performs its tasks perfectly in times of peace, but in the case of a conflict it can be used as a blackmail factor to paralyse the operation of the economy. You do not need to think of a state of war, as even a natural disaster can result in such a plight, when the internet – which is slowly permeating everything – or the electricity network become inaccessible. In such cases, the electronic form of currencies cannot operate in a crisisresistant manner either (it may be added here that it is also a problem persisting in the case of central bank digital currency). 69 70

Yuvel Noah Harari: Money. Source: Vintage Classics, 2018. In Sweden this is an especially pronounced aspect in discussions held on the future of money. See: Ingves (2018).

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What money of the future may look like on a global and local scale? The means of payment playing the role of the global reserve currency has changed continuously over time. Throughout history a country’s economic, commercial, financial and military role determined which currency was the most important reserve on a global scale (Chart 7-5). At the beginning of the Age of Discovery, the Portuguese real was the leading currency of the world, and after the Portuguese succession crisis the Spanish real took over this role. In the 17th century, Amsterdam was Europe’s commercial and financial centre, so the Dutch guilder was regarded as the world currency in that period. The decline of the Dutch East India Company and the Anglo-Dutch wars weakened the global role of the Netherlands and after that, up until the Napoleonic Wars, the French franc was the most significant reserve currency in the world (Kiss, 2018). Chart 7-5: Global reserve currencies since 1450 1 20

US dollar British pound sterling

105 year (1815 1 20)

French franc

5 year (1720 1815)

Dutch guilder

80 year (1640 1720)

Spanish real

110 year (1530 1640)

Portuguese real 1400

80 year (1450 1530) 1500

1600

1700

Source: Authors’ own compilation.

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1800

1900

2000

2100

7.1 Challenges of the digital era

At the beginning of the 20th century there were four currencies – the Deutsche mark, French franc, British pound sterling and US dollar – that seemed to function as world currency, but it actually materialized in the case of the pound and the dollar. For the first time in 1922, at the Genoa Conference, it was declared that the dollar and the pound were equivalent to and of the same quality as gold, confirming by this their function as world currencies. In 1944, besides setting up the International Monetary Fund (IMF) as the main institution working to facilitate international cooperation, the Bretton Woods Gold Standard System was established as a compromise solution between the British and the Americans. In this system only the dollar functioned as world currency, as only the US dollar was linked to the gold standard peg, while the currencies of the other 44 countries were linked to the gold standard only through the dollar (Botos 1983). In 1967, the member states of the International Monetary Fund decided to introduce a new liquidity facility. Special drawing rights (SDR) were established to cover member states’ current account deficits, to create reserves and to repay IMF loans. No member state contributions were needed to create the SDR as a “quasi currency”,71 and it was regarded as an international currency based on trust, with no collateral value (Botos 1983). In August 1971, United States President Richard Nixon cancelled the convertibility of the dollar to gold, and in 1973, when the leading economic powers changed over to the floating exchange rate system, the Bretton Woods System collapsed altogether. Although in the last quarter of the 20th century the Bretton Woods System no longer existed, the dollar continued to play an international and reserve currency role. As a result of the oil crisis in the 1970s, the price of crude petroleum oil increased tenfold during a period of 10 years. The dollar revenue 71

It limitedly fulfils the traditional functions of money, which, by itself – according to certain theories – would not exclude the possibility of functioning as a world currency; at the same time, the SDR, as it is not a common means of payment, can only be regarded as a world currency initiative.

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7 The future of money and the money of the future

generated by this on the part of petroleum exporting countries resulted in significant liquidity on the world’s financial markets, and the new concept of the petrodollar was born. As the dollar preserved its dominance, even among the globally significant central banks, the Federal Reserve still had the greatest influence on global financial conditions, and particular attention was given to the monetary policy of the Federal Reserve. Despite the clear domination of the dollar in the 20th century, currently there is a great deal of uncertainty about money of the 21st century and the future. A question in recent years has been whether the dollar will remain the only global currency. The euro – although it has been overtaken by the dollar regarding its international role – has become increasingly more significant in trade, currency reserves and bond markets at the beginning of the 21st century. Despite the 2009/12 crisis in the euro area, the euro is still regarded as the world’s second most important international currency, which also demonstrates that several currencies could function as world currency at the same time. Besides the dollar and the euro, in the not too distant future increasingly more emphasis may also be given to the Chinese renminbi-yuan. In recent years, China has played an increasing role in the world’s financial processes, and the share of the renminbi-yuan on the global foreign exchange market – although it is still low – is increasing. According to certain analyses, in the 21st century China will take over economic leadership from the USA, and the renminbi-yuan will become the most important world currency (Eichengreen et al. 2018). There is further uncertainty over the role of local currencies too. Is the historical development of money pointing towards world currencies, or towards local currencies coming into the foreground? Even the definition of local currencies is disputed as, besides the volume of the leading currencies of the world, a small country’s own currency can also be regarded as local currency, while local money was previously used by academic writers to refer to a means of payment used in a given country to stimulate a small local economy (Helmeczi – Kóczán 2011). Local currencies do not yet play a significant role in financial processes, their convertibility — 348 —

7.1 Challenges of the digital era

is not always ensured either, and digitalisation also facilitates the spreading of global currencies, although the economic crisis in 2008 revealed that local economy stimulating solutions might be necessary, and renewed emphasis has been placed on research in this field (Chart 7-6). Chart 7-6: Global and local currencies Local currencies

One dominant world currency

Source: Authorsâ&#x20AC;&#x2122; own compilation.

In connection with the emergence of virtual currencies of the 21st century, the question arises whether a privately issued currency can become a world currency. The emergence of virtual currencies is the result of technological innovation, as they were created by setting up an electronic system without a central actor, and these systems enable fast and cheap transfers via the internet. At the same time, cryptocurrencies that have emerged in recent years have not been able to spread widely as they do not have a sustainable value, and their use is limited. Libra, the cryptocurrency announced by Facebook, seeks to overcome the deficiencies of virtual currencies in respect of value stability and widespread use, and by this it may contribute to setting up a less costly, more easily accessible, global financial system. At the same time, virtual currencies, due to the fact that they are privately issued, may face an increasingly stricter regulatory environment, and as the issue of money should be kept under state control both for economic â&#x20AC;&#x201D; 349 â&#x20AC;&#x201D;

7 The future of money and the money of the future

and political reasons, it is questionable whether cryptocurrencies will be able to replace traditional currencies.

What digital central banks of the digital era may look like? In many ways, the digital era will constitute a new situation for the financial system, while in the changing environment central banks will have to fulfil the same two functions as presently: on the one hand they need to participate in the issue of digital money in some form, while on the other hand they need to regulate money creation taking place beyond central banks. Central banks may face financial technological challenges that may reduce the efficiency of monetary policy transmission in the longer term, and in an extreme case the central bank may lose control over the processes. One of these challenges is the spreading of virtual currencies,72 which are not yet able to fulfil money functions completely, but the possibility cannot be excluded that one day a virtual currency will appear which will be able to take the place of traditional money and become very popular. Further challenges for the efficiency of monetary policy transmission may be represented by large internet companies, which would use their own money within their own ecosystems for online trade, and the development of a cashless society73 resulting in non-bank participants ceasing to have access to central bank money. There is no clear answer to the question, to what extent these challenges endanger the efficiency of monetary policy transmission, and how central banks could best address these challenges. As a result of the emergence of virtual currencies, a new type of money has come into existence, and as a potential central bank response to this the concept of central bank digital currency (CBDC) has emerged in economic For a detailed description of virtual currencies see: Bank of Finland (2017), Camera (2017), ECB (2012, 2015). 73 In the case of Sweden there is a real chance of the development of a cashless society (Riksbank, 2017). 72

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thinking.74 Central bank digital currency is a legal tender issued by a central bank, which is electronic and widely (also for households and non-financial companies) and continuously (every day and in every hour) accessible (BIS, 2018). In theory, the method of using central bank digital currency can range from simple cash replacement to the central bank completely taking the place of commercial banks in money creation, resulting in a one-tier banking system. A distinction can be made between deposit-taking and lending central banks depending on which side of its balance sheet the central bank allows access for non-financial participants when introducing central bank digital currency. A deposit-taking central bank accepts deposits from the participants on the liability side but does not allow access to them on the asset side, while a lending central bank accepts deposits and also extends loans on the asset side of the balance sheet for nonbank/financial participants (Chart 7-7). Chart 7-7: Access to the balance sheet of deposit-taking and lending central banks Central bank counterparties Liabilities

Assets

Commercial banks

Currently

Government

+ Non-financial private sector’s credits

B) Creditor central bank

+ Non-financial private sector’s deposits

CBDC

A) Deposit-taking central bank

Source: Authors’ own compilation. 74

See, for example, the studies by Barrdear – Kumhof (2016) és Bech – Garratt (2017), and the speech of Mojmír Hampl presented in 2017.

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7 The future of money and the money of the future

In the case of deposit-taking central banks, central bank digital currency is created by the participants of the non-financial private sector converting their cash and depositing central bank digital currency on the central bank account, or by transferring their commercial bank deposit money on their commercial bank account to the central bank (Chart 7-8). In this case, the commercial bank layer can perform its lending activity as a real financial intermediary, because although the commercial bank may continue money creation, deposits may flow into central bank digital currency, and thus the bank may need central bank refinancing. At this point, the final money creation decision and control is in the hands of the central bank. On the whole, by crediting the CBDC account, the central bank balance may increase, while the aggregate money supply in economy remains the same: although the CBDC is added to the M1 monetary aggregate (cash and demand deposits), overall it would be a transfer between the elements. Chart 7-8: The hypothetical development of the balance sheet of a deposittaking bank75 Central bank Assets Liabilities Cashâ FX reserve

Commercial banks Assets Liabilities Deposit at central bank

CBDC áá

Credit to commercial

Credit

Banks á

Commercial bank deposit

Other (net)

Government debit (net)

Private sector Assets Liabilities

Central bank assets (net)

Cash â Central bank Credit á

Government Assets Liabilities

Other (net) CBDC áá

Private sector debit (net)

Other (net)

Deposit â Deposit â Credit Government assets (net)

Source: Authors’ own compilation.

The balance sheets included in this chapter are for illustration, the relative proportions of the items are not necessarily realistic. For convenience, we presumed that the central bank deposit base or equity of commercial banks is not adjusted to the increased liquidity needs or capital requirements. The darker blue areas indicate changes in the balance sheets.

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In the case of lending central banks, besides deposits, commercial bank loans may also be included in the central bank’s balance sheet (Chart 7-9), and the central bank would finance the loans of the nonfinancial private sector directly and by creating central bank digital currency. Thus, the CBDC created in the event of central bank lending may also increase the amount of money in circulation. If the central bank decides to pay interest on CBDC too, a new interest rate condition would be added to its facilities. Through interest paid on CBDC, deposit-taking central banks may have a direct influence on the participants’ conduct, while in addition to this, through interest on loans extended to the private sector, lending central banks are able to influence the participants of the non-financial sector even without going through the commercial banks. Chart 7-9: The hypothetical development of the balance sheet of a lending bank Central bank Assets Liabilities Cash â FX reserve Credit to private sector á Credit to commercial banks Other (net)

Commercial banks Assets Liabilities Deposit at central bank

CBDC áá Credit â Commercial bank deposit Government debit (net)

Central bank credit Deposit â

Private sector Assets Liabilities

Government Assets Liabilities Central bank assets (net)

Cash â

Other (net) CBDC áá

Private sector debit (net)

Other (net)

Deposit â

Central bank credit á

Government assets (net)

Credit â

Source: Authors’ own compilation.

While in the case of a deposit-taking central bank the central bank “competes” with commercial banks in the field of account management, lending banks also compete with them in the field of lending. This centralised scenario, which is fundamentally different from market operation, should only be addressed as a theoretical possibility, as so far none of the developed countries have suggested it as a real alternative or objective. If central bank lending is not too popular, there is no significant change in the current operation of commercial banks, but the more popular it becomes, the smaller — 353 —

7 The future of money and the money of the future

market share is left for commercial banks, so market competition may become reduced and distorted. In an extreme case, in the practical sense this may result in the banking system becoming a one-tier system. At the same time, the question arises whether it is necessary or possible for central bank lending to replace the entire commercial bank lending in respect of both quality and quantity. If a central infrastructure is created instead of the two-tier banking system, this would present serious system security risks, and a significant credit risk would build up in the central bank’s balance sheet. In addition to this, the central banks’ tasks would be significantly expanded – for example, a complete bank administration would have to be set up and operated –, therefore the introduction of central bank digital currency would generate significant costs (Benk et al. 2018). The development of the central bank balance sheet is mainly influenced by whether CBDC would crowd out only cash or commercial bank deposit money as well. Forcing only cash out would not change the monetary base, but if commercial bank deposits also flowed over to the central bank, the monetary base would increase, which would result in central bank balance sheet growth. At the same time, as the size of the central bank balance sheet changes in line with lending, economic processes and money creation, it may become volatile. The introduction of the CBDC may shrink the fiscal policy’s room for manoeuvre because of the building up of the credit risk undertaken by the central bank, and it may make the retail funding of government debts substantially more difficult. On the one part, if as a result of the lending processes of commercial banks CBDC flows into the central bank balance sheet, and in return for this the central bank extends loans to the commercial banks, then it must assume indirect credit risk. On the other part, if the central bank performs a lending activity, then direct credit risk builds up in its balance sheet. If the non-performing loan ratio increases in a crisis, loss may be ultimately incurred in the central bank’s balance sheet too. If because of the loss suffered the central bank — 354 —

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is in need of recapitalisation, then it results in the shrinking of the budget’s room for manoeuvre. In respect of the financing structure and strategy of the government debt, central bank digital currency may represent a potential challenge if households play a significant role in directly financing the government debt. If the CBDC has favourable conditions, short-term retail savings may flow towards the CBDC, which makes it difficult to finance the state from such sources. The more favourable the CBDC conditions are for households, the greater the suction effect. At the same time, in the digital era central banks must also be able to compete with the private currencies of large technological companies. By virtue of their regulatory functions they need to obtain all the knowledge to ensure the secure and sustainable operation of the payment and financial system. Significantly more intensive cooperation may be required between the state and the central bank in order to perform this task in the changing world. If commercial banks are left behind in the digitalisation competition, they may even become disintermediated, and this results in a new role for central banks performing the supervision and regulation of the financial system. This is one of the reasons why the analysis, study and – after appropriate planning – introduction of the CBDC has become a primary concern for many central banks (Riksbank, People’s Bank of China, etc.)

References Armelius, H. (2019): CBDCs could protect citizens from e-currency abuse, official says. Source: Central Banking, 4 July 2019 Bank for International Settlements (BIS) (2018): Central bank digital currencies. Bank of Finland (2017): Monopoly without a monopolist: An economic analysis of the bitcoin payment system. Bank of Finland Research Discussion Paper No. 27/2017. Barrdear, J. – Kumhof, M. (2016): The macroeconomics of central bank issued digital currencies. Bank of England, Staff Working Paper No. 605. Bech, M. – Garratt, R. (2017): Central bank cryptocurrencies. BIS Quarterly Review, September 2017.

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7 The future of money and the money of the future Benk, Sz. – Kajdi, L. – Kollarik, A. – Mamira, Z. – Szebeny, M. – Török, G. – Varga, L. (2018): Digitalisation and the monetary system. In: Bankok a történelemben – innnovációk és válságok (Banks in history – innovations and crises) MNB, 2018. BIS (2018): Cryptocurrencies: looking beyond the hype. In: BIS Annual Economic Report 2018 Borio, C. (2018): On money, debt, trust and central banking. Keynote speech. Cato Institute, 36th Annual Monetary Conference, 15 November 2018, Washington DC Bossone, B – Costa, M. (2018): Money As Equity: For An “Accounting View” Of Money. Feb 12, 2018. Economonitor Botos, K. (1983): Pénz – nemzetközi pénz (Money – international money). Közgazdasági és Jogi Könyvkiadó, Budapest, 1983. Camera, G. (2017): A perspective on electronic alternatives to traditional currencies. Sveriges Riksbank Economic Review 2017:1, 126–148 p. Carstens, A. (2018): Money in the digital age: what role for central banks? Lecture, House of Finance, Goethe University Frankfurt, 6 February 2018 Carstens, A. (2018b): Technology is no substitute for trust. BIS speech published in Börsen-Zeitung, 23 May 2018. Eichengreen, B. – Mehl, A. – Chitu, L. (2018): A világ valutarendszere. Múlt, jelen és jövő. (How global currencies work: Past, present, future.) Translated by: Valér Bedő. Pallas Athéné Könyvkiadó Kft., Budapest, 2018. European Commission (2019): Water and sanitation are a human right! Water is a public good, not a commodity! Source: EC, 2019. European Central Bank (2012): Virtual currency schemes. European Central Bank (2015): Virtual currency schemes – further analysis. Graeber, D. (2011): Debt - The First 5,000 Years. First Melville House Printing: May 2011 ISBN: 978-1-933633-86-2 Hampl, M. (2017): Central banks, digital currencies and monetary policy in times of elastic money. A speech, https://www.bis.org/review/r170720b.pdf downloaded: 10 July 2019 Harari, Y. N. (2017): Homo Deus. A Brief History of Tomorrow. Animus. Budapest. Harari, Y. N. (2018): Money. Source: Vintage Classics, 2018. Helmeczi, I. – Kóczán, G. (2011): A “helyi pénznek” nevezett utalványokról (On vouchers referred to as “local currency”). MNB-szemle, April 2011. Ingves, S. (2018): The e-krona and the payments of the future. Source: Riksbank, November 11, 2018

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7.1 Challenges of the digital era Kiss A. (2018): The Beginnings: From Mesopotamia through Florence to London. In: Bankok a történelemben – innnovációk és válságok (Banks in history – innovations and crises) MNB, 2018. Kolozsi, P. P. (2017): What can we learn from the large banker dynasties? – Report about the annual conference of EABH. Financial and Economic Review 16(3), September 2017, pp. 168-172. Lagarde, C. (2018a): Addressing the Dark Side of the Crypto World. March 13, 2018 IMF Blog. Lagarde, C. (2018b): An Even-handed Approach to Crypto-Assets. April 16, 2018. IMF Blog. Lagarde, C. (2018c): Winds of Change: The Case for New Digital Currency. Singapore Fintech Festival November 14, 2018. Levine, M. (2019): Facebook Will Make the Money Now. Bloomberg opinion. 06/18/2019 Riksbank (2017): The Riksbank’s e-krona project. Report 1. Sveriges Riksbank. Rowling, R. (2019): Central Banks Are Ditching the Dollar for Gold. Source: Bloomberg, May 2, 2019 Strauss, I. (2016): The Myth of the Barter Economy. Source: Atlantic, February 26, 2016 White, L. (2018): The World’s First Central Bank Electronic Money Has Come – And Gone: Ecuador, 2014–2018. Source: Alt-M, March 29, 2018

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7.2

The role of the financial system in sustainable development Directorate Financial System Analysis76

Enterprises and households that do not participate in the financial system have weaker income generating abilities, which makes it difficult for them to break away from poverty. This currently affects 1.7 billion people, therefore the World Bank, together with the governments of over 60 countries, has determined financial inclusion as a reform goal. Improving the access of financial services may have numerous favourable effects from the aspect of financial stability. However, increasing financial access may also lead to the building up of systemic risks, therefore macroprudential policy plays an outstanding role in maintaining the resilience of the financial system. The coexistence of competition, efficiency and stability in the banking system is essential for economic actors to be provided with sufficient banking services at appropriate prices in all phases of the financial cycle. At the same time, there is no unanimous view either in historical experience or in academic literature on market structure and on the optimal level of concentration. In the case of the currently overbanked systems, increased efficiency and profitability realised through consolidation may result in greater stability, while at the same time the problem of “too big to fail” was clearly highlighted by the experience obtained from the most recent crisis. The financial sector, which was considered the most innovative sector before the crisis, has lost its leading role in recent years. The emerging new participants 76

Authors: Nedim Márton El-Meouch, Alexandr Maxim Palicz, Tamás Nagy, Nóra Sljukic, Róbert Mátrai

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with their innovative solutions have become the banks’ competitors, and banks are now facing new business solutions as opposed to the operating model they have been using. The evolution of FinTech companies has been induced, in particular, by technical development and changing customer habits, so these companies are typically developing new solutions for certain bank products or services. The rise of services of these companies is first of all due to the fact that they are able to transform the entire value chain, resulting in better customer experience. Consequently, FinTech solutions represent both risks and opportunities for banks, and we believe that these solutions should be regarded as solutions challenging the traditional banking system. Innovations also bring the requirement of ethical operation to the forefront, as novel business practices often appear in the focus of regulations only with a delay. At the outbreak of the crisis, it was observed that the innovations that were favourable by themselves (e.g. securitisation, assessments by credit rating agencies, or subprime loans) could cause systemic damage because of their excessive nature and lack of transparency. In the light of this, it is essential to expect moral behaviour, but the operation of the system should not be based only on this – i.e. on the self-regulation of the financial sector – because of the logic underlying market competition. Self-regulation should be accompanied by appropriate prudential, through-the-cycle regulation. As a result of global climate change the frequency and amount of loss deriving from extreme weather events is increasing, which is directly eroding the banking infrastructure (operational risk) on the one part, and is reducing the collateral value of immovable properties and the profitability of companies through damaging means of production and real estate on the other part, which results in an increase in bank credit losses (credit risk). The spillover effect of physical risks also affects money and capital markets through the depreciation of company shares and bonds (market risk). The intensifying regulatory actions aimed at addressing climate change and the changing of consumer attitudes may result in a forced transformation of the infrastructure, technology and operating model of the sectors causing the highest greenhouse gas emissions, which, through their exposures, also affects banks’ credit and market risks.

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7 The future of money and the money of the future

The increased risks related to climate change make it necessary for banks to deal further with this issue, therefore banks’ successful adaptation also makes it essential to transform risk perception and corporate governance principles. Besides risks, climate change, together with the changing regulatory environment and consumer attitudes, also present business opportunities for banks. The banking system plays a dominant role in financing investments, in rechannelling of funds to green projects, and – through product innovation – in catalysing sustainable development.

How can the banking system contribute to the prudent deepening of financial inclusion? Financial inclusion means the access and broad availability of financial services in respect of both price and proximity, for an ever wider range of society and economic actors. Among financial services, from the aspect of access, focus should be put first of all on basic products, i.e. account management and payment services, as well as credit and insurance functions (Demirguc-Kunt–Klapper 2012). The complete lack of financial inclusion means that individuals do not use any financial services (not even account management). Financial inclusion plays a significant role in economic development. Those who do not participate in the financial system have weaker income generating abilities, which makes it difficult for them to break away from poverty (Suri–Jack 2016). Furthermore, by being connected to the financial system, financial risks can also be managed more easily, for example through accepting financial from geographically distant relatives or friends (Jack–Suri 2014). Finally, relationships with financial intermediaries result in an increase in savings and facilitate the acquisition of basic consumer necessities (Dupas–Robinson 2013, Prina 2015, Brune et al. 2016). For this reason, one of the aims is to involve social groups that are less active in the field of banking services, because among these groups there is a low level of trust in the financial system (Hannig–Jansen 2010). Another aim is to ensure the possibility of access — 360 —

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to the financial intermediary system for disadvantaged or low-income social classes through price and proximity, which is one of the primary pillars of increasing penetration (Khan 2011). With a view to increasing penetration, the World Bank has set a strategic aim to involve 1 billion people between 2015 and 2020, and the governments of over 60 countries have also determined financial inclusion as a reform goal. Between 2011 and 2017, 1.2 billion people opened a bank account all over the world, but 31 per cent of the adult population (Chart 7-10), about 1.7 billion people, are still not connected to the system of financial institutions (World Bank 2018). Examining this issue in a global context, the lack of financial inclusion is more typical in developing countries: half of those not using financial services are concentrated in seven countries (Bangladesh, China, India, Indonesia, Mexico, Nigeria and Pakistan). On a local level, women, the poor, people with low educational attainment and those with a lower labour market status are over-represented among those not having access to such services. Chart 7-10: The proportion of adults with an account (%), 2017

0 20 2 40 40 65 65 0 0 100 No data

Source: World Bank Global Findex Database.

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Improving the accessibility of financial services may have numerous favourable effects from the aspect of financial stability (Khan 2011). On one hand, low-income social layers will be less sensitive to economic fluctuations if they have savings through which they become integrated in the financial sector (Hannig–Jansen 2010). On the other hand, in case of smaller businesses, which grant a significant part of employment but appear on the market of financial services more rarely, limited access to credit has an above-average negative effect on output. Therefore, the development of their financial awareness and inclusion also constitutes a pillar of financial and economic stability (Prasad 2010). Deeper financial integration, through the increase of deposits and loans and enhanced accessibility to savings and credit market products, may contribute to more stable consumption by customers, also promoting the more effective transmission of monetary policy. Through increasing banks’ customer base, the wider accessibility of financial services also supports the more efficient and more sustainable operation of these services. However, enhancing financial accessibility may also lead to the building up of financial systemic risks. The expansion of financial services may entail increased lending to debtors which are more vulnerable or have lower financial awareness than the average (Mehrotra–Yetman 2015). This may lead to excessive risk-taking both on the part of banks and consumers, which may cause increased credit losses and in extreme cases may also endanger financial stability (Khan 2011). Financial stability risks may be increased by the appearance and spreading of less transparent and less regulated new financial products that are necessary for the inclusion of the social groups concerned. In case of raising financial inclusion, therefore, special attention should also be paid to maintaining the resilience of the financial system, in which macroprudential policy plays a highlighted role (Chart 7-11).

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Chart 7-11: Relations between financial inclusion and financial stability INCREASES FINANCIAL STABILITY: Limited lending to riskier, less conscious consumer groups Regulatory goal

Narrower financial inclusion DECREASES FINANCIAL STABILITY: Lower bank deposits, higher liquidity risk Consumption smoothing of consumers is limited, which can deepen economic cycles Lower profitability of banks

Supporting the broadening of financial inclusion while maintaining financial stability

INCREASES FINANCIAL STABILITY: Increasing bank deposits, lower liquidity risk More efficient smoothing of consumption by consumers increases their resistance Higher profitability of banks Broader financial inclusion DECREASES FINANCIAL STABILITY: Wide access to credit market can result in loosening credit conditions It may lead to the emergence of new, less regulated, riskier financial solutions

Source: Authors’ own compilation based on Mehotra et al. (2015).

Ensuring the appropriate operation of the financial intermediary system and strengthening trust may contribute to the sustainable increase of access to financial services. The building up of financial systemic risks while improving access to financial services can be mitigated by projects and actions aimed at raising consumers’ financial awareness on one hand, and by regulatory measures to counter excessive risktaking on the other hand. By raising financial awareness, trust in the institutions increases, and customers are more open-minded to financial products. On one hand, this contributes to the deepening of financial intermediation, while on the other hand, it helps consumers in choosing products suited to their risk appetite when using financial services. Furthermore, those concerned will choose their financial service provider more consciously, contributing by this to growth of competition, which facilitates more efficient customer service.

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From the regulatory aspect, macroprudential policy instruments may efficiently restrict the emergence of excessive systemic risks and adjust excessive cases of risk appetite. If risk appetite is too low, it will be increased by strengthening trust in the financial system; whereas when market actors seem to be willing to take excessively high risks, they will be prevented from doing so. This results in a sustainable supply of financial services as well as a sustainable demand for certain products and services by the consumers. The sustainable increase of access can be supported most efficiently by so-called debt cap instruments, which are targeted and affect individual credit transactions. These may relate to a wide range of features characterising the credit transaction and the debtor, such as the amount that can be borrowed, the maturity or the amount of the maximum instalment, the collateral, the credit currency, or the debtor’s income, age, etc. Most often, the instruments introduced mitigate the maximum indebtedness related to the individual debtor’s income or wealth, as well as the maximum level of encumbrance of the collateral in case of covered loans (Chart 7-12). Debt cap rules may prevent the excessive indebtedness of vulnerable customers involved in the course of improving financial access, and by this mitigate potential future bank losses. In addition to this, the rules limiting indebtedness in proportion with income contribute to obtaining a more accurate picture of debtors’ income situation, and to the whitening of the economy through the necessity of providing proof of income. Loan-to-value requirements relating to the provision of down payment may facilitate demand for financial services aimed at savings, increasing the stable funding of the banking system.

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Chart 7-12: Debt cap rules and requirements in Europe

Only income-based regulation recommendation Only collateral-based regulation recommendation Only collateral-based regulation compulsory Income-, and collateral-based regulation recommendation Income-, and collateral-based regulation compulsory No current income-, or collateral-based regulation Note: In Denmark and Latvia the loan-to-value regulation is mandatory, while the income-based limit has been determined in the form of a recommendation. Source: ESRB, MNB.

Can a banking system be efficient, competitive and stable at the same time? The coexistence of competition, efficiency and stability in the structure of the banking system is essential for economic actors to be provided with sufficient banking services at appropriate prices in all phases of the financial cycle. In the case of healthy competition, customers â&#x20AC;&#x201D; 365 â&#x20AC;&#x201D;

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can have access to services of increasingly better quality and more favourable prices, to which the gradual improvement of efficiency contributes considerably, and it is financial stability that makes this sustainable in the long term. However, the presence of an adequate market structure also plays a significant role in the fulfilment of the conditions. In respect of organisational structure, “overbanking” represents a problem in a number of EU member states, which – in variable configurations – shows up particularly in the exceptionally high number and excessive size of institutions, in the inefficient operation of branch networks, in moral risks, and in the decline of alternative (nonbanking) forms of financing (ECB 2018, ESRB 2014). The market structure is closely linked to the issue concerning the relative size of institutions. As a consequence of this, regardless of the historical background, regulatory environment and economic abilities, dilemmas about market concentration and institutional consolidation arise in the case of all banking systems. There is no unanimous agreement stemming either from historical experience or academic literature on whether consolidation and thus increased concentration has an overall positive or negative effect on the banking system in its fulfilment of its economic role. Accordingly, there is no universal recipe for achieving an optimal market structure, and while seeking to do so, attention should also be paid to the individual characteristics of the banking systems. With regard to the importance of this issue, the Magyar Nemzeti Bank, in its study entitled Átalakulóban a magyar bankrendszer (Hungarian banking system in transformation) (2014), listed the indicator capturing the consolidation of the banking system and competition and measuring the respective market share of the three largest institutions (C3) in all segments among the ten criteria of a well-functioning banking system. There are numerous indicators for measuring systemic concentration, market share and market power. These include, in particular, the concentration ratios mentioned above, market share based on balance sheet total or product, the HerfindahlHirschmann index, the Panzar-Rosse H-Statistic, the Lerner index, and the Boone indicator, but on the basis of academic literature no strong — 366 —

7.2 The role of the financial system in sustainable development

and clear link can be established between them. Consequently, the effect of bank concentration is not clear and not necessarily linear. Chart 7-13: The threefold target system of concentration Stability

Concentration

Efficiency

Competition

Source: MNB.

According to the classical interpretation, in the case of a lower number of institutions with greater market power an oligopolistic market develops, which results in unreasonably high interest rate spreads for customers. In other cases, the competition for customers might even intensify between a few large participants, which appears in innovative and customer-friendly services and lower spreads in the best-case scenario, and in risk-based competition in the worst-case scenario. In academic literature there is no agreement as to whether higher concentration would reduce competition (De Graeve et al. 2007, Bain 1956, Demsetz 1973, Ă lvarez et al. 2017). Consolidation may also contribute to improving efficiency. The bank, by increasing its activity and by regional and product diversification, can make a more efficient use of its physical and human capacities, its customer base, even by exploiting the synergies between the organisational units. Due to greater operational efficiency and a diversified portfolio, a given bank can reduce the average risk of its credit volume on the one part, while on the other part it can apply â&#x20AC;&#x201D; 367 â&#x20AC;&#x201D;

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lower spreads as a result of lower operating costs. The integration of data warehouses also reduces the information asymmetry of banks, and the consolidation of “big data” resources makes it easier to develop services and sell products. In recent years, a greater emphasis was put on the optimal size and role of branch networks and on the organisational structure, i.e. the optimal rationalisation of operating costs and business complexity, which is made possible first of all by domestic consolidation (ECB 2017). In addition to this, the termination of bank units with a low added value, new capacities are released to satisfy economic sectors suffering from labour shortage (ESRB 2014). However, consolidation may also support the improvement of the efficiency of sales channels indirectly. In a newer and bigger institution more professional knowledge is concentrated, and greater capacities are available for realising digital innovations. There comes a point, however, when the increase in size incurs additional costs. Firstly, despite the initial positive effect of consolidation, the organisation becomes more complex in the case of further expansion, which requires higher level and more expensive management control, and moral risks may also arise from reduced transparency (Davies – Tracey 2012). Following consolidation, by extending market presence to wider segments (retail, business, SMEs, commercial real estate, trust activities, etc.) the bank is able to diversify its income creating ability and risks more efficiently, even across borders. This effect occurs on the liability side: the more widely a bank is able to collect deposits (or issue securities), the more stable financing structure it will have. On the basis of the above, as a result of higher efficiency and risk diversification – up to a certain point – substantially stronger and more resilient institutions will develop with a stable liquidity situation and solvency. Stable liability structure and profitability contribute to the institutions’ adequate resilience to shocks and their being able to support the operators of the real economy even in an unfavourable

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macroeconomic environment. A considerable part of academic literature also argues in favour of this (Schaeck et al. 2006, Beck et al. 2006). At the same time there are studies presenting empirical evidence of the opposite link, according to which excessive concentration may also result in greater fragility (De Nicoló et al. 2004 or Uhde–Heimeshoff 2009). For example, in the case of excessive concentration mentioned above, the risk of “too big to fail” increases, moral risks may be more easily asserted in the bank’s business decisions, and procyclical behaviour may become more prominent in the upswing of economy. Excessively large institutions, through their emergence, presuppose implicit government guarantees for “bad” times, which economically reduces their cost of capital (in the case of a crisis) and increases their risk appetite (in “good” times). One of the bitter lessons learnt from the 2008 economic crisis is that excessively large institutions may fill critical functions even at a system level both on money markets and on the credit market. Therefore, in their case there may be a greater risk of contagion, and their vulnerability may sweep away other stable institutions too. Excessive size also slows down the organisation’s adaptability, so in the case of a greater external shock (crisis, changes in competitive conditions, the permanent transformation of the economic environment) the bank will be able to adjust its operation to the new conditions only very slowly and at a great cost. In addition, higher concentration, moderate competition often entailed by increasing market power, the environment of relative abundance of funds and ample liquidity, and high costs of switching between banks may also suppress monetary transmission, but there is no absolute agreement on this subject in academic literature either (Gambacorta 2005, 2008; Havránek et al. 2015; De Bondt 2012)

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7 The future of money and the money of the future

Increase in efficiency, decrease in risks

Chart 7-14: The relation of optimal concentration to competition and stability

Cheaper banking, More stable institutions

Monopolistic profit, Rising systemic risks

Optimal concentration

Degree of concentration

Source: MNB.

In light of the above, we can conclude that concentration – subject to certain conditions – has an optimal level, below which a substantial increase in efficiency, cheaper banking and greater stability can be achieved, while above this level these benefits may reduce and risks may increase. Consequently, several concentration indicators should be applied when doing research, and their role should be examined both along the dimensions described above, as well as in a holistic manner.

The risks and opportunities presented by digital solutions For decades the financial sector was regarded as the most innovative sector in world economy. Both on the asset and liability side it was characterised by product development, and its services and service channels were continuously expanded and digitalised (Arner, Barberis, & Buckley, 2015). However, it gradually lost this leading role because of the difficulties caused by the global crisis and by the prolonged management of the consequences of the crisis. While banks were busy with managing the crisis, i.e. bad loans, and minimising their — 370 —

7.2 The role of the financial system in sustainable development

losses (rationalising costs and the business model), developments were pushed into the background, and new actors taking advantage of the opportunities of technological development appeared on the market, thus increasing competition. As a result, today 4 actors can be identified in the financial system: 1) incumbent77 institutions, 2) new institutions established on digital foundations, so-called neobanks or challenger banks, 3) FinTech companies, and 4) ICT (Information and Communications Technology) companies, with special emphasis on Big Tech commonly known as GAFA (Google, Apple, Facebook, Amazon) (EBA, 2018). The new participants, with their innovative solutions have become the competitors of incumbent institutions, who were now facing new business models as opposed to the operating model they had been used to. The emergence of FinTechs was in fact made possible by technological development; it is enough to mention increased computing and IT capacities, or new solutions that make it possible to connect certain systems more easily, e.g. through APIs78. These technological solutions made it possible to develop more complex platforms that are easy to handle at the same time, on which it is easy to build up business solutions and financial services. (Bossert, Desmet, & McKinsey, 2019). FinTech solutions are developed on so-called platforms, which are first of all characterised in that they are open, i.e. they can be accessed by customers via the internet or by developers via APs, and their IT systems contain the basic functionalities that support the entire business process. (Dhar & Stein, 2017) As a result of the wide use of the internet and smart devices, consumer habits are also changing, creating new requirements in the field of financial services. At the same time, the digital transformation taking place in the field of finance is not purely a technological revolution, By incumbent institutions we mean traditional financial institutions already present on the market. 78 API: application programming interface 77

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but much rather it is due to the fact that the increasing everyday use of digital devices and digital platforms also results in the changing of customersâ&#x20AC;&#x2122; banking habits. Market expectations are changing in line with this, financial intermediary systems are gradually transforming, and new business models are created (Dhar & Stein, 2017). Typically, FinTech companies develop new solutions for certain bank products or services, such as mobile payment solutions, products supporting personal financial management, or among new business models, so-called peer-to-peer (P2P) lending can be included, as well as crowdfunding, the appearance of cryptocurrencies or robo-advisory solutions. Chart 7-15: Factors influencing and shaping the business model change of incumbent institutions

Increasing competition

Profitability concerns

Customer expectations / behaviour

Business model change

Regulatory changes

Source: EBA.

FinTech companies have brought a new approach to fast, cheap and experience-based customer service. They focus on the given problem, on customer demand when developing financial solutions (for example, foreign currencies can be transferred by minimising conversion costs) and services using the latest technology. The rise in services of FinTech companies is first of all due to the fact that they are able to transform the entire value chain and renew customer experience by doing so. Thus, for example, banking habits are changing as payment services â&#x20AC;&#x201D; 372 â&#x20AC;&#x201D;

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are being placed on new foundations with the rise of mobile payment (due to the use of so-called wallets). With mobile banking coming into the foreground, solutions such as personal financial planners are added to the services, but there are also applications with the help of which monthly savings can be automatically controlled. As a result of the emergence of FinTech companies, traditional banks are facing new competitors on the market of financial services, as these companies can transform the entire value chain and intervene in it by breaking products or services down into modules and reconnecting them in an innovative manner (Omarini 2018). For incumbent institutions the greatest challenge is that the value chain, which they used to take for granted, cannot be taken for granted any longer. This brings a new perspective to their strategies too, as they need to consider which functions can be completely replaced by FinTech solutions, and which ones can hold their value, so that their business model can remain sustainable in the long term (Omarini 2018). The most popular FinTech solutions that are based on platforms and provide a novel customer experience include the following: payment services, robo-advisory activities, P2P (peer-to-peer) lending platforms, insurance solutions.

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Chart 7-16: The effect of the most important FinTech solutions on the value chain • Personal finance management (account aggregation) • Peer-to-peer (P2P) lending and investment

l ai

Deposit and lending

Investment management, wealth management

DLT, Smart contract, AI

• Telematika • IoT

s ne

i ta

sin

Fintech solution classification by economic function

Payments

Digital ID

sin

• Next generation trade finance • E-trading

Cloud computing

s ne

lin

Insurance

• Mobil payment (e.g. NFC) • International remittances • Other payment processing

• Crowdfunding • P2P lending • Digital cash management

Big data, visualisation

• Robo-advisory • Social investments

Note: the solutions are categorised according to their economic functions, with examples given for the different sectors. The services are typically supported by the use of advanced technology, such as the use of clouds or big data analysis. Source: Authors’ own compilation based on FSB, McKinsey.

P2P (peer-to-peer) lending lays completely new foundations for lending. Although the viability of the business model of so-called marketplace lending platforms is debated79 (Deloitte 2016), it is common ground that it transforms the savings and lending value chain and the function of the financial intermediary system, as in this case there is direct contact between the creditor and the borrower, via the platform. The advantage of the platform lies in data use. For example, one of the advantages of P2P lending platforms focusing on SMEs is that in 79

In a low interest rate environment it is attractive for creditors, but risk weighs on the return of the amounts invested, for which there is no insurance. Although on certain platforms creditors can also use collection service against payment in the event of non-payment by the borrower, the competitiveness of the service vis-à-vis other investment products is called into question.

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addition to traditional data analyses – such as a company’s financial data or ownership structure – they are also able to analyse nontraditional data – e.g. supplier behaviours, owners’ networks – from public sources. By uniting traditional models and advanced methods of data analysis, P2P platforms are able to prepare a more accurate risk profile for creditors. In respect of investment services, so-called robo-advisory solutions – i.e. offering customised and automated investment portfolios suiting customers’ risk appetite – mark a breakthrough, especially on the retail market. Their benefits include that based on customer preferences they present investment possibilities in a more understandable and comprehensible manner, thus rendering decision-making simpler. Due to these solutions, the retail business of incumbent institutions is going through a drastic transformation. In customer-centred banking, however, technological development is taking place not only in the field of mobile devices or advanced data analyses, but in more efficient background operations have also contributed to increased customer value. FinTech solutions can also make a change in real estate lending: today there are a number of solutions from which financial service providers can also attach credit requests to a given property viewed on the internet, based on its location and parameters. If this process is supplemented, for example, with mortgage registration based on blockchain, it may result in the transformation of the entire real estate lending model. Accordingly, typically in the field of cash flow, financial planning, savings, investment services and lending activities, novel solutions have appeared, which can produce a breakthrough in the financial sector. For the time being, FinTech solutions are becoming more prominent mostly in the field of retail financial services, due to the large customer base. This puts pressure on the business model of incumbent institutions, as these solutions result in a significant loss of income for banks (EBA 2018). Moreover, through the arrangement of

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7 The future of money and the money of the future

daily financial affairs, customer relations are already realised with the FinTech company. On the regulatory side, it is necessary to closely monitor the transformation of business processes, as these may affect the stability of the financial system. While the spreading of cost-efficient FinTech solutions constitutes an advantage for customers, it poses a profitability risk for poorly adapting incumbent institutions. They face a number of risks in respect of the sustainability of their business model, such as the recruitment of specialists with appropriate skills, or the feasibility of certain innovative strategies because of the complexity of internal processes and outdated IT systems, and – last but not least – the management of increased cyber risks. (EBA 2018) Consequently, for incumbent institutions FinTech solutions present risks and opportunities at the same time. They need to review their business model by focusing on customer-centred banking. For this, it is necessary to ensure an infrastructure and process operation, which requires a change by all means as compared to traditional silotype operations, organised on the basis of functions in a hierarchical structure. During operation, FinTech companies –although supported by the regulator on the open banking side – face numerous risk factors that they need to handle and minimise, as opposed to incumbent institutions, in the case of which regulatory compliance forms an organic part of daily operation. Because of the latter, the majority of customers still trust in incumbent institutions, but there is an increasing number of users who – besides classical banks – also use the products of innovative service providers (E&Y 2019). Cooperation has several benefits for both parties and – accordingly – for financial stability too. There are several FinTech solutions for making regulated bank operation more cost-efficient. Overall, FinTech solutions must be regarded as the challengers of the traditional banking system, which also present opportunities for the financial sector. Adaptation is required on the side of both parties: — 376 —

7.2 The role of the financial system in sustainable development

FinTech companies must face stronger regulations, while banks need to transform their business models, providing an adequate response to the changes occurring in the value chain.

Banks and morals: to be expected but not relied upon? The committee investigating the causes of the subprime mortgage crisis that occurred in the United States in 2007 established that one of the most important developments leading to the crisis was the systemic erosion of moral standards (Financial Crisis Inquiry Commission 2011). Practices that could be at the very least questionable from an ethical point of view were identified on nearly all levels of the financial system. The intermediary agents concentrating on loan volumes and their conflicts of interests, the creditors’ focus on short-term profitability and their high leverage, the securitisation process sometimes based on misleading information, credit rating agencies’ procyclical ratings performed on a limited information base lacking transparency, which were often flawed, the fragmentation of the regulatory system – these phenomena all constitute a basis for the ethical investigation of financial processes (Schoen 2016). The deterioration of ethical standards, however, is not only a characteristic of this crisis. According to experience, during the period of credit boom typically preceding financial crises, financial anomalies are common (Kindleberger-Aliber 2005). Standards become looser in a period of upswing, in which optimism characterising boom periods plays a significant role (“this time is different” – Reinhart – Rogoff 2008), which affects market participants and often regulators too.

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7 The future of money and the money of the future

Chart 7-17: A lesson learnt (?)

Source: courantblogs.com

It is important to assert the aspects of ethical conduct especially in such periods. In a period of credit boom, financial institutions often seek to expand their customer base by introducing innovations, which, at the time they are developed, do not always come into the focus of regulations. Accordingly, the process of innovation – whether it involves variable rate loans or foreign currency denominated loans granted to less wealthy households, or securitisation implying the transformation of cash flows –, during its initial phase, is left to the self-regulation of the sector until regulations catch up with the market. These processes share a commonality that through them financial institutions can generate significant profits in the short term, and competition drives them not to skip such activities (Dancsik – Fábián 2019). Another similarity is that events are viewed completely different during the process, when numerous narratives are available for pushing moral aspects into the background. Although subsequently the moral perception of these issues seems obvious, in the majority of the cases the ex-ante assessment of a bank’s practices is not at all just black or white. The basic idea behind innovations that subsequently prove to be risky at system level is often a completely legitimate market — 378 —

7.2 The role of the financial system in sustainable development

response given to a completely legitimate market demand, which has significant positive results. For example in the USA, due to the disbursement of so-called subprime loans and their distribution by securitisation, millions of poor households typically belonging to some ethnic minority and lagging behind from an economic aspect were able to acquire their own real estate (Gramlich 2007). Many of them could avoid being permanently in default of payment, and are still enjoying the benefits of their loans. Table 7-1: Certain innovations leading to the outbreak of the crisis â&#x20AC;&#x201C; initial idea and morally questionable application Initial idea

Morally questionable application

Credit intermediary

Innovation

Financial institutions need to maintain a branch network to be able to reach their customers, which incurs significant costs. Under certain circumstances it is more efficient to outsource customer acquisition and delegate this activity to intermediaries.

If the intermediary is paid simply on the basis of volume, then it is interested in realising as many loan disbursements as possible. If the intermediary is paid more for riskier loans (e.g. floating rate), then it may even direct customers towards this product for whom other products would be better suited.

Subprime loans

Subprime loan disbursement makes it possible even for poorer households to have access to credit and acquire their own real estate.

In the event of the excessive easing of credit standards even customers can have access to credit in the case of whom disbursement is preceded only by an extremely superficial and sometimes even specifically misleading credit scoring.

Securitisation

Securitisation enables the structuring of cash flows deriving from mortgage loans and the diversification of certain risks. As a result of reducing risks, even institutional investors that only invest in relatively safe financial instruments can be involved in the financing process.

If the company performing securitisation conceals the actual risk of the underlying cash flows, the securities created in this way do not necessarily result in a real reduction of risks and mislead institutional investors.

Credit rating

Credit rating allows investors the possibility of not having to examine the credit risk of each single security or institute, thereby increasing efficiency at sector level.

As the assessed party pays for credit rating, the objectivity of the assessing company and the accuracy of the assessment is not ensured.

Source: MNB.

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During the operation of banks the assertion of ethical aspects is significant both on the micro- and macro-level. The former category is important from the aspect of the fair relationship between the financial institution and the actual debtors, and the relationship between the bank and its local environment in the strict sense. Typically, this category includes banks’ corporate social responsibility policy (CSR) (Lentner et al 2015). At the sectoral level examples of ethical “self-regulation” are the codes of conduct, in which banks undertake commitments going beyond legislative requirements. In Hungary, the Code of Conduct on fair conduct shown towards customers by financial organisations granting retail loans entered into force on 1 January 2010, so it played a role in the mitigation of the consequences of the crisis rather than in preventing the crisis. From the perspective of financial stability, the assertion of banking “ethics” at the macro-level is a more important aspect. Financial institutions should operate in a sustainable manner, which also means that they should pursue a policy which guarantees that the system they form parts of also remains permanently sustainable. This demand, however, may be contrary to the bank’s profit interests if the negative consequences of the bank’s risky and systemically harmful activity occur only years later. Consequently, because of the profit aspect, banks can only be limitedly expected to act in compliance with moral rules going beyond statutory limits and reduce their efficiency. This is true mainly in situations when “moral” behaviour would be expected from the whole of the sector rather than from individual institutions. Excessive lending relevant from the stability of the financial system generally occurs because of the unethical behaviour of numerous operators of the sector rather than just certain institutions. According to Herzog (2017), in order to resolve such situations the participants must overcome three “challenges”:

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7.2 The role of the financial system in sustainable development

– Epistemic challenge: a large majority of bank employees – mainly employed in the operative part of the processes – are not aware of the systemic effects of certain lending practices. They cannot even be expected to do so because of the extremely complex nature of the financial system. In this way, however, when making decisions, bank employees do not consider such “systemic” moral aspects at all. – Motivational challenge: even if bank employees are aware of systemic consequences, they find it difficult to identify with them. While interacting with customers they need to communicate with real people, the systemic effects of certain bank practices can only be observed in statistical summaries. Another motivational problem can be if the remuneration of bank employees is dependent on shortterm efficiency, which encourages them to pay less attention to risks occurring in the long term. – Coordination challenge: today the financial system clearly operates on a global level, so the systemic impact of any bank practices should be hindered at this level, and this obviously represents a challenge to organise. Another problem is that in each case regulators quite rightly watch coordination between financial institutions with suspicion, besides preventing system risks, the coordination of business practices may also be suitable for harming consumers. In light of the above, Herzog (2017) emphasises the role of associations, the members of which are private persons covering a wide range of areas of financial institutions, and their function may be specifically to obstruct practices that are profitable at the individual level but harmful at the system level. It is questionable, however, how successfully these associations can prevent “deserter” behaviour, i.e. that an institution, going against previously established standards, still becomes engaged in a “banned” practice, which is profitable in the short term.

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7 The future of money and the money of the future

In view of this the above study underlines that it is not possible to rely purely on market participants’ self-regulation, rather regulations and the sector’s self-restraint should appear in a complementary and integrated manner. In the years since the crisis the growing role of external regulations could be observed in this respect: significantly more attention is given to consumer protection rules and to ensuring compliance with these via supervision, while financial education and awareness-building (both for consumers and financial institutions) also play a substantially more prominent role as compared to the years before the onset of the crisis. Overall, it can be concluded that by all means banks should be expected to assert ethical aspects, but this should not be relied upon, i.e. it would be unfortunate to presume that banking ethics can take the place of strict regulations. Banking ethics may operate as a brake to slow down the building up of risks in periods of upswing. Against this background, it is especially important that ethical aspects should be covered in education and banking courses, and brought into the focus of organisations consisting of banking experts. However, because of the cyclical narratives fuelled by optimism, regulations play a highly important and unavoidable role in determining future-proof minimum requirements (e.g. by introducing debt cap rules), which can guarantee the stability of the financial system even through the cycle. Box 7-1 What are the risks posed by global climate change to the functioning of the financial system?

Since the beginning of industrialisation, the amount of – anthropogenic – greenhouse gases emitted due to human activity has been continuously increasing, as a result of which global warming has risen by 1.0°C at present as compared to the average temperature in the period between

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7.2 The role of the financial system in sustainable development

1850 and 1900. The most striking effect of the climate change, which can be felt almost everywhere on Earth is the increased occurrence of extreme weather events such as droughts, heat waves, floods and storms. The consequences of the climate change, the frequency and severity of natural disasters may grow further, even in the case of scenarios modelling a global average temperature increase of 1.5–2°C set as an objective of the Paris Agreement (IPCC 2018). Among the participants of the financial sector, climate change has the most direct impact on insurance companies. In the past 40 years, the annual number of natural loss events reported tripled all over the world, while every year for the past decade losses were above the average recorded between 1980 and 2000 (EMDAT 2019). The surge in event frequency and the value of losses causes significant loss to the insurance sector, if by underestimating risks no appropriate reserves are created for the payment of insured losses. Further negative consequences of climate change may include a change in insurance companies’ pricing behaviour, increase in premiums, or even the termination of insurance policies against certain risk exposures, which may reduce the insurance coverage of economic actors. Lower insurance protection may lead to a reduction of the collateral value of real estate and production equipment, which may result in a deterioration in the creditworthiness of companies and households. Underinsurance may also undermine the financing of investments aimed at restoring damage, which, through loss of production, may impair economic performance in the affected region. In the case of significant natural disasters, negative macroeconomic effects may be strengthened so that in order to obtain the financial coverage needed for the payment of large amounts of losses occurring in a short period of time, insurance companies may be forced to sell their investments, which may even result in a reduction in asset prices and an increase in yields (Batten et al. 2016).

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7 The future of money and the money of the future

Chart 7-18: The development of the number of reported natural incidents worldwide Annual number of disasters

Annual number of disasters

450

400

350

300

250

200

150

100

1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2014 2018 Drought Extreme weather Mass movement (dry)

Earthquake Flood Volcanic activity

Extreme temperature Landslide Wildfire

Source: Authors’ own compilation based on EMDAT (2019).

The consequences of climate change present significant physical and transition risks80 to the operation of the banking system. Physical risks directly occur mainly as operational risks, which, because of the loss deriving from extreme weather conditions, may lead to the failure of financial infrastructures (e.g. damage to buildings, power outage, failure of IT systems). At the same time, as natural incidents are becoming more frequent and stronger, they may erode the profitability of bank customers and even reduce the value of their own real estate, the properties used as collateral and their other assets, which through the deterioration of the customers’ repayment ability may lead to an increased credit risk borne by banks. The spillover effects occurring on money and capital markets may

Physical risk is the risk of damage caused by extreme weather events occurring as a consequence of climate change. Transition risk is the risk deriving from transition to a low-carbon economy, the impact of which is significant especially in the case of sudden or unexpected decarbonisation (e.g. imposed by the regulatory authority).

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7.2 The role of the financial system in sustainable development

also influence the financial sector’s market risks through the depreciation of the assets in their balance sheet. A significant reduction in greenhouse gas emissions required in order to curb the rise in global temperature would lead to transition risk, which is unachievable without the rapid and major restructuring of the infrastructure, technology and operating model of the sectors causing the highest emissions. Decarbonisation will be presumably accompanied by radical environmental policy changes (e.g. banning polluting technologies) and market changes (e.g. the large-scale use of electric vehicles), which may result in a surge in the operating expenses of the relevant economic sectors and significant changes in asset prices. The changes in consumer attitudes and the increasing rejection of carbon-intensive technologies may also affect the reputation of financial institutions, if through their investments and lending they finance companies that contribute to global warming. Transition risks may lead to the reduction of bank revenues (impact on cash flows), the depreciation of assets and the withdrawal of funds (impact on balance sheets), which may result in the transformation of banks’ credit, market and liquidity risks (DG Trésor 2017).

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7 The future of money and the money of the future

TRANSITION RISK

FINANCIAL RISK

PHYSICAL RISK

Chart 7-19: The impact of physical and transition risks posed by climate change on banks Acute climate events

Chronic climate shifts

Impact on balance sheets

Credit risk

Impact on cache flow

Market risk

Liquidity risk

Impact on balance sheets

Climate policies

Impact on bank’s functioning

Technological changes

Operational risk

Impact on cache flow

Reputation

Market changes

Source: Authors’ own compilation based on DG Trésor (2017).

The enhanced financial risks related to climate change make it necessary for financial institutions, regulatory and supervisory authorities and central banks to increasingly address climate change issues. Successful adaptation makes it essential to change risk perception and management practices and corporate governance principles in the entire financial sector.

How can banks contribute to managing ecological risks? The previous subchapter dealt comprehensively with the risks that global climate change posed to the financial system. In this field, the primary and most urgent task of financial institutions is to understand — 386 —

7.2 The role of the financial system in sustainable development

and identify the effects of climate change on their own operation. Currently the vast majority of banks do not deal substantively with climate change. In the spring of 2019, the Magyar Nemzeti Bank conducted a survey among Hungarian credit institutions in order to explore the institutions’ risk perception and risk management practices in connection with climate change. Although 92 per cent of the 23 banks that completed the survey – representing 77 per cent of the balance sheet total of the domestic banking system – find that climate change is a relevant risk, only 13 per cent of them have already identified risks related to the climate change within the 3 to 5-year time horizon of their business planning period. The rest of the banks consider climate change a risk they do not need to deal with, because it is only relevant over a longer time horizon or it is not yet measurable. A survey conducted by the Bank of England covering 90 per cent of the bank sector came to a similar conclusion as the Magyar Nemzeti Bank survey (Bank of England 2018). Chart 7-20: The proportion of banks in Hungary that consider climate change as a relevant risk within the time horizon of their business planning

30%

13%

87%

39% 4% 4%

Identified climate-related risks Risk relevant, but difficult to measure Risk relevant beyond the business planning horizon Risk not relevant Risk relevant, but doesn’t have the capacity to analyse No answer

Source: MNB.

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In April 2019, the Bank of England was the first regulatory authority in the world to set expectations for the institutions it supervises concerning the management of risks related to climate change. The recommendation prepared as a result of public consultation attempts to strengthen the role the British banking system plays in addressing risks related to climate exchange along four themes: corporate governance, risk management framework, scenario analysis and financial disclosures (Bank of England 2019a). The better understanding and more efficient management of the financial risks of climate change can be facilitated by banks incorporating considerations related to the financial risks deriving from climate change in their corporate governance system. As a result of this, senior management can monitor the development of these risks and address them, while in the course of determining risk appetite they can take into consideration long-term risks going beyond the institutionâ&#x20AC;&#x2122;s business planning time horizon. Climate change considerations should be included in the risk management framework in accordance with the risk appetite accepted by senior management. The framework set up should be suitable for identifying, measuring and monitoring risk exposure, and for laying the foundations for measures aimed at the mitigation and management of risks. In order to inform the management of the institution, climate risk considerations should also form an integral part of the management information system. Institutions should also assess short- and long-term risks of climate change in the form of scenario analyses and stress tests. In addition to facilitating the identification of the vulnerabilities and the assessment of resilience to shocks, scenario analysis may also efficiently contribute to determining the business strategy and the risk tolerance policy. Through their application, it is possible to test the feasibility of measures aimed

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at the reduction and management of risks, as well as their consistency with regulatory expectations. Pursuant to the CRR81, banks already have certain disclosure obligations concerning their significant risks. Financial institutions need to consider extending the information disclosed by them in order to increase transparency in relation to the management of climate risks. When determining the disclosure requirements relating to climate change risks, the guidelines of several organisations (e.g. the Financial Stability Board combined with the G20’s supervisions and central banks82) published in recent years can be transposed (Bank of England 2019b). Besides risks, global climate change and the transition of the regulatory environment and consumer attitudes also present business opportunities for financial institutions. Decarbonisation, which means transition to “green” technologies with low greenhouse gas emissions, requires a significant increase in the volume of public and private investments, and the rechannelling of funding sources towards lowemission infrastructures, buildings and services. According to EIB (2016) estimates, in the EU annual infrastructural investments should be more than doubled as compared to the current level of EUR 258 billion per year in transport, water and waste management and energy sectors alone, in order to achieve sustainability and climate protection goals.

Regulation (EU) No 575/2013 of the European Parliament and of the Council of 26 June 2013 on prudential requirements for credit institutions and investment firms 82 https://www.fsb-tcfd.org/publications/final-recommendations-report/. 81

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Chart 7-21: Annual investment needs in the EU in order to achieve sustainable development goals EUR Billions

EUR Billions

100

130

Energy

Water & Waste

Transport

50 Current

100

150

200

250

Required

Source: Authors’ own compilation based on EIB (2016).

The banking system has an indispensable role in financing investments and channelling funds into a “green” direction. The green financial segment serving sustainability goals and financial product innovation related to it has been through an explosive development in recent years. The supply of and demand for green deposits, bonds, loans and investment funds is expanding dynamically as an increasing number of economic actors commit themselves to addressing climate change and realise the business potential therein. The Green Program83 launched by the Magyar Nemzeti Bank in February 2019 is aimed at facilitating the Hungarian financial intermediary system to support environmental sustainability substantially more powerfully than now.

https://www.mnb.hu/en/supervision/green-program

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References Álvarez, J. M. – Deblas, C. – Izquierdo, J. F. – Rubio, A. – Zurita, J. (2017): The impact of European banking consolidation on credit prices. BBVA Working paper series No. 17/08, 2017. Arner, D. W. – Barberis, J. – Buckley, R. P. (2015): 11. Retrieved from https://www.researchgate. net/publication/313365410_The_Evolution_of_Fintech_A_New_Post-Crisis_Paradigm Bain, J. S. (1956): Barriers to New Competition: Their Character and Consequences in Manufacturing Industries. Harvard University Press. Bank of England (2018): Transition in thinking: The impact of climate change on the UK banking sector. Bank of England Prudential Regulation Authority, London. https:// www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/report/ transition-in-thinking-the-impact-of-climate-change-on-the-uk-banking-sector. pdf?la=en&hash=A0C99529978C94AC8E1C6B4CE1EECD8C05CBF40D Bank of England (2019a): Avoiding the storm: Climate change and the financial system. Speech given by Sarah Breeden, Bank of England, London. https://www.bankofengland.co.uk/-/media/ boe/files/speech/2019/avoiding-the-storm-climate-change-and-the-financial-system-speechby-sarah-breeden.pdf?la=en&hash=AC28DFEFED7B14A197E6B0CB48044D06F4E38E84 Bank of England (2019b): Supervisory Statement SS3/19, Enhancing banks’ and insurers’ approaches to managing the financial risks from climate change. Bank of England Prudential Regulation Authority, London. https://www.bankofengland.co.uk/-/ media/boe/files/prudential-regulation/supervisory-statement/2019/ss319. pdf?la=en&hash=7BA9824BAC5FB313F42C00889D4E3A6104881C44 Batten et al. (2016): Let’s talk about the weather: the impact of climate change on central banks. Staff Working Paper No. 603. Bank of England, London. https://www.bankofengland.co.uk/-/ media/boe/files/working-paper/2016/lets-talk-about-theweather-the-impact-of-climate-changeon-centralbanks.pdf?la=en&hash=C49212AE5F68EC6F9E5AA71AC404B72CDC4D7574. Beck, T. – Demirgüç-Kunt, A. – Levine, R. (2006): Bank concentration, competition, and crises: First results. Journal of Banking and Finance, Vol. 30, Issue 5, pp. 1581–1603. Bhaskar, P. V. (2013): Financial inclusion in India–an assessment. Speech at the MFIN and AccessAssist Summit, New Delhi, https://www.bis.org/review/r131211h.pdf Bossert, O. – Desmet, D. – McKinsey. (February 2019). www.mckinsey.com. Retrieved May 2019, https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-platformplay-how-to-operate-like-a-tech-company Brune, L. – Giné, X. – Goldberg, J. – Yang, D. (2016): Facilitating Savings for Agriculture: Field Experimental Evidence from Malawi. Economic Development and Cultural Change 64 (2): 187–220.

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7 The future of money and the money of the future Dancsik B. – Fábián G. (2019): Amikor nem elég az erkölcs: az állami beavatkozás szerepe a “fair” bankrendszer kialakításában (When morals are not enough: the role of state interventions in the development of the “fair” banking system). In György Kocziszky (ed.): Etikus közgazdaságtan (Ethical Economics). Magyar Nemzeti Bank, Budapest, pp 247–275. Davies, R. – Tracey, B. (2014): Too Big to Be Efficient? The Impact of Implicit Funding Subsidies on Scale Economies in Banking. Journal of Money, Credit and Banking, Vol. 46, Issue 1, pp. 219-253. De Bondt, G. (2002): Retail Bank Interest Rate Pass-Through: New Evidence at the Euro Area Level. European Central Bank, Working Paper Series, April, No. 136. De Graeve, F. – De Jonghe, O. – Vander Vennet, R. (2007): Competition, transmission and bank pricing policies – Evidence from Belgian loan and deposit markets. Journal of Banking Finance, Vol. 31, Issue 1, January, pp. 259–278. De Nicoló, G. – Bartholomew, P. – Zaman, J. – Zephirin, M. (2004): Bank consolidation, internalization, and conglomerization. Working Paper No. 03/158, IMF. Deloitte (2016): A temporary phenomenon? Marketplace lending. Retrieved from https://www2. deloitte.com/content/dam/Deloitte/uk/Documents/financial-services/deloitte-uk-fsmarketplace-lending.pdf Demirguc-Kunt, A. – Klapper, L. (2012): Measuring financial inclusion: The global findex database. The World Bank. http://siteresources.worldbank.org/EXTGLOBALFIN/ Resources/8519638-1332259343991/Findex_G20_09272012.pdf Demsetz, H. (1973): Industry Structure, Market Rivalry, and Public Policy. Journal of Law and Economics, Vol. 16, No. 1, April, pp. 1–9. DG Trésor (2017): Evaluating Climate Change Risks in the Banking Sector. Directorate General of the Treasury (with support from the Banque de France and the Prudential Supervisory and Resolution Authority). https://www.tresor.economie.gouv.fr/Ressources/File/447123 Dhar, V., & Stein, R. M. (2017): FinTech Platforms and Strategy. MIT Sloan School Working Paper 5183-16, 3-5. Retrieved June 2019 https://papers.ssrn.com/sol3/papers.cfm?abstract_ id=2892098## Dupas, P. – Robinson, J. (2013): Savings Constraints and Microenterprise Development: Evidence from a Field Experiment in Kenya. American Economic Journal: Applied Economics 5 (1): 163–92. E&Y. (2019): Global FinTech Adoption Index 2019 As FinTech becomes the norm, you need to stand out from the crowd. https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/bankingand-capital-markets/ey-global-fintech-adoption-index.pdf EBA (2018): EBA report on the impact of fintech on incumbent credit institutions’ business models. London: EBA https://eba.europa.eu/documents/10180/2270909/Report+on+the+impact+of+Fintech+on+incumbent+credit+institutions%27%20business+models.pdf ECB (2017): Financial Integration in Europe, Special Feature: Cross-border Bank Consolidation in the Euro Area. May.

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7.2 The role of the financial system in sustainable development ECB (2018): Financial Stability Review, Special Features: How can euro area banks reach sustainable profitability in the future? November. EIB (2016): Restoring EU competitiveness. European Investment Bank, Luxembourg. https://www. eib.org/attachments/efs/restoring_eu_competitiveness_en.pdf EMDAT (2019): OFDA/CRED International Disaster Database. Université catholique de Louvain – Brussels – Belgium. https://ourworldindata.org/natural-disasters#number-of-reported-disasterevents ESRB (2014): Is Europe Overbanked? Reports of the Advisory Scientific Committee, No. 4, June. Financial Crisis Inquiry Commission (2011): The Financial Crisis Inquiry Report. FSB. (2017): Financial Stability Implications from FinTech: Supervisory and Regulatory Issues that Merit Authorities’ Attention. FSB. https://www.fsb.org/wp-content/uploads/R270617.pdf FSB. (2019): FinTech and market structure in financial services: Market developments and potential financial stability implications. https://www.fsb.org/wp-content/uploads/P140219.pdf Gambacorta, L. (2005): Inside the Bank Lending Channel. European Economic Review, Vol. 49, Issue 7, October, pp. 1737–1759. Gambacorta, L. (2008): How do banks set interest rates? European Economic Reviews, Vol. 52, Issue 5, July, pp. 792–819. Gramlich, E. (2007): Booms and Busts: The Case of Subprime Mortgages. Federal Reserve Bank of Kansas City Hannig, A. – Jansen, S. (2010): Financial inclusion and financial stability: Current policy issues. https://www.adb.org/sites/default/files/publication/156114/adbi-wp259.pdf Havranek T. – Irsova Z. – Lesanovska J. (2015): Bank Efficiency and Interest Rate Pass-Through: Evidence from Czech Loan Products. Czech National Bank, November, Working Paper Series, 9. Herzog (2019): Professional Ethics in Banking and the Logic of “Integrated Situations”: Aligning Responsibilities, Recognition, and Incentives. Journal of Business Ethics 156 (2) pp 531-543 IPCC (2018): Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. World Meteorological Organization, Geneva, Switzerland. https://www. ipcc.ch/sr15/ Jack, W. – Suri, T. (2014): Risk Sharing and Transactions Costs: Evidence from Kenya’s Mobile Money Revolution. American Economic Review 104 (1): 183–223.

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7 The future of money and the money of the future Khan, H. R. (2011): Financial inclusion and financial stability: are they two sides of the same coin? Address by Shri HR Khan, Deputy Governor of the Reserve Bank of India, BANCON 2011, the Indian Bankers Association and Indian Overseas Bank, Chennai, 4 November 2011. https:// www.bis.org/review/r111229f.pdf Kindleberger, C. P. – Aliber, R. Z. (2005): Manias, Panics, and Crashes. A History of Financial Crises. John Wiley & Sons, Hoboken, New Jersey. Lentner Cs. – Szegedi K. – Tatay T. (2015): Társadalmi felelősségvállalás a bankszektorban (Social responsibility in the banking sector). Pénzügyi Szemle 2015/1 pp 96–104. McKinsey (2016): Bracing for seven critical changes as fintech matures. https://www.mckinsey.com/ industries/financial-services/our-insights/bracing-for-seven-critical-changes-as-fintech-matures Mehrotra, A. N. – Yetman, J. (2015): Financial inclusion-issues for central banks. BIS Quarterly Review March. https://www.bis.org/publ/qtrpdf/r_qt1503h.pdf MNB (2014): Átalakulóban a magyar bankrendszer (Hungarian banking system in transformation): Vitaindító a magyar bankrendszerre vonatkozó konszenzusos jövőkép kialakításához (A keynote paper for developing a consensus-based vision for the Hungarian banking system). MNB Occasional Papers. Omarini, A. E. (2018, August): Banks and Fintechs: How to Develop a Digital Open Banking. International Business Research, Vol. 11 (No. 9; 2018), 27. Retrieved June 2019, from https:// www.researchgate.net/publication/326959594_Banks_and_Fintechs_How_to_Develop_a_ Digital_Open_Banking_Approach_for_the_Bank’s_Future Prasad, E. S. (2010): Financial sector regulation and reforms in emerging markets: An overview (No. w16428). National Bureau of Economic Research. https://www.nber.org/papers/w16428 Prina, S. (2015): Banking the Poor via Savings Accounts: Evidence from a Field Experiment. Journal of Development Economics 115 (July): 16–31. Reinhart, C. M. – Rogoff, K. S. (2008): This Time is Different: a Panoramic View of Eight Centuries of Financial Crises. NBER Working paper, No. 13882. NBER. Schaeck, K. – Čihák, M. – Wolfe, S. (2006): Are More Competitive Banking Systems More Stable? Working Paper, No. 06/143, IMF. Schoen, E. J. (2016): The 2007–2009 Financial Crisis: An Erosion of Ethics: A Case Study. Journal of Business Ethics 146 (4) pp 805–830. Suri, T. – Jack, W. (2016): The Long-Run Poverty and Gender Impacts of Mobile Money. Science 354 (6317): 1288–92 Uhde, A. – Heimeshoff, U. (2009): Consolidation in banking and financial stability in Europe: Empirical evidence. Journal of Banking & Finance, Vol. 33, Issue 7, pp. 1299–1311. World Bank (2018): UFA2020 Overview: Universal Financial Access by 2020. https://www. worldbank.org/en/topic/financialinclusion/brief/achieving-universal-financial-access-by-2020

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8.1

The current state and the future of globalisation Álmos Telegdy

Globalisation is driven by changes in companies’ costs. In the first period of human history transport costs were high, and for this reason production and consumption were concentrated at the same place. The invention of the steam engine significantly reduced transport costs, and the volume of foreign trade started to increase. This marked the beginning of the first wave of globalisation, which lasted – with minor interruptions – until the end of the 20th century. With the emergence of information and communication technologies (ICT), communication costs also started to decline. This enabled companies to coordinate their complex production structures across country borders, and to take advantage of local benefits (primarily cheap labour). This led to the development of global value chains, and a large proportion of industrial production was relocated to emerging countries. This was the second wave of globalisation. The third wave of globalisation started in the last decade and is characterised by two phenomena. On the one hand, new information and communication technologies cut down the costs of physical presence, and some services can be accessed from great distances. This has led to the expansion of service exports. On the other hand, emerging countries are now consuming significantly more than in the past, which reduces total exports (as now a higher proportion of locally produced goods are consumed within the producing countries) and increases trade between developing countries. Starting from the nineties, in line with the development of ICT, companies set up cross-border production chains to better exploit local benefits, primarily cheap labour. This resulted in the development of international value chains, — 397 —

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which would not exist without globalisation and modern communication technologies. In the third wave of globalisation, however, it is not only cheap labor that determines the location choice of companies. The presence of skilled labour, the existence of the necessary know-how in the economy, the proximity of product markets and the availability of raw materials all became very important factors for the companiesâ&#x20AC;&#x2122; location decisions. The participation of a company in global value chains or the exposure of a whole country to these also entail considerable risks. Complex production links lead to increased risks, which may cause disruptions in production and make costs volatile. The presence of global production chains in a country increases the probability and strength of the spill-over of external shocks. Due to global production chains, multinational companies have gained considerable market power, which may increase prices and raise further entry barriers to new companies.

What is the driving force behind globalisation? The first wave of globalisation was induced by the technological revolution in the 18th to 19th century, which drastically reduced transport costs. Although today we find it natural that most of the goods we consume come from other countries or even from other continents, in the first ten thousand years of human history people obtained most of their consumption from their immediate neighbourhood. Transportation costs were so high that the vast majority of production and consumption inevitably took place within the same geographical proximity. This changed at the turn of the 18th and 19th century, when in 1769 Scottish inventor James Watt developed a model of the steam engine also suitable for industrial purposes. Forty years later, in 1807, Robert Fulton, inventor and painter (!) used this steam engine to drive a ship. The wide use of steamboats led to the rapid reduction of

â&#x20AC;&#x201D; 398 â&#x20AC;&#x201D;

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transportation costs,84 which marked the beginning of the first wave of globalisation. In the following 170 years, globalisation was fuelled by the considerable decrease in transportation costs. During this period the volume of foreign trade mostly increased, and only protectionist regulations could slow down or temporarily reverse this tendency. Chart 8-1: Export to GDP, 1828–2014 30

Per cent

30 25

0 1828 1835 1842 1849 1856 1863 1870 1877 1884 1891 1898 1905 1912 1919 1926 1933 1940 1947 1954 1961 1968 1975 1982 1989 1996 2003 2010

Note: The graph presents the ratio of exports to GDP. Source: Ortiz-Ospina et al. (2018).

The protectionist economic policy between the two World Wars suppressed international trade and the world’s exports to GDP ratio dropped from 14 per cent in 1913 to 6 per cent in 1938. After World War II, however, foreign trade started to grow again, slowly at the beginning, and then faster from 1970, and the export to GDP ratio reached 15 per cent by 1990. In this period the reason behind trade 84

Between 1740 and 1820, for example, the real transportation cost of a ton of coal was around 12 shillings along the route between Northern England and London, which continuously reduced after 1820 and had decreased to 3 shillings by the turn of the century (Harley, 1988).

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expansion was the same as in the 19th century: transportation costs continued to decrease (Box 8-1) and regulations also contributed to the expansion of foreign trade. Increasing efficiency in transportation led to the separation of production and consumption. Production was concentrated in a few developed industrial countries, which supplied the whole world with products: in 1990, the G7 countries accounted for approximately twothirds of total exports (Baldwin 2016). This resulted in large inequalities between countries, when the per capita GDP of “Western” countries increased by multiple times of that of other countries in the 19th to 20th century. Box 8-1 Standardized containers reduced trade costs

The standardized shipping container was developed by Malcolm Lean, an American transport entrepreneur and company manager. He wanted to create a method of transport which is durable, provides physical protection and also protects the cargo against theft, and makes loading easier due to its standard size. The very first version of today’s containers was made in 1955 and met all the above conditions. The company was enormously successful, as the containers shortened loading time so much that the normal loading rate at the time, 1.3 tons per hour, increased to 30 tons per hour. It also contributed to considerable cost reductions as port workers could not steal the cargo. As a consequence, Lean could offer a 25 per cent price reduction relative to other shipping companies. Obviously, the trade union of dockers was against the wide use of the containers as they made it unnecessary to employ such a large number of workers. However, the expected profits generated by introducing the containers were so high that companies could pay high severance payments to dismissed workers, which broke their resistance.

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Container transport spread very rapidly: while in 1966 only 1 per cent of countries had ports suitable for accepting containers, by 1983 this proportion grew to 90 per cent. Today the loading of a ton of goods costs USD 0.16 (it cost USD 5.86 in 1956), and there are approximately 20 million containers all over the world, which make about 200 million journeys per year. Source: Discover Containers.

Around 1990, besides the decline of transport costs, the unprecedented development of information and communication technologies (ICT) multiplied computing capacities and made data storage and communication very cheap. Communication and information tools (Chart 8-2) had a great impact both on production technologies via robotization and on coordination costs. This created the conditions for the emergence of complex production structures. Cheap intercontinental communication opened up new opportunities for manufacturing companies. Until then they typically carried out production in their own country, or in another developed country which was geographically close. But now they had the opportunity to take advantage of cheap labour in emerging countries and move the labourintensive processes of their production (not requiring a lot of skill) to these countries. At the end of the 20th century, the trade of China, India, Indonesia and some other emerging countries had increased because by that time they produced about one-fifth of the global manufacturing output, due to huge capital investments by developed countries.

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Chart 8-2: Use of the internet, mobile phones and social media in the world

Internet

Mobile phone

Social media

53%

68%

42%

Note: The chart shows how widely different means of communication were used in the world in January 2018. Source: McDonald (2018).

New technologies made it possible to create a new economic structure, the international value chains. These, following the globalisation of the consumption of goods, also globalised production (this is discussed in the third part of this chapter in detail). International value chains perform different phases of production in different companies (and countries), always taking advantage of the benefits of the given country. For example, they moved labour-intensive activities to emerging countries, while they kept activities requiring expertise in developed countries. This also led to a significant change in the nature of trade. While in the first wave of globalisation raw materials and finished goods usually constituted a major part of exports, in the second wave semi-finished goods flowed from one country to another, in between the different work phases. The globalisation of production could not have taken place without the globalisation of financial markets that funded the companiesâ&#x20AC;&#x2122; foreign subsidiaries. This process accelerated in the 1980s, and it facilitated global capital flows. Sometimes the excessive volatility of this caused imbalances, but altogether it accelerated the growth of the world economy. In 1995, foreign assets accounted for 51 per cent of global GDP, which increased to 185 per cent by 2007. This proportion dropped in the aftermath of the financial crisis, but in 2016 it returned to its preâ&#x20AC;&#x201D; 402 â&#x20AC;&#x201D;

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crisis levels (IMF Balance of Payments database). An increasing part of these foreign assets is foreign direct capital investment, which is one of the drivers of the growth of global value chains. Chart 8-3: The waves of globalisation were caused by cost changes PRE-GLOBALIZATION: ...−1820 • Trade costs, Communication, Personal presence • Production and consumption in the same place

FIRST WAVE: 1820−1990 • Trade costs, Communication, Personal presence • Trade takes place in a few countries, consumption globalises SECOND WAVE: 1990−2008 • Trade costs, Communication, Personal presence • Productions globalises, emergence of global value chains THIRD WAVE: 2008−? • Trade costs, Communication, Personal presence • Services globalize

Note: red = high costs; green = low costs. Source: Baldwin (2016).

Globalisation is therefore fuelled by the companies’ pursuit of profit, and their opportunities are determined by the costs they incur: transportation costs, communication costs and the costs of being physically present. Chart 8-3 illustrates that in the first period of human history all these costs were high, so production and consumption took place at the same location. After steamboats appeared, transportation costs decreased rapidly, and the most efficient nations took over a large part of goods production. In the second wave of globalisation communication costs declined, which enabled more complex while cost-efficient forms of production. Currently we are witnessing that services – which have been subject to physical presence so far – have started to become global as the costs of being physically present and the costs of communication have fallen (this will be discussed in the following chapter in detail). — 403 —

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The second wave of globalisation reduced income disparities between countries, as it increased the living standards for a wider set of countries more so than the first wave, from which only developed countries could benefit. The relocation of production to certain emerging countries led to an increase in these countries’ per capita GDP and reduced the companies’ labour costs. Other reasons behind the growth of prosperity included increased competition, which forces companies to increase their cost-efficiency and their innovation activities as otherwise they would be forced out of the market and go bankrupt. In addition, companies that join international markets can grow more rapidly, and so they can benefit of economies of scale, i.e. they become more efficient. The acquisition of machines, equipment and intermediate products from the international market also reduces the costs of inputs and capital goods, and it may increase their quality. International relations may launch learning processes concerning modern technologies and efficient business organisation, which may also lead to productivity increases (Ortiz-Ospina 2018). Those entrepreneurs will be successful, who have been able to connect their companies to global value chains and keep up with global competition. Cost reductions, strong competition and the increasing efficiency of companies will lead to price reductions on the consumer markets, which will increase welfare. However, globalisation also makes some worse off. The largest group is represented by workers of developed and middle-income countries, who have lost their jobs as a result of companies relocating their production to emerging countries. For example, in the United States the wages of production workers did not increase at all between 1990 and 2005, while in positions requiring at least a college degree wages increased by 24 per cent (Autor–Dorn 2013). Robotization has also endangered the jobs of production workers in the last thirty years, as new technologies could be applied primarily in industrial production. Another large group on the losing side is formed by the owners of small and medium-sized enterprises who were not able to join global product chains and were unable to survive the international competition of well-capitalised large multinational companies. These companies — 404 —

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do not enjoy the benefits of globalisation, but they have to compete with companies that are able to take advantage of the cost-efficient production methods of the new economic system.

What characterises the third wave of globalisation? Technological development and the changes entailed by it may lead to a new third wave of globalisation. A digital space has emerged, which has resulted in a number of changes. It is becoming easier to make personal contact even across large geographical distances, and as a result many services are now accessible remotely. Furthermore, information can be collected globally, and it is more and more valuable as large databases need to be set up for numerous products and services. Consumer habits are also changing, and people tend to buy experience (i.e. services) rather than products (Chart 8-4). Chart 8-4: The impacts of new technologies and the changing of habits

Personal presence from distance Remote access to services Global information gathering Experience based economy Source: Authorâ&#x20AC;&#x2122;s own compilation.

The first wave of globalisation was characterised with goods trade becoming international, in the second wave global value chains emerged, which also involved capital in international circulation, while in the third wave the development of information and communication technologies make information one of the most important production factors, and services become global (Chart 8-5). â&#x20AC;&#x201D; 405 â&#x20AC;&#x201D;

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Chart 8-5: Changes in the nature of globalisation XXI. CENTURY XX. CENTURY

SERVICES

GOODS LABOR CAPITAL

INFORMATION

Source: Author’s own compilation.

The change of globalisation has is visible. Although the total value of global exports has increased, its ratio to GDP has been stagnating since the financial crisis, despite that global economy has experienced one of the longest growth periods (Chart 8-6). In foreign trade the weight of services is continuously rising as opposed to that of products. Chart 8-7 shows that while between 2007 and 2017 the export of products increased by 2.4 per cent per year on average, the export of services expanded by 3.9 per cent. Although the growth rate of services is high in statistics, it is still lower than their real share in exports, as it is probably underestimated in statistics (Box 8-2). Box 8-2 The value of services is underestimated in statistics

According to an analysis by McKinsey (2019), the export of services that do not appear on national accounts amounts to 8.3 trillion dollars per year. Half of this value remains completely hidden from traditional statistics, and the other half is recorded in the accounts under products. This is attributable to the following reasons:

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1) Some exported products also contain services. About half of the value of a telephone is represented by the software running on it, and a large proportion of the value of the device also derives from innovation. 2) Services delivered across a multinational companyâ&#x20AC;&#x2122;s different locations are not recorded in statistics. A considerable part of the value of premium products lies in marketing and the trade name rather than in the product itself. 3) Internet services provided free of charge, such as video sharing or email services, constitute a significant value for consumers. Chart 8-6: Export to GDP ratio, 2000-2017 31

Per cent

31 30

Third wave

29 Second wave

28 27

27 Financial crisis

26 25

Source: World Bank Data.

â&#x20AC;&#x201D; 407 â&#x20AC;&#x201D;

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

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Chart 8-7: Growth rate of the export of services Total goods 2.4% Total services 3.9%

Export growth 2007â&#x20AC;&#x201C;2017

ICT 7.8% Business services 5.3% Intellectual property charge 5.2% Tourism 3.7% Finance 3.2% 1.7% Note: increase in exports: the average annual growth rate of a given activity between 2007 and 2017. Tourism: travel arrangements. Source: McKinsey (2019).

Foreign trade patterns have changed not only among industries, but also among groups of countries in favour of emerging countries (Chart 8-8). While in the nineties half of global trade took place between developed countries, and only 13 per cent was realised among emerging countries, now the two country groups have similar shares (29 per cent). Meanwhile, the weight of trade between emerging countries and developed countries has not changed. This also indicates the increasing role of emerging countries in world economy.

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Chart 8-8: The share of emerging and developed countries in world trade 29% Emerging

Emerging 13%

23%

19%

20%

19%

48% Advanced

Advanced 29%

Export share 1995 Export share 2014

Source: Ortiz-Ospina et al. (2018).

There are two reasons behind the structural transformation of global trade: one of them is demand, while the other is again technology. If we understand these two factors, we can find an explanation to the increasing weight of services and the surge in exports between emerging countries. The reason related to demand lies in the increase of the weight of emerging countries in world economy and their internal consumption. These countries consume more of their production within their borders than in the past and so, they sell less abroad. At the same time, emerging countries have developed their own local value chains and partly use these instead of global value chains, which also reduces the proportion of exports. The increasing weight of services is primarily due to the development of information and communication technologies. Communication and data transmission technologies have developed so much in recent years that now, besides the possibility of offshoring production to other â&#x20AC;&#x201D; 409 â&#x20AC;&#x201D;

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countries, even the persons who provide and receive services can be in different countries. In the case of digital services, the physical presence of the service provider is not necessary. These include, for example, audio-visual products, financial services, telecommunication, software production, telephone helpdesk services, etc. In 2014, 54 per cent of the services exported by the United States were suitable for digital use (UNCTAD 2017). In the future, an increasing number of services will be suitable for digital transmission, and so low-income countries will export them (“telemigration”). There are many jobs even now that can be done such that an individual performs tasks as an entrepreneur, without meeting the person he or she is working for. Some services require high quality infrastructure, but the emergence of the 5G network may provide significant support in this respect. Many tasks, on the other hand, can be performed remotely by small businesses, like certain office activities, some of which require high-level qualifications (financial consultancy, engineering design), and some of which are easy to learn (data entry, word processing). Communication and search costs are significantly reduced by new platforms created to connect employees and job providers on the global market. These platforms can also generate trust between two strangers, as even payment for the work is realised through them and so it makes certain that workers will be paid when the work is completed. Currently, access to this market is restricted by the lack of knowledge of foreign languages (communication is essential here as opposed to manufacturing). Therefore, global services are provided by the residents of countries where English is widely spoken.85 Modern translator devices, however, will offer a solution for this problem for some of the services, and language barriers will soon be removed.

Presently, a quarter of online employees are Indian, another quarter of them are from Pakistan and Bangladesh, and one-eighth of them are citizens of the United States or the United Kingdom (iLabour Project).

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In addition to low labour costs, local businesses have additional benefits from employing telemigrants. These employees are not subject to national regulations, so they can be easily and costlessly dismissed (in practice they appear as entrepreneurs on the labour market). The globalisation of services will most certainly trigger changes on a much wider scale than the second wave of globalisation when industrial production became globalised. This remains true notwithstanding the fact that the robotization and globalisation of industrial production also made a huge difference in people’s everyday life. In addition to positive welfare impacts (products have become cheaper) certain groups – primarily skilled workers – lost their jobs and faced reducing wages. Although these changes also generated enormous problems, the globalisation of services will trigger changes on a much wider scale than the globalisation of product markets. There will be a greater change firstly because industrial employment made up about 20 per cent of all workers, while a much larger proportion works in the service sector in developed countries (Baldwin 2019). Secondly, some industrial workers were able to find a job after retraining and taking up work the service sector. If an increasing proportion of services are performed on the global market by employees of other countries, the employees of developed countries with high wages will not have alternative job options. This problem is exacerbated by the fact that both globalisation and robotization displace labor and they go hand in hand, i.e. they substitute the same type of labour. A few years ago machines could yet not perform tasks that required the processing of complex patterns (driving or cleaning) and communication with people (for example tasks performed by call centres). The widespread use of artificial intelligence (which was induced by high calculating power and huge databases) enables machines to do such work without human intervention (Brynjolfsson – McAfee 2016).86 86

Obviously we cannot know for sure what processes the third wave of globalisation will launch. Price reductions may result in an increase in consumer demand for services that cannot be performed by robots or cannot be outsourced to other countries. But it is highly likely that the labour market is facing great changes.

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The losers of globalisation need help to become integrated in the new economic system and find jobs. Through low prices and diversified products globalisation has enhanced consumer welfare, but many employees lost their jobs due to staff reductions caused by robotization and foreign competition. In response to general discontent, in recent years national governments have started to protect their internal market from foreign goods by introducing protective tariffs and non-monetary sanctions. We cannot be certain, however, that this is the best way to support the losers of globalisation. A trade war may have a negative impact even on the country imposing tariffs, and global value chains may exacerbate this impact or export it to other countries. Berthou et al. (2018) analyse a hypothetical situation in which all states introduce a 10 per cent tariff and find that it may result in a decline in GDP by as much as 3 per cent in a period of three years. The direct impact of the tariffs will be an increase in the price of imported products both for companies and for households and customers will stop buying imported goods and will rather buy domestic products. This impact may increase national GDP, but only if the given foreign and domestic products are similar to each other. On the other hand, the increase in prices will increase households’ costs, so they will consume less, which will reduce GDP. The third impact will affect the economy through intermediate products: if intermediate products become more expensive, companies will be forced to make their final products more expensive too, which will reduce demand and – ultimately – GDP. Furthermore, even the quality of the products may decline if, on the domestic market, companies are unable to buy the same intermediate product that they have imported thus far. In addition, companies may even postpone their investments if protective tariffs make the economic environment more uncertain, which raises interest rates.

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What happens to global value chains in the third wave of globalisation? In the second and third wave of globalisation, international trade companies mainly sell intermediate products rather than products intended for consumption, which will be used at a later point by a different company during its production process. For example, in 2016 intermediate products accounted for 47 per cent of the total exports of the European Union and 57 per cent of its imports, while consumer products accounted for about 21 per cent (Eurostat 2019).87 Although trade between companies is not a new phenomenon, due to the development of ICT, companies have created much longer cross-border production chains to exploit local opportunities â&#x20AC;&#x201C; such as cheap labour and local knowledge. This is how global value chains (GVC) developed which was made possible by globalisation and modern communication technologies. GVCs, however, had an impact themselves on globalisation by generating a large proportion of international trade, and in the form of higher wages they brought welfare for the workers of emerging countries. Contrary to common belief, in the third wave of globalisation it is not only cheap labour that plays a role in the geographical location of companies. While between 1995 and 2005 trade between low-wage and high-wage countries increased continuously as the companies of developed countries moved their production to emerging countries, McKinsey (2019) finds that this trend came to a halt and did not increase any further. In the period between 2005 and 2017 the proportion of exports induced by low labour costs was only 18-19 per cent.88

87 88

Most of the remaining part is made up of capital goods. Exports induced by low labour costs are defined such that wages in the exporting country are at least five times lower than in the receiving country. If wage costs differ by a factor of two, the share of exports is still only 30 per cent (the exports of agricultural, mining and energy products were not used in this analysis, as the location of the production of such products is determined by nature).

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Consequently, in the third wave of globalisation, companies do not only consider cheap labour when making the decision to move their production abroad, but they consider other aspects too. Skilled workers, the existence of the necessary knowledge in the economy, proximity to product markets and the accessibility of raw materials are also becoming important. The most important change occurring in global value chains in the third wave of globalisation will be the increasing significance of the role of knowledge. This will profoundly affect international trade. As a large proportion of the value added is generated at the beginning of the supply chain (R&D, planning) and at its end (marketing), multinational companies’ channel most of their resources into these activities and realise production with the help of suppliers (Chart 8-9). A country’s share of the GVCs’ income depends on where it can join the supply chain. If activities with a high innovation index are performed in a country, it has a much greater share of the GVC’s profit than it would have if it participated in production. This is reflected by investments in intangible assets, which are high and increased in nearly all sectors between 2000 and 2016. The increase in the value of intangible assets in proportion to revenue intensified in all GVCs (Chart 8-10). The increase was the highest in innovative industries, but even in the textile industry – for example – this proportion increased by 8 per cent between 2000 and 2016.

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Chart 8-9: Value added generated in the supply chains High

Driving force of the specialisation

Value added

Knowledge

Market size Labour cost

Concept and R&D

After sales support

Branding Design

Marketing Distribution Production

Low

Production chain (time) Source: Author’s own compilation.

While technological development facilitated the widening of Global Value Chains in the past, some of the latest technologies may hold it back. New automation solutions have extended the robotization of production to an increasing number of areas, and as a result, machines now perform tasks that could only be performed with human help until now. This extreme form of automation is present both in production and in office work. As a result, labour costs are reduced within the total cost of companies and have a decreasing influence on the geographical location of the company. Thus, other considerations are given priority, such as the proximity of producers to the market of their final products. This way the product reaches the consumer or the purchasing company sooner, and transport costs are lower. For example, Adidas relocated some of its production back to Germany and the United States (see Box 8-3). Obviously, this reduces the volume of exports, as production and consumption take place in the same region. Additive manufacturing technologies (3D printing) will also change the level of trade. Such technologies are more flexible than mass production and so 3D printing will also reduce exports. Instead of delivering products from distant companies, entrepreneurs can produce them close to the consumer with a printer, a program and some raw material. — 415 —

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Some newly developed products also reduce the length and complexity of global value chains. Electric cars have only 7 thousand components as opposed to combustion engine driven vehicles, which are made up of 30–35 thousand parts. This implies shorter supply chains and lower labor intensity. Consequently, when making a decision about the place of production, labour costs or the proximity of the companies of the value chain do not have an exclusive role, but for example the proximity of the place of consumption is also considered. Chart 8-10: Level and growth rate of intangible assets 66

Pharma, medical devices 29

Machinery 17

Computers, electronics IT services

Chemicals

Electrical machinery

Mining

Agriculture

Professional services

Trade

Printing, paper

Rubber, plastics

Energy, utilities

Food, beverage

Textile

Auto

12 4 7

Health care

Transportation

Change 2000 2016 Cost of intangibles/revenue

Note: dark blue column: the cost of intellectual assets relative to revenue; Light blue line: the cost of intellectual assets relative to revenue, changes in 2000–2016. Source: McKinsey (2019).

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Box 8-3 Speedfactory: Adidas’s factory in Bavaria

In 2015 Adidas built a shoe factory in the Bavarian Ansbach, and soon after that another one in Atlanta in the United States. There were two reasons behind building the two “Speedfactories”. Shoemaking is a labourintensive production process, and labour costs were increasing on the Chinese market. Obviously, the increased wages still remained far below the wage levels in Bavaria, but the difference and the profit deriving from it was decreasing. The European factory significantly reduced labour costs and shortened the long production and delivery times by taking production closer to final consumers. In addition to increasing labour costs, the company’s other concern was that the planning and manufacturing of the shoes took very long. In traditional factories, shoes are manufactured according to 40-year-old manufacturing processes, and their production takes two months because of the long value chains. After this, following placement of the order it takes 2 more months for the sports shoes to be delivered to European or American stores, unless expensive air transportation is used. In the new factory production has been automated to a large extent and as a result labor costs were drastically reduced. Only 160 workers are employed at the Speedfactory. Consequently, high labour costs did not represent a barrier to relocating production to Europe. Obviously, due to the location of the new factory, the delivery time and costs of European orders have been reduced. In addition, Adidas has reduced the time lost because of global value chains in such a way that the factory itself produces nearly all intermediate products instead of purchasing them from other producers. The production of new shoes is modelled by computer simulation in order to detect potential problems before physical production. As a result, the time required for manufacturing shoes has been shortened to such an extent that the factory is able to take orders as early as one week after planning.

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The new technology also allows greater freedom in planning. Adidas manufactures shoes that are adjusted to the characteristics of the average runners of different cities and serve special local needs better (for example in London many people go to work running, while in New York they tend to run long distances). In 2018, Adidas won the German Innovation Award in the category of large enterprises for its Speedfactory. Nike, Adidas’s competitor, has introduced similar changes in its production. According to estimates, 20 per cent of sports shoes will be manufactured in this way in 2023. Source: Bain (classic.qz.com).

How significant are the risks of participation in global value chains? The participation of a company in global value chains or the exposure of a country poses considerable risks besides its benefits. Companies’ costs can be reduced by joining global value chains, but the length and complexity of sophisticated production relations may cause both disruptions in production and fluctuating costs. The shutdown of partner companies may result in a loss of income all along the distribution chain. A company struggling with disruptions decreases its demand with regard to its suppliers, while its customers do not have access to the intermediate product, hindering thereby the manufacturing of their final product. Such risks can be posed by natural disasters, damage caused to supplying or purchasing companies, financial crises, shocks suffered by companies, or changes in countries’ trade regulations. For example, the earthquake and tsunami that struck Japan in 2011 not only set back Japan’s car manufacturing by 48 per cent, but also that of other countries to which Japanese companies supplied intermediate products: the output of car manufacturing companies fell by 19 per cent in Thailand, by 24 per cent in the Philippines, and by 6 per cent in Indonesia. The effects of the earthquake made itself felt — 418 —

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for about three months in the global car industry (UN ESCAP, 2013). Chart 8-11 shows that the most important event causing disruptions in the operation of GVCs was the merger, acquisition or sale of the trading partner (or of the partnerâ&#x20AC;&#x2122;s partner), and this was followed by fire, extreme weather and company restructuring. Chart 8-11: The most important events causing disruptions in global value chains

113

120

125

Strike

Regulatory change

Factory shut-down

150

210

237

Earth quake, flood

Reorganization

Weather

250

580

Fire

Acquisition, sale

Note: the chart shows the most important events that Resilinc, a company monitoring disruptions, assessed as potentially dangerous. The results come from monitoring over 100 000 sources. Source: Kahn-Perez (2019).

Companies respond to the risks generated by GVCs by trying to reduce their exposure to a given company or geographical region. For example, global companies may perceive it as a risk if they have only a few suppliers and these are all Chinese companies. Having only a few suppliers poses a threat to permanent supply, and a distant country may make companies vulnerable to changes in transport costs and to potential problems in transport capacities, and it may also pose â&#x20AC;&#x201D; 419 â&#x20AC;&#x201D;

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a foreign-exchange risk. To reduce disruptions and risks affecting costs, companies established supplier relationships with companies of other emerging countries too (Malik et al. 2011). The presence of global production chains in a country increases the probability of external shocks spilling over and the strength of such shocks. Crises cause a significant setback in trade, which has a negative impact on the output of the countries. Intermediate products participate in trade several times, so if the demand for a final product declines, its effect will influence the entire GVC, and will reduce trade on all levels (OECD 2013). The impact of the global financial crisis – which started in 2007 to 2008 – on the entire world economy was caused not only by financial globalisation but also by interlinkages that had taken place via value chains. For example, the declining demand on the global automotive market does not only set back growth in traditional vehicle manufacturing countries, but through offshore production and through the supplier chain it also sets back growth in Central Eastern European countries and in numerous developing economies. This risk may pay off, however, because these countries benefit from global economic upturn more than they would if they did not take part of GVCs. Another risk to countries participating in global value chains is that leading multinational companies – which are the main winners of GVCs – have acquired enormous market power. As a result of acquisitions and company mergers that took place in the recent period, extremely large “superstar companies” have emerged. For example, the revenues of Walmart in the USA, which is the largest company, are comparable to Argentina’s GDP, the revenues of Volkswagen with Finland’s GDP, and the revenues of Samsung with Greece’s GDP (Chart 8-12). These companies are very large and innovative and have significant market power, so they are characterised with enormously high productivity and a high profit generating capacity. Market power, however, may increase prices, and in addition to this it may function as an entry barrier to new companies. In the long term, the lack of competition may

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lead to low level of investment, deteriorating research and development activity and, resultantly, declining productivity. It is partly superstar companies that are responsible for the fact that in the past decades the share of wages on national accounts was continuously decreasing. These companies have large revenues, while the number of their employees is very low compared to their capital stock. As a consequence of their growth, people working in the industry receive an increasingly smaller share of the value produced, which leads to decreases in labour income shares (Autor et al. 2017). Chart 8-12: The annual value of sales of the largest companies is as large as certain countriesâ&#x20AC;&#x2122; GDP.

23,4 %

25,7 %

22,0 %

Note: The chart shows the largest global companies and the countries with GDP comparable to their annual value of sales. Source: MNB infographics.

The companies of global value chains that are present in several countries also have a negative impact on fiscal revenues. These companies manage their accounts so that their subsidiary undertakings in tax havens are much more profitable than those operating in highâ&#x20AC;&#x201D; 421 â&#x20AC;&#x201D;

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tax countries. The result of this is that they pay much lower taxes in high-tax countries than what would be expected on the basis of their operation (Torslov et al. 2018). These processes limit governments’ fiscal policy space.

References Autor, D – Dorn, D. (2013): The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market. American Economic Review 103(5), 1533-1597. Autor, D. – Dorn, D. – Katz, L. – Patterson, C. – Van Reenen, J. (2017): The Fall of the Labor Share and the Rise of Superstar Firms. NBER Working Paper No. 23396 Bain, M.: Adidas. A German Company Built a „Speedfactory” to Produce Sneakers in the most Efficient Way. https://classic.qz.com/perfect-company-2/1145012/a-german-company-builtaspeedfactory-to-produce-sneakers-in-the-most-efficient-way/ Baldwin, R. (2016): The Great Convergence. Information Technology and the New Globalization. Cambridge and London: The Belknap Press of Harvard University Press. Baldwin, R. (2019): The Globotics Upheaval. United States: Oxford University Press. Berthou, A. – Chung, J. – Manova, K. – Sandoz, C. (2018): Productivity, (Mis)Allocation and Trade, mimeo, University College London. Brynjolfsson, E. – McAfee, A. (2016): The Second Machine Age. Work, Progress and Prosperity in a Time of Brilliant Technologies. New York and London: W. W. Norton and Company. Discover Containers, The Complete History of Shipping Containers. discovercontainers.com/acomplete-history-of-the-shipping-container/. Last opened on 29/05/2019 Eurostat (2019), Statistics Explained. https://ec.europa.eu/eurostat/statistics-explained/index. php?title=File:Extra-EU_trade_in_goods_by_broad_economic_category,_EU-28,_2016_(%25_of_ total)_GL17.png Harley, C. K. (1988): Ocean Freight Rates and Productivity, 1740–1913: The Primacy of Mechanical Invention. The Journal of Economic History 48(4) 851-876. iLabour Project, Investigating the Construction of Labour Markets, Institutions and Movements on the Internet, ilabour.oii.ox.ac.uk. IMF Balance of Payments Database: data.imf.org. Khan, S. – Perez, A. (2019): EventwatchR 2018 Annual Report. Resilinc. Malik, Y. – Niemeyer, A. – Ruwadi, B. (2011): Building the Supply Chain of the Future. McKinsey Quarterly, January.

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8.1 The current state and the future of globalisation McDonald, N. (2018): Digital in 2018: World’s Internet Users Pass the 4 Billion Mark. Wearesocial. com. McKinsey Global Institute (2019): Globalization in Transition: The Future of Trade and Value Chains. Organization for Economic Co-operation and Development (2013): Interconnected Economies: Benefitting from Global Value Chains – Synthesis Report”. Ortiz-Ospina, E. – Beltekian, D. – Roser, M. (2018): Trade and Globalization. Our World in Data. ourworldindata.org/trade-and-globalization. Ortiz-Ospina, E. (2018): Does Trade Cause Growth? Our World in Data, ourworldindata.org/ trade-and-econ-growth. Torslov, T. – Wier, L. – Zucman, G. (2018): The Missing Profit of Nations. NBER Working Paper No. 24701. United Nations’ ESCAP (2013): Building Resilience to Natural Disasters and Major Economic Crises. UNCTAD (2017): Information Economy Report 2017. Digitization, Trade and Development. United Nations. World Bank Data, https://data.worldbank.org/, last opened on: 31/05/2019.

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8.2

New commercial and economic systems Viktor Eszterhai

Following the 2007 to 2008 financial crisis, when the growth of global trade stalled, for a short time it seemed that the trend of globalisation, which had been unstoppable before, would come to an end. In the decade that followed the crisis, however, it was widely assumed that globalisation rather entered a new phase, which can be described as “post-Atlantic globalisation”. “Post-Atlantic globalisation” questions the Atlantic-centredness of world economy and allows a greater space for non-Western powers to actively shape their environment. China is the most significant emerging power, which, through the Belt and Road Initiative, has started to transform its network of Eurasian relationships to help this mega-region to regain its former leading role in the world economy. The cooperation between China and the European Union bears key importance from the aspect of the initiative, and although it is not free from challenges, in the long term it promises to steer the process of globalisation in a direction which is fairer for developing countries too, and is environmentally sustainable.

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How did the global trading system evolve? We cannot really talk about independent national economies from the beginning of the 21st century, as they – apart from a few extreme exceptions – have integrated into world economy. Most commonly, this process can be identified as globalisation, which is a broad concept89, but one of its main sources is – by all means – the increasingly deeper integration of world economy. The consensus of which determined the direction of globalisation for decades is well reflected by the words of Kofi Annan, former Secretary-General of the United Nations (19962006): “globalisation is an irreversible process, not an option” (Habich – Nowotny 2017). The majority of economists viewed globalisation, i.e. the deepening of cross-border economic relationships, as a positive process (Ohmae 1999, Cairncross 2001). According to David Ricardo’s principle of comparative advantage everyone benefits from trade, and everyone can have a share in it (Friedman 2005). Thus, decision-makers’ task was none other than removing the barriers to international trade and achieving broader liberalisation. In the past century and a half, world trade increased dynamically not only in respect of volume, but it has an increasing role even in relation to the performance of the world economy: while in the middle of the 20th century exported products and services barely exceeded 20 per cent of global GDP, today this ratio is close to 25 per cent (Chart 8-13).

In economic terms, globalisation means increasing interdependence between economic operators, which extends to the cross-border movement of capital, goods, services and human resources. This process reduces geographical, cultural, economic and institutional distances between countries.

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Chart 8-13: Value of exported goods and services as a share of global GDP 35

Per cent

Per cent 29.38

35 30

0 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Source: World Bank, 2019.

Academic literature dealing with the history of globalisation typically divides the progress of globalisation into several phases (Ortiz – Beltekian – Roser 2019). Although some find that integrated world economy is an interpretative framework that can already be applied to the period of early colonisation (16th century) (O’Rourke – Williamson 2002, Steger 2017), academic literature agrees that the first large wave of globalisation is linked to changes in the 19th century, including mass production induced by the industrial revolution, technological innovations (first of all in the field of transport) and colonial competition too (Baldwin 2019). After the two World Wars, the expansion of world trade temporarily halted, and after World War II the second wave of globalisation resulted in a drastic surge in trade, and the presently known era of the integration of national economies began. Technological innovations, which significantly reduced transaction fees played a decisive role in this process (the development of civil aviation, the increasing productivity of maritime transport, and the wide-spread — 426 —

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use of telephones being the primary form of communication, etc.). Reduced transaction costs meant that besides products missing from individual national economies, even goods belonging to the same product categories appeared in trade between countries, in accordance with comparative advantages. This resulted in greater specialisation, as well as the development and the increasing complexity of production and distribution chains (Ortiz – Beltekian – Roser 2019). According to a dominant trend in world economy, the proportion of finished products is continuously reducing within international exchange, as opposed to semi-finished products and components (Rees 2018). Typically, the stages of the value chain representing a lower added value – where there is no need for highly qualified staff or advanced technologies – were moved to developing countries. Another important feature of the second wave of globalisation after World War II was that for developed countries the providing of services became the most important sector of economy, which also affected global trade. By 2017, the share of services within global exports was above 24 per cent (Ortiz – Beltekian – Roser 2019). Finally, another important feature of the second wave of globalisation was that the so-called Bretton Woods System was created after World War II, in the framework of which the World Bank, the International Monetary Fund (IMF) and the General Agreement on Tariffs and Trade (GATT) were established. In 1995, the Bretton Woods System was renewed as the World Trade Organisation (WTO) with the need to control the world economy – including global trade – as a whole.

What is the impact of post-Atlantic globalisation on the global trade system? The setback in the growth of global trade following the 2007 financial crisis was widely considered as the end of globalisation (King 2017). There is no doubt that the volume of global trade reduced significantly, which called into question the forms of development of globalisation, which seemed self-evident before, such as unlimited — 427 —

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growth, standardisation, or the irrelevance of geographical space. Some consider, however, that this setback is only temporary, as the flow of capital, information and people (e.g. international tourism, free calls via the internet, etc.) is still dynamically increasing (Altman 2019). Other experts examining the characteristics of globalisation argue in support of globalisation entering a new phase, which they try to describe with the concept of post-Atlantic globalisation (or “globalisation 2.0”) (Li 2012). According to this view, the earlier phase of globalisation was mainly characterised by the assumption that Western culture was universal, and that the global trading and economic system was built on it with the belief that Western norms and values were decisive. Thus, post-Atlantic globalisation means the end of this era, and at the same time interdependence between identities and cultures characterised by new forms of non-Western modernity. In the past two centuries, an important characteristic of “Atlantic” globalisation has been that its operation has been determined by the interests of Western powers, first of all the United States of America (USA), which was truly reflected by the international institutional system. Although the USA typically supported the growth of emerging economies, most states were not entitled to have a substantial influence on the control of world trade, and they only followed the rules of the USA. The concept of post-Atlantic globalisation presumes a new type of regionalism, where other states also try to act as rule-makers. So what are the arguments that can be raised in support of post-Atlantic globalisation? First of all, it must be emphasised that the dominance of Western countries is diminishing in world economy, while new actors are becoming stronger. Consequently, the old regime, which could be characterised by the dominant role of the USA, has changed and become multi-polarised (Acharya 2017). Presently, besides the USA, the EU and China have become similarly significant actors in the world economy and global trade. Although the USA is still the world’s largest national economy in current prices, in terms of purchasing power — 428 —

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standards it is preceded by China and the EU. According to the value of products moving in trade – not including trade within the EU – the USA continues to be the biggest importer in the world, followed by the EU and China. In respect of exports China comes first, preceding the EU and the USA (Chart 8-14). Chart 8-14: The share of the three economic centres of the world in terms of GDP (purchasing power parity) and trade (2018) 60

Per cent

50 40 30

16.3 14.9 15.2

20 10

18.7

40 15.1 30

16.6

10.9

13.6

16.2

Share of Global Import

Share of Global Export

20 10 0

0 Share of Global GDP (PPP) China

United States

European Union

Source: IMF, 2019 & WTO, 2019.

Another important aspect is the regionalisation of value chains. If we address the question, what percentage of traded goods forms part of the global value chain, we find that the three main centres of world economy have similar shares in the global value chain. This could be established with regard to 46 per cent of the products exported by the USA, and 44 per cent of the products exported by China. In the case of the EU, if trade within the EU is filtered out, this value is only 23 per cent. It is also interesting to consider what percentage of the traded products are incorporated in further products in the countries examined. Only 3.3 per cent of the EU’s exports realised exclusively via — 429 —

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global value chains came from the United States, and 4.2 per cent came from China. The value chains between the United States and China are limited. Only about 3 per cent of the gross exports of the United States came from value chains linked to China. China is even more independent than this, only 2.6 per cent of its exports from the USA are linked to US value chains. European value chains represent higher values both in the case of the USA and China, amounting to 16.2 per cent and 17.1 per cent, respectively. These are the values. The markets of China, the USA and the EU are more independent from each other than what is suggested by anecdotic examples (e.g. Apple) (Rees 2018). All of this reflects that in the case of the three big economic centres, the production chains extend primarily to their regions, playing a dominant role therein (Timmer et al. 2014). The regionalisation of the markets is the third important characteristic feature of post-Atlantic globalisation. In the case of the earlier phase of globalisation, the American market was the most important one. Today, the USA is able to maintain its earlier position in the case of a decreasing number of products. As a consequence of the above, products are changing to suit standards and the demand of big markets, and they lose their former “universal” and uniform nature. This is especially true at the level of regional production: while earlier there was the global market, today producers make a distinction between the Chinese, the American and the European market. The fourth important characteristic feature is protectionism. Several Western countries – primarily the USA – are characterised by isolation and the rejection of costs incurred by ensuring common good. The USA’s increasingly more obvious withdrawal from its role as a global leader demonstrates the multi-polarisation of the international regime, and also questions the existence of the earlier phase of globalisation, because – as it was explained above – it was based mainly on the interests and values of the USA. In line with the USA becoming increasingly more protectionist, developing countries want more say in global economic issues, especially China, which is well reflected — 430 —

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in Xi Jinping’s keynote speech made at the World Economic Forum in Davos in January 2017. It is important to emphasise that developing countries are still not interested in terminating the system, so primarily they argue in support of reforms that represent their own interests, and their population has a typically favourable opinion on globalisation (Stokes 2016). In such circumstances the Trump administration’s approach consisting of using duties as a political weapon is especially dangerous. The impact of this in international trade does not simply occur as a significant factor of uncertainty, but it threatens the entire trading system, as the protectionist forces of other countries have no reason not to use Donald Trump’s threats to support their own claims in other commercial disputes. The post-Atlantic globalisation model suggests that despite the tensions experienced recently (e.g. US-China trade war), globalisation remains a process which would be difficult to halt or reverse, but earlier schemes and truths considered as universal seem to be questioned at the same time. Thus, multi-polarisation and regionalisation will become dominant trends in the new era of globalisation.

Is Eurasia the new axis of world economy? Today Asia is the most important region of world economy, representing about 60 per cent of the world’s population, while in terms of purchasing power standards in 2018 it gave 46.7 per cent of the world’s gross economic output (35.5 per cent at nominal value) (Chart 8-15). In recent decades, the Asian region could be identified as the driver of global growth, where in the following decades the annual growth is expected to be faster than in most regions of the world.

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Chart 8-15: Share of Asia in global GDP (purchasing power parity). 50

Per cent

Per cent 45.30

2018

2016

2014

5 2012

5 2010

2008

2006

2004

2002

2000

1998

1996

1994

1992

1990

1988

1986

1984

1982

1980

Source: IMF, 2019.

Asia’s rapidly increasing significance fundamentally challenges the Atlantic centredness that dominated world economy for centuries. Although a number of challenges lie ahead in the future (the middle income trap, the competition for finite natural resources, the remaining significant differences between countries and regions, global warming and climate change, etc.), it seems that the global economic order that existed before the industrial revolution – when Asia was the most important centre of world economy – will be restored in the future. For all these reasons, in the future the Asian continent and the regions successfully joining it are expected to play a dominant role in the globalisation process. Primarily Europe is the region that can be expected to play an important role as one of the centres of world economy. The trade realised between the two continents can already

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be identified as the most important relationship in world economy (Khanna, 2019). The EU is the most important partner of the Asian continent, significantly exceeding the USA (Chart 8-16). Chart 8-16: Asia’s trade with the EU and the USA (2018) 1,400

USD Billions

USD Billions 1,145

1,200 1,000

1,088

947

1,400 1,200 1,000

800

800 584

600

400

200

USA

Asia’s Import from

USA

Asia’s export to

Source: International Trade Centre, 2019.

Initiatives aimed at facilitating connectivity between the continents in the framework of post-Atlantic globalisation will play a decisive role in the future in deepening relationships between Europe and Asia (Acharya 2017). These initiatives include infrastructure, international lending and investments, cooperation on research and innovation, the propagation of technical and regulatory standards, and the expansion of the institutions of political decision-making. In recent years, one of the most significant initiatives has been the Chinese One Belt, One Road (Zheng 2017).

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Is the belt and road initiative rewriting Eurasian relationships? The Belt and Road Initiative – also known as the Silk Road Economic Belt and Maritime Silk Road – was announced by Xi Jinping, President of the People’s Republic of China in September 2013 at Kazakhstan’s Nazarbayev University. By now the concept covers the major proportion of the country’s foreign projects like an umbrella, and it has become the flagship initiative of China’s foreign policy. The initiative can be grasped as a vision, the aim of which is to redefine the system of relations between Europe, Asia and Africa. As it is underlined by Chinese official documents, it is not a plan but only an initiative, as there are no clearly identified phases for its realisation, and it has no previously determined script (Vision – Actions 2015). The projects and ideas linked to the initiative are flexibly adaptable, and the Chinese party expects that other states, organisations and foreign companies will participate in it. The Belt and Road Initiative is intended to be analogous to the old Silk Road, which used to be an extensive commercial network connecting the most significant centres of civilisation in Eurasia and Africa by land and sea. The explicitly declared aim of the Belt and Road Initiative is to deepen economic relationships similarly to the old Silk Road and create new channels to facilitate the flow and exchange of information, knowledge, thoughts, ideas, arts and technologies. The initiative is aimed at linking regions, which, despite being geographically close to each other, have limited contact because of the dominance of world trade based on maritime transport. Although it may seem that the emphasis is on being connected by land, maritime links also form an important part of the initiative, which is demonstrated by the part of the Belt and Road Initiative referred to as the 21st Century Maritime Silk Road (Wang 2016). Relationships and connectivity is in the focus of the entire concept, and official state documents describe five ways of promoting it (Vision and Actions 2015). The first is political coordination, which means the alignment of the policies of individual national, regional — 434 —

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and international institutions. The second is setting up physical infrastructure, which involves connecting new and already existing networks, such as road, railway, air, oil and gas pipelines and optical networks, together with cooperating industrial parts, logistics centres and seaports, rewriting the production centres of this huge region and the traditional economic relationships between its markets and raw material sources. The third way is ensuring unhindered trade, which means the elimination of bureaucratic barriers in the way of trade at the beginning, while in the long term it also involves the expansion of free trade areas. The fourth element of connectivity is financial integration, which is aimed at harmonising and jointly regulating financial services, and substituting the currencies of the regions concerned. Finally, strengthening relationships within the human sector also has an outstanding role, laying great emphasis on cooperation in the field of culture and research & development, offering scholarships and exchange programmes for students, experts and researchers, supporting tourism, etc. On the basis of the five types of relationships described above, the Belt and Road Initiative can be identified as a complex network, which can be extremely flexibly expanded in space. At the same time, the infrastructure network – as defined in the physical sense or to be set up in the future – has specific significant channels and nodes concentrated along so-called main economic corridors. The six land corridors defined include the New Eurasian Land Bridge Economic Corridor, the China–Pakistan Economic Corridor, the China–Indochina Peninsula Economic Corridor, the Central Asia–West Asia Economic Corridor, the Bangladesh–China–India–Myanmar Economic Corridor (Vision – Actions 2015), and the 21st Century Maritime Silk Road (Chart 8-17).

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Chart 8-17: Economic corridors of the Belt and Road Initiative.

Source: Authors’ own compilation.

Consequently, the initiative is far more than just a large-scale infrastructure programme, and as a geo-economic initiative with a new Eurasian continent in its focus, through the “five connections”, China attempts to transform global economy and the international system (Wang 2016). The deepening integration of Asia and Europe may change the Atlantic nature of the current global system, which was originally set up by Western powers by controlling sea trade and commercial maritime routes, starting from colonisation in the 16th century. China, however, has an impact on the existing international order not simply by setting up a new network. It has started to fill the framework represented by the Belt and Road Initiative with new “parallel” institutions. These include interregional institutions directing the relationship between the individual regions and China on a new track, such as the “16+1 cooperation” or the Asian Infrastructure Investment Bank, China’s new financial institution, which has also drawn significant attention (Heilmann at al. 2014). In the future, the Belt — 436 —

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and Road Initiative may play a key role in transforming the structure of the global production value chain too. Consequently, the Belt and Road Initiative envisages connectivity, a deeper cooperation, and it also stands by continuing globalisation while attempting to moderate its “Western” nature. There are also other reasons why it can be regarded as a decisive initiative of postAtlantic globalisation. Some believe that in the period of post-Atlantic globalisation an increasing emphasis is placed on investments and the development of the infrastructure as opposed to the earlier period, when globalisation was primarily driven by the expansion of trade.

What are the opportunities offered and the challenges posed by the Belt and Road Initiative for the European Union? The relationship between the EU and China was extremely ambivalent in the past decades. On the one part they are important partners for each other, while on the other part their cooperation is characterised by numerous conflicts of interests and differences of opinion. This represents a framework, which has a strong influence on the diverse views and cooperation possibilities in connection with the Belt and Road Initiative within the EU. Inside the EU, one of the most common criticisms expressed in connection with the Belt and Road Initiative is that it is a rough vision, in which the tasks of the concerned parties are not defined clearly: often it is not clear which Chinese institutions are responsible for planning, and with whom the EU’s individual subsystems should cooperate with (Grieger 2016a). Another frequently raised criticism is that the projects implemented so far in the framework of the Belt and Road Initiative – mainly infrastructural investments and their form of financing – are not transparent and run counter to EU legislation (Grieger 2016b). Better connectivity resulting from the infrastructural developments — 437 —

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realised via the projects implemented in the framework of the Belt and Road Initiative (e.g. railway lines, road network) is not necessarily an advantage either, as it also ensures wider access for Chinese companies to the markets of European countries and neighbouring countries, which may obviously mean increasing competition for certain companies in the EU. All of this is accompanied by the structural change currently taking place in the Chinese economy. Because of increasing prices and stricter internal regulations, China is going in the direction of highquality industrial production driven by innovation, and in support of this the Chinese government announced the smart industrial production, modernisation programme focusing on combining IT technology and production (Made in China 2025) (Wübbek et al. 2016). Chinese companies that produce increasingly added value inevitably introduce greater competition for European manufacturing companies. According to critical voices, China’s Belt and Road Initiative is not without geopolitical goals either, as it divides the EU by separating the Member States into supporters and opponents. The new infrastructure realised in the framework of the Belt and Road Initiative (e.g. railway transport) grants an advantage to the EU’s eastern Member States and to Mediterranean ports (e.g. Pireus), while Western European states are confronted with the rearrangement of transport routes. It is frequently expressed criticism that the new institutions linked to the initiative (e.g. AIIB, Silk Road Fund, etc.) were established without the EU’s active participation, and all the EU can do is to join them. The waiver of the rulemaking rights creates a dilemma, which reflects that China wants to obtain Europe’s supportive approach so that it assigns a typically passive and inclusive role to Europe. At the same time, the Belt and Road Initiative promises a number of benefits too. The new transcontinental connections may also mean new markets for European companies. The relative isolation of the neighbouring regions (e.g. Eastern Europe, Central Asia, the Caucasus, etc.) is a burden on European companies too, while the new infrastructure to be realised and the services related to it may bring

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significant benefits (Herrero–Xu 2016). In addition to this, the projects of the initiative offer innumerable investment opportunities for the European financial sector, because they affect regions with a more dynamic growth potential than European markets. In respect of its objectives the initiative largely overlaps the European Commission’s Investment Plan for Europe, which, in particular, is aimed at removing infrastructural bottlenecks, first of all in respect of East-West relations. The greatest promise of the Belt and Road Initiative is to set up a Eurasian economic space, as a result of which the barriers to trade can be reduced and a so-called “Silk Road value chain” can be created. The “Silk Road value chain” may represent a significant change in the global commercial system, because it may coincide with the fourth industrial revolution. The fourth industrial revolution (via big data, the Internet of Things, artificial intelligence, quantum information and genetic technology) is expected to transform production and supply chains fundamentally. Until today, multinational companies connected the world with industrial chains and they were interested in the maximum and optimised allocation of resources. Through digital connectivity, the fourth industrial revolution enables the automated and self-optimised production of goods and services (including transport and storage), and the creation of self-regulatory production systems without human interventions based on transparency and predictive performance. Within these, system value chains operate in a decentralised manner, and the system elements make independent decisions (Hofmann – Rüsch 2017). In the future, technological innovations resulting from the fourth industrial revolution will enable the evolution of Eurasian production chains, for which increased connectivity between China and the EU is required. The Belt and Road Initiative may play a key role in this process. Moreover, China’s large-scale investments in technological developments will reverse the traditional West-East direction of technological flow in the near future.

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Conclusion: is this the end of unipolar world economy? The EU’s active participation in the Belt and Road Initiative may result in transforming Europe’s Atlantic focus, which was dominant for centuries, leaving a wider scope of Eurasian orientation. The rise of Eurasia in world economy may drastically reduce the USA’s international role and influence, which may accelerate the fragmentation of the unipolar world economy. As a result of a transforming world economy, in the short term the actors will undoubtedly have to face numerous uncertainties, because the existing norms, values and rules will lose their universal nature. In the long term, however, Eurasia’s rise is promising to direct globalisation onto a fairer and environmentally more sustainable path even for developing countries.

References Acharya, A. (2017): After Liberal Hegemony: The Advent of a Multiplex World Order. Ethics & International Affairs. 31(3), 271–285. Altman, S. A. (2019): Five myths about globalization. The Washington Post, January 25. Baldwin, R. E. (2019): The great convergence: Information technology and the new globalization. Baldwin, R. – Martin, P. (1999): Two Waves of Globalisation: Superficial Similarities, Fundamental Differences (Sz. w6904). Cairncross, F. (2001): The death of distance: How the communications revolution is changing our lives (Completely new ed). Boston: Harvard Business School Press. Duchâtel, M.– Duplaix, A. S. (2018): Blue China: Navigating the Maritime Silk Road to Europe. European Council of Foreign Relations, April. http://www.ecfr.eu/page/-/Blue_China_ Navigating_the_Maritime_Silk_Road_to_Europe.pdf (11/06/2019). Frank, A. G. (1998): ReOrient: Global economy in the Asian Age. Berkeley: University of California Press. Friedman, T. L. (2005): The world is flat: A brief history of the twenty-first century (1st ed). New York: Farrar, Straus and Giroux. Grieger, G. (2016a): One Belt, One Road (OBOR): China’s regional integration initiative: European Parliament Think Tank, Briefing, July. http://www.europarl.europa.eu/RegData/etudes/ BRIE/2016/586608/EPRS_BRI(2016)586608_EN.pdf (12/06/2019).

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8.2 New commercial and economic systems Grieger, G. (2016b): Why China’s public procurement is an EU issue. European Parliamentary Research Service, December 2016. http://www.europarl.europa.eu/RegData/etudes/ ATAG/2016/593571/EPRS_ATA(2016)593571_EN.pdf (14/06/2019). Habich, J. – Nowotny, V. (2017): A Closer Look at Globalization – Roots and Remedies. in A Closer Look at Globalization – The Positive Facets and the Dark Faces of a Complex Notion. Background paper, Trilogue, Salzburg 2017: Arts, Economy, Politics, BertelsmannStiftung, pp. 3-19. Heilmann, S. – Rudolf, M. – Huotari, M. – Buckow, J. (2014): China’s Shadow Foreign Policy: Parallel Structures Challenge the Established International Order, Merics: China Monitor, no. 18, 28 October. http://www.merics.org/fileadmin/templates/download/china-monitor/China_ Monitor_No_18_en.pdf (19/06/2019). Herrero, A. G. – Xu, J. (2016): China’s Belt and Road initiative: can Europe expect trade gains? Bruegel Working Paper 5., 5 September. http://bruegel.org/wp-content/uploads/2016/09/WP-05-2016. pdf (19/06/2019). Hofmann, E. – Rüsch, M. (2017): Industry 4.0 and the current status as well as future prospects on logistics. Computers in Industry International Journal, 89, 23–34. IMF (2019): World Economic Outlook, April 2019. https://www.imf.org/external/datamapper/ datasets/WEO (12/06/2019) International Trade Centre (2019). List of exported products for the selected product. https:// www.trademap.org/(X(1)S(lfqvcv45vpfg3n452e2j2s55))/Product_SelProduct_TS.aspx?nvpm=1%7c%7c%7c%7c%7cTOTAL%7c%7c%7c2%7c1%7c1%7c2%7c2%7c1%7c1%7c1%7c1 (12/06/2019) Khanna, P. (2019): The future is Asian: Commerce, conflict, and culture in the 21st century (First Simon & Schuster hardcover edition). New York: Simon & Schuster. King, S. D. (2017): Grave new world: The end of globalization, the return of history. New Haven, CT: Yale University Press. Li, E. X. (2012): Globalization 2.0. New Perspectives Quarterly. 29(1), 40–44. O’Rourke, K. H. – Williamson, J. G. (2002): When did globalisation begin? European Review of Economic History, 6(1), 23–50.

Ōmae, K. (1999): The borderless world: Power and strategy in the interlinked economy; [management lessons in the new logic of the global marketplace] (Rev. ed). New York: HarperBusiness. Ortiz-Ospina, E. – Beltekian, D. – Roser, M. (2019): Trade and Globalization. Published online at OurWorldInData.org Rees, A. (2018): What if? Trade wars and global supply chains. Unicredit, Economics Thinking. 7 September. Steger, M. B. (2017): Globalization: A very short introduction (Fourth edition). Oxford, United Kingdom; New York, NY: Oxford University Press.

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8 Geopolitics and economy in the 21st century Stokes, B. (2016): Unlike the West, India and China Embrace Globalization. Yale Global Online, October 18, yaleglobal.yale.edu/content/unlike-west-india-and-china-embrace-globalization (17/06/2019). Timmer, M. P. – Erumban, A. A. – Los, B. – Stehrer, R. – de Vries, G. J. (2014): Slicing Up Global Value Chains. Journal of Economic Perspectives, 28(2), 99–118. Vision and Actions (2015): Vision and Actions on Jointly Building Silk Road Economic Belt and 21stCentury Maritime Silk Road. Issued by the National Development and Reform Commission, Ministry of Foreign Affairs, and Ministry of Commerce of the People’s Republic of China, with State Council authorization, March 2015. http://en.ndrc.gov.cn/newsrelease/201503/ t20150330_669367.html (12/06/2019). Wang, Y. – Chen, F. (2016): The belt and road initiative: What will China offer the world in its rise (First edition). Beijing: New World Press. World Bank (2019): Exports of goods and services (% of GDP), The World Bank Data. https://data. worldbank.org/indicator/ne.exp.gnfs.zs (19/06/2019). WTO (2019): Global trade growth loses momentum as trade tensions persist. Press Release 837. 2 April. https://www.wto.org/english/news_e/pres19_e/pr837_e.htm (19/06/2019). Wübbeke, J. – Meissner, M. – Zenglein, M J. – Ives, J. – Conrad, B. (2016): Made in China 2025: The making of a high-tech superpower and consequences for industrial countries. Mercator Institute of China Studies, 2., December. https://www.merics.org/en/papers-on-china/made-china-2025 (14/06/2019) Xi, J. (2017): President Xi’s speech to Davos in full, World Economic Forum, 17 January. https:// www.weforum.org/agenda/2017/01/full-text-of-xi-jinping-keynote-at-the-world-economicforum/ (21/06/2019) Yafei, China’s Role in Steering the Future of Globalisation. Telegraph, May 10, 2017, www.telegraph. co.uk/news/world/china-watch/politics/role-in-steering-globalisation/; Zheng B., China’s ‘One Belt, One Road’ Plan Marks the Next Phase of Globalization. Huffington Post, May 18, 2017.

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8.3

Global cities are the new power centres of the 21st century: Long-term sustainable urban growth Norbert Csizmadia

In these days, the majority of the population of the Earth lives in cities. This proportion is going to increase further in the future. Economic development is concentrated in the space, mainly in global cities and megaregions. Our research examining the urban competitiveness of “Fusionopolises” showed that there are 64 global urban areas and megaregions in the age of the rise of cities which contain links related to each other in a very complex way, but a sharp competition for global functions can also be observed between them. Urban areas of developed regions have now become beyond doubt giant economies. In the future, the rise of cities and city networks is going to continue, and they are going to act as major growth axes and zones of global economy. The future city network of Budapest is the whole Carpathian Basin. Budapest is a capital of 2 million inhabitants, constituting a Budapest Economic Zone of 4 million inhabitants, being the capital of a country of 10 million inhabitants, the centre of the Carpathian Basin with 24 million inhabitants, the centre of the Visegrád Four with 64 million inhabitants which, together with Slovenia and Croatia, would have as many as 72 million inhabitants, and the centre of the 16+1 initiative of 128 million inhabitants.

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What is the significance of cities? In 1800, only 3 per cent of the population of the world lived in cities. This number increased to 47 per cent by the end of the 20th century and exceeded 50 per cent by 2015. In 2018, 51 per cent of the population of Earth (3.6 billion people) lives in cities and this proportion is going to increase to 67.7 per cent (6.3 billion people) by 2050 (UN 2018). 75 per cent of natural resources are used in urban territories. 80 per cent of the global GDP is produced in cities. 60 to 80 per cent of global greenhouse effects originate from cities. However, cities cover only 3 per cent of the surface of Earth. (UNEP 2013) Cities are also important spaces of growth and paradigm shift. While there were 83 cities with more than 1 million inhabitants in 1950, now there are 577 cities with more than 1 million inhabitants, 384 with more than 2 million inhabitants, 90 with more than 5 million inhabitants, 64 with more than 7 million inhabitants, 28 with more than 10 million inhabitants, and 12 with more than 20 million inhabitants throughout the world. Asian and African cities grow the most dynamically (UN 2018). Chart 8-18: Urban population of the world between 1950 and 2030

Source: UN, 2015.

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Richard Florida, Professor of the University of Toronto, proves with his huge database that the most important factor in our life is where we live. Drivers of economic development are not distributed in the world evenly but are concentrated in space (Florida 2003). Cities have their own personalities. It is not technology that makes the economy big and prospering but people who shape it. World and especially world economy are concentrated and reaches its peak in global cities and megaregions. Global cities are no longer defined by their past but by their future. This future is influenced by globalisation, urbanisation and technological development. Besides, we have to take into consideration the extent to which cities have educational and innovative potential with regard to the future and whether they are able to utilise environmental resources on the long term. New ideas, innovation-oriented economy, technology, the attraction of talents and the inclusive labour market as well as the real estate market dynamics of cities become more and more important. “New world cities” redefine the meaning of the word “global” since several smaller cities compete successfully against their bigger neighbours. In the age of globalisation, it is not only national economies but cities, too, who compete with each other for regional corporate centres. In the globalising global economy, a new global urban hierarchy is formed, one of its major drivers being the international flow of capital, information and services. Cities that are able to attract regional or global centres of international corporations may position themselves on top of this hierarchy.

Why is the hierarchy of cities a determining factor? Geographically speaking, HUBs are the most active centres of various economic, commercial, transport and innovation networks, which play an outstanding role globally and/or regionally too. Their appeal strongly influences the processes of neighbouring areas and world economy. HUB cities often play the role of hubs for other reasons as — 445 —

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well, apart from their economic power, in the global network of cities. Hubs can be transport hubs, knowledge/innovative/creative hubs and energy network hubs. Giant cities or, in other words, megacities are cities with more than 10 million inhabitants (UN 2014). The top megacity is the Japanese capital, Tokyo with its 35 million inhabitants, but Shanghai, Hong Kong, New York, Los Angeles, Chicago, Bombay, New Delhi, Mexico City, São Paulo and Rio de Janeiro are important megacities as well. Megapolises are created when several megacities merge. 80 million inhabitants live in the megapolis band of a length of 700 km from Boston to Washington. Technopolises are settlements where economic and scientific life is concentrated. The most important technopolis area is Silicon Valley on the Western coast of the USA where the most important state-of-the-art production is established and going on. (Kovács 2013) Conurbations are urban areas consisting of several settlements where the physical boundaries of settlements are blurred due to the increase of the number of inhabitants and the related expansion of built-up territories, thus making up a continuous built-up territory. The most important European example is the Ruhr district where more than 5 million people live in almost 40 settlements. (Kovács 2013) World cities or global cities are cities that exert a determining influence on the social/economic, cultural or financial and political areas. As globalisation expands, we use the term global city more and more often. The characteristics of global cities include that they actively participate in the organisation of international events and they provide the venues of significant international institutions. They have at least one big international airport linked to all parts of the world, and they are major destination centres of the biggest aviation companies. Centres of global cities host the most important international financial institutions, corporate centres and stock exchanges affecting the whole — 446 —

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world. They have cultural and educational institutions, universities and museums of international fame. They have a vivid cultural life with significant international film festivals, a lively musical and theatrical life, they are centres of internationally distributed media services and they contain publishing houses. Their sports life is vibrant, with venues and facilities for international competitions, world competitions and the Olympic Games (Kovács 2013). Chart 8-19: Urban agglomerations grouped by population numbers

Source: Martineau, 2018.

The most important scientific research relating to world cities was conducted at the Globalisation and World Cities (GaWC) Research Network of the Loughborough University in Leicestershire which attempted to define and categorise world cities. As a result of the research, cities were grouped into the categories Alpha, Beta and Gamma cities (GaWC 2018). Later, the concept of world cities was redefined and grouped by other means, an initiative led by P.J. Taylor (Taylor – Derudder 2016).

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Widely global cities – Cities with a very important role: London and New York – Cities with a less important role and cultural influence: Los Angeles, Paris, San Francisco – Global cities in an advantageous situation: Amsterdam, Boston, Chicago, Madrid, Milan, Moscow, Toronto Cities in a special situation: – Cities in a special economic situation: Hong Kong, Singapore and Tokyo – Cities in a special political and social situation: Brussels, Geneva, Strasbourg and Washington World cities: – Culturally: Berlin, Copenhagen, Melbourne, Munich, Oslo, Rome, Stockholm – Politically: Bangkok, Vienna, Beijing – Socially: Manila, Nairobi, Ottawa Cities having a leading role globally: – Mainly economically: Frankfurt, Miami, Munich, Osaka, Sydney, Singapore, Zurich – Mainly non-economically: Abidjan, Addis Ababa, Atlanta, Basel, Barcelona, Mumbai, Denver, Harare, Cairo, Lyon, Manila, Mexico City, Shanghai, New Delhi

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Chart 8-20: Global distribution of world cities as ranked by the GaWC

Source: GaWC, 2011.

Why do we reinterpret the concept of cities? The Brookings Institute published its analysis defining seven types of global cities in September 2016. Besides a novel approach, the strengthening of the global role of Asian cities caused by urbanisation trends of recent decades is noteworthy (Trujillo â&#x20AC;&#x201C; Parilla 2016). The ranking of global cities is important for cities because it may have a role in improving their ability to attract investment and may provide input for transnational corporations as regards the location of their centres and offices. Competitiveness ranking of global cities in the modern sense spread barely a decade ago. Since categorisation is possible along several criteria, absolute global cities do not exist, nor can we consider a single categorisation as absolute. There are comprehensive rankings using detailed analyses, rankings aggregating other rankings (rankings of rankings), rankings based on macro-economic and future

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growth forecasts, rankings following the criteria of certain social or economic/corporate trends, etc. The economic weight of big cities is becoming more and more important. Global economy is not managed by a few financial centres only, like New York, London, or Tokyo, but the international flow of goods, services, people, capital and ideas involves a wide and complex network of cities, significantly contributing to global growth. The definition of the seven types focuses on competitiveness as well as the existence of exportable sectors, with indicators of innovative capacity, talent, infrastructural links, governance and general industrial and economic characteristics. Naturally, global growth involves more than these metropolitan areas. It is also contributed to by small and medium towns. As a result, the seven types of global cities are the following: global giants, Asian centres, emerging gateway cities, Chinese industrial cities, knowledge centres, American middleweight cities and international middleweight cities weight (Leff â&#x20AC;&#x201C; Petersen 2015). The global giants are the managing centres of the most developed countries. These include the biggest cities of the USA, Japan, France and the United Kingdom, New York and Los Angeles, Tokyo and Osaka, Paris, and London. These metropolitan areas not only ensure the management of their own countries, but the most property, corporate decision-making and the coordination of international trade is also concentrated here. These cities are the most important hubs for the flow of people, knowledge and capital. From among the seven city types, they have the highest qualification level, the second highest number of patents per capita and also the second highest number of scientific publications per capita. Asian anchors include 5 Eastern-Asian metropolitan areas (Beijing, Hong Kong, Seoul, Shanghai and Singapore), as well as Moscow. These cities serve as gateways between global investors and their quickly â&#x20AC;&#x201D; 450 â&#x20AC;&#x201D;

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growing countries. These cities received a high volume of foreign investment, later reinforced by investments into local infrastructure and training. Now Asian centres have the highest population numbers and the highest concentration of commercial activities. They have the highest internet connection speed and the most extensive, relatively well-trained labour force. The type of emerging gateways include 28 metropolitan areas which are also the biggest commercial, transport and, mostly, political centres of their countries and regions. Roughly one-third of the city group includes capitals (e.g., Ankara, BrasĂlia, Mexico City, Pretoria, Santiago, Budapest and Warsaw). Eight are financial centres of their countries and several serve as gateways for the whole region. The category of Factory China includes Chinese manufacturing centres. These 22 cities well represent the geographical diversity of the Chinese technological and industrial revolution, with industrial centres on the Eastern coast of the country (Hefei and Nantong), in inner areas (Chengdu and Zibo), and in the delta of the Pearl River (Foshan and Dongguan). The group of Chinese industrial cities includes quickly expanding population centres of second and third rank. Knowledge capitals are rather centres with a medium population density, being among the wealthiest and most productive cities in the world. The average population of the 19 cities in this group is 4.2 million. The nominal GDP per capita and the GDP per worker is the highest here. Knowledge centres are leading knowledge-creating centres of the world. Their infrastructural links are excellent, they compete in economic sectors with the highest added value, and they have significant human resources, innovative and entrepreneurial capacities. They have the highest venture capital investment rates per capita throughout the world (with San Jose, San Francisco and Boston ranking at the top).

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American middleweights, roughly spread throughout the territory of the whole United States, cities with a significant growth in population numbers recently (e.g., Miami, Phoenix, Orlando, St. Louis, Tampa, Sacramento). The group of international middleweights is rather diverse, including the wealthier cities of Canada, Europe, Asia and Australia. The average number of the population of the 26 metropolitan areas is close to 5 million, their economy is rather complex, there are national and macroregional corporate and financial service centres among them (e.g., Toronto, Sydney, Frankfurt, Madrid, Copenhagen), as well as industrial centres (Fukuoka, Nagoya, Stuttgart, Karlsruhe, Milan, Barcelona). They increasingly specialise in knowledge-intensive sectors, modern manufacturing technologies or a combination of both.

Which are the most competitive global cities? As regards 21st century city development, we can identify several city types. There are green cities with vertical architecture, flexible cities which are both economic and conscious of the natural environment, walkable cities, cultural centres and aeropolises, meaning a city built around a global distributive airport. In the next 15 years, the cities of the world will tend to be more focussed in the South and to the East. Urban areas of developed regions have become beyond a doubt giant economies now. In the 21st century, cities are major arteries and target areas of economic life. Examining the competitiveness of global cities as well as the most important cities and urban areas consisting of city aggregations, we can draw several conclusions. In the age of fusions and networks, cities and the roles of cities are more appreciated: liveability, diversity, cultural features, international connectivity, and a role in financial and scientific life (start-up cities, smart cities, location of the best universities in the world) demonstrates new functions. Linking these new functions, new fusions are created.

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Therefore, these new types of competitive global world cities and city aggregations are called fusionopolises (Csizmadia 2016). The ranking in global competition of each city is increasingly stated by complex analyses which take alternative environmental and social data into consideration apart from the level of economic development. The ranking according to liveability of cities often appears as an independent criterion for the choice of the centre and the determination of geographical expansion and geostrategy of multinational corporations. Based on existing competitiveness indices, we synthetised the results, and thus determined the competitiveness ranking of global cities which was a new ranking including every factor. The competitiveness of cities increasingly includes the population number, economic indicators, technological, financial and cultural role, accessibility, involvement in the global economy, infrastructure as well as new indicators like the size of green areas, the number of digital nomadic jobs, sustainable urban transport, family- and childfriendly cities, the role of culture, number of start-up companies, the relationship between universities and young high-tech companies, sports opportunities, liveability and sustainability criteria. Based on our research started in 2017, we examined the economic performance and the population number of cities and weighted the results based on 28 existing competitiveness indices. New types of competitiveness factors, focusing mainly on innovation, education, liveability and global involvement had significant weight. The four main topics were the global urban character, infrastructural features, liveability factors and knowledge factors. As a result of the research, we identified 64 functional global cities, that are, fusionopolises. The ten cities ranking top in the competitiveness of fusionopolises are the following: Singapore, Hong Kong, Shenzhen (Pearl River Delta), Tokyo, London, New York, Paris, Seoul, Sydney, Amsterdam-Rotterdam, Toronto, Shanghai, Los Angeles and Beijing.

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Chart 8-21: Global cities and megaregions

Source: Authorsâ&#x20AC;&#x2122; own compilation.

Following our research results, the JLL (an international financial and professional real estate market advisory company) and the research centre of the Business of Cities elaborated a novel ranking method for the examination and grouping of cities in the summer of 2018 (JLL 2018). They were no longer engaged in the competitiveness ranking of cities, but rather identified city types. The new typology was based on the different roles of cities in the global economy and on the examination of the commercial and economic activities and cultural and institutional functions they encompass. The JLL and the research centre of the Business of Cities collected more than 300 global data which relate mainly to financial and business activity, investment profiles, infrastructure, living quality, innovation activities, governance and demographic relations. Another essential examination criteria relates to the size of the cities, the GDP per capita and the industrial structure of the city.

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As a result of the research, 4 main city groups were identified with 10 subgroups within them, having many features in common, facing several identical challenges and having a development path that is similar from several aspects. The first identified main group is that of established world cities, the second is for new world cities, the third is for emerging cities, and the fourth is “hybrid cities” or “growing urban drives”. Based on the global cities, 10 subgroups can be identified: 1) The “Big Seven”, that is, the seven big world cities. One quarter of all real estate market capital investment goes to these cities. 2) The Group of the “Contenders”. This group includes 10 members, and these cities have caught up with the “seven big cities” mentioned in the previous point in several characteristics. They successfully compete for the most talented people in the world, for capital and for the highest quality business investments. From among all the city types, they achieved the quickest growth as regards the number of real estate market investments in recent years. 3) The Group of the “Innovators” features excellent scientific, technological and business life, promoting the spread of innovation and entrepreneurial skills. They have a very significant real estate market capital attraction ability which is the highest compared to their size. Their capital attraction ability is the most significant following the “Big Seven”. They are favoured by foreign investors as well. These cities include Austin, Berlin, Boston, Denver, Dublin, Milan, Munich, Stockholm, San Diego, Seattle, Silicon Valley, Stockholm and Tel Aviv. 4) “Lifestyle Cities”. These cities are mostly characterised by the high quality of life among their inhabitants. The rental fees of urban cities have significantly grown during recent years. This category includes Auckland, Brisbane, Copenhagen, Hamburg, Helsinki, Melbourne, Oslo, Vancouver and Zurich. From among these, Melbourne is prominent, the city with the biggest real estate market. — 455 —

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5) The Group of “Influencers”. The primary aim of cities in this group is to locate transnational institutions and to provide for commercial functions. This group was less successful compared to “innovators” and “lifestyle cities” for real estate market investors. This category includes Barcelona, Brussels, Frankfurt, Geneva, Kyoto, Miami and Vienna. 6) The Group of “Megahubs”. Their development has been swift during the last decade. They became important financial and business service centres, real estate and corporate centres and commercial centres too. Furthermore, they achieved significant progress in the field of higher education, scientific life and healthcare. Real estate investment intensity is the lowest here. These include Bangkok, Delhi, Istanbul, Jakarta, Johannesburg, Manila, Mexico City, Moscow, Mumbai and Sao Paulo. 7) The Group of “Entreprisers” represents countries of emerging economies. This is a group of highly innovative and economic productivity. They are business and entrepreneurial centres. They perform well in the area of business services, engineering studies, finance and retail trade as well as in the creative industry. These cities saw a significant economic boom. This group includes Bangalore, Guangzhou, Ho Chi Minh City, Kuala Lumpur, Shenzhen and Taipei. 8) “Powerhouses”. This is a group of mainly Chinese cities including primarily industrial cities. In recent years, they were transformed into cities producing higher values. They receive significant government support which further promotes their growing value production. This group includes the cities of Chengdu, Chongqing, Hangzhou, Nanjing, Suzhou, Tianjin, Wuhan, Xian. 9) “Hybrids” have the features of “emerging” and “new world cities” simultaneously, are typically medium sized and show significant improvement in the whitening of real estate market abuses. This group includes Abu Dhabi, Bucharest, Budapest, Cape Town, Doha, Prague, Santiago, and Warsaw. — 456 —

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10) The Group of “National Growth Engines”. These cities can highly benefit from wide national markets. They are the venues of very significant real estate market investments. These include Atlanta, Dallas, Houston, Nagoya and Osaka.

What role do cities play in long-term sustainable growth? The global system of cities is continuously changing. New leading cities continue to emerge which gives a new meaning to competition in its process. The most important factors in the future will be the number of technological companies, education, environmental protection, transparency, the development of infrastructure and the number of international patents. The calculation of the index also includes the change in the urban GDP, infrastructural investments, the number of newly built offices and their share in proportion to all the offices, the number of office rooms let, the size and hosting capacities of new shopping centres, the number of hotel rooms and measures related to environmental protection. Cities that develop in a sustainable way on the long term and those having the most innovative economy worldwide invest high amounts of money into the technological and digital industry. Another common feature of cities is that sustainability is an important part of urban planning. Education also has an important role, and these cities provide the location for several universities and research centres of global recognition. Cities that develop in a sustainable way on the long term are to be found only in the most developed areas of the world (North America, Western Europe, Eastern Asia, Australia). Urban economies growing the most quickly on the short term develop along similar principles and have much in common with cities that develop in a sustainable way on the long term. Due to their high number of populations, they have a large number of cheap labour force. Their population increases very quickly, accompanied by an outstanding — 457 —

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rate of economic growth. Developed technological and pharmaceutical industries play an important role. This category primarily includes the quickly developing regions of Eastern Asia and Southern Asia.

Why are we in the age of city networks? Presently, 147 global corporations produce 40 per cent of the global GDP and almost 700 corporations produce 80 per cent of the global GDP in the global economy (Manyika et al. 2018). These corporations are concentrated in hubs in cities, especially where creative labour force is available. Apart from strategic corporations and nation-states, the new power centres of the 21st century are going to be cities, beyond a doubt (Khanna 2016). Now, in the age of the emerging of cities and city networks, there are 64 global urban areas and megaregions to produce 80 per cent of the global GDP. If the five most significant global cities of the world (New York, Los Angeles, Tokyo, Paris and London) would constitute a single state, this fictitious territory would be the third biggest economy in the world after the USA and China (Trujillo – Parilla 2016). International forecasts suggest that urbanisation is going to be focussed in the global East and South by 2030 (McKinsey 2011). Growth axes and zones start to be established, the centres of which are cities from the Boston-New York-Washington axis through the new European “Hanseatic League” and Asia, the Pearl River Delta (Hong Kong - Shenzhen - Guangzhou) to Singapore. The cities on the Eastern coast of Asia play a more and more important role in new competitiveness rankings. Taking new-type urban competitiveness factors like connectivity, creativity, knowledge, technology, innovation, involvement in global trade, as well as welfare factors, security, liveability, and the size of green areas into consideration, Singapore and Shanghai are going to be the winners without a doubt. City-states played an important role throughout history: they had a vibrant commercial life, and operated as financial, economic, — 458 —

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educational and cultural centres, for example, in the Renaissance period. Let us just think about the importance of Venice or Genoa in which location played the most determining role. Their major objective was to become involved in global economy and trade. As now, in the age of the new renaissance: Roads, zones, cities, networks and centres. What is important for us is that the Carpathian Basin works as such a natural zone. The future city network of Budapest will not be the Vienna-Budapest axis but the whole Carpathian Basin. That’s why it is important to link the settlements and centres of the Carpathian Basin more closely by motorways, infrastructural development, and educational and cultural cooperation. It is not by chance that our cities prepared the programme of modern cities and Hungarian villages (Fekete 2019, Prime Minister’s Office 2018), which can result in the implementation of complex economic development programmes. Such a development would cover viable rural small settlements too, which can have an identically important role as part of a network. It can be illustrated by the spokes of a wheel and the air in between. This should be extended to the whole Carpathian Basin. The reason is that the Carpathian Basin as a natural, uniform cultural and economic space unit operates as a zone, with natural boundaries (the Carpathian Mountains), wonderful natural features and an excellent geostrategical position. Let us link the Carpathian Basin with infrastructural lines so that a cooperation as close as possible can be realised in the age of connectivity (Decision of the Parliament No. 1/ 2014. (I. 3.), 2013). Now, Budapest is a capital of 2 million inhabitants, constituting a Budapest Economic Zone of 4 million inhabitants, being the capital of a country of 10 million inhabitants, the centre of the Carpathian Basin with 24 million inhabitants, the centre of the Visegrád Four with 64 million inhabitants which, together with Slovenia and Croatia, would have as many as 72 million inhabitants, and the centre of the 16+1 initiative of 128 million inhabitants.

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References Berube, A. et al. (2015): Global Metro Monitor 2014. An Uncertain Recovery. Brookings Institution Metropolitan Policy Program. https://www.brookings.edu/research/global-metro-monitor/ Accessed: 03 July 2019. Decision of the Parliament No. 1/ 2014. (I. 3.) (2013): National Development 2030 – National Development and Urban Development Concept. Annex to Decision of the Parliament No. 1/2014. (I. 3.). http://www.terport.hu/webfm_send/4616 Accessed: 03 July 2019. Csizmadia, N. (2016): Geopillanat. A 21. század megismerésének térképe. (Map of the exploration of the 21st century) L’Harmattan Kft. Budapest. Fekete, D. (2019): A Modern városok program jelentősége a hazai városfejlődésben. [The significance of the Modern Cities Programme in Hungarian city development] Tér és Társadalom; Vol. 33. no. 1 pp. 27-43. DOI: https://doi.org/10.17649/TET.33.1.3066. Florida, R. (2003): The Economic Geography of Talent. Annals of the Association of American Geographers, Vol. 92/4, pp. 743–755. DOI: 10.1111/1467-8306.00314 GaWC (2018): The World According to GaWC 2018. 13 November 2018. https://www.lboro.ac.uk/ gawc/world2018t.html Accessed: 03 July 2019 GaWC (2011): GaWC World Cities, Wikimedia Commons. https://commons.wikimedia.org/ wiki/File:GaWC_World_Cities.png Gere, L. (2016): Global cities redefined. Hungarian Geopolitics, Vol. I. Fourth Issue, pp. 8-15. JLL (2018): World Cities: Mapping the Pathways to Success. http://cities-research.jll.com/citiesresearch/Documents/benchmarking-future-world-of-cities/Cities-Research-Mapping-Pathwaysto-Success-2018.pdf Accessed: 03 July 2019 Khanna, P. (2016): Connectography: Mapping the Future of Global Civilization. Random House Kovács, Z. (2013): Népesség- és településföldrajz. (Population and settlement geography) Budapest, ELTE Eötvös Kiadó. Leff, S. – Petersen, B. (2015): Beyond the Scorecard: Understanding Global City Rankings. The Chicago Council on Global Affairs. http://www.thechicagocouncil.org/sites/default/files/ BeyondtheScorecardReport.pdf Accessed: 03 July 2019. Martineau P. (2018): A Cartographer Maps The Global Impact Of Humanity. https://theoutline.com/ post/5287/a-cartographer-maps-the-global-impact-of-humanity?zd=1&zi=jo4uifgz Accessed: 03 July 2019 Manyika J. et al. (2018): ‘Superstars’: The dynamics of firms, sectors, and cities leading the global economy. McKinsey Global Institute. Discussion Paper, October 2018. https://www.mckinsey. com/featured-insights/innovation-and-growth/superstars-the-dynamics-of-firms-sectors-andcities-leading-the-global-economy Accessed: 03 July 2019.

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8.3 Global cities are the new power centres of the 21st century Markieta M. (2013): Flight paths crossing the globe. Michael Markieta, GIS Consultant, Arup. Data from openflights.org. Quoted by: BBC News (2013): In pictures: Global flight paths. 28 May 2013. https://www.bbc.com/news/in-pictures-22657086 Accessed: 03 July 2019. Martineau P. (2018): A Cartographer Maps the Global Impact of Humanity. The Outline. https://theoutline.com/post/5287/a-cartographer-maps-the-global-impact-ofhumanity?zd=1&zi=jo4uifgz Accessed: 03 July 2019. McKinsey (2011): Urban world: Mapping the economic power of cities. McKinsey Global Institute, March 2011. https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/ Urbanization/Urban%20world/MGI_urban_world_mapping_economic_power_of_cities_full_ report.ashx Accessed: 03 July 2019. Prime Minister’s Office (2018): The implementation of the Modern Villages Programme is going to start in 2019. 18 July 2018 https://www.kormany.hu/hu/miniszterelnokseg/parlamenti-allamtitkar/ hir/2019-ben-elkezdik-vegrehajtani-a-modern-falvak-programot Accessed: 03 July 2019 Taylor, P. J. – Derudder B. (2016): World City Network: A Global Urban Analysis. 2nd Edition. Routledge. Trujillo, J. L. – Parilla, J. (2016): Redefining Global Cities – The Seven Types of Global Metro Economies. https://www.brookings.edu/research/redefining-global-cities/ Accessed: 03 July 2019 UN (2015): World Urbanization Prospects: The 2014 Revision, Final Report. United Nations, Department of Economic and Social Affairs, Population Division. New York, 2015. https:// population.un.org/wup/Publications/Files/WUP2014-Report.pdf Accessed: 03 July 2019. UN (2015): World Urbanization Prospects. United Nations, Department of Economic and Social Affairs, Population Division https://population.un.org/wup/Publications/Files/WUP2014-Report.pdf Accessed: 03 July 2019. UN (2018): World Urbanization Prospects: The 2018 Revision, Online Edition. United Nations, Department of Economic and Social Affairs, Population Division. https://esa.un.org/unpd/ wup/Publications Accessed: 03 July 2019. UNEP (2013): City-Level Decoupling: Urban resource flows and the governance of infrastructure transitions. A Report of the Working Group on Cities of the International Resource Panel. Swilling M., Robinson B., Marvin S. and Hodson M. https://wedocs.unep.org/handle/20.500.11822/8488 Accessed: 03 July 2019.

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Closing thoughts Barnabás Virág

The more than 450 pages of the previous seven chapters focused on several challenges and issues that determine our everyday lives and on the possible solutions. These challenges will definitely continue to grow and become more complex. To find the appropriate ways to address the new hurdles, both the natural sciences and the social sciences, and in particular economics, need to be reformed. Although there are areas where much headway has been made, it is undeniable that renewal is still progressing only slowly overall. A mere facelift will not suffice this time; we need to rethink the basics. Success hinges mainly on increasingly harnessing the power of fusions among the various disciplines. Scientific progress has proved countless times that new ideas come from fields that were previously considered peripheral. The boundaries between the various disciplines are melding, while digitalisation will also put the science of measurement, a pillar of development, on a new footing. Instant access to huge databases, the exponential growth of computing capacities and the integration of the findings of psychology, sociology, game theory, network science, geosciences and political science could herald a genuine golden age for the economics of a sustainable future. However, the road to that is still long and fraught with difficulties, and it can only be traversed with the right amount of openness, creativity and perseverance. The aim of our book was to take the first steps on this road. The future will indisputably be about major, often systemic changes. By projecting recent decades’ trends, we tend to downplay the significance of change by suggesting that it is linear in nature. Experience shows — 463 —

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that the opposite is true: in the era of technological revolutions, nonlinear changes, like structural breaks, are beginning to take place that ultimately transform our lives. But one thing will certainly stay the same. In the future, any new idea, claim or correlation can only become general knowledge if it is verifiable. This also holds true for the theories described in the book. Precisely because of this, the closing segment of our book on the challenges of the future summarises the major trends that will shape the decades ahead.

Megatrend 1: Climate change – Earth as a global hothouse? The latest trends in climate change paint a rather bleak picture. Despite all the promises, the overall greenhouse gas emissions of the Earth continued to increase in 2018. Emissions would still grow until the end of the next decade even if all the countries implemented the national commitments under the Paris Climate Agreement.90 However, the postponement of the turnaround in greenhouse gas emissions also means that the economic transformation (decarbonisation) that would ensure the maximum 1.5–2°C rise in average temperatures targeted in the Climate Agreement would need to be increasingly radical, yet this makes the implementation of the turnaround less and less realistic in terms of (geo)politics. An even grimmer picture is shown by the new studies that examine the relationship between the man-made surge in temperatures and Earth’s own natural processes. Based on these, there are many “vicious circle” feedback processes that increase the probability of the so-called Hothouse Earth scenario. This is because Earth’s natural structures also influence climate change. They significantly influence the reflection of 90

UN Economic and Social Council (2019): Special edition: progress towards the Sustainable Development Goals, Report of the Secretary-General. Available at: https://unstats.un.org/sdgs/files/report/2019/secretary-general-sdg-report2019--EN.pdf. Downloaded: 22 August 2019

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the incoming sunrays or even store a huge amount of greenhouse gases. However, these structures, such as the large ice fields and glaciers, may become unstable even under the scenario with an average temperature rise of 1–3°C, which is the most optimistic assumption in the Paris Agreement. The growing heat absorption due to the thawing of the ice fields would cause a domino effect resulting in further heating, which may result in the thawing of the permafrost areas that preserve large amounts of methane gas or the collapse of the ecosystem services of the South American and South Asian rainforests that act as Earth’s “lungs”. In the Hothouse Earth scenario, the new equilibrium position would be reached after sea levels increasing by 10–60 metres and average temperatures rising by 4–5°C, making many regions inhospitable.91 Of course, Hothouse Earth is only a potential scenario, but its probability increases as time goes on. The only thing that seems certain is change: the global economy needs to quickly dispense with fossil fuels and every other greenhouse gas, or the climate as we now know it will radically change, with all the social consequences that this entails.

Megatrend 2: The unbalanced growth of the global population In the decades to come, global population may continue to increase, whereby Earth’s population may reach new highs. In 1950, global population was 2.5 billion, which had tripled by 2015. In 2050, the number of people living on Earth may be close to 10 billion. According to the UN’s population forecast, global population is set to remain on an upward trend until 2100, peaking at 11 billion at the end of the century. Notwithstanding this, population growth may diminish in the decades ahead, due to the gradual decline in the total fertility rate. 91

Steffen et. al. (2018): Trajectories of the Earth System in the Anthropocene. Proceedings of the National Academy of Sciences. August 14, 2018 115 (33) 82528259. https://doi.org/10.1073/pnas.1810141115

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However, the future change in population sizes may vary across continents. Because of the high total fertility rate and growing life expectancy, the greatest population growth may be in Africa. The African population could double in three and a half decades from the 1.2 billion in 2015, rising to around 2.5 billion by 2050. In the first half of the 2060s, more than 3 billion people may be living on the continent. In contrast, in Asia the population might increase only at a slower pace, from 4.4 billion in 2015 to 5.3 billion. The only continent where the population could decline is Europe: Europeâ&#x20AC;&#x2122;s population could decrease from 743 million in 2015 to under 700 million in the second half of the 2050s, due to the low total fertility rate.

Megatrend 3: Ageing societies One of the greatest challenges of the global economy is the ageing of the population, caused by the falling total fertility rate and growing life expectancy. The number and population share of those aged 60 and over is expected to increase everywhere in the coming decades and may surge at an unprecedented rate from 900 million in 2015 to 2 billion in 2050. In the long run, the ageing of the population may exert a negative impact on growth opportunities through various channels. Ceteris paribus, the growing ratio of old and young generations requires new solutions in financing the budgets (e.g. reforming the taxation of capital, green taxes). However, the undesirable effects can be mitigated with the appropriate economic policy preparation, and ageing may also entail potential opportunities in certain areas of the economy. An important question is whether growing life expectancy will go hand in hand with the rise in the number of healthy life years. If the additional life years are spent in good health, ageing may provide potential opportunities for society, for example longer active careers.

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Megatrend 4: The twilight of the hydrocarbon economy Humanity’s annual energy consumption has risen almost 30-fold since the onset of the Industrial Revolution, and the composition of the energy sources used has also changed considerably. While in the early 1800s the energy mix was dominated by biomass fuels, coal became increasingly central from the mid-19th century, and so did oil and gas from the 20th century. Today, more than 80 per cent of global energy production comes from fossil fuels, and even though the use of renewables other than the biomass is continuously increasing, their proportion is still below 5 per cent. The composition of the energy mix also affects the sustainability of growth through environmental effects. Since the beginning of industrialisation, greenhouse gas emissions have increased sharply, mainly because of the widespread use of fossil fuels. As a result of accelerating climate change and the increasingly frequent extreme weather events, the measures introduced to curb global warming will attract more and more attention, which may entail a radical transformation of the energy mix. Within primary energy, the amount of coal, oil and gas may drop to less than half, while the use of renewables (solar, wind and geothermal energy) may increase manifold, and the proportion of nuclear energy could also grow. To ensure the shift to a low-carbon economy and the proliferation of lowemission technologies, each year trillions of dollars in funding could flow into the energy sector globally in the decades to come.

Megatrend 5: New geopolitical age – the rise of Eurasia We are at the dawn of a new world order. While 1980–2010 was dominated by hyper-globalisation, the economic crisis of 2008 started to engender new forms of cooperation, new players, new conceptual

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forms, new solutions and new value systems. In 2010, globalisation entered a new age, where innovation and knowledge are crucial, and in 2013 it entered a Eurasian age based on long-term sustainable growth. In this new era, economic geography is on the rise, and geopolitical processes are being replaced by geo-economic developments. In the 21st century, we will live in the interconnected world of networks and fusions, in which it will be ever more important to apply a complex approach. The power centre of the global economy will increasingly shift towards the East, thereby potentially making this Eurasiaâ&#x20AC;&#x2122;s century. China will play a leading role in connecting Europe and Asia. The essence of the New Silk Road is that it moves the axis of the world economy from the oceans to the land, and restores and rebuilds the former economic, political and cultural role of Eurasia. Meanwhile, the Central and Eastern European region may become a gateway to the Eurasian continent. To understand the processes of this new age, new maps are required that show the powers and major centres of the 21st century with their hubs.

Megatrend 6: The rise of megacities Nowadays in the world economy, 147 global corporations produce 40 per cent of world GDP, and around 700 companies generate 80 per cent of global GDP. These firms are clustered in cities where creative workers with the appropriate skills are available. Accordingly, besides strategic companies and nation- states, the new power centres of the 21st century will be cities. At present, in the age of the rise of the cities and networks of cities, there are 64 global urban regions and megaregions that produce 80 per cent of global GDP. The proportions in respect to urbanisation are also forecast to shift towards the East and South by 2030. â&#x20AC;&#x201D; 468 â&#x20AC;&#x201D;

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Growth axes and regions are starting to form, with cities at their centre, from the Boston–New York–Washington axis to the New Hanseatic League in Europe to the Pearl River Delta in Asia (Hong Kong–Shenzhen–Guangzhou) to Singapore. In the new competitiveness rankings, the cities on the eastern coast of Asia are becoming increasingly important. New competitiveness rankings are needed that also apply to cities and highlight new factors such as interconnectedness, creativity, knowledge, technology, innovation, integration into global trade, welfare factors, security, liveability and the proportion of green areas. In the future, Budapest could become one of the centres of a network of cities throughout the Carpathian Basin. Partly because of this, it is important to link the centres of the Carpathian Basin even closer together, through motorways, infrastructure developments and cooperation in education and culture.

Megatrend 7: Globalisation in the 21st century – Competing for knowledge and information Two things set apart the latest wave of globalisation from the earlier ones. Emerging countries have become richer, which influences the volume of foreign trade, and more and more products are consumed locally, instead of being exported to advanced countries. This effect will increase in the decades ahead, as the purchasing power of developing countries grows. Therefore, the volume of trade between advanced and developing countries relative to GDP will probably decline, but it will increase among emerging countries. This phenomenon will most likely create distinct blocks in the global economy. The development of robotisation also points towards this. The proliferation of robots and artificial intelligence reduces the labour-intensity of production, thereby shortening production chains. Companies no longer focus merely on unit labour costs when picking a location for their production; they also take into account the proximity of end markets. — 469 —

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Another similarly important phenomenon is the digitalisation of services, which allows them to be accessed from increasingly remote locations. This will boost foreign trade, and the same process is expected to play out in services that were seen on the market for industrial goods in the second wave of globalisation: the emerging countries with lower wages will produce most of the services. The most important raw material of the 21st century digital economies will be data and the huge databases built by collecting them. Data will become an important factor in competition, not only locally but also globally. In the short run, trade tensions and the restrictions that appear in their wake may hamper the growth in the volume of foreign trade. Just as the volume of trade diminished between the two world wars despite transportation costs not rising, in the coming period, a potential tariff war may considerably sour trade relations. However, we believe that in the long run, economic interests and technological opportunities will determine the economyâ&#x20AC;&#x2122;s direction, and globalisation will not abate as a result of unfavourable regulation.

Megatrend 8: Robots and artificial intelligence as the new factors of production Data use and the development of data analysis technology will become one of the most important forces shaping the future. Due to the proliferation of the new means of production, i.e. artificial intelligence and robots, several types of jobs may disappear on the labour market, yet technological progress also leads to new jobs. These jobs produced by innovation may also play a key role going forward. Lifelong learning, and the continuous development of our knowledge will become even more important than today, so that employment can remain high even after robots become widespread. Nonetheless, as a result of robotisation and innovation, labour market polarisation â&#x20AC;&#x201D; 470 â&#x20AC;&#x201D;

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could continue to grow. Digitalisation will affect not only automation but also transform the features of work processes, while flexibility will become more important, both in time and space as well as in terms of the forms of employment. Going forward, the trend that in certain fields the place and time of work will increasingly change, could continue. This is reflected in the growth of the sharing economy, which provides greater freedom than traditional employment relationships. Virtual employment means more flexible opportunities, and the number of people working in the digital space (digital nomads) is steadily increasing, while this trend is expected to continue in the years and decades to come. The new technologies accelerate the change in the skills considered important by employers, with those skills becoming more valuable that can only be substituted by machines in the distant future. In light of this, future jobs will mainly require creativity, critical thinking and advanced social skills (communication, cooperation).

Megatrend 9: Information will become the oil of the 21st century Almost 90 per cent of the currently available data has been produced in recent years. And this process is continuing rapidly: each day, 2.5 quintillion (10 to the power of 30) bytes of data are produced. Based on forecasts, the pace at which data is being generated will continue to grow exponentially. This staggering amount of data currently provides the basis for artificial intelligence and machine learning. These technologies are currently far from their potential maximum utilisation. Besides self-driving cars and retail trend analyses, machines will be able to analyse emotions, explore space and treat illnesses. Innovation substantially transforms the labour market and, in tandem with that, the required skills and competencies too. According to the latest forecasts, big data will soon be replaced by “fast data”, where data is analysed instantly, in 1 millisecond, by the computers programmed to — 471 —

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do so. Whereas in the 20th century the chief raw material of the global economy was oil, in the 21st century it is increasingly being replaced by information. However, progress also entails challenges, and several questions need to be addressed to allow data to become the true “oil” of the present and the near future. The rapidly growing amount of data represents major risks in the protection against unauthorised access and cyberattacks, since the current level of data protection cannot keep up with the pace of data growth. The encryption of data, the reduction of fraud and the level of confidence in those who use our personal information should all be improved.

Megatrend 10: The general proliferation of the platform economy The emergence of the sharing and platform economy disrupted whole industries over the span of a couple of years, clearly upsetting the former business status quo in mobility and transportation, retail trade, tourism, multimedia and telecommunication, finance, energy and HR. This business innovation continues to proliferate very rapidly, so we are definitely in for further radical transformations in the future, and not only in single sectors but in the economic environment as a whole. The best-known firms of this new business model have become almost indispensable players in the global economy in a very short time, and their market capitalisation often already exceeds that of most traditional businesses. According to a PwC estimate, while these sharing companies generated revenues of USD 15 billion in the most relevant sectors in 2013, 2025 will see over 20 times that much, at USD 335 billion. The proliferation of the sharing economy is mainly influenced not only by technology but also demographic developments. The most important of these is the continued growth of the global middle class

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(expanding to over 5 billion people in 10 years), the steady increase in the number of female consumers, who are the main users of the sharing firms (establishment of the “she-conomy”), and the surge of the older generation who maintain their community and economic activities on the platform. The successes of this business model achieved so far and expected in the future do not mean that the platform economy is guaranteed to succeed, as many companies that have a large user base struggle to turn a profit. Looking ahead, platform firms will have to take into account efficiency and business considerations, and especially tackle the challenges arising from using personal data. They will also undoubtedly face the regulatory measures that will endeavour to address the economic, political and power aspects of the huge amount of amassed data.

Megatrend 11: The age of zero interest rates Even before the latest financial crisis, nominal interest rates were generally on a downward path, however, central banks were faced with the issue of the effective, zero lower bound only after the eruption of the crisis. During the crisis management efforts, the room for manoeuvre for conventional monetary policy instruments became limited. In the context of the prevailing inflation expectations, central banks were unable to maintain the real interest rate necessary for stabilising the economy, even though the base rate was cut to the effective lower bound. It was demonstrated that there can be situations when monetary policy could only achieve the necessary level of the real interest rate by pushing nominal rates into negative territory. Some advanced-economy central banks used negative interest rates, however, the room for manoeuvre proved to be limited in these cases as well, not to mention that negative interest rates can have several unintended side effects.

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As a result of the continued decrease in the global equilibrium interest rate level, the likelihood increased that in the future central banks would hit the zero lower bound of nominal interest rates more often. Due to the falling neutral interest rate level and the prolonged crisis management, the overwhelming majority of central banks were unable to raise their benchmark rate well above zero per cent. What is more, the room for manoeuvre is expected to disappear shortly in the newly deteriorating economic situation. As seen in the years following the crisis of 2008â&#x20AC;&#x201C;2009, after reaching and maintaining the zero lower bound, monetary policy can best stimulate the economy by using targeted, unconventional instruments. The importance of coordinated economic policy increases, since it can foster recovery more effectively. The process may be changed by the development and introduction of central bank digital currency, which may open up a completely new territory for central banks.

Megatrend 12: Digitalisation of money The 21st century may guide the development of the money used by us in an altogether new direction. Historically, money was mostly designed to express and strengthen sovereign state authority and consolidate the given area with monetary instruments. Nowadays, as the sovereign corpus is determined by nation-states, from citizens but in a way regulated by the constitution, they would be entitled to designate and issue money. However, the introduction of the two-tier banking system and the prohibition of monetary financing of budget deficits had made the situation more complex by the end of the 20th century: although the state designates the ultimate means of payment, new money in circulation is created by players in the banking sector, through lending and in the form of deposit money. Currently, the role of the central bank is limited to the regulation of money creation by commercial banks, with a special focus on the stability of prices and the financial system. Yet judging from the current trends in globalisation and digitalisation, the central banks of nation-states may be forced to act in the 21st century. â&#x20AC;&#x201D; 474 â&#x20AC;&#x201D;

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This is because a digital super money spanning across national borders and facing regulatory hurdles may emerge (such attempts include Libra announced by Facebook).92 The nation-states that do not wish to relinquish their monetary sovereignty will be forced to make cash available in electronic form to households and companies, and not only to the privileged commercial banks, by opening the liabilities side of their balance sheet, and this is referred to in the literature as central bank digital currency. This may considerably transform banksâ&#x20AC;&#x2122; current operating models, but it would provide an opportunity for establishing a negative interest rate environment preventing the excess accumulation of money, as propagated by Silvio Gesell 100 years ago, as well as a much more efficient monetary transmission mechanism. The means of payment used as a global currency could also be significantly transformed. After the Second World War, the US dollar became the dominant global currency. Not even the introduction of the euro could substantially influence the monetary dominance of the dollar. In this context, the rise of China coupled with the decline of oil as a basic raw material and digital progress may bring about fundamental changes. The backing of the fiat money of the 20th century decoupled from gold was the long-term potential economic output of the issuing country, while in the case of smaller countries, the IMF sought to back the cash by building foreign currency reserves. However, this could also change in the 21st century, as our world will increasingly focus on the complex systems of energy and data. Of course, international competition would be reduced if the currency of the future was issued without backing, like an energy-efficient, scalable cryptocurrency. It remains to be seen, however, how the user confidence necessary for long-term sustainability could be established for a currency like that, even though it would be a vital precondition of the currency fulfilling its traditional standard of value, transaction and means of hoarding functions.

https://www.centralbanking.com/central-banks/4376401/central-banks-face-lossof-independence-central-banking-survey

â&#x20AC;&#x201D; 475 â&#x20AC;&#x201D;

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Megatrend 13: Bigtech firms in finance Investments in FinTech companies has increased exponentially in recent years. Globally, funds of USD 55 billion are estimated to have flowed into such firms in 2018,93 and investors’ appetite does not seem to abate. In fact, in the first half of 2019, a record amount of investments of USD 2.5 billion flowed into the greatest challengers of traditional banks, the so-called NEO banks94 (new banks that only offer mobile banking services without branches and use a new approach). Banks’ business model will undoubtedly change in the next decade, as the digital world forces the financial sector to progress. FinTech firms introduce a new approach to banking, providing simplicity and access to daily finances, primarily because of their ability to efficiently use technology to place the customer at the focus with their services. They offer financial solutions on a platform along the whole banking value chain, sometimes supplemented with personalised services. At the same time, today only traditional banks can offer fully individual services to customers and respond quickly to the creation of special products (e.g. subsidised loans or other economic stimulus programmes). This is because FinTech firms offer a schematic range of products, the main point of which is simplicity and that it should be available to the public at a low price. Although our daily finances may be transformed in the short run by digitalisation and the appearance of these new players, complexity and the need for personalised services will not disappear. Therefore traditional banks will have their own role to play on the market, which, however, may require them to change their business model.

https://newsroom.accenture.com/news/global-fintech-investments-surged-in2018-with-investments-in-china-taking-the-lead-accenture-analysis-finds-uk-gainssharply-despite-brexit-doubts.htm 94 https://www.portfolio.hu/finanszirozas/bankok/rekordmennyisegu-penzaramlik-a-neobankokba.4.334147.html 93

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In other words, there are opportunities for optimisation in terms of banks’ operating processes, but when it comes to our personal or business finances, our needs call for professional banking service providers in all situations, and FinTech firms need to adapt to this. In the future, this may be provided to customers by a whole financial ecosystem. Only those banks and FinTech companies will remain on the market that are able to tweak their business models in line with this. In the years and decades to come, both parties have much to do for their customers and sustainable business models. The expectation of our age and the future is to continuously learn and adapt.

Megatrend 14: Long-term ESG approach in investments instead of short-term profits In the decades ahead, the world needs to face several environmental and social challenges that are interconnected in many aspects and that pose an increasingly high risk from an investment perspective. The adjustment and the mitigation of the negative effects call for a change in the market mechanism with a short time horizon. On the one hand, short-term market activities with the sole focus on profits are one of the main reasons behind the social and environmental risks. On the other hand, the efficient and sustainable distribution of the resources (human resources, technology etc.) necessary for addressing the problems can partly be implemented on the market. Therefore in the near future, the methodical consideration of environmental, social and governance (ESG) factors may become increasingly important in the investment processes. This could mean the integration of many, previously disregarded but significant environmental and social factors in investment decisions. The integration of the ESG approach may become a general, or even required, method for investment funds. However, real effects can only be achieved by designing appropriately “strict” ESG standards, and — 477 —

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the coming years will hopefully be about ensuring this. Failing that, the concept of ESG may become hollow, making it suitable only for disguising the lack of the necessary measures.

Megatrend 15: Growing role of green taxes Future budgets are expected to focus more on green taxes based on both regulatory and revenue considerations. The proliferation of green taxation will help curb global polluting activities and improve the health of the public and, indirectly, assist labour productivity growth. Green taxes make environmentally harmful activities more expensive and encourage the implementation and development of solutions replacing polluting activities. Their beneficial effect on economic performance is exerted through two channels in the long run. First, levying green taxes helps prevent pollution from curbing future growth, and second, reducing pollution leads to healthier life conditions and thus, ultimately, more hours worked. Green tax revenues can be spent by governments on green research and development facilitating environmentally friendly solutions, either directly or indirectly through subsidies to businesses. In the countries seeking to escape the middleincome trap, this could help encourage the shift to an innovative economy, whereas in economies that are already innovation driven the expansion of research and development opportunities can be fostered. The currently low level of green tax revenues is expected to substantially increase on a global scale, and environmental and economic sustainability can be further strengthened by levying new green taxes on consumption. In 2016, green tax revenues in OECD countries amounted to 1.6 per cent of GDP on average. Both this and the Hungarian figure (2.7 per cent of GDP) fall short of the leading Danish (4 per cent of GDP) and Dutch (3.5 per cent of GDP) values. In the future, other countries may also considerably raise current values as green taxes become widespread. The number and extent of the taxes on greenhouse energy use (primarily carbon dioxide â&#x20AC;&#x201D; 478 â&#x20AC;&#x201D;

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emissions) is expected to increase and the emissions trading systems spanning multiple countries are forecast to expand, which boosts the revenues from this tax type. Carbon dioxide taxes may help reduce global warming and thus strengthen environmental sustainability. Environmental load charges on air, water and soil use, which represent a relatively large proportion within green tax revenues in Hungary, will be introduced or raised worldwide, facilitating the preservation of the natural environment.

Megatrend 16: Social polarisation or inclusive development Recent decades have seen income and wealth inequalities rising in most countries, however, the future paths of development are far from clear-cut. Several factors influence how inequalities change. Todayâ&#x20AC;&#x2122;s technological progress and globalisation have brought about numerous innovations and deepened trade relations, however, history suggests that it has also contributed to a rise in inequalities within the economies. Experience shows that the benefits of increasingly rapidly developing technology have not been distributed equally among the different groups of society. Several fundamental factors can be identified in respect to future directions. If the trend from earlier decades continues (i.e. the proportion of wages relative to capital income steadily declines), high earners will have an ever-growing proportion of total wealth. Based on experiences from economic history, technological revolutions usually point towards this. In the absence of appropriate measures, societies may become extremely polarised, which could lead to major political and economic instability. However, the current trends could also be reversed with the appropriate instruments, including, among other things, the provision of access to high-quality education and healthcare for as many people as â&#x20AC;&#x201D; 479 â&#x20AC;&#x201D;

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possible, the introduction of a job guarantee or the strengthening of financial regulation. In respect to technological progress, the balance between those earning capital income and earned income should be maintained. In this regard, the way in which capital is taxed may have to be reformed. This would ensure inclusive growth improving wealth for large swathes of society.

Megatrend 17: New set of measures instead of GDP Today, the best-known measure used in economics for gauging economic development is gross domestic product and its various versions. However, as modern economies develop, the measurement framework developed during the growth of the 1930s driven by the manufacturing sector needs to be revisited completely. The currently used measure has several shortcomings. It does not measure welfare accurately, as it cannot quantify many subjective factors, such as people’s sense of happiness, and it disregards the role of natural resources and the issue of ecological sustainability. What is more, it does not focus on issues of distribution and financing, including social and financial sustainability. In the digital age, the System of National Accounts also needs to be based on a completely new footing. At the same time, the development of alternative measures addressing the shortcomings of GDP has already begun. The heterogeneous “multilingual” groups should be harmonised to create a homogeneous multidisciplinary welfare and sustainability science, which could ultimately produce a new system of Global and National Accounts.

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Acknowledgements This book was inspired by sustainable development, which has been drawing increasing attention in recent years. The studies in it rely heavily on the decisions of the Monetary Council of the Magyar Nemzeti Bank, the analyses and workshops based on which they were taken, as well as discussions at various professional forums. The editors are indebted to Governor György Matolcsy and Deputy-Governors Csaba Kandrács, Márton Nagy, Mihály Patai and László Windisch for their stimulating support, and all the members of the Monetary Council for their professional comments on the analyses previously prepared in this field. Special thanks are due to the authors of the studies in this book, namely: Eszter Baranyai, Norbert Csizmadia, Nedim Márton El-Meouch, Levente Erdélyi, Viktor Eszterhai, Gábor Gyura, Mihály Hajnal, Róbert Hausmann, Gábor Horváth, Katalin Kis, András Bese Kolok, Pál Péter Kolozsi, Emese Kreiszné Hudák, Kristóf Lehmann, Róbert Mátrai, Zsolt Mihálovits, Tamás Nagy, Gábor Neszveda, Alexandr Maxim Palicz, Éva Paulik, Géza Rippel, Annamária Sipos-Madarász, Nóra Sljukic, Gábor Soós, Balázs Spéder, Attila Tapaszti, Álmos Telegdy, Judit Várhegyi, Balázs Vonnák. The authors and editors are especially grateful to Réka Egervári, Péter Kálmán, László Csaba Körtvélyesi, István Schindler and Árpád Vadkerti for their editing and coordination work. We thank Attila Kathi and Kinga Lengyel for facilitating the communication work for the book. We ought to thank Soma Szabó and Károly Pavela for their layout and graphics work on the volume. The authors owe their thanks to Maja Bajcsy, István Csonka and all other colleagues for their conscientious work, without which this publication could not have been released. — 481 —

List of charts and tables List of charts Chart 2-1: GDP, CO2 emission and the income share of the top 1 per cent in the world

Chart 2-2: What needs to be better integrated into macroeconomics?

Chart 2-3: GDP per capita and recessions in the US

Chart 2-4: The global wealth pyramid

Chart 2-5: Measures of economic development

Chart 2-6: Interpretation of GDP in Maslow’s hierarchy of needs

Chart 2-7: Relationship between the happiness index, infant mortality and GDP per capita

Chart 2-8: Relationship between GDP per capita and Welfare

Chart 2-9: Distribution of average annual income growth in the United States by percentile, 1980–2014

Chart 2-10: The lights of India on satellite images from outer space in 1994 and in 2010

Chart 2-11: Developments in global GDP and global internet use between 1700 and 2018

Chart 3-1: Environmental Kuznets curve

Chart 3-2: Ecological footprint deficit of certain countries and the world

Chart 3-3: Limits of safe human existence

Chart 3-4: The Great Acceleration: Impact of human activities on the natural environment

Chart 3-5: Red List Index of species survival, 1993–2019, and projections for 2020–2030

Chart 3-6: Development of world population size and its distribution across regions (per cent)

Chart 3-7: Number of those aged 60 and over in different regions of the world, 1950–2050

Chart 3-8: Old-age dependency ratio in the different regions of the world in 2015 and 2050 (per cent)

Chart 3-9: Evolution of the top 1 per cent national income share and global extreme poverty

Chart 3-10: Distribution of global wealth

— 483 —

List of charts and tables Chart 3-11: Physiological characteristics and access to basic services in major regions

Chart 3-12: Appearance of new technologies and the number of years necessary for their widespread adoption

Chart 3-13: Factors shaping the structure of production before and after the turn of the millennium

Chart 3-14: Tech giants

Chart 3-15: Digital technology adoption of large European companies, 2017 (per cent)

Chart 3-16: The owner of data in the automotive industry based on managers’ and consumers’ opinion

Chart 3-17: Major risks of data management

Chart 3-18: Changes in employment shares in the US by income groups, 1980–2005

Chart 3-19: Attitude towards technology on the labour market

Chart 3-20: The shifting centre of gravity of the world economy between AD 1 and 2025, based on GDP

Chart 3-21: Railway links of the One Belt, One Road Initiative

Chart 3-22: Megatrends established by the Bank of England

Chart 3-23: Distribution of global money by monetary aggregates and the forms of money

100

Chart 3-24: Central banks researching the topic of central bank digital currency

104

Chart 4-1: Green growth framework

111

Chart 4-2: Forest area as share of land area, 2015

113

Chart 4-3: Correlation between CO2 emissions and economic growth

116

Chart 4-4: Composition of global primary energy consumption

118

Chart 4-5: Death rate from ambient particulate air pollution, 2017

121

Chart 4-6: Annual infrastructure investment needs and fuel savings for sustainable development according to climate goals

124

Chart 4-7: Sources of green growth

125

Chart 4-8: Expected characteristics of environmental regulation

130

Chart 4-9: Range of possible environmental regulation approaches

131

Chart 4-10: Development of carbon allowance prices in the EU ETS (EUR)

135

— 484 —

List of charts and tables Chart 4-11: Change of the ecological footprint of the world population

146

Chart 4-12: Microeconomic effects of imposing green (Pigouvian) taxes

148

Chart 4-13: Aims and consequences of green taxation

149

Chart 4-14: Double dividend effect concerning green taxation

150

Chart 4-15: Estimated change in energy consumption (2016–2040, million tonnes of oil equivalent)

151

Chart 4-16: Ocean pollution by plastic waste

153

Chart 4-17: Income from green taxes relative to GDP (2016)

156

Chart 4-18: Income from environmental taxes relative to all government incomes (2017)

158

Chart 4-19: Green taxes by sectors (EU28, 2017)

159

Chart 4-20: The European Union’s Emissions Trading System

160

Chart 4-21: Functioning of the Finnish deposit scheme

162

Chart 4-22: Shareholder vs. Stakeholder

171

Chart 4-23: Methods of the practical application of the system of sustainable approach

173

Chart 4-24: The integration of the system of sustainable approach into the investment process

174

Chart 4-25: Sustainable development goals as determined by the United Nations

176

Chart 4-26: Project categories financed by green bonds

177

Chart 4-27: Green bond issuing

178

Chart 4-28: Process of prior screening (DNSH)

184

Chart 4-29: Main pillars of the ESG approach

186

Chart 5-1: Fertility rate in the regions of the world, 1950–2055

203

Chart 5-2: The development of the fertility rate and GDP per capita, 2017

205

Chart 5-3: Proportion of the population above 60 in certain continents of the world in 2015 and 2050 (in per cent of the whole population)

206

Chart 5-4: Change in the working-age population in each continent of the world between 2015 and 2050 (change percentages)

208

Chart 5-5: Distribution of the population by age group in each continent of the world in 2015 and 2050 (per cent)

209

Chart 5-6: Activity rates in different social groups in the V4 countries, in 2008 and 2018 (per cent)

213

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List of charts and tables Chart 5-7: The employment rate of age group 55 to 64 years in OECD countries between 2005 and 2018 (per cent)

214

Chart 5-8: Distribution of the population by age in certain regions and countries of the world in 2030 (per cent)

216

Chart 5-9: Ageing of the labour force and aggregate productivity

217

Chart 5-10: Number of workers employed in various economic sectors in proportion to all employees in certain regions of the world (per cent), 2018

219

Chart 5-11: Change in the number of working-age persons and old persons in G7 countries between 1995 and 2015 (per cent)

222

Chart 5-12: The development of real GDP, GDP per capita and GDP per workingage person in Japan and in OECD countries (per cent)

223

Chart 5-13: Development of GDP per hour worked in the G7 countries, between 1990 and 2017 (per cent change compared to 1990)

224

Chart 5-14: Development of labour income per capita and consumption per capita by age in France in 2011

225

Chart 5-15: Effects of ageing on consumption and savings

227

Chart 5-16: Coverage of the pension systems in each country of the world (latest available data)

230

Chart 5-17: The labour market participation rate of men older than 65 in certain regions of the world (per cent)

231

Chart 5-18: GDP-proportionate public pension expenditure and old-age dependency rate in European countries in 2016

233

Chart 5-19: Challenges of pension systems due to ageing in the 28 EU Member States

234

Chart 5-20: Life expectancy at birth in certain regions of the world (2010 to 2015) and the level of increase in life expectancy to be expected by 2055

236

Chart 5-21: The estimated development of GDP-proportionate healthcare public expenditure in EU Member States, 2016–2070

237

Chart 5-22: Global growth incidence curve (1980–2016)

247

Chart 5-23: Income inequalities by country in 2008 and 2015

248

Chart 5-24: Factors determining the changes in disposable income

250

Chart 5-25: Merchandise exports of China and US manufacturing employment

253

Chart 5-26: Productivity and real earnings in the UK (left panel) and in the USA (right panel)

255

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List of charts and tables Chart 5-27: Earnings relative to those with a basic education and the evolution of income inequality (USA)

257

Chart 5-28: Income inequality and the decomposition of the inequality of opportunity

259

Chart 5-29: Income inequality and intergenerational earnings mobility

261

Chart 5-30: Share of higher educated in top and bottom quintile and life expectancy at birth

263

Chart 5-31: The theoretical Laffer curve

267

Chart 5-32: Offshore financial wealth in major economies (2015)

268

Chart 6-1: Share of the main sector of the US labour market

277

Chart 6-2: Range of automation estimates for current workplaces

278

Chart 6-3: The connection between automation and innovation

280

Chart 6-4: Connection between the extension of employment and the proportion of new professions

282

Chart 6-5: Effect of the development of technology on the characteristics of work

284

Chart 6-6: Projected income growth of social economy

286

Chart 6-7: Online service providers (platforms) based on place of service and type of work required

287

Chart 6-8: The changing relationships of the participants in the labour market

289

Chart 6-9: State subsidy spent on employee training

290

Chart 6-10: Expected changes in demand for workforce skills

292

Chart 6-11: Unemployment based on time required to find a job

293

Chart 6-12: Bandwidth change

299

Chart 6-13: Rate and changes of ICT use between 2005 and 2018

300

Chart 6-14: The analogue and digital data processing process

302

Chart 6-15: Possible benefits of using personal data, according to executives (per cent)

304

Chart 6-16: The income surplus generated by the use of AI by 2030 in the EU (per cent)

307

Chart 6-17: Digital responsibility basics

311

Chart 6-18: Proportion of companies that meet the digital responsibility criteria by sectors (per cent)

313

Chart 6-19: Real GDP per capita (left axis, USD) and mean happiness (right axis) in the USA between 1973 and 2009

320

â&#x20AC;&#x201D; 487 â&#x20AC;&#x201D;

List of charts and tables Chart 6-20: Average of social happiness (0–10) and national income per person in 2017 (USD)

321

Chart 6-21: Framework of actual and necessary income based on the General Social Survey of USA (1952–1987)

322

Chart 6-22: Connection between average happiness and number of hours spent with certain activities weekly

326

Chart 7-1: Classification of money types

338

Chart 7-2: What exists in each type of ledger system to ensure trust in money?

340

Chart 7-3: Potential collaterals underlying money

341

Chart 7-4: Development of the proportion of cash in certain countries

342

Chart 7-5: Global reserve currencies since 1450

346

Chart 7-6: Global and local currencies

349

Chart 7-7: Access to the balance sheet of deposit-taking and lending central banks

351

Chart 7-8: The hypothetical development of the balance sheet of a deposit-taking bank

352

Chart 7-9: The hypothetical development of the balance sheet of a lending bank

353

Chart 7-10: The proportion of adults with an account (%), 2017

361

Chart 7-11: Relations between financial inclusion and financial stability

363

Chart 7-12: Debt cap rules and requirements in Europe

365

Chart 7-13: The threefold target system of concentration

367

Chart 7-14: The relation of optimal concentration to competition and stability

370

Chart 7-15: Factors influencing and shaping the business model change of incumbent institutions

372

Chart 7-16: The effect of the most important FinTech solutions on the value chain

374

Chart 7-17: A lesson learnt (?)

378

Chart 7-18: The development of the number of reported natural incidents worldwide

384

Chart 7-19: The impact of physical and transition risks posed by climate change on banks

386

Chart 7-20: The proportion of banks in Hungary that consider climate change as a relevant risk within the time horizon of their business planning

387

Chart 7-21: Annual investment needs in the EU in order to achieve sustainable development goals

390

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List of charts and tables Chart 8-1: Export to GDP, 1828–2014

399

Chart 8-2: Use of the internet, mobile phones and social media in the world

402

Chart 8-3: The waves of globalisation were caused by cost changes

403

Chart 8-4: The impacts of new technologies and the changing of habits

405

Chart 8-5: Changes in the nature of globalisation

406

Chart 8-6: Export to GDP ratio, 2000-2017

407

Chart 8-7: Growth rate of the export of services

408

Chart 8-8: The share of emerging and developed countries in world trade

409

Chart 8-9: Value added generated in the supply chains

415

Chart 8-10: Level and growth rate of intangible assets

416

Chart 8-11: The most important events causing disruptions in global value chains

419

Chart 8-12: The annual value of sales of the largest companies is as large as certain countries’ GDP.

421

Chart 8-13: Value of exported goods and services as a share of global GDP

426

Chart 8-14: The share of the three economic centres of the world in terms of GDP (purchasing power parity) and trade (2018)

429

Chart 8-15: Share of Asia in global GDP (purchasing power parity).

432

Chart 8-16: Asia’s trade with the EU and the USA (2018)

433

Chart 8-17: Economic corridors of the Belt and Road Initiative.

436

Chart 8-18: Urban population of the world between 1950 and 2030

444

Chart 8-19: Urban agglomerations grouped by population numbers

447

Chart 8-20: Global distribution of world cities as ranked by the GaWC

449

Chart 8-21: Global cities and megaregions

454

— 489 —

List of charts and tables

List of tables Table 2-1: Select journals’ reliance on or connections to other disciplines

Table 2-2: Rankings of GDP and some composite indices in the first 15 countries and Hungary

Table 2-3: Consumer surplus stemming from free digital goods in the USA

Table 4-1: Green bond: Pros and Cons

181

Table 4-2: Classification of climate change physical risks

183

Table 4-3: Main parameters of GBP and CBI frameworks

185

Table 4-4: Examples of SASB sector materiality map

192

Table 7-1: Certain innovations leading to the outbreak of the crisis – initial idea and morally questionable application

379

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