Sustainable GDP

“The concept of the GDP indicator was developed almost a 100 years ago and it has not followed the changes of economic and social requirements.”

Gergely Baksay

“The sustainability turnaround requires not only a new theoretical approach, but also new metrics, therefore GDP needs to be upgraded.”

György Matolcsy

“The new main economic indicator should also take into account environmental, social and financial sustainability.”

Barnabás Virág

SUSTAINABLE GDP

Global Discussion Paper

Edited by

Gergely Baksay, György Matolcsy and Barnabás Virág

MNB Book series

Works previously published in the Magyar Nemzeti Bank book series

dr. Kandrács Cs. (ed.): Stabilitás és bizalom: A magyar pénzügyi felügyelés története [Stability and confidence: The history of Hungarian financial supervision]. MNB, Budapest, 2023

Virág B. and Horváth M. (eds.): Geo awakenings: Building a sustainable future in the emerging Eurasian era. MNB, Budapest, 2023

Matolcsy Gy., Kandrács Cs., Patai M. and Virág B. (eds.): Fenntartható Egyensúly és Felzárkózás 144 pontja [Sustainable Balance and Convergence]. MNB, Budapest, 2022

Patai M. and Horváth M. (eds.): Jelenünk a jövő – Eurázsiai jegybankok az innováció élén [The Future is Now – Eurasian central banks at the forefront of innovation]. MNB, Budapest, 2022

Baksay G., Matolcsy Gy. and Virág B. (eds.): Új fenntartható közgazdaságtan: Globális vitairat [New Sustainable Economics: Global Discussion Paper]. MNB, Budapest, 2022

Banai Á. and Nagy B. (eds.): Egy új kor hajnalán – Pénz a XXI. században [At the Dawn of a New Age – Money in the 21st Century]. MNB, Budapest, 2021

Patai M. and Horváth M. (eds.): Eurázsia kora [Age of Eurasia]. MNB, Budapest, 2021

Matolcsy Gy.: Egyensúly és növekedés 2010–2019. Sereghajtóból újra éllovas [Economic Balance and Growth 2010–2019. From the Last to the First] MNB, Budapest, 2020

Virág B. (ed.): Fenntartható felzárkózás euróval [Long-Term Sustainability and the Euro] MNB, Budapest, 2020

Virág B. (ed.): Tízszer tíz év számokban – Magyarország elmúlt 100 évének gazdaságtörténete [10x10 Years in number – The Economic History of Hungary for the Last 100 Years]. MNB, Budapest, 2020

Kocziszky Gy. (ed.): Etikus közgazdaságtan [Ethical Economics]. MNB, Budapest, 2019

Virág B. (ed.): A jövő fenntartható közgazdaságtana [Long-Term Sustainable Econo-Mix] MNB, Budapest, 2019

Fábián G. and Virág B. (eds.): Bankok a történelemben: innovációk és válságok [Banks in History: Innovations and Crises]. MNB, Budapest, 2018

Lehmann K., Palotai D. and Virág B. (eds.) A magyar út – Célzott jegybanki politika [The Hungarian Way – Targeted Central Bank Policy]. MNB, Budapest, 2017

Vonnák B. (ed.): Modern jegybanki gyakorlat [Modern Central Bank Practices] MNB, Budapest, 2017

Palotai D. and Virág B. (eds.): Versenyképesség és növekedés [Competitiveness and Growth]. MNB, Budapest, 2016

Matolcsy Gy.: Egyensúly és növekedés. Konszolidáció és stabilizáció Magyarországon 2010-2014 [Economic Balance and Growth. Consolidation and stabilisation in Hungary 2010-2014]. Kairosz, Budapest, 2015

SUSTAINABLE GDP

Global Discussion Paper

Edited by

Gergely Baksay, György Matolcsy and Barnabás Virág

Sustainable GDP – Global Discussion Paper

Edited by Gergely Baksay, György Matolcsy and Barnabás Virág

MNB Book series

The authors would like to thank György Matolcsy, Governor of the Magyar Nemzeti Bank, as well as Deputy Governors of the Magyar Nemzeti Bank, for their assistance in the preparation of the book.

Editing © Gergely Baksay, György Matolcsy and Barnabás Virág, 2024

© Magyar Nemzeti Bank, 2024

All rights reserved.

Cover and layout © Budapest Metropolitan University

Published by Magyar Nemzeti Bank

1013 Budapest, Krisztina krt. 55., Hungary www.mnb.hu

Prepress and printing: Prospektus Kft.

8200 Veszprém, Tartu u. 6., Hungary

ISBN 978-615-5318-64-1

CSABA KANDRÁCS, GYÖRGY MATOLCSY AND BARNABÁS VIRÁG

Foreword

“Catching up processes driven by new visions can only be organised around the idea of sustainability.”

György Matolcsy

Achieving the sustainability turnaround requires a renewal of measurement as well as a renewal of thinking. Without measurement, the target cannot be clearly identified, nor can the progress towards it be tracked. However, there are no fully fledged, widely accepted measures of sustainability and sustainable development. The Magyar Nemzeti Bank’s new global discussion paper aims to help measure sustainable economic growth in a similar way to the New Sustainable Economics discussion paper, which served to lay the foundations for the sustainability turnaround.

The revolution in economic theory and measurement has gone hand in hand with previous great innovations in economics. After John Maynard Keynes formulated the foundations of macroeconomics and state-controlled demand in the 1930s, it became necessary to measure economic performance and demand much more accurately than before. In response to this, the system of national accounts and its headline indicator, GDP, were born. It was the combination of theory and measurement that created the basis for the major economic achievements of the 20th century, and without it we would probably not be talking about the post-World War II economic miracle in Europe or the miracles of the Asian Little (and Big) Dragons.

But GDP as a statistical indicator bears the imprint of its time. Its approach made it particularly suitable for measuring the performance of mass-production-based manufacturing industries. Its philosophy did not change with the needs of the economy and society, and GDP took a life of its own, becoming an end rather than a means. However, by the end of the 20th century the outdated metric fuelled outdated economic strategies. As a result, the economic model of the 20th century, measured by GDP, depleted environmental resources, indebted future generations and created unsustainable social tensions in many places.

The sustainability turnaround requires new measures that go beyond GDP, said György Matolcsy in his article containing the 36 points of the New sustainable economics in 2021. “Convergences driven by new visions can only be organised around the idea of sustainability.” If we set ourselves a target, we are halfway there. And if we also start measuring,

we are more than halfway there. Sustainable development can only be achieved if we are able to measure both sustainability and development.

The new character of the 21st century requires new metrics. Therefore, at least four dimensions of sustainability should be added to measuring GDP.

1. Environmental sustainability should be included in the calculation of sustainable GDP. Between 2015 and 2022, we experienced the hottest eight years in human history. Global warming is a fact, but excessive warming is still avoidable. It is never too late, “there is always a way out” – wrote Sándor Kopátsy. Keeping the Earth’s temperature under control can only be achieved through conscious policies to reduce energy intensity and carbon emissions, which require continuous measurements.

2. Sustainable GDP should reflect demographic and income sustainability. The least developed countries have excessively high birth rates, while developed countries have unsustainably low birth rates. No country in Europe has the fertility rate to maintain its population, so the continent’s population is ageing and declining. At the same time, in developed countries, immigration and inequality are leading to social tensions not seen for decades. The distribution of wealth follows the Pareto principle: globally, the top 1 percent own 46 per cent of wealth, while the bottom 50 per cent own only 1 per cent. However, economic growth is only sustainable if it maintains population and social cohesion.

3. Financial sustainability is a key area for measuring sustainability. The nature of economic development is that growth comes from debt and eliminates debt. If this equilibrium is lost, it leads to financial crises, but the equilibrium point is dynamically changing. Total world debt now stands at around 250 per cent of global GDP, 50 percentage points higher than before the 2008–2009 global financial crisis. The level of public and private debt should therefore be taken into account in the calculation of sustainable GDP to a detailed extent.

4. Finally, we need to measure the sustainability of the economy’s capacity to grow. Once the limits of natural and human resources are reached, the main driver of economic growth is productivity improvement, but this has been slowing down in the developed world

for several decades. To re-accelerate this, we need to apply the formula 4T, which says the nurturing and exploitation of capital, knowledge, technology and talent can lead to productivity growth again. To achieve this turnaround, the capacity and potential output of the economy must be measured.

Publications aiming at discussing the renewal of GDP and measuring the sustainability of economic development have not yet been published in Hungarian. However, the international literature is quite rich and includes, among others, the development of comprehensive concepts and alternative metrics. The limitations of GDP in measuring sustainability and well-being, and the research and new metrics that seek to overcome them, are presented in the first part of the book.

The way the economy works today evokes the world of quantum mechanics, which must be reflected in measurement and metrics. As in quantum mechanics, the role of uncertainty in measuring sustainability must be accepted. And just as in physics, where the observed variables can be dual or multiple in nature, the dimensions of sustainability are not the same. Therefore, in the second and third parts of the discussion paper, two measurement methods are used to estimate the sustainable level of GDP in the “electron cloud” around GDP as measured by traditional statistics.

The discussion paper was produced in cooperation between the Magyar Nemzeti Bank, the Hungarian Central Statistical Office and the Hungarian academic community. In addition to experts from the MNB and the HCSO, several chapters have also been contributed by academics and researchers from Budapest University of Technology and Economics, John von Neumann University and Pázmány Péter Catholic University.

As with all discussion papers, our aim is to move forward in our collective thinking. Just as Simon Kuznets presented his first estimate for the calculation of GDP a year after Keynes’s General Theory, this discussion paper and calculation follows on from the New Sustainable Economics publication. We recommend this standalone publication, as well as both of them together to anyone who, like us, believes that a sustainability turnaround is not possible without a renewal of thinking and measurement.

RAEKWON CHUNG

Introduction

“You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.”

Richard Buckminster Fuller

YOU GET WHAT YOU MEASURE

We have measured what we produced since Simon Kuznets developed GDP in the 1930s. And we got economic growth, the sum of what we produce. Since the Second World War until the first oil shock in 1973, during the so-called Golden Age of capitalism, the extended period of sustained high economic growth improved quality of life and environmental performance.

The virtuous cycle of economic growth improving the quality of life and environmental performance worked relatively well until neoliberalism surged in the 1990s. Until then measuring GDP delivered not only what we produced but also what we wanted. In other words, short-term productivity improved long-term sustainability as well.

In the wake of deepening globalisation and financial liberalisation, the cycle among the economic growth, quality of life and environmental performance begins to creak a discordant outcry. Economic growth incurred widening income gaps and worsening ecological sustainability. The social safety net gets weaker and climate crisis exacerbated.

The virtuous cycle between short-term productivity and long-term sustainability turned into a vicious cycle. Economic growth no longer improves long term sustainability. The positive relationship turned into negative one. A vicious cycle among the economic growth, quality of life and environmental performance sets into our economic system.

GDP OUTLIVED ITS MISSION: PARADIGM SHIFT TOWARDS SUSTAINABLE DEVELOPMENT

At the Rio Earth Summit in 1992, the United Nations adopted a landmark document titled “Agenda 21”, a blueprint for sustainable development for the 21st century. The global community confirmed its commitment to pursue sustainable development, a new paradigm for our development; pursuing economic development while improving the quality of life and the resilience of our eco-system.

However, we are still sticking to GDP as a measure of our development. In spite of many attempts to come up with new measures for sustainable development, GDP still remains the central measurement of our economic policymaking.

As long as we are stuck with GDP, measuring short-term production, we cannot align our economic policymaking towards the new paradigm of sustainable development that pursues long-term sustainability.

SUSTAINABLE GDP AS A TOOL FOR SUSTAINABLE DEVELOPMENT

In spite of many shortcomings of GDP, there are possibilities we can still improvise GDP as a tool for sustainable development until we come up with a comprehensive measure for long-term sustainability.

Numerous attempts have been made so far by many international organisations, including the United Nations and the OECD, to come up with a new measure that could replace GDP. Some of the examples are HDI (Human Development Index), GPI (Genuine Progress Index), GNH (Gross National Happiness), SPI (Social Progress Index) and Ecological Footprint.

Specific suggestions made by the OECD include the development of the System of National Accounts (SNA), introduction of satellite accounts, the Quality of Life Indicator and an indicator for inclusive development. All of these are meaningful suggestions that could broaden the scope of economic measurement beyond GDP.

In spite of all these numerous attempts, none of them comes close to the concept of Sustainable GDP, making GDP sustainable; a novel attempt by the Central Bank of Hungary.

The idea of making GDP sustainable presents numerous merits compared to the attempts to replace GDP with other measurements, as none of the new measurements suggested so far to replace GDP could be readily available for practical use in daily policymaking.

MAKING INVISIBLE SOCIAL AND ECOLOGICAL COSTS VISIBLE

GDP could be made sustainable if we could internalise social and ecological costs in calculating GDP. We are running many invisible social and ecological costs in maximising short-term production. Many social and ecological costs are not visible as we don’t have a price for them. But we can measure the costs by calculating the waste of the economic goods that has a market price.

The cost of traffic congestion presents an interesting case. Many big cities are suffering from heavy traffic congestion. The waste of gasoline and man-hours due to traffic congestion amounts to whopping 3.6 per cent of GDP in 2018 in South Korea. This is a huge cost even compared to the heavy spending on defence, which stands at 2.2 per cent of Korean GDP. If we add the health cost of air pollution caused by the traffic congestion, it will be even much higher. Korea is losing a big chunk of its GDP from traffic congestion. As this traffic congestion cost is invisible, the Korean Government is cutting down instead of increasing its investment in rail and metro under the excuse that they are running a deficit. But if the benefit the public transport is making by reducing the cost of traffic congestion is added into the revenue, public transport cannot run a deficit. If we add the avoided CO₂ emission by the public transport as a benefit, the revenue will be an even much higher surplus, not a deficit.

Another critical factor that could make GDP sustainable is internalising the cost of CO₂ emissions into the calculation of GDP. The cost of annual increased amount of CO₂ emission can be calculated by applying the shadow price of carbon to be set by each Government. In Europe, the shadow price of carbon could be the price of EU ETS (Emissions Trading System), which currently runs around at €100. Thus, the cost of 1 million tonnes of increased CO₂ emission will be €100 million. This amount needs to be deducted from the GDP. If CO₂ emission is reduced by 100 million tonnes, then €100 million can be added to the GDP. Such internalisation of CO₂ emission costs into GDP will make the GDP climate friendly and sustainable.

Traffic congestion and CO₂ emissions are just initial examples of ecological and social costs that need to be subtracted from GDP. There can be many more such costs that could be internalised into GDP. The more ecological and social costs are internalised, the more sustainable GDP can become.

VALUE OF SUSTAINABLE GDP: SUSTAINABLE ALLOCATION OF RESOURCES

One might wonder what the value of Sustainable GDP would be. One of the real values of Sustainable GDP will be the possibility of making our resource and investment allocation aligned with longterm sustainability.

For example, investment in public transport is often cut short in many countries based on the excuse of running a deficit, in particular under the neo-liberal paradigm sweeping through globalisation that focuses only on visible short-term return on investment while ignoring invisible long-term social and ecological costs.

Under the Sustainable GDP paradigm, if the contribution public transport is making in reducing traffic congestion and CO₂ emission is added as revenue, then in fact public transport is making a surplus, not a deficit. Thus, investment in public transport has to be increased rather than cut short.

In Korea, investment for express metro lines that goes through the centre of Seoul from various suburban areas has been rejected repeatedly for years based on a feasibility study that focused mainly on profitability and monetary return on investment, in spite of the huge potential for reducing the notorious traffic congestion in the Seoul metropolitan area and avoiding unnecessary CO₂ emissions from driving private cars. But if a sustainable GDP paradigm is applied that makes invisible social and ecological costs visible and such costs are reflected in the calculation of return on investment of those express metro lines, those express metro lines would have been constructed and running already, making a substantial contribution to reducing traffic congestion and CO₂ emissions.

This is just an example. There could be more cases in many other countries. Making invisible social and ecological costs visible based on a sustainable GDP paradigm will stimulate huge increases in socially inclusive and ecologically green investments and resource allocation, thus contributing to long-term sustainability.

SUSTAINABLE GDP: A PROCESS TO BE DEVELOPED AND IMPROVED

Making GDP sustainable is a process that cannot be completed in one go. It will take time to identify various invisible ecological and social costs and the process of valuing the costs could also require learning by doing.

The process of making GDP sustainable will not be easy and simple. But the need to make GDP sustainable is urgent and getting ever more critical as climate and social crises aggravate day by day. Collective wisdom and collaboration for trial and error will be critical in promoting sustainable GDP as a driver of long-term sustainability.

LIMITATIONS OF GDP IN MEASURING SUSTAINABILITY AND WELL-BEING

TIBOR PRINCZ-JAKOVICS AND GYÖRGY ÁDÁM HORVÁTH

Shortcomings in measuring sustainability with GDP

“Not everything that counts can be counted, and not everything that can be counted counts.”

Albert Einstein

GDP is an indicator of current economic performance. However, it does not include information on the sustainability of that economic performance. This chapter summarises the methodological limitations of GDP in the four aspects of sustainability (ecology, society, finance and innovation). From the perspective of environmental sustainability, the most significant limitation of GDP is the lack of reflection on the quantitative and qualitative changes in natural capital. From a social point of view, the shortcoming in measuring sustainable growth with GDP is due to the fact that the reduction of inequalities, the development of human capital (needed to generate future economic output) and demographic trends are only partially reflected in national accounts. From a financial perspective, unlike the national accounts, GDP does not give an indication of the drivers of growth, since it does not track what share of growth is due to investments of domestic assets and what share of it can be attributed to potentially unsustainable indebtedness. Finally, GDP does not measure the capacity of the economy to adapt and innovate. In that sense, it does not tell us much about the sustainability of growth in the future.

INTRODUCTION

The concept of sustainable development first appeared in the 1987 UN report Our Common Future by the Bruntland Commission (United Nations, 1987). Since then, the international and Hungarian professional community has made considerable efforts to elaborate the theory of sustainable development, answer conceptual questions, set targets and solve measurement problems.

Our aim is to explore the problem of measuring sustainability, building on the theoretical background and experience of translatability into practice. In this chapter, therefore, we look beyond the theoretical approach to sustainability to consider its practical applicability. Our work follows the approach previously used by the MNB to examine the sustainability criteria, thus illustrating the

shortcomings of GDP through environmental, social, economic and financial aspects of measurement. Generally speaking GDP cannot provide meaningful information on economic sustainability beyond the current economic performance, based on the criteria presented in more detail below. Sustainability must be understood in a broader context than the exclusivity of economic performance, and thus needs to be complemented by environmental, social and financial dimensions.

SHORTCOMINGS: ENVIRONMENTAL ASPECTS

In examining environmental aspects, we look in more detail at the factors that are accepted in the field of environmental economics. The international and Hungarian literature (e.g., Szlávik, 2007; Bartus and Szalai, 2014) deals with the limitations of GDP and alternative indicators. The identification of shortcomings and the possibility of correcting the identified issues open up a range of alternatives to improve GDP or to use a combination of several indicators together with GDP.

Environmental quality, state of natural capital

GDP does not fundamentally reflect changes in the quality of the environment because it was not created for that purpose. It is not intended to measure the quality of life or sustainability, and therefore necessarily does not include the results of external processes outside the economy that are not directly linked to economic performance. We have micro-level indicators on the quality of the environment (pollution levels, state of natural resources) that can be considered accurate, but we do not have sufficient macro indicators. If we want to take account of changes in the state of natural resources in macrolevel decision-making, we need a suitable indicator. The variety of indicators currently available is shown in Chapters 5 to 7.

Among the shortcomings in terms of environmental aspects, it is worth highlighting the changes in natural capital and the impact of shocks originating outside the markets that have environmental relevance. Also, GDP is a flow variable and not a stock variable, so it is only partially suitable to measure the size of inventories and wealth (although there is a place for it in the system of national accounts). The first environmental shortcoming is therefore the lack of assessment of the quantitative changes of natural capital and of the qualitative changes in the state of the environment. Economic processes use natural resources, then production and consumption generate waste/by-products. In general, the quantity and quality of natural resources is decreasing while other resources are increasing, resulting in an environmentally unfavourable conversion between different forms of capital. Achieving a weak version of sustainability requires preserving the combined capital sum of all resources over the long term, so different changes in capital sizes have a significant impact on our sustainability potential. Strong sustainability goes further than the above and requires the conservation of natural capital per se.

The definition of the weak version of sustainability is that forms of capital can be interconverted while keeping the total capital of all resources fixed.

A fundamental economic reason for the excessive environmental damage caused by economic activities is the existence of externalities. According to the perfect market theory of classical economics, if the use of a resource or the production of a product causes some damage, the value of this damage is incorporated into the price of the product or service. In this case, for example, the polluting product would be more expensive, which would force the producer to reduce excessive pollution. In practice, however, part of the costs incurred in the activity are not incurred on the producer side (i.e. they become an externality)

and thereby are not included in the price of the product, either. Consequently, the market price of the product is lower than its real cost, taking into account its environmentally damaging impact. Thus, the demand for the product is higher than it would be at a higher price, so a large amount of the product is consumed, which increases its environmental impact. Depending on the sign of the change it causes, the externality can have a negative or positive value, but here we focus on the negative effects.

Environmental problems affect the level of aggregate welfare of the national economy and also generate unintended income redistribution within aggregate welfare by not compensating those affected by the negative externality for their losses, even though additional income is generated for those causing the impact. For example, the transport sector alone, apart from its many benefits, causes social damage equivalent to 6.6 per cent of GDP, including pollution, time spent in congestion and accidents (European Commission et al., 2019).

A negative externality occurs when the incremental costs of producing or consuming a product are not reflected in its producer or consumer price but are spread across other actors in the economy.

One of the most cited examples of negative externalities is the tragedy of the commons (Hardin, 1968). For those public goods where exclusion is not feasible due to open access, there will be no incentive for anyone to cover the cost of maintaining the resource. The tragic consequence is that the public good is over-used and the resource is degraded due to wasting. In order to avoid socio-economic damage caused by negative externalities and the degradation of public goods, environmental regulation is needed to internalise externalities, for example through environmental taxes. The complete consumption of environmental resources and public goods can increase GDP

today at the cost of future economic performance, thus reducing the sustainability of GDP.

Another measurement anomaly is related to damage control activities. These are activities that are necessary to deal with negative externalities and repair the damage caused. These activities are as much a part of GDP as other construction-related investments. Since investments in environmental remediation aimed at the elimination of existing pollution are counted as positive, they are taken into account in a way that runs counter to the sustainability approach. This bias is particularly striking in periods when the share of damage control in investments is high (e.g., in times of accidents or disasters).

Ecosystem services

GDP is also unable to measure the services provided by nature (e.g., self-cleaning capacity) that mitigate the environmental damage caused by the economy. Therefore, their omission is considered a shortcoming. A comprehensive study entitled “Millennium Ecosystem Assessment”, compiled by UN experts, analysed the ecosystem services. Ecosystems provide a range of valuable services that, according to public estimations, may reach up to nearly double the global GDP, contributing more to welfare than economic output (Costanza et al., 1997). The diversity of services provided by ecosystems is illustrated in Figure 1.1.

PhotosynthesisSoilFormation

Biodiversity

Habitat

Clean Water Food

Fish Wood Pollination

Ecosystem Services

What Nature provides us for free

StewardshipAestheticRecreation

SUPPORTING PROVISIONING REGULATING CULTURAL

Education

Clean Air

Cool temp.

Controlflooding

StorePurifywater

Carbon

Source: TEEB Europe, https://ecology.fnal.gov/ecosystem-services/

GDP shortcomings in terms of natural resource characteristics

We use natural resources in economic processes, regardless of whether we analyse the processes from the production or consumption side. We use natural resources both as inputs and outputs: nature is both the cradle and the grave of the goods and services we produce. Both processes involve taking raw materials and energy from nature; transforming them and producing final

Figure 1.1 Types of ecosystem services

products, intermediate products and by-products; and returning them to nature as waste at the end of their useful life.

Resource-side problems

Several approaches are used to characterise input resources. Resources include non-renewable, renewable and conditionally renewable resources. Non-renewable resources are destroyed in the course of their use, and either they are not produced again (e.g., fissile materials) or they take much longer to be replenished than is usual in economic thinking (e.g., for natural gas, oil and coal it takes thousands or millions of years). In the case of renewable resources, the rate of natural renewal is sufficiently fast, so that the material and energy flows from them can be maintained virtually continuously. Some resources are conditionally renewable under human control and supervision. This requires either the use of additional resources or letting nature take its course, such as in the case of soil fertility (humus) or reforestation.

From the perspective of GDP, materials, goods and services used for production increase GDP, while discarding them reduces GDP. Furthermore, the change in the quality of the regenerated or replenished materials is only partially accounted for in GDP, if at all. Let us illustrate this point with the example of timber: we can tell how much a cubic metre of timber beams adds to GDP, but how high a tree trunk grows is irrelevant to GDP. As became clear after the 2019 fire that destroyed the roof of Notre Dame Cathedral in Paris, forests nurtured artificially and originating from renewable sources are not suitable for an authentic reconstruction, as the trees do not grow large enough. In other words, even if we can replenish some resources, they may not be the same as under natural conditions. It is also a distorting factor that near-natural methods of protection/ yield improvement do not increase GDP if their creation is free, but chemical, artificial methods do so through the output of the chemical industry. Of course, in both cases the change in yields is reflected

in the measure of economic performance. Monocultures and loss of genetic diversity are also irrelevant to GDP. Such and similar biologicalgenetic peculiarities are insignificant externalities in terms of GDP, even though they may lead to a reduction in GDP later on. Indigenous or more natural species are essential for biodiversity, but they mean nothing to GDP, even if they are the basis for future GDP.

Output-side problems

On the output side, resources are important because of their pollutant absorption and storage capacity. Some media are used for temporary storage of pollutants, while others are used for permanent storage. For temporary storage, the duration of regeneration and the amount of human intervention required are important considerations. Rapidly regenerating storage media are able to return to full availability sooner, making any GDP decline temporary. Accelerating this means increasing GDP. For permanent storage media, there may be a need for human control, which also has an impact on GDP.

Perhaps the greatest global challenge of our time is climate change and global warming caused by anthropogenic greenhouse gases. Some have high hopes for high- and low-technology solutions to reduce the amount of greenhouse gases in the atmosphere, such as the capture of CO2 from the atmosphere by chemical-physical means, or the injection of the CO2 produced into gas storage (Carbon Capture and Storage, CCS), or its utilisation (Carbon Capture, Use and Storage, CCUS). At the moment, however, their costs and capacities do not allow this to be a viable alternative in the short term. By contrast, the cheapest carbon mitigation strategy is still no emissions or natural sequestration by trees, which has a neutral reducing effect in terms of GDP.

SHORTCOMINGS: SOCIAL ASPECTS

GDP is primarily a measure of productive activity, based on a methodology that has been established for almost 100 years. Households’ activities appear in the national accounts since households are the source of labour input of production, the recipients of labour income and consumers of goods and services, as well as savers. However, the national accounts reveal little or nothing about their quality of human capital, the nature of its contribution to production and the distribution of income. Also, non-productive human resources (children, the elderly) do not appear in the national accounts either.

Inequalities

On the road to a sustainable society, differences in the material welfare of individuals must also remain sustainable (IUCN et al., 1991). However, the optimal level and limits cannot be determined in the same way as for natural resources, as they depend on subjective factors, values, norms and cultural attitudes. Different societies tolerate and consider optimal very different levels of inequality. Moreover, these levels are constantly changing. However, in general, excessive levels of inequality can, in the long run, undermine social cohesion and make sustainability efforts more difficult. However, changes in these aspects of sustainability are not measured by GDP because differences in income distribution are not included. GDP includes both the income and consumption of higher and lower income groups, while it does not capture the changes in the gap between them.

GDP fails to capture not only the current level of inequality, but it also fails to account for the different sources of it. This is why the Sustainable Development Goals (SDGs), set by the UN for the period up to 2030, focus on inequality. Of these, Goal 10 sets out endeavours to reduce inequalities in the most direct way: “Reduce inequality within and among countries” (United Nations, 2015, p. 28).

Economic and social statistics naturally measure inequality using other indicators. According to HCSO data, income inequality in Hungary is below the EU average, as shown by the ratio of income between the richest and poorest fifth of the population in Figure 1.2.

Hungary

EU28

Source: Authors’ editing, based on HCSO, https://www.ksh.hu/sdg/2-1-sdg-10.html

Improving human resources (demography, health, education)

At the time of writing the discussion paper, the human population had passed 8 billion. The global metrics of total population masks significant regional differences. Population trends vary around the world: less developed countries have increasing populations, while developed regions have too low fertility rates. There are successful programmes to increase fertility in the developed countries. However, it is challenging to reach the desired fertility rate of above 2.1.

Figure 1.2 The evolution of income inequality in Hungary and the EU

Hungary belongs to a group of countries with a long-term trend of population decline and where demographic trends have a negative impact on future economic performance. In 2070, according to standard versions of the various population projections, the population size in Hungary will be between 7.66 and 8.93 million. As a result, the number of people of working age will fall, and their share in proportion to the elderly will also fall. Based on these analyses, it can be concluded that it is necessary to start preparing for the increase in the dependency ratio as soon as possible (Drabancz and Berde, 2022).

Not only the quantitative but also the qualitative characteristics of the population are important in terms of economic performance, sustainability and well-being. Human capital is the sum of individual knowledge and competences, the utilisation of which is naturally influenced by health. At the level of the national economy, human capital is the sum of individual human capital, so population size also matters in this respect. The total amount of capital to be preserved to meet sustainability requirements also includes human capital. The quality of human capital is best nurtured and developed through education and health services in the broad sense.

Human capital cannot be measured in itself, but many of its characteristics can. The National Council for Sustainable Development’s “Guidelines to a Sustainable Future” (NCSD, 2020) provides a detailed analysis of the relationship between health and the efficiency of the health care system, including relevant data from the HCSO. Health can be measured in terms of inputs such as health expenditure as a share of GDP, health infrastructure and staff numbers. There are significant differences in terms of ownership of health care provider companies: in some countries it is the private sector, while in some other countries it is the public sector that is the main provider of health care services. The output indicators of health include life expectancy, preventable and treatable mortality, and deaths by leading causes of death. Some related aspects to health are fertility and the prevalence of alcohol and tobacco consumption, neither of which is directly related to health outputs.

Human capital accumulation via gaining new knowledge and competences can be developed by education. Of course, this does not only apply to school-based education, although it is particularly important in this area. Individual knowledge and performance can only be maintained at a high level if learning does not end when leaving school, but continues throughout life, or at least one’s working life. Education, like health, has measurable input and output indicators. The input indicators are expenditures on education, the size and condition of the infrastructure, and the number of teachers. The transition between input and output indicators is the number of years spent in education and the distribution of the population by educational attainment. Qualitative indicators provide information on real results, such as international education surveys, university rankings, digital skills and the ability of the education system to eliminate any disadvantages arising from the home environment.

In summary, although GDP reflects the consumption-type and physical-type investments in health care and education system (the two most important providers of services generating high social value), it offers only limited information about the quality of their services and their contribution to human capital formation.

SHORTCOMINGS: ECONOMIC ASPECTS

Chapter 2 of this book deals in detail with the problems arising from the approach to and methodology of GDP. Here we mention only those factors that are closely linked to sustainability.

The national system as a whole, and GDP as part of it, is based on the positive, descriptive-analytical branch of economics, with its strongly accounting-based methodology. We get a picture of what is happening, what happened and what is to come. These studies fundamentally lack value judgements: they do not examine whether a phenomenon is desirable or not. GDP as an economic-financial outcome can be overheated, for example by unnecessary investment, unnecessary trade, warfare or even the premature consumption of

natural capital. Herman Daly called this “uneconomic growth”, which in time will have greater social and environmental costs and damage than benefits (Daly, 2005).

GDP, like all other statistical measures, is retrospective, i.e., it shows the economic performance of the past period. However, GDP cannot predict whether past performance can be repeated in the future. While in the short term certain factors can be taken as constant, in the long term all factors must be seen as changing: dwindling and exploited resource supplies, the ever-increasing supply of renewable energy, changes in demand due to socio-economic-environmental factors, global political events – all influence future trends. Among the factors that determine future GDP, information on the amount of capital accumulated and labour available is included in the national accounts, but there is no information on factors with uncertain outcomes such as innovation or technological progress. In particular, it is important to have an accurate understanding of these, as they are the most important sources of economic growth in the long term. According to the system of national accounts and the accepted economic theory, the two input factors behind GDP are capital and labour. So economic growth in principle comes from their growth. However, the statistics show that the increase in production cannot be explained solely by an increase in capital employed and labour time spent. The remainder – the part of economic growth that cannot be explained by quantitative factors – is due to improvements in productivity and technology (called total factor productivity because it increases the efficiency of both factors, i.e., capital and labour). Experience indicates that this is the source of much of the economic growth (Figure 1.3).

Taiwan (1969-1997) Singapore (1986-2007)

Republic of Korea (1981-2007) Ireland (1986-2007) Japan (1950-1995) Hong Kong (1960-2011) Austria (1954-1973) Finland (1993-2011)

Technology and efficiency (TFP) Labour Capital GDP (%)

Source: Penn World Table, MNB calculation

SHORTCOMINGS: MONETARY ASPECTS

Ensuring financial sustainability is a vital condition for sustainable catching-up to ensure welfare. Fiscal sustainability can be assessed from several angles. The three most important elements are the indebtedness of the public sector and the private sectors and the country’s external balance position. The specificity of the factors listed is that they are measurable, and some of them are included in the financial accounts of national accounts. However, if we look only at gross domestic product (GDP), we do not get a picture of them.

Figure 1.3 Sources of successful growth periods

The sustainability of fiscal policy should be assessed in the short, medium and long term, and is most often characterised by gross public debt as a share of GDP and by indicators describing its change and structure. The public debt ratio incorporates the impact of – among other things – the primary budget balance, government interest expenditure, inflation, the exchange rate and real economic growth, and is therefore an important measure of the effectiveness of economic policy measures. However, the level of indebtedness alone is not sufficient to assess solvency. Still, it is essential to look at the direction and extent to which debt and its structure are changing. There is no professional consensus on the optimal level or change in the debt ratio. Some studies link the optimal level to the level of development of countries, while most economic schools of thought argue that indebtedness with a domestic source is significantly more sustainable.

In general, developed countries can maintain higher debt levels than those with lower GDPs, which may be due to a more developed financial system, higher tax potential and greater confidence in

Figure 1.4 Development of public debt in the countries of the world (2022)

economic governance. In many countries around the world, public debt as a share of GDP has exceeded 100 per cent, i.e., debt exceeds one year’s domestic product (Figure 1.4). In the past, this tended to happen only in warfare situations.

Not only the state, but also the private sector – households and companies – are falling into debt. Just like public debt, credit can be a source of or a barrier to economic growth. The question is how the debt was used and, in part, under what conditions it was taken on. Loans for investments that will pay off later can accelerate GDP growth by bringing forward developments that would only be implemented later with company funds alone. On the other hand, those who cover their current expenditure with debt can quickly find themselves in a debt trap, i.e., they can only cover their debts with new, even higher amounts of debt. This process is not sustainable.

The importance of the debt structure has also been strongly illustrated by the experience of recent decades in Hungary. It is mainly smaller, less or moderately developed countries that are indebted in foreign currency. The risk of foreign currency debt is particularly high when it is not accompanied by income in foreign currency, because the borrower is then fully exposed to exchange rate risk. Some economists called the limit on domestic foreign currency debt, and hence the reliance on foreign currency debt, an “original sin”, suitably characterising its gravity (Eichengreen and Hausmann, 1999). Another risk of the debt structure depends on whether the loan has a fixed or variable interest rate. It is worth finding the optimal balance between the two, bearing in mind that variable interest rates always carry a higher risk.

Private debt also tends to be higher in more developed countries. The causal link between higher economic development and financial intermediation is two-way: with higher economic development, financial intermediation becomes more prevalent. At the same time, lending contributes to economic development, at least to some extent (Figure 1.5).

An important dimension of financial sustainability is a country’s financial position vis-à-vis the rest of the world. The current balance of payments shows the extent to which the economy’s current expenditure abroad is covered by income from abroad, thus giving an idea of the economy’s external balance and its reliance on external resources. The current account is the sum of the external trade balance (goods and services) and the income balance (wages, profits, interest). In general, a current account surplus is more favourable than a deficit, but an excessive surplus may also indicate imbalances or an unhealthy economic structure. The main negative consequence of the current account deficit is that it typically leads to an increase in external debt (Figure 2.6). The only way to avoid this is if foreign actors finance the deficit not with debt but with investment (FDI or financial investment). However, investments almost never fully cover the current account deficit.

As the global financial crisis revealed in the case of Hungary, excessive indebtedness to foreign actors poses external vulnerability problems, financing and refinancing risks. An important measure of the country’s external indebtedness is net external debt excluding

Figure 1.5 Financial development effect on economic growth

shareholder loans, which shows the amount of the country’s liabilities owed to non-residents after deducting receivables from the same. During the crisis, Hungary’s net external debt was several times the level that of the average for Central and Eastern Europe, posing a serious financial sustainability problem. However, thanks to the high financing capacity in the past decade and the reduction of foreign debt, the Hungarian economy managed to overcome its significant disadvantage in this indicator. The indicator improved steadily (and at a rate that is outstanding in the EU), falling from close to 55 per cent in 2009 to 7 per cent in 2019, and has remained at a similar level of between 7 and 8 per cent since then.

Figure 1.6 Evolution of global debt, 1970–2022 (as a percentage of GDP)

CONCLUSIONS

Our research finds that GDP is not a suitable measure of sustainable economic performance. The factors underlying future performance, the quality of human capital, indebtedness, environmental issues and innovation capacity are not reflected at all in the current GDP. This is not only a problem in the long term; history’s economic crises show that accumulated imbalances can lead to unexpected falls in GDP in the short term. Recessions can set back living standards for complete generations. We can achieve better and more balanced economic policy decisions and contribute to the full quantification of efforts for sustainability by overcoming methodological, data collection and institutional barriers to measuring real progress. To measure sustainable development, GDP must be complemented by indicators measuring sustainability.

MAGDOLNA CSATH

Gaps in GDP as a measure of economic performance

“Someone’s sitting in the shade today because someone planted a tree a long time ago.”

Warren Buffett

GDP as part of the system of national accounts is an economic statistical measure developed in the first half of the 20th century. This provided data on economic developments to analysts, economic policymakers and, of course, the public with unprecedented accuracy and detail. However, the circumstances in which GDP was created still influence and limit its usability even today. The system of national accounts emerged in an era when the most important sectors were industry and agriculture, which had just switched to mass production, companies were relatively closely linked to national economies and production chains were linear. In contrast, nowadays, the service industry is the largest sector in all developed countries, with multinational companies covering the globe and platformbased or seemingly free services becoming more and more common. While the methodology for measuring GDP has changed over the past decades, questions were raised about whether GDP is a good measure of economic performance.

In this chapter we demonstrate the limitations of GDP as a measure of economic performance. We discuss issues such as the problems of measuring household work and volunteering, the informal economy and quality characteristics, and how ignoring the negative externalities of growth can mislead decision makers, leading to decisions that may even hamper the sustainability of growth in the longer term. The chapter also illustrates the danger of growth being accompanied by rising deficits and debt, and that economic growth can occur alongside rising inequalities and regional disparities, and even in a poor economic structure. Finally, we address the fact that globalisation, digitalisation and infocommunications have created new situations that GDP cannot handle. These include the issue of rent seeking in transfer pricing and the value creation of free services offered by the social economy, IT and platforms.

INTRODUCTION

The GDP indicator was developed by Simon Kuznets, who worked as an economist at the US National Bureau of Economic Research. Kuznets was commissioned by the US Department of Commerce to estimate US national income in order to assess the impact of the Great Depression. In 1937, he presented his calculations to Congress under the title “National Income 1929–35”.

However, even from the beginning, GDP was not designed to measure social well-being. Its purpose was to measure production capacity and economic growth. This was also pointed out by Kuznets himself. Nevertheless, economic policymakers and economists often talk about it as a measure of the development of a nation in itself. Today it is generally accepted that growth measured by GDP and economic development are two different things. While growth is a quantitative concept and basically reflects the results of production, development in turn expresses the efficiency of the economic structure, the functioning of the institutional system, the quality of human wealth, the degree of inequality, the possibility of access to education and health care.

McKeown (2022) stresses the importance of measuring national well-being, because, in his view, it is a way of analysing progress. According to the OECD (2018), no single indicator is a good measure of the performance of a country’s economy. The importance of measuring real results in multiple dimensions has long been explored by the MNB (Palotai and Virág, 2016; Virág, 2019). Good measurement would be important because, as Sen et al. (2010) point out, it is important for performance-oriented societies to have a complete picture of real performance. If they don’t do so, they may set the wrong goals, and in trying to achieve them, their performance will be poorer. Some authors assume that GDP will be replaced by other measures by 2030, as shown in Figure 2.1.

Source: Hoekstra, 2019

Schumpeter is invoked for the idea of creative destruction, to suggest that the new indicator will also be an innovation bringing “creative destruction”, which eliminates one indicator (GDP) but creates another. In this direction, several initiatives have already been taken to modify GDP or to use other indicators alongside it.

In 2008, the French government asked a commission of eminent economists to examine how to better measure economic performance and social progress (Commission on the Measurement of Economic Performance and Social Progress). The committee was chaired by Nobel laureate Joseph E. Stiglitz and advised by Nobel laureate Amartya Sen. New Zealand’s Prime Minister Jacinda Ardern announced in a speech at the 2019 Davos Conference that her government intended to present a well-being budget after July 2019, one that addresses not only economic well-being but also social well-being and that also sets targets in this area. In the UK, the Office for National Statistics and the Treasury are also experimenting with ways of expanding the GDP indicator to take into account the effects of growth on people, climate and the environment, as well as other important factors. This is reported by Heys (2022), who adds that the UK Office for National Statistics now regularly publishes quarterly wellbeing indicators alongside GDP. However, the methodology is still being developed, and social feedback is expected.

Figure 2.1 The “Schumpeterian Dream”

THE MOST IMPORTANT SHORTCOMINGS OF GDP

In Table 2.1, we group the most important shortcomings of GDP into three main categories, some of which developed over time and some of which were described as methodological problems from the outset. These shortcomings cause measurement problems of varying magnitude, and cannot be fully separated, since ultimately the economy, environment and society form a larger system.

Table 2.1 The most important shortcomings of GDP

BASIC METHODOLOGICAL PROBLEMS

• M easures only what is monetary: it is insensitive to the creation of value that is useful but cannot be measured in monetary terms (work at home, volunteering)

• C annot measure, only estimates the performance of the informal economy

• Counts depreciating activities as valuable (speculation, damaging activities, etc.)

• Insensitive to the negative environmental and social impacts of economic growth

• C annot distinguish between price and value

• Quantity- and not qualityoriented

• Past-oriented, short-term approach

MEASUREMENT PROBLEMS

• Insensitive to debt and deficit growth

• D oes not perceive when growth occurs in a distorted economic structure

• I nsensitive to rising inequalities, regional problems

• D oes not measure the differential impact of alternatives on GDP in the case of investments (returns, yields, time effects, “opportunity cost”)

• U nable to measure investment in human capital

• Unable to measure the correlation between GDP growth and “well-being”

• Unable to measure well the value-creating or rent seeking effects of public administration and government organisations

PROBLEMS CAUSED BY CHANGES IN THE ECONOMIC ENVIRONMENT

• D oes not measure well the impact of transfer pricing on GDP, which is a consequence of globalisation

• D oes not measure the value creation of free IT and knowledge products

• D oes not measure well the value of free (or seemingly free) products and services

• Insensitive to the valueadding impact of the sharing economy

• In general, the growing role of services makes it difficult to measure performance objectively in terms of GDP

Source: Own editing

In what follows, we highlight and analyse the most important considerations of the three themes, relying also on international literature.

BASIC METHODOLOGICAL PROBLEMS

Some methodological problems have characterised the GDP indicator since its inception. It may be added that, the indicator was not designed originally to address some of the mentioned problems. For example, GDP ignores the harmful social, environmental and climate change impacts of economic growth. For instance, the production of cars increases GDP, but emissions do not reduce the value of GDP. The construction of new buildings, factories and warehouses contributes to GDP growth, but the fact that it may require cutting down forests or paving agricultural land does not reduce its value. These characteristics are noteworthy because if we measure incorrectly, we can make bad decisions. Since GDP is not sensitive to the environmental, human and social consequences of growth, decision-makers may consider “unsustainable” or “harmful” growth as good, and may support environmentally, humanly and socially unsustainable growth in the absence of an assessment of the consequences. The costs of negative impacts such as environmental degradation, air pollution, health deterioration, reduced life expectancy and other negative impacts appear, though with a temporal delay, and can hold back important investments needed for growth. A particular concern about the negative consequences (externalities) of economic growth is that, while they do not reduce GDP, the elimination of the negative effects increases GDP. For example, if a company releases a pollutant into the environment, it does not appear as a GDP-reducing factor. However, eliminating pollution means increasing GDP. So it might seem that the more damage – natural or otherwise, such as to health –economic growth measured by GDP causes, the better for the economy. Let us look at some examples.

1. If someone has a heart attack and therefore needs to be treated, it increases the output of the health sector.

2. If somebody’s house burns down and it has to be replaced, including furniture, it adds to GDP.

3. If oil from an oil tanker is spilled into the sea and it has to be cleaned up, it increases GDP.

4. If someone chooses to work shorter hours to have more free time and thus to improve his/her quality of life, this reduces GDP because of the reduction in income.

5. If a household worker who used to clean for money marries her employer and cleans “for free”, this reduces GDP.

6. Divorce increases GDP because of the legal fees incurred.

GDP also does not capture the qualitative difference in spending. However, it makes a difference in terms of development whether we spend our resources on building prisons or on education and health. The differences also have implications for future growth opportunities. Coyle (2014) makes an interesting observation about the quality of values created. He explains that it is easy to measure the number of cars, refrigerators or other objects produced, but what to do with the “output” of kindergarten teachers, accountants, musicians or health workers? We can measure how many people are doing these jobs and for what pay, how many “customers” they serve, but these measures say little about the content, quality and value created, which is particularly important for services. The products and services produced are characterised by their diversity, variety and quality, not just their quantity and price.

Mazzucato (2018) raises the question of whether tech companies, big banks and pharmaceutical companies, which generate huge profits, actually seek rents from society because of their monopoly position and market power. In general, we can also mention that, although the profits generated increase GDP, GDP is insensitive to the activity that generates the profits and whether it is useful to society. We can think of advertising of products that are harmful to health, such as cigarettes, but also of their manufacture, or of advertising to encourage consumption in general. The social benefit of profits generated by gambling is as questionable as profits generated by the sale of games that encourage aggression, for example. It should also

be noted that, although the informal economy is included in GDP by estimation, the total value thus created is also unlikely to be included in GDP. The informal economy tends to be more prevalent in less developed economies, but this does not mean that it does not exist at all in developed economies. According to an analysis, the lowest shares of the informal economy as a percentage of GDP in 2021 were witnessed in Europe, in Switzerland and Austria, with 5.8 and 6.9 per cent respectively. The highest shares were in Croatia, Romania and Hungary (29.0, 28.9 and 25.0 per cent, respectively) (Schneider, 2022).

Finally, let us mention the lack of a system approach. The economy is part of larger systems, it affects them, and they also have an impact on the economy. Dasgupta (2021) argues that economic performance should therefore only be measured in conjunction with the other systems that are linked to it.

Figure 2.2 The socioeconomic system Source: Dasgupta,2021

Natural

MEASUREMENT PROBLEMS

Measurement problems refer to shortcomings where the measurement of the new value or the lack of value cannot be solved by the GDP indicator. This is the case, for example, when a country makes significant public investments to increase GDP, but finances them partly by increasing the budget deficit or debt, and furthermore, in an unsustainable way. Investment increases GDP, but indebtedness has no effect on the GDP indicator, so it is not possible to judge from looking at GDP whether future debt repayments may put the economy on an unsustainable financial path.

Strong economic growth can also take place in a bad economic structure. Economic structure is an important development issue. For example, the share of high value-added “high-tech” sectors such as pharmaceuticals or infocommunications in a country’s economy matters a lot. However, GDP growth can also come from increased production in low value-added sectors, which contribute little to overall development. For example, they create low-skill jobs that do not allow the skills and knowledge of workers, i.e., the human asset, to grow. So what we produce, not just how much we produce, is important for the development and the growth of national wealth.

Underemployment, where there are not enough high-quality jobs that can make full use of the local knowledge available, can also be a problem resulting from the economic structure. Untapped knowledge reduces the potential value of GDP, i.e., creating a job that does not require knowledge, for example one that involves simple work processes, does not create as much new value as one that requires a lot of knowledge.

Another shortcoming of GDP is that it ignores temporal effects. That is, measured consumption relates to the welfare of the present, while the results of measured investment are felt in the longer term. We can also add that it is also insensitive to efficiency: it does not distinguish between investments according to their content. It is clear, however, that the impact on future growth of an investment

in machinery or technology is different from that of a construction project in a resort area. Even more different results are generally obtained by so-called tangible investments in machinery and infrastructure and intangible investments in education, training, innovation and IT. According to a recent analysis, economic growth in developed countries is increasingly driven by a rise in the share of intangible investment (McKinsey & Co., 2021).

This means that the success of an economy is increasingly dependent on unmeasurable or not easily measurable outcomes and their accumulation, such as knowledge and skills enhancement.

Let us look at some interesting data!

The European Investment Bank (EIB) has long analysed the distribution between tangible and intangible investments in EU countries. Figure 2.3 shows data for 11 EU countries for the year 2021. By tangible investment, the EIB means investment in machinery and equipment, buildings and infrastructure. Intangible (or smart) investment includes investment in research and development (R&D), software procurement, data and web operations, as well as expenditure on employee training and on organisational and business process innovations.

What we can observe is that the more economically developed countries are characterised by a higher intangible investment ratio, and this helps them to maintain their development advantage.

The importance of intangible investments is demonstrated by the correlation between ratios of intangible investment and competitiveness (Figure 2.4).

Figure 2.3 Distribution of investments (%, 2021)

In relation to these analyses, we can note that GDP also cannot measure the development path of a country: whether it is creating a capital-intensive, resource-intensive or knowledge-intensive economic structure.

The previously cited Dasgupta (2021) study also warns that GDP ignores the depreciation of national assets, which are important features of progress, and this in turn affects sustainable development. This is because it relies essentially on flow metrics. It takes into account, for example, the expansion of physical capital, such as roads, machinery, buildings, but does not take into account the evolution of national assets such as the quantity and quality of land, air, water and all living things, or the state of human capital (knowledge, skills, health). An economy that grows while the value of any element of national wealth declines is not on a sustainable growth path. However, Dasgupta warns that this decline in wealth is not reflected in GDP.

Another important issue is the measurability of inequalities. If GDP per capita is growing while income and wealth inequalities are

Figure 2.4 Correlation between competitiveness and the ratio of intangible investments

rising excessively, then overall there is no social progress. Excessive increases in income and wealth inequalities hold back social progress, which also has a negative impact on the sustainability of growth. This also reflects the difference between the short-term view of GDP and the long-term view of development. Because of its insensitivity to inequalities, GDP cannot measure how society as a whole is developing, whether there is a general catching-up in living standards and quality of life, which would be a sign of social progress. Regional differences may also be exaggerated by the fact that in less developed regions, it is likely that there is much more work done at home that does not appear in the accounts: gardening, childcare, cooking at home, etc., which, because it is not included in GDP, reduces the value of the GDP generated there, as well as the GDP per capita. A further distortion is when workers commute, travelling to more developed regions to work, the value of their work adds to GDP in areas away from their place of residence. This can make some areas, especially those with large companies employing many commuters, look more developed than they actually are. This is especially true if we also take into account the fact that a large company – if it is foreign-owned –can take the profits it generates to another country, which become part of that country’s GDP.

Finally, it should be noted that GDP growth is not clearly associated with an improvement in the well-being of the population. The characteristics of “well-being” have been described in many different ways. These factors include health, ability to express and utilise skills, job and job satisfaction, public safety, any beautiful natural environment and the level of corruption. This is discussed in more detail in Chapter 5, but it should be stressed that GDP was not, as we have said before, designed to measure well-being.

PROBLEMS CAUSED BY CHANGES IN THE ECONOMIC ENVIRONMENT

Globalisation enabled the emergence of global value chains. Global value chains are characterised by the distribution of the value creation process across several countries, which allows for so-called transfer pricing, i.e., firms to report costs in consideration of taxation. This means that costs higher than the real costs are reported in countries with higher corporate taxes or where they want to pay less tax. In this case, incoming products, components and, for example, expert knowledge or management or IT knowledge are accounted for at a higher price than justified. Intellectual activities have a particularly wide scope for manoeuvre, as they have no easily quantifiable arm’s length value. Reducing the tax base in this way reduces the contribution to GDP. Another interesting issue for the measurement of economic growth is profit repatriation, which is a practice that is mainly characteristic of multinational companies.

Hoekstra (2019) mentions that between 1990 and 2015 the number of multinational companies that organise the production and sales process into value chains doubled. The value chain looks at the production and distribution chain in terms of the value added at each stage of the chain and, depending on the value added, it considers which stages should be deployed in particular countries. (In contrast, the supply chain describes the coordination of the organisation of interrelated activities and supply systems.) Repatriation of profits does not reduce GDP, it only reduces the part that stays and can be used locally. The distorting effect of transfer pricing and profit repatriation on GDP may also make the reliability of results from international comparisons of development levels uncertain. Another difficulty in measuring performance with GDP is that it is able to measure an increasingly small slice of the new information and digital economy, because the new value generated in the modern information-based economy is outside the scope of what GDP can measure.

GDP was designed to measure tangible physical reality, production. Since then, there have been significant changes in the economy,

such as an increase in complex, often free, digital services. As infocommunication technologies advance, people are buying more and more online instead of going to stores. In addition, the range of services that can be accessed for free is growing. These include social media, maps, music, sheet music, dictionaries or open source free software. Their value cannot be reflected in GDP in the same way as traditionally purchased services.

Solow (1987) had already noted that the results of the proliferation of computers are not reflected in statistics. He is credited with the saying that we see computers everywhere except in productivity statistics. His remark was later referred to in the literature as the Solow paradox.

The sharing economy and the operation of platforms are parts of the information economy. The sharing economy is an economic solution to access goods, services, data or knowledge without having to buy them. Its operation is made possible by the use of the internet. Products and services include car sharing (ride sharing, carpooling), room rentals (Airbnb), taxi driving with own car (Uber), coworking offices, community art workshops or the EU farmers’ market (crowdfarming). A common feature of these systems is that the parties involved are in interrelation with each other. It also creates values such as relations within the community and knowledge exchange that can be greater than the monetary value in GDP. An important feature of the sharing economy is that, unlike traditional market models where consumers pay for a product or service to become its owner, the sharing economy is based on the sharing and use of products and services within the community. People make their own property, their homes, their cars, their tools, their time, their skills available and accessible to others through online platforms (Dudás and Boros, 2019). As the system helps to mobilise unused assets, capacities and knowledge, it generates significant added value and even productivity gains, part of which is not reflected in GDP, such as the free transfer of information between two stakeholders. The sharing economy works through platforms. In the case of companies operating platforms with applications, it is interesting to note that the value of services

increases when they are used by more people, as this increases accessibility to the services and to a wealth of knowledge. This can be called the “network effect”, and its capability to create added value cannot be measured by GDP. Operation in networks is increasingly typical of firms, as well as the blurring of activity boundaries, which also increases the scope for transfer pricing.

There are also significant changes in the labour market that are difficult to track in terms of their contribution to GDP. The network economy is spreading, with cooperation between firms in variable and sometimes temporary relationships, which also adjusts labour needs, i.e., employment is also temporary. As networks disappear, workers are also looking for new opportunities. Trust is a prerequisite for the sharing economy, for platform- and network-based operations. Stiglitz (2013) points out that without trust there can be no harmony and no strong economy. Yet we do not measure the durability and predictability of relationships with national accounts. Investing in trust is just as important as investing in machinery.

We measure the level of trust and the effectiveness of cooperation with the social capital indicator. Social capital refers to the interrelationships between individuals. Its important features are the level of trust and mutually agreed norms and values, which is a stock concept. Studies show that the characteristics of social capital affect economic performance (e.g., Hoesktra, 2019; Roth, 2022).

A strong level of trust reduces operating costs and promotes collaboration and what is known as open, multi-stakeholder innovation. In general, countries with weak social capital are more likely to have a proliferated informal economy. However, GDP does not scrutinise social capital.

There are already initiatives to measure the value added from the information economy. One interesting approach is the development of a new “GDP-B” indicator, which is the work of Brynjolfsson and Collis (2019). This is how it is described: an alternative indicator that complements the traditional GDP indicator by taking into account new and free goods that increase the purchaser’s value. As this increases the value of GDP, one of the indicators used to measure

productivity, GDP per capita, will also increase. This also gives a more realistic picture of productivity trends. The digital economy is measured using the model in Figure 2.5. This model also allows us to examine a slice of the subjective indicator of social well-being.

Social value, satisfaction (well-being)

More

Importance by social value

Less

Subjective

Source: Brynjolfsson and Collis (2019)

Digital added value for the customer (free) “GDP+”

Objective Measuring

SUMMARY AND CONCLUSIONS

Macro indicators (GDP)

In this chapter, we have summarised the main economic areas where the GDP indicator does not allow us to measure results. These have been grouped into three main categories: basic methodological problems, measurability problems and problems caused by changes in the economic environment. GDP is an important indicator in decision making, so it is justified to give as accurate a picture as possible of the real state and development of the economy. Therefore, it is important to be aware of its limitations, which are partly due to its design and partly due to the technical and economic changes that have taken place since it was proposed.

Figure 2.5 Measuring the digital economy “GDP-B”

ESZTER BARANYAI AND LILLA BÁNKUTY-BALOGH

The impact of factors on well-being: beyond GDP

“Life is not what one lived, but what One remembers and how One remembers it in order to recount it.”

Gabriel García Márquez

There is little doubt in our minds about how non-economic factors – such as our family, our health, the state of our environment and our freedom – can affect our quality of life. These factors may even outweigh considerations like our financial situation. Nevertheless, a typical way to compare living standards between countries or time periods is to turn solely to per capita income, i.e., GDP. In this chapter we explain how contemporary social science research distinguishes between material welfare and well-being as a measure of life satisfaction. The main message of this chapter is that the system of national accounts is not able to measure non-material factors – a point to bear in mind when using GDP figures. Therefore, other indicators should always be taken into account when measuring living standards and life satisfaction.

The dynamics of well-being are often hidden in key economic indicators, even though their importance for a country’s development is fundamental and may signal the need for important changes. The two main dimensions of (subjective) well-being are life satisfaction (cognitive) and the net balance of emotions (affective). Factors affecting well-being have now been widely identified. Current research suggests that 30–40 per cent of our well-being is due to genetic factors and 60–70 per cent to environmental factors. These factors affect us through a subjective lens and their impact can vary significantly from individual to individual. Most research is based on subjects’ responses, but there is a growing usage of other methods, such as neuroimaging or text recognition, that attempt to exploit the potential of technology or other disciplines.

WHAT IS WELL-BEING AND WHY SHOULD WE CARE ABOUT IT?

In recent years, there has been a growing emphasis on well-being in both policy discourse and academic work, as opposed to the earlier focus on wealth and welfare. But what exactly is well-being, which many people associate with happiness?

Well-being is a subjective concept, which we draw on psychological literature to understand. Subjective well-being has several components:

• satisfaction with our life in general,

• satisfaction with certain aspects of our life (e.g., health, marriage),

• our positive emotions and

• our negative emotions.

It is important to see that, although there is a correlation between the components, it is not particularly strong, except for the relationship between the first two components (Schimmack, 2008). Having a lot of positive emotions does not preclude negative emotions, as some people have a wider range of emotions, and people who are generally satisfied with their lives can also have negative emotions, and vice versa. Some critics argue that the existing components describe hedonic well-being and that a fifth element is needed, which includes fulfilment and meaningful life (eudaimonia). A common feature of all attempts to define well-being is that they all go well beyond the purely material aspects (wealth, income).

Why should we care about subjective well-being? Because it helps to put economic factors in a broader context. In a broad sense, wellbeing is the goal of life – though individuals will differ regarding what makes them feel good. The aim of economic activity should therefore be none other than to increase well-being through its own means. Our financial situation can affect our sense of security, health, ability to achieve self-actualisation and many other subjective areas of life satisfaction. However, economic indicators do not accurately reflect trends of well-being. Economic and well-being indicators may even move in opposite directions. An example is Egypt in the second half of the 2000s (Figure 3.2), when it achieved an average GDP growth of 6 per cent between 2005 and 2010, measured in purchasing power parity. Over the same period, however, the share of people who were very satisfied with life fell dramatically from 29 per cent in 2005 to 12 per cent in 2010. Well-being indicators can therefore provide additional information that is worth paying attention to.

The link goes both ways. Not only does the economic situation affect well-being, but well-being also has a positive feedback effect on economic growth. Indeed, people with higher subjective wellbeing are known to be more successful at work, have better work performance, are more helpful, and therefore have a more positive influence on others (Conceição and Bandura, 2008; Diener et al., 2018).

THE COMPLEX SYSTEM OF FACTORS AFFECTING WELL-BEING

In recent years, there has been a substantial increase in the focus on subjective well-being within social science research and a wide range of factors has been linked to it. This chapter groups the factors based on policy considerations (Figure 3.3). In order to make decisions and to choose the right policy tools it is useful to understand which are the factors that can be changed (as opposed to those that are fixed)

Figure 3.1 Egypt’s economic development and the proportion of people who are very satisfied with life

and whether it is the individual or the environment that primarily determines a given factor. The exact positioning of the factors on an objective-subjective scale is, of course, open to debate – in any case, it is not the exact ordering that is important.

Personal Environmental

Personal attributes

Objective

Healthy lifestyle

Work and scheduling

Invisible work

Attitudes and values

Self-actualisation

Physical environment context

Political and social institutional system

Economic context

Digital world

Personal relationships

Subjective Temporary vs. permanent effects

Community life and social status

What is important is that factors close to the objective endpoint are either impossible or difficult to change. These are, for instance, age or gender. However, most of the factors can be influenced by the individual as well as by the policymaker (e.g., how much invisible work a person does, how much that invisible work is valued).

Furthermore, as we move towards the subjective end of the scale, our subjective “lens” – through which we see our given objective situation and translate it into a subjective well-being value – becomes more and more important. For example, the number of social relations may suggest that an individual’s need for his/her social environment is satisfied, but this may not be the case if the individual is not satisfied with the depth of the relationships.

In addition to some of the objective characteristics, genetics also affects our subjective lens, our perception. Recent research concludes that overall, 30–40 per cent of the deviations in subjective well-being

Figure 3.2 Groups of factors affecting well-being

scores is explained by genetic – hereditary – factors, while 60–70 per cent is explained by circumstances (Diener et al., 2018).

It is important to see that the factors often interact (Figure 3.4). This is illustrated by the relationship between green spaces, health, sense of security and subjective well-being. A greener environment is good for health, well-being and sense of security in general. However, better health and a sense of security were also directly shown to increase subjective well-being, and a lower sense of security has been shown to have a detrimental effect on mental and physical health.

Linkages between the factors are not one-way in their direction. For example, our subjective well-being also has an impact on our health (De Neve et al., 2013). Childhood stress and difficulties have been linked to chronic inflammatory processes in the body years later. Our emotions and well-being have a particular impact on our cardiovascular, immune and endocrine systems, which is reflected in the frequency of illnesses, speed of recovery and life expectancy. It is not just that happier people have healthier lifestyles and better social relationships (which lead to better health), but also – through a more direct channel – our well-being affects our physiological processes Stress, for example, can shorten telomeres at the end of DNA, which causes faster ageing.

Figure 3.3 A complex relationship system of some of the factors affecting well-being

Source: Own editing

Green space

Subjective well-being

Health

Feeling safe

ENVIRONMENTAL FACTORS

Social environment

Man is a social being. High-quality social relationships increase our well-being and have a positive impact on our health. At the same time, our positive emotions improve our social relationships, so the effect is two-way.

Looking at some examples of the most important social ties in life, we see a temporary rise in well-being levels for a few years around the time of marriage, whereas after losing a spouse to death, a persistently lower level of well-being is typical. The direction of the impact of having children is less clear-cut and depends on other factors such as family finances, the couple’s relationship, or how disrupted sleep becomes.

Not only close relationships matter. Interactions with our neighbours, trust in our neighbours, all contribute to our well-being. Other dimensions of social inclusion also have a positive impact, such as a sense of belonging to our community or country. Áron Tamási (1934) phrased this in his book Ábel in America: “We are in the world to be somewhere at home in it.”

In social relationships it is important to us how others treat us, for example whether we are respected as we would wish to be.

Socio-political context

Research finds that less social inequality, greater political freedom and lower corruption all lead to higher subjective well-being (Diener et al., 2018). An interesting observation about inequality is that people use their environment as a reference point. The most typical example is that, regardless of the objective level of material wealth, subjective well-being is lower when neighbours’ incomes are higher than the income of the person evaluating his/her own well-being. Separately, corruption has a big impact on our life satisfaction, explaining 13 per cent of the variance in one study (Tay et al., 2014). Corruption reduces not only national income but also trust in institutions.

Culture enriches people. Occasional visits to museums, exhibition halls and historical sites were found to have a positive effect. Our own artistic activities can also be beneficial, but it was found important for these to be regular activities.

Welfare functions of the state, such as health, education, social security and housing, play a major role in shaping the resources and opportunities of individuals. As these individually make a major contribution to individual well-being, the state can help by making them more widely available than they would otherwise be through market-based distribution. Through a complex web of well-being factors, these can spill over into reducing inequality, feelings of security, opportunities to develop individual skills and countless other aspects of well-being.

Physical environment

The physical condition of our environment is obviously important to us – for example, cleanliness or the presence of trees, the aesthetic appearance and the density of buildings. A greener environment is associated with higher subjective well-being. In contrast, air pollution reduces our well-being, both in the short term, as we experience it, and in the longer term, through its impact on our health (Diener et al., 2018).

There are also practical considerations when judging our environment. How accessible are recreational activities or shops, how convenient is transport, how far away is work, how far away are friends, how is public safety and how far away are problematic neighbourhoods? Individual considerations are obviously important, with some preferring a bustling city, others a more family-oriented suburb, or perhaps an even quieter rural environment.

Digital world

The newest factor affecting well-being is the digital world, which was little known 20 years ago, but in which we now spend a significant part of our days. The impact of the internet and the expansion of digital connections on well-being is not clear. One would think that the explosion of opportunities and the constant maintenance of social relationships would increase well-being. The increase in the number of opportunities, however, can also cause frustration as we realise that, at an individual level, only a fraction of these are truly there to take. Social relationships tend to increase our well-being, but more superficial relationships, the resulting social pressures, self-esteem problems and, in extreme cases, exposure to hurtful behaviour can significantly reduce well-being. As a result, some research suggests that social media increases well-being, while others suggest that it decreases it (Kim, 2017).

Economic environment

Although the economic environment is dealt with in more detail in other chapters of this book, it is worth noting here that there may be aspects of the economy that are not adequately reflected in a single GDP figure, but which, at the same time, do have an impact on our well-being. Such things are the unemployment rate or the rate of inflation.

INDIVIDUAL FACTORS

Self-actualisation

Attitudes and values

Invisible work

Work and time schedules

Health and lifestyle

Personal attributes

Source: Own editing

Personal attributes

Regarding individual determinants of subjective well-being, the literature addresses genetic determinants, age and gender among other factors. However, analyses of these attributes show mixed research results (Diener et al., 1999, 2018; OECD, 2020).

The average level of subjective well-being is related to the cultural values and norms of the community in a given country (Diener et al., 2018). An analysis of the word ‘happiness’ in 30 countries revealed that in 24 of them (e.g., Japan, Korea, China, Russia and Norway), happiness is associated with luck, while in the United States, for example, it is associated with success.

The Anglo-Saxon term “pursue happiness” literally refers to actively “chasing” the feeling of contentment. In contrast, a Chinese proverb says that “when man has done his work, the rest is up to the Heaven”, similarly to the Hungarian proverb “Man proposes, God disposes”.

Figure 3.4 Scale of individual factors affecting well-being

The sense of agency associated with happiness, and related emotional patterns such as excitement and pride, or conversely calmness and contentment, were shown by research to predict national cultural differences in the experience subjective well-being.

Education, particularly years spent in higher education, has a positive effect on later socio-economic status, income levels and health, thereby affecting subjective well-being. Those with tertiary education perform better than those with secondary education in almost all areas of well-being, except for long working hours (OECD, 2020). Higher educational attainment is generally associated with higher life satisfaction and lower incidence of negative affectivity. Education also has a key role to play in reducing gender inequalities. Lifelong learning and active citizenship also have a positive impact on well-being.

Healthy lifestyle

A key predictor of subjective well-being is the subjective perception of one’s own health. This correlates more strongly with subjective well-being than one’s objective physical condition (Diener et al., 1999). However, if a person suffers from several different or chronic health conditions, there are limits to coping that the individual might not be able to compensate for. Poor health can negatively affect well-being by making it more difficult to achieve personal goals and creating obstacles in everyday life.

The relationship between health and subjective well-being is a twoway dynamic. Individuals who enjoy higher subjective well-being tend to be healthier and live longer. This is partly due to the fact that they are more likely to engage in health-preserving behaviours, such as engaging in more physical exercise, smoking less and consuming less alcohol. Psychological well-being also has a positive effect on cardiovascular, immune and endocrine system functions (Diener et al., 2018). Subjective well-being is furthermore strongly influenced by the health of family members. For example, caretakers of a person in need of care are at significant risk of stress, clinical depression and excessively poor quality of life (Cummins, 2001).

Work and time schedule

In most countries, job satisfaction is positively related to subjective well-being and also has an indirect impact by influencing one’s selfesteem, perceived social status and financial situation. A two-way dynamic can be examined in the case of work as well: more satisfied individuals typically perform better at work, miss fewer days of work and tend to be more creative.

Telic theories study human behaviour in terms of goals. The nature of individual goals and the pace of progress towards them affect well-being. Progress is positive, while stagnation or regression has a negative impact. According to Csíkszentmihályi (Nakamura and Csíkszentmihályi, 2014), the presence of either intrinsic (selfmotivation) or extrinsic (e.g. workplace) motivation is better than having no goal in mind. Commitment to goals increases a sense of personal agency, helps structure everyday activities and contributes to the notion of a meaningful life. Experiencing autonomy is key: those who feel they have substantial control over what happens at work report being happy at a significantly higher rate. Unemployment is strongly negatively correlated with subjective well-being, and does not improve over time (Lucas et al., 2004). The autonomy to decide how to spend time affects satisfaction levels in rich and poor countries alike (Diener et al., 2018). The length of time spent at work does not in itself affect well-being, but rather the disparity between individual working time preferences and actual hours worked can be decisive (Wooden et al., 2009). Other variables around work (high/low skilled, white-collar/manual work, employee/entrepreneurial work) influence subjective well-being depending on the socio-economic context.

Invisible work

According to Daniels (1987) in her seminal article on invisible work, the commonplace definition of work as “something you have to do to get paid” automatically devalues and renders invisible a significant part of women’s work. Research following Daniels’ work describe

the culturally and economically devalued status of housekeeping, volunteer work, emotional support, care work or breastfeeding, for example, which are the cornerstones of our social functioning. which negatively affects the subjective well-being of those who perform invisible work.

This includes the mental strain caused by the combination of cognitive and emotional labour involved in caring for the community. It also includes activities such as keeping in mind and preventing needs, considering decision options, planning, organising and monitoring related processes (Daminger, 2019). Mental strain is characterised by having no time limits; it is present during leisure and sleep time; and it is continuous, as it is linked to caring for loved ones. Cognitive and emotional labour is a gender-based phenomenon, with women and mothers generally bearing a significantly higher burden.

According to an OECD (2020) report, men perform on average 90 minutes per day more paid work, however, when both paid and unpaid work are taken into account, women work on average half an hour more daily in almost all OECD countries. In Hungary, this figure is one hour a day. Higher hours of unpaid work performed by women contribute to higher levels of stress perceived by women. In a European survey (Boye, 2009), one third of the difference in subjective well-being between genders could be attributed to the difference in time spent on paid work and housekeeping.

Attitudes and values

Personality and personal attitudes (e.g., affective propensities, rewarding behaviours, positive/negative outlook) are among the strongest and most consistent predictors of subjective well-being. Diener et al. (1999) described the happy individual in a nutshell as extroverted, optimistic and worry-free. Cognitive tendencies influence personality and they both interact with subjective well-being. For example, extroverts are more sensitive to rewards in a positive sense, therefore they seek out social situations and are generally happier. Neuroticism is typically associated with negative mood effects and

aloofness. In contrast, the optimistic person expects positive outcomes, strives accordingly and is typically more successful in achieving their goals than their pessimistic counterpart. Happy people encode more events into their memories positively and therefore recall more pleasant experiences, while those who dwell more on negative memories report lower subjective well-being.

Attitudes towards our own circumstances play a key role in experiencing subjective well-being, as individuals compare themselves to different reference points, such as other people, past circumstances or imagined ideals. The difference between the reference point and the current state determines perceived well-being. However, social comparisons are flexible, and their upward/downward direction and impact (e.g., motivational/stressful) depend largely on personal attitudes.

Among the effects of personal values on subjective well-being, one distinct topic is the issue of religiosity. There is a positive relationship between religiosity and happiness: spirituality, religious coping and faith are important predictors of life satisfaction. However, religiosity is more strongly correlated with life satisfaction in religious countries than in secular ones (Diener et al., 2018). Research in Hungary (Kopp et al., 2004) also shows that practicing religion is associated with better physical and mental health: those practicing their religion smoke less, consume less alcohol, demonstrate better work performance, are less likely to have harmful emotional coping methods and report having more social support.

0-19%

20-39%

40-59%

60-79%

80-100% No data

Source: Pew Research Center (2018)

Self-actualisation

Self-actualisation is linked to living a meaningful life and achieving personal goals. Self-actualisation can be defined as the need to fulfil one’s potential, which may vary from person to person. People may be fulfilled in work, sport, art or family life. In the context of selfactualisation, telic theories –the importance of striving towards a goal – again come into focus. The process of progress and the content of the endeavour are more important in terms of subjective well-being than the probability of achieving the goal or its end state. However, if a person becomes overly obsessed with the outcome of their ambitions, it negatively affects his/her subjective well-being.

Csíkszentmihályi (Nakamura & Csíkszentmihályi, 2014) introduced the term of autotelic personality, those who usually do things for themselves rather than pursuing some external goal. The motivation of the autotelic person is the intrinsic reward of striving. Autotelic people

Figure 3.5 How important is religion in our lives?

report more positive cognitive and emotional states, experience less stress and tension, and spend more time in a “flow” state, a total joyful immersion in an activity.

Transitional effects

The balance of subjective well-being is shaped by environmental influences, personality and affective propensities (e.g., emotionality, mood intensity and mood variability). In the short term, subjective well-being can be influenced by simple environmental factors such as time of day or differences during the week: typically, positive emotions peak at noon and in the early evening, and Saturday is typically a happier day than Monday (Diener et al., 2018).

However, in the long run, personality has a greater impact on life satisfaction than temporary environmental influences. According to the set-point theory, external events may cause spiking emotional responses, but satisfaction with life returns to a relatively stable baseline over the years (Diener et al., 1999; Lucas et al., 2004). Exceptions may include certain traumatic life event, such as becoming widowed, experiencing divorce, disability or loss of employment, which in some cases can alter the long-term balance.

Measuring subjective well-being

A wide range of assessment methods and instruments are now used to measure subjective well-being and to explore causal links. Subjective well-being is investigated directly and indirectly, in real time or retrospectively, through cross-sectional/longitudinal research, experimental and interventional methodologies. Direct measures are typically based on self-reporting, where subjects rate their satisfaction with life over a given period. Meta-analyses show that the results are fairly stable over time and consistent with assessments in the immediate environment of test subjects. The empirical sampling

method collects real-time data at different moments of everyday life and aggregates it (Larson & Csíkszentmihályi, 2014). Indirect measures look at indicators such as frequency of smiling, number of good and bad memories recalled, use of negative/positive words or changes in certain physiological indicators. With advances in technology, analysis of indirect indicators may become more widespread with the help of smart devices, facial recognition software, language recognition algorithms, brain imaging and data analysis. The internet and social media make it possible to conduct intensive longitudinal studies on a sample that could be representative of almost the entire world. That said, it is important to note that most of the research on subjective well-being to date has been conducted in economically developed Western countries, therefore our knowledge is limited as to the universal validity of the findings discussed in this chapter.

GÁBOR BARTUS

Conceptual summary of proposals beyond GDP

“When you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.”

Antoine-Augustin Cournot

We have seen above the limitations of GDP, the most widely used measure of countries’ economic performance, in terms of measuring sustainability, broader well-being and economic performance itself.

The gross domestic product (GDP) indicator, which is of great importance in assessing economic performance and in economic policymaking, has stood the test of time in many respects and provides a useful indicator for the aggregate assessment of goods with market value, government expenditure and investment. However, the size of GDP and its variation over time (economic growth), among other problems, does not tell us much about our impact on the accumulation of the factors of production that underpin our future well-being, and in particular the size and sustainability of natural capital.

One of the important challenges of our time is to ensure that our efforts to increase current output do not have a negative impact on production potential in the more distant future. It is therefore timely to try to develop alternative ways of measuring well-being, where the given indicator or value is not only an indication of momentary but also of long-term well-being that can be sustained over time.

In this chapter, we address the conceptual issues of measuring sustainable well-being, starting from the fact that societies use various indicators to assess their success and capacity to create wellbeing. Our conclusion is that we do not yet have a single, all-around measurement system, and the popularity and impact of each type of measurement on decisions is not always fully in line with the accuracy of the measurement method, and in particular with what we expect from the indicator and what it can actually measure.

MEASURING SOCIAL WELFARE AND WELL-BEING IN A BROADER SENSE

The aim of cooperation between members of societies is usually to increase well-being in the broad sense, to create the conditions that allows us to live the best, happiest life possible. The extent to which people are successful in achieving greater happiness and satisfaction at an individual level is based on both objective and subjective factors when assessing their own situation: how much money do I have in my bank account, do I have a job and how satisfied am I with it, do I receive recognition, do I have friends and how strong is my relationship with them, do I have a family and am I happy around them? Evaluating the well-being of societies (and here we mean well-being in a broad sense, in the light of the totality of material and non-material factors) is also a complex task. On the one hand, we do not have a tool or a method that can aggregate individual people’s feelings of satisfaction, well-being, happiness, and on the other hand, we do not have social measurement procedures that can answer our question. The success of nations is characterised by a few measurable, producible socio-economic indicators, such as gross domestic (or national) product (GDP and GNP), unemployment rate, inflation, life expectancy at birth, income or wealth inequality. Even if we carefully and prudently start from the picture conveyed by many of these indices, we are still ignoring many of the factors that ultimately determine the well-being of society. If we focus on GDP exclusively, we can fall even further into the trap of trying to make a general assessment from partial information.

When we think about whether it is possible to get a more complex, accurate, general picture of society’s performance in terms of the fulfilment of well-being in the broad sense, based on some kind of measured values, and if so how, then it is worth starting from how this well-being is produced. Our model here is economic in nature, i.e., we approach the functioning of society, the mutually beneficial cooperation of people, in economic terms.

The sources of well-being, satisfaction or happiness are partly non-material and partly dependent on the availability of goods and services. The two factors – material and non-material – are often linked. For example, the enjoyment of music is mainly a non-material factor, but the creation of sounds requires instruments and concert halls, which are material products of the economy.

Material wealth achieved in the present (the utility of goods, welfare) depends on how much of our past income and how efficiently we spent on creating the goods that we use to produce material wealth today – these are the factors of production, also known as resources or capital goods (Table 4.1). The more and more valuable factors of production (resources) a nation possesses, the more it is able to create goods and services, thus contributing to the creation and further increase of both material and broader well-being (satisfaction, happiness).

ECONOMIC RESOURCES

HUMAN RESOURCES

Production tools, equipment Population size and its rate of change

Infrastructural facilities

Low levels of inequality and poverty that do not hamper social mobility

SOCIAL RESOURCES

System of government, quality of institutions

Trust between members of society and towards institutions

NATURAL RESOURCES

Raw materials, energy carriers

Ecosystems, biodiversity: the carriers of ecosystem services

Capital Knowledge, skills No corruption Climate stability

Macro-level prudence Health status Social inclusiveness Land use

Source: Own editing

The problem of measuring and evaluating social well-being in the broad sense is that it is always easiest to measure the value of the goods and services currently produced, so the indicators presented

Table 4.1 Four groups of national resources (factors of production) – not a complete list

to the public – the indices influencing the choice between economic policy alternatives – reflect only part of the broad sense of well-being. The other pitfall is that maximising the metrics that measure the material dimension of current well-being can lead to, for example, bad decisions about the size and type of investments that underpin future consumption.

The socio-economic indicators used today are useful, they measure important aspects of social cooperation, and the results of these measurements are meaningful. Thus, for example, the gross domestic product (GDP) indicator and its year-on-year variation (growth) reveal information about the extent and quality of social cooperation, and indicate the income available to members of society, i.e., the level of material welfare. At the same time, GDP ignores the magnitude of factors not measurable in the market but contributing to well-being, and does not reflect on the possible exploitation of resources (especially pollution) or the problems arising from their underutilisation. In other words, GDP-type indicators are not suitable for capturing total well-being in the broad sense, nor do they indicate problems where the source of the current output boost is the degradation of national resources, the consumption of wealth or imposing indebtedness on future generations.

Figure 4.1 A simplified scheme of the evolution of well-being and its measurement

Figure 4.1 attempts to show both the social processes that create well-being and what GDP measures from these processes. What it measures completely is the aggregate economic value of the goods and services that change hands in the market. In some cases, we already have estimates of the economic value of factors that are not valued in the market but that affect our well-being (for example, the [negative] economic value of air pollution or the extent to which voluntary service activities increase well-being). Also included in GDP are the values of investments that increase the factors of production, such as fixed asset accumulations, or, among government expenditures, we consider expenditures on increasing the quality of education or health care.

Extending the measurement towards resources

If we look at the left and upper middle section of Figure 4.1, it is clear that the material foundations of well-being cannot be created from nothing. Output (measured by GDP) depends on the quantity and quality of our factors of production:

Y = f (Km, Kh, Ks, Kn)

where Y is the output and K is the factors of production, where, according to our current knowledge, we distinguish four large groups: K m for physical capital, Kh for human resources, Ks for social capital and K n for natural resources (Acemoglu, 2011; as well as Barro and Sala-i-Martin, 1995).

The more productive assets we have at our disposal, the more people work with higher knowledge and competences, the more we can enjoy the ecosystem services of natural resources in sufficient abundance, the more supportive the values that members of society follow, the more inclusive the social system, the more valuable goods we can create and the greater the well-being of the members of society will be.

The monetised, economic value of resources (the sum of which constitutes the total national wealth – TNW) is the aggregate of the product of the elementary quantity and value of resources:

TNW=ΣEV(Ki) and EV(Ki) = pi*Si

where EV is the economic, monetised value of a unit of resource (Ki), pi is the unit value (accounting price) of the resource, and Si is the stock or quantity of the resource (UNECE-OECD-EUROSTAT, 2008).

To put it more simply, our annual income is used for consumption and investment, i.e., to replace the depreciation of the factors of production, to expand resources and capital: Y

where C is consumption and I is the size of investment (here we do not separate government consumption [G] and we do not consider export-import [X, M]).

Investment is spread across the resources mentioned above: I

where I m is the amount of investment that increases Km, Ih is the amount of investment that improves Kh, and so on.

Societies are constantly facing important choices in this respect:

(1) What should the C/I ratio be? How much of our income should we spend on our current consumption, and how much should we spend on replacing, maintaining and improving the factors of production?

(2) How much of our investment budget should we spend on developing each type of resource? Should we plant a forest or rather build another factory? Should we spend more on improving the quality of the education system? Or should we increase the size of our family support grants?

(3) Within a given type of resource, which future investments have the potential to increase output and, as a result, well-being in a broad sense, to a greater extent and in a more sustainable way?

Sustainability is about consciously examining and interpreting these questions and finding the right answers where possible.

Extending measurement towards non-material well-being

Another driver for research on measurement methods beyond GDP is creating the possibility of valuing factors that are important in valuing our lives but not measured in the market. People’s perceived satisfaction and happiness is not just a function of their earnings, the material opportunities valued in market terms. This is why it is not surprising if someone gives up a well-paid job to do something close to their heart, or turns down an offer of extra work to preserve their free time.

Research on people’s perceptions of happiness confirms this: being in intimate emotional contact, relaxing, interacting with others, and being in social relationships are all factors that significantly improve our well-being, but their value is not captured in GDP because there are usually no market transactions in relation to which we could measure them (Kahneman et al., 2004).

Clearly, we should also value the well-being that results from nonmarket transactions when assessing the quality of life of people in a given society. It can easily happen that a country’s GDP grows, but if, for example, individuals’ free time is decreasing or the quality of their social relationships is deteriorating (for example, divorce is on the rise), then overall well-being may decline even as GDP grows.

The problem is that, while all these factors are clear and almost self-evident in principle, the quantification and measurement of these factors faces a number of methodological obstacles (Fleurbaey and Blanchet, 2013). One solution could be to calculate equivalent income, which reflects the willingness of individuals to pay to compensate for the difference between their actual situation and a reference

level. However, measuring happiness, the subjective feeling of wellbeing, is always questionable, because it is easy for people to become confused when it comes to their feelings and their actual state when answering questionnaires. The use of composite indicators can also be misleading here, when there is no sound objective argument to establish the weighting between the individual elementary indicators (Fleurbaey, 2009).

Thus, the reform of measurement has two basic directions that extend the scope of consideration: on the one hand, we would like to be able to measure factors of production/resources/capital goods and their changes (sustainability); on the other hand, we would like to be able to measure non-market goods that determine well-being, i.e. we would like to be able to measure our well-being in the broad sense (Stiglitz et al, 2009, 2018). In the following sections, we mainly follow the first direction.

THE MEANING AND MEASUREMENT OF SUSTAINABILITY

In today’s societies, there are two interrelated phenomena that have a significant impact on people’s quality of life and well-being, yet we do not pay enough attention to them: the conflict between short- and long-term effects, and the priority of outputs and income over the resources and factors of production that make them possible. By ignoring or undervaluing them, we fail to achieve the best possible outcome in one of the fundamental goals of community and political action, i.e., to make decisions that affect the community in a way that results in the greatest aggregate utility.

Short term versus long term

One of our fundamental problems is the nature of the perception and evaluation of time horizons. Our modern social, economic and financial instruments allow us to systematically and significantly separate the short-term benefits and some long-term costs when

making decisions (naturally, since we cannot see into the future, the assessment of the long-term effects of decisions is inherently fraught with uncertainty). Our current social and economic institutions and their functional standards provide specific incentives for decisionmakers. The policies that incentivise them suggest that they should give preference to those alternatives that bring substantial benefits in the shortest possible timeframe, regardless of their costs in the more distant future.

For example, draining swamps to increase agricultural land, and thus the output quantity of agricultural products, leads to a short-term increase in income (GDP). However, the longer-term consequences of this decision may be that the elimination of water retention capacity increases the frequency of droughts, which could ultimately lead to a significant reduction in crop production capacity. In other words, a decision that is useful in the short term can be extremely harmful in the long term. Separating benefits and some costs in this way leads to imposing indebtedness on future generations.

The fact that natural resources began to become scarce in the second half of the 20th century raised the question of whether it is possible to maintain output at a sustained high level if the amount of natural capital falls below a critical level. Is the era of natural resource conversion over? And if so, is it possible to develop physical, human and social resources in a way that can make up for the income benefits that previously accrued from the exploitation of natural capital?

Imposing indebtedness on future generations can take place not only through the depletion of natural resources and climate change, but also through rapid and persistent population loss, insufficient development of the education system, excessive public debt or the implicit indebtedness of pension systems. By ensuring sustainability, we want to avoid negative feedback that appears over time.

In other words, if we judge performance only on GDP, we make decisions and choose between alternatives with poor judgement and by not being fully informed. Importantly, the problem is not with GDP as a measurement method per se, but with the way GDP is used by

decision-makers and the public to substantiate their decisions while omitting other factors!

Choosing between opportunities for investing in our future

Interpretations of theories and practical experience regarding economic development and sustainable growth have shown that the conditions for future sustainable well-being are changing, and that regarding the expansion of factors of production over other resources, it matters in which era it takes place, at what stage of development, and which factors of production are involved (Barro and Sala-i-Martin, 1995; Hanley and Atkinson, 2003; Acemoglu, 2011).

The other fundamental problem regarding sustainability is that we pay little attention to the development of our resources, our factors of production, and to the question of which type of capital is more worth investing in, which investment strategy leads to greater prosperity in the future. The size of output (the value of gross domestic product, GDP) and how much of it we consume and what we consume are naturally more interesting questions for households, companies and governments than how we should develop our factors of production and resources in order to live more prosperously in the future.

The problem of imposing indebtedness on future generations is thus compounded by the problem of choosing the wrong, inefficient portfolio of investments for our future.

Unsustainability is therefore the result of two interconnected perceptual errors, the fundamental feature of which is our relationship to time, our short-term view. The short-term view, short-term optimisation, leads to a disconnection between the time horizon of benefits and costs, and to the choice of inefficient strategies of investing in our future.

The two fundamental problems of sustainabilityare the tension between the short and long term and the lack of care about investing in our future

Sustainable development as a political action and an institutional solution is needed precisely because, while market economies and democratic political systems could theoretically incorporate institutions to prevent future indebtedness, in practice leaders (both corporate and community) interested in short-term success often prevent the introduction and application of these constraints. At the same time, the lack of these constraints may be more convenient for voters and consumers in the short term.

Reforming measurement, developing alternative indicators is an opportunity to provide feedback. This can be used for informing incentives that can help avoid the short-run-long-run trap and support us to have a well-balanced portfolio of investments in our future.

Sustainability is not an end in itself

It is important to be aware that sustainability is not important just because it is now a fashionable concept in international politics. Meeting the criteria of sustainability (consuming and investing in our future at the right rate, balancing investment across resources, including ensuring that the social division of labour does not exceed the Earth’s ecological limits) has many social benefits.

Respecting ecological limits and making good use of natural capital ensures that we are resilient to changes in the natural environment (such as climate change). A high level of social capital makes political communities resilient to social crises, for example in times of war in the region. Those who invest more and more wisely in their future will have higher national incomes in the longer term and will be more competitive in peaceful economic competition between nations.

Source: Own editing

For centuries, the resource management pattern of societies has been based on the expansion of all resources, but also on the depletion of natural resources. A trade-off took place, with natural capital being reduced (overfishing the seas, cutting down forests, depleting the fertility of soils, overpolluting the air and water, concreting over biologically active surfaces, etc.), while the other three resources were increased.



 

Y = f(Km, Kh, Ks, Kn)

NEW MEASUREMENT DIRECTIONS

Based on international practice, there are several possible directions and ways to expand measurement based on GDP logic. There are several alternative approaches because sustainability cannot be measured directly. Indirect approaches are clearly more diverse. The different methods therefore differ in the characteristics of sustainability that we consider to be most valid for the whole.

Figure 4.2 Main social and economic characteristics depending on the quality of sustainability

Level

Competitiveness

Social resilience

Ecological resilience

Long-term level of well-being

One of our choices is whether we want to approximate the completeness of well-being by a composite indicator (one aggregate number tells the whole story) or whether we measure the factors constituting well-being separately (and thus evaluate several measures by “aggregating” them). The first approach is better able to meet communication needs and may be more suitable for shaping attitudes, while the second approach may, for example, make us more alert to harmful trade-offs. The closer our indicator is to our elementary measurement capabilities, the fewer methodological problems arise in adding up values of different nature, which is a fundamental difficulty of composite indicators.

Goods

Source: Own editing

Another important question is how to choose the unit of measurement to which all the factors are translated, and which allows the elementary values to be aggregated. Should this be monetised value? This would harmonise with our current measurement habits, where many indicators (including GDP) are measured in monetary terms (forints, dollars, euros). Or should we use some indexed value?

Figure 4.3 The directions of extending the measurement (see also Figure 4.1)

Many sustainable development composite indices use this possibility to aggregate different phenomena.

A further problem for measures of economic nature is the difference between income and wealth: if we want to adjust GDP for sustainability within an index, we need to aggregate income and wealth factors.

MEASURING WELL-BEING IN THE BROAD SENSE

HDI Human Development Index

BLI OECD Better Life Index

IHDI Inequality-adjusted HDI

WHI The World Happiness Index

WGI The Worldwide Governance Indicators

SUBJECTIVE WELL-BEING INDICATORS

SWB Subjective Well-Being

MEASURING NATURAL ENVIRONMENTAL RESOURCES

EPI Environmental Performance Index

EFP/ EF Ecological Footprint

MEASURING CAPITAL GOODS, RESOURCES

GS Genuine Savings

NW National Wealth

COMPOSITE INDICES OF MARKET GOODS AND RESOURCES (EXCLUDING SUBJECTIVE WELL-BEING)

MEW Measure of Economic Welfare

ISEW Index for Sustainable Economic Welfare

GPI Genuine Progress Indicator

SNBI Sustainable Net Benefit Index

CIW Canadian Index of Well-being

SNI Sustainable National Income

Table 4.2 Attempts to measure factors beyond GDP (alternative indices)

AGGREGATE MEASUREMENT OF ALL WELL-BEING FACTORS

SDI Sustainable Development Index

LPI The Legatum Prosperity Index

SPI Social Progress Index

HPI Happy Planet Index

Sources: Kulig et al. (2010); Schoenaker et al. (2015); Wang and Chen (2022)

The dilemma with measuring resources – capital goods – is whether to measure their total stock (as in the National Wealth-type measure) or whether it is sufficient to measure changes in stocks in a positive or negative direction (as in the Genuine Savings index)?

A further problem is that in all cases where the elementary information has different dimensions, aggregation (summability) requires a common denominator, i.e., finding an equivalent dimension, a unit of measurement, to which all elementary factors can be converted to perform the summation. The performance of this step often lacks an objective basis and depends heavily on the prior normative commitments of the aggregating actor. Different ethical perspectives result in different reference parameters (Fleurbaey and Blanchet, 2013, p. 245).

Table 4.3 The development direction of social performance measurement (Hoekstra, 2019)

TRADITIONAL MACROECONOMIC MEASUREMENT

NEW SUSTAINABILITY AND WELL-BEING MEASUREMENT SYSTEM

Purpose Economic growth Well-being and sustainability

Underlying sciences Macroeconomics Economics, well-being and sustainability sciences

Accounting system SNA (System of National Accounts) SGNA (System of Global and National Accounts)

Key indicator GDP System and quality indicators

Source: Own editing

Depending on the responses to these decision alternatives, the following directions of measurement beyond GDP have emerged:

(1) G DP-based indicators that extend GDP by additional elementary factors. Typically, we add to GDP the externalities of pollution, the annualised value (loss) of natural capital consumption and the estimated value of activities that are not measured in the market but contribute to well-being. Examples of such indicators are MEW, ISEW and GPI. These indicators are monetised, measured in monetary units. They intend to implement the most complex measurement.

(2) Well-being indices, such as the HDI, are also based on GDP and weighted by its certain factors. These indicators aim at a more precise measure of well-being in a broad sense, and do not deal with stocks of resources, capital goods and their changes. They are usually not monetised.

(3) These are additional indicators that provide a resourcebased assessment, leaving GDP unchanged but approaching sustainability. These can be focused only on natural resources [Kn] (EPI, EFP), and then they use some form of non-aggregation (EPI measures on a 0–100 point scale, EFP measures in units of biologically active area).

(4) Asset type indicators. In monetary terms, either the current total stock of resources [K] (NW) is measured, or changes in stocks [I] are monitored (GS).

(5) Complex measurement systems for measuring the state of resources and quality of life. Based on the SNA (System of National Accounts) system, which produces the GDP indicator, and as a radical extension of it, a SGNA (System of Global and National Accounts) system is created, which measures the state of natural environmental resources (GENA), the amount of social capital (GSA), the amount of economic assets (GECA) and the income/wealth distribution (GDA), as well as the broader quality of life (GQA) in separate clusters (Hoekstra, 2019).

(6) Composite sustainable development indicators. Usually, they aim to measure over a wide range, similar to Type 1; however, they are not monetised, but perform numerical normalisation and aggregation of the chosen elementary indicators and data. One such indicator is the SDI. This is the composite sustainability indexing used by the Magyar Nemzeti Bank in its Sustainability Reports, and the Hétfa Research Institute prepared the proposal of such a composite index on behalf of the Hungarian Kék Bolygó Alapítvány (Blue Planet Foundation).

It can be seen that the research is based on a number of concepts. The task is not easy because of the limited statistical quantification possibilities and the difficulty in accessing data, and in some cases the data available in kind are difficult to convert into monetary value. However, experimentation is important, because we need to broaden the basis for our community decisions, to expand our knowledge.

Table 4.4 Typical differences in the methodological factors of alternative well-being and sustainability indicators

SUMMARY

Our expectations have changed in consideration of GDP as a measurement method with a purely economic focus and based on the production conditions of the 20th century. In other circumstances, community decision-making has to find answers to other problems, and GDP as an indicator alone does not sufficiently help distinguish between the different options. The fundamental problem of modern democracies and market economies is that, while we increased technical, financial and procedural possibilities to impose more indebtedness on future generations – for example, by rapidly depleting and overusing natural capital, by demographic deficits or by increasing public debt – we have no indicators that can provide a tangible measure of the extent of this indebtedness. Meanwhile, GDP is growing steadily, which suggests that all is well with our economic management-type decisions. Measuring sustainability factors on their own, or combining them with economic output and income, helps us to gain more nuanced and meaningful feedback on our performance at the societal level, and to be able to choose between the alternatives that lie ahead, taking into account the (not always clearly definable) interests of future generations.

The author is an environmental economist, lecturer at the Department of Environmental Economics and Sustainability at the Budapest University of Technology and Economics, secretary of the National Council for Sustainable Development

JÓZSEF POPP

Currently used alternative indicators to measure sustainability

“Growth is uneconomic if it increases environmental and social costs more than production.”

Herman Edward Daly

In the previous parts of the book (especially in Chapter 4) we have seen that GDP is an indicator of current economic performance. Therefore, by definition it does not provide information on the sustainability of the performance. However, there is a legitimate need to understand not only the current performance when assessing the state of the economy, but also whether this can be replicated and sustained in the future. Several attempts have been made to fill this gap by using alternative indicators. In this chapter, we describe the internationally used indicators that aim to complement and enrich GDP by quantifying sustainability. The alternatives cover the economic, environmental and social aspects of sustainability, and highlight the different trends in economic growth and welfare. While the development of these indicators was a major step towards better measuring sustainable development and wealth, they have their limitations. Observing and evaluating the individual components involved in the measurement is a complex task, and not without subjective elements. This is partly the reason why none of the alternatives has yet come close to GDP in terms of general acceptance. In this chapter, we describe these indicators: some of them supplement GDP, while others do not take it into account when measuring sustainability.

INDICATORS CALCULATED BY EXTENDING GDP

Measure of Economic Welfare (MEW)

Nordhaus and Tobin (1972) were the first to develop the MEW (Measure of Economic Welfare) indicator to better understand the relationship between economic growth and welfare, but this indicator also includes information on sustainability. In the calculation, GNP is adjusted in three ways: a) by subtracting certain costs or negative externalities, such as pollution; b) by excluding certain intermediary services, such as defence and police services, as they have no direct impact on welfare growth; and c) by adding certain activities to

GNP, such as household (housework, home repairs, etc.) and leisure activities.

Sustainability is primarily reflected in the MEW by subtracting from GNP the estimated costs of the disadvantages of urbanisation, including pollution, litter, congestion, noise and crime. Welfare is adjusted in accordance with the place of residence with the cost of housing and the probability of traffic accidents, both of which are clearly higher in large cities than in rural areas. However, the calculation also takes into account that higher urban wages partly compensate for the disadvantages of urban life, and that the population benefits from technological progress as a result of moving to the city.

MEW = GNP – depreciation + value of free time + non-market services or activities – intermediary costs – pollution costs

The MEW was calculated mainly on US data and did not become popular in other countries. However, the creation of the MEW proved to be a good stimulus for the development of further alternative indices.

Index of Net Economic Welfare (NEW)

The measure of economic welfare (MEW) was amended by NEW (Net Economic Welfare), developed by Samuelson and Nordhaus in 1980, which attempted to include environmental changes (Samuelson & Nordhaus, 1987). The authors expanded the factors counted, classifying expenditure into new categories. The value of household work, leisure and the informal economy are counted as additions to GNP, and health and education expenditure is counted as an investment in human capital. However, certain components, such as the maintenance of the police, are interpreted as costs because they do not improve welfare inherently and directly. Sustainability, similarly

to MEW, is mainly reflected by deducting certain costs of specific components, such as pollution and urbanisation.

NEW = GNP – depreciation – environmental degradation + value of free time + non-market services or activities + value of unrecognised income – intermediary costs

In the intermediary expenditures, i.e., the neutral category, the indicator includes those economic activities that do not directly affect welfare. These activities are in practice inputs to production and do not bring direct benefits, but they increase the utility of other goods and services: such as police, defence, diplomacy, road maintenance, depreciation (production costs) and commuting.

Index of Sustainable Economic Welfare (ISEW)

The ISEW (Index of Sustainable Economic Welfare) is one of the most comprehensive measures of sustainable economic welfare. Daly et al. (1989), by adjusting MEW, created the ISEW indicator, which starts from personal consumption and then adjusts income distribution by the income distribution factor to indicate incomedistribution-weighted personal consumption, i.e., taking into account the welfare effects of changes in consumption inequality. To this result, it adds or subtracts elements representing economic, social or environmental harms or benefits. Household consumption includes both own income and social benefits (both cash and in-kind) as well as consumption of self-produced goods. The indicator therefore adjusts household consumption in different directions with items affecting welfare: of the 22 indicators, 6 indicators are positive, 2 positive or negative and 14 negative. Studies of the correlation between GDP and ISEW show that the indices diverged from the beginning, and that since 1960, US Sustainable Economic Welfare has essentially flat-lined. This suggests, among other things, that economic growth occurred at the expense of social equality, but also by exploiting the economic

environment, and that while incomes rose in monetary terms, this was not accompanied by a similar increase in perceived welfare (Figure 5.1).

The grouping of economic, social and environmental factors and the positive and negative directions of the adjustment are shown in Figure 5.2. The problem with the calculation of the indicator is that it is data-intensive and relies on data that is not collected regularly in most countries. In particular, the costs of long-term environmental damage are difficult to quantify. Nevertheless, the ISEW has been calculated in several countries, such as Austria, the Netherlands, Germany, Italy, Finland, Sweden and Chile.

Figure 5.1 Development of GDP per capita and ISEW in the USA between 1960 and 2010

Economic (9)

+ personal consumption

- income distribution

+ personal consumption weighted by income distribution

+ services of consumer durables

+ costs of consumer durables

+ public expenditure on health and education

- private health and education expenditure not related to welfare

+/– net capital investment

+/– net lending or borrowing abroad

ISEW indicators

Social (6)

+ housework

+ services of motorways and other roads

– national advertising costs

– urbanisation cost

– direct cost of commuting

– cost of traffic accidents

Environmental (7)

– cost of water pollution

– cost of air pollution

– cost of noise pollution

– loss of wetlands

– loss of agricultural land

– depletion of non-renewable resources

– costs of long-term environmental damage

Genuine Progress Indicator (GPI)

The GPI (Genuine Progress Indicator) is an extended version of the ISEW (Cobb et al., 1995). The GPI includes both the value of market and non-market activities in a consolidated structure. It also takes into account the depletion of natural and social capital, thus providing information on the long-term sustainability of current economic activities. The GPI is calculated on the basis of personal consumption and then its total value is adjusted by the income distribution factor to obtain the income-distribution-weighted personal consumption. Then the economic, social and environmental costs are deducted, and the economic, social and environmental benefits are added.

The GPI is composed of 26 indicators, categorised into economic, social and environmental categories, with 7 economic, 10 social and 9 environmental components. Compared to the ISEW, four

Figure 5.2 Economic, social and environmental indicators of ISEW

Source: Own editing

indicators were omitted: health and education expenditure, national advertising expenditure and urbanisation costs. At the same time, the indicator includes nine new indicators. Six of these are social and two are environmental. The only new economic indicator is the cost of underemployment (negative factor). Of the new social indicators, two are positive factors (the value of voluntary work and the value of higher education), while four are negative factors (the cost of crime, the cost of family breakups, the cost of household pollution abatement, the cost of loss of free time). The two new negative environmental indicators are ozone depletion and the costs of deforestation. GPI therefore added more data sources that influence social and environmental welfare to the calculation of the indicator compared to ISEW (Figure 5.3).

Economic (7)

+ personal consumption

- income distribution

+ personal consumption weighted by income distribution

+ services of consumer durables

+ cost of consumer durables

– cost of underemployment

+/– net capital investment

GPI indicators

Social (10)

+ value of housework and childcare

+ value of tertiary education

– cost of family breakdown

– cost of crime

– households’ pollution abatement costs

– value of voluntary work

– cost of loss of leisure time

+ services of motorways and other roads

– direct cost of commuting

– cost of traffic accidents

Note: Compared to ISEW, the 9 new indicators are shown in italics. Source: Author’s editing

Environmental (9)

– cost of water pollution

– cost of air pollution

– cost of noise pollution

– loss of wetlands

– loss of agricultural land

– loss of forest cover

– climate change

– cost of ozone depletion

– depletion of non-renewable resources

Figure 5.3 Economic, social and environmental indicators of the GPI

COMPOSITE MEASURING SYSTEMS

Sustainable Social Index (SSI)

The SSI (Sustainable Social Index), created by the Cologne University of Applied Sciences (Technische Hochschule Köln: TH Köln) assesses the sustainability of the studied countries in terms of human, environmental and economic welfare. The development of the SSI started in the early 2000s. The SSI was originally developed by the Dutch Sustainable Society Foundation and audited by the European Commission’s Joint Research Centre in 2012. The SSI was published every two years between 2006 and 2016. In 2019, TH Köln took over responsibility for the further development and maintenance of SSI (TH Köln, 2022a).

The SSI is considered one of the most comprehensive sets of indicators, as its three dimensions cover social, environmental and economic sustainability, which it assesses in 7 categories with 21 indicators in 154 countries (see Table 5.1). The main message of the report is that social and economic conditions have improved for many people around the world, while environmental sustainability is deteriorating. Environmental welfare is closely linked to economic activity, with poorer countries performing better in this respect, while dynamic and/or resource-rich countries are at the bottom of the list.

Finland (1st), Portugal (2nd) and the Netherlands (3rd) were ranked in the top three for human welfare, while Zimbabwe, Burundi and Zambia topped the rankings for environmental well-being, and Qatar, Switzerland and Singapore were ranked in order of highest score for economic welfare, respectively. Hungary ranked 22nd out of 154 countries, with the Czech Republic (8th) and Slovakia (13th) ranking higher and Poland (26th) ranking lower among the V4 countries. Compared to 2008, Hungary moved up nine places (Kowalski and Veit, 2020).

DIMENSION CATEGORY INDICATOR

enough food

basic needs

human welfare

environmental welfare

personal development and health

balanced society

economic welfare

natural resources

sufficient drinking water safe hygiene

education healthy life gender equality

income distribution population growth good governance

biodiversity renewable water source consumption climate and energy

energy consumption energy savings greenhouse gases energy from renewable sources

transition organic production genuine savings economy

GDP employment government debt

Table 5.1 Structure of the Sustainable Social Index (SSI)

Source: Author’s editing, based on TH Köln (2022b)

In 2015, the 193 member states of the United Nations adopted the 2030 Agenda for Sustainable Development, in which they set 17 Sustainable Development Goals (SDGs) and committed to achieving them by 2030 (United Nations, 2022). The SDG index is primarily designed to measure progress on social and environmental sustainability in the light of the agreed SDGs. The reports prepared accordingly look at 193 countries to see how they are meeting the needs of the present without compromising the needs of future generations.

The SDG Index measures countries’ performance in the range between 0 and 100 points. Different numbers of indicators (1–7) are assigned to each target with the same weight, because there is no hierarchical relationship or order between the targets. Indicators were grouped into three categories: the first included those that reduce people’s dependence on natural resources (e.g., facilitating access to water, zero-emission energy), the second included those that increase dependence on resources (e.g., building a hospital, a school) and finally the third included indicators that are not directly related to resource needs (e.g., women’s equality). The closer a country is to the target, the higher it scores on a 0–100-point scale. So, for example a score of 80 means that the country met 80 per cent of the targets across the 17 targets comprehensively and on average. While the 2016 indicator included 60 indicators, in 2022 it included 120 indicators, of which 94 are global and 26 additional indicators are only for OECD member countries (Sachs et al., 2022).

In the 2022 SDG report, the global SDG index averages 66 points, a decrease compared to 2020. Between 2015 and 2019, the global SDG index increased by an average of 0.5 points per year, but the UN says this is still too slow to reach the SDGs by 2030. The backlog in the goals on poverty eradication, decent work and economic growth is particularly large, which contributed to the failure to meet the goals on hunger eradication, health and well-being, quality education and

The Sustainable Development Goals (SDG) index and the Sustainable Development Report (SDR)

environmental protection. Finland, Denmark and Sweden top the 2022 ranking. The top ten countries are in Europe, all with a strong performance in economic, social and environmental sustainability. East and South Asia has made more progress than any other region since the targets were adopted in 2015. However, even developed countries are making only slow progress towards mitigating climate change and protecting biodiversity (Goals 12–15) and achieving sustainable food systems and diets (Goal 2) (Sachs et al., 2022).

In the case of international spill-over effects, positive and negative externalities should be measured and carefully managed, as the countries concerned cannot achieve their goals if negative externalities from other countries hinder their efforts. The international spill-over effects in the context of SDGs are felt in trade, air and water pollution, economic and financial flows, peacekeeping and security.

Key findings of the Sustainable Development Goals Report 2022 on the achievement of each of the goals (United Nations, 2022):

1. Eradicate poverty: 657–676 million people are currently living in extreme poverty, compared to 581 million before the pandemic.

2. Ending hunger: one in ten people worldwide is starving.

3. Health and well-being: the COVID-19 pandemic threatens decades of progress in global health.

4. Quality education: Between 2020 and 2021, 147 million children missed more than half of their compulsory in-person education and 24 million pupils never returned to school.

5. Gender equality: Women accounted for 39 per cent of the workforce in 2019, rising to 45 per cent of global employment in 2020.

6. Clean water and basic sanitation: to meet the drinking water and sanitation targets by 2030, the rate of progress needs to quadruple.

7. Affordable and clean energy: the pace of electrification slowed down, with 679 million people projected to still have no access to electricity in 2030 according to current trends.

8. Decent work and economic growth: one in ten children worldwide is involved in child labour – 160 million in 2020.

9. Industry, innovation infrastructure: global production recovered after the pandemic, but this recovery is most visible in the least developed countries.

10. Reducing inequalities: the pandemic caused income inequality between countries to rise for the first time in 20–30 years.

11. Sustainable cities and communities: to ensure that no one is left behind, increased attention must be paid to the population of around one billion slum dwellers.

12. Responsible consumption and production: 13.3 per cent of global food production is lost in the process between harvest to trade, and 17 per cent is lost as a result of consumer waste.

13. Action on climate change: energy-related CO2 emissions increased by 6 per cent in 2021, reaching their highest level ever.

14. Protecting oceans and seas: In 2021, more than 17 million tonnes of plastic were dumped into the ocean, a figure that is expected to double or triple by 2040.

15. Protecting terrestrial ecosystems: 10 million hectares of forest are lost every year, and almost 90 per cent of global deforestation is linked to agricultural production.

16. Peace, justice and strong institutions: Between 2015 and 2020, the homicide rate fell by 5.2 per cent, but a quarter of the world’s population lives in conflict-affected countries.

17. Partnership for reaching the goals: net ODA reached a new high of USD 177.6 billion, largely thanks to COVID-19-related aid, but support for SDG data fell by more than 18 per cent in 2020.

MEASURING ECOLOGICAL SUSTAINABILITY

Ecological footprint (EF)

The EF (Ecological Footprint) indicator, associated with Wackernagel and Rees (1996), expresses the amount of bioproductive (fertile) land that human society needs to sustain itself and absorb the waste produced, given the level of technological development, taking

into account the ecological carrying capacity of the land. Since 2003, the Global Footprint Network has been calculating the ecological footprint based on the UN database. The ecological footprint is therefore defined as territorial units (global hectares) that can support a population at a given standard of living and indefinitely. The global hectare is a common denominator between the ecological footprint of people or activities and the biocapacity of the Earth or a given region, taking into account the diversity of land types. An ecological footprint can be calculated at the level of an individual, organisation, social group, region or country, and other footprint indicators (e.g. carbon footprint, water footprint) are also common.

The difference between the demand for biocapacity (ecological footprint) and the supply of biocapacity (both expressed in global hectares) is the size of the ecological balance. If the difference between the two values is negative (i.e., the footprint is larger than the biological capacity), the country has an “ecological deficit”, but if the value is positive, an “ecological reserve” is the result. The Global Footprint Network data published in 2022 covers the period 1961–2018. In the case of the ecological balance, 51 countries have a biocapacity that exceeds their ecological footprint. These countries, mainly in Africa and South America, but also some European countries, have an ecological reserve. The other 134 countries have ecological deficits. Singapore, a small, densely populated and developed country, has the largest deficit among these countries. Hungary ranks 110th with a 50 per cent deficit.

Every year, Earth Overshoot Day marks the ecological “overshoot day”, when the Earth’s population consumes the amount of natural resources that would be available for a whole year in a sustainable world. The ecological overshoot date was 25 December 1971, and then gradually moved earlier in the year to 28 July 2022 (Figure 5.4).

Environmental Performance Index (EPI)

The Environmental Performance Index (EPI) specifically ranks a country’s environmental performance against environmental indicators and is well aligned with the Sustainable Development Goals and indicators. The EPI report is published by Yale University (Center for Environmental Law and Policy) and Columbia University (Center for International Earth Science Information Network) in collaboration with the World Economic Forum and the European Commission’s think tank (Wolf et al., 2022).

Figure 5.4 Global Overshoot Day (1971–2022)

EPI focuses on three policy objectives: (1) reducing the impact of the environment on human health (environmental health); (2) improving ecosystem vitality and (3) reducing climate change. The climate change target area is first mentioned in the 2022 EPI report. The three target areas have 11 themes with different weights (Figure 5.5).

The EPI is therefore a composite indicator, which calculates an aggregate value between 0 and 100 for the countries under study from several basic indicators. The value of the indicator is relative, as it compares with the targets set and the values of the currently used indicators are also normalised. So, it is also influenced by the performance of the other countries evaluated. The main principle of the calculation is that the value of each indicator for a given country is calculated from the deviation from the targets (Wendling et al., 2018, p. 9).

The 2022 EPI uses 40 benchmarks to rank 180 countries and also provides a powerful tool to measure the UN’s Sustainable Development Goals. In 2022, top-ranked Denmark’s indicator was 77.9. Hungary ranks 33rd in the EPI ranking with an index of 55.1. The EPI rankings show that economic development tends to increase environmental pressures, but the most developed countries were able to reverse this trend.

According to EPI analysis, few countries, including Denmark and the UK, will achieve carbon neutrality by 2050, when more than 50 per cent of emissions will come from four countries: China, India, the USA and Russia (Wolf et al., 2022).

and natural environment 18%

Exposure to heavy

and drinking water

Air EPI Acid rain 4% Agriculture 4%

quality Fishery 5%

Water resources 3% Sanitation Ecosystem services 8%

Note: The EPI consists of 3 target areas, 11 topic categories and 40 performance indicators: the climate change target area has 1 topic category and 9 indicators, the healthy environment target area has 4 topic categories and 13 indicators, the ecosystem viability target area has 6 topic categories and 18 indicators.

Figure 5.5 Environmental Performance Index (EPI) components (target area and topic category)

Climate Change Performance Index (CCPI)

The CCPI (Climate Change Performance Index), published jointly every year since 2005 by Germanwatch, NewClimate Institute and Climate Action Network International, tracks the climate protection performance of 59 countries and the EU, which are together responsible for at least 90 per cent of greenhouse gas (GHG) emissions. The four categories of the assessment are GHG emissions, renewable energy, energy use and climate policy, with 14 corresponding indicators (Figure 5.6). The CCPI aims to increase the transparency of international climate policy to allow comparison of the climate protection efforts and progress of the countries under review (Burck et al., 2022). The survey involves 450 climate and energy experts.

CCPI 2023 was published in November 2022. According to the 2023 assessment, the world’s energy supply remains heavily dependent on fossil fuels (coal, oil and gas) in many countries, where strong market players are hampering a sustainable and equitable transformation of the energy sector. Thus, the voluntary commitments made in the Paris Agreement are not enough to keep the global average annual temperature increase below 1.5 °C above pre-industrial levels. This requires achieving carbon neutrality at global level by 2050 and a 50 per cent reduction in emissions by 2030. That is, a much larger reduction in annual emissions is needed than the magnitude of the current measures.

The top three places in the CCPI ranking are empty because none of the countries in the ranking scored outstandingly well in all categories, meaning that no country made sufficient efforts to keep global warming below the 1.5 °C limit by 2050, according to those compiling the ranking. This leaves the leading country, Denmark, in 4th place with 79.61 points, followed by Sweden (5th), Chile (6th), Morocco (7th) and India (8th) with over 67 points. At the bottom of the list are Russia (59th), Korea (60th), Kazakhstan (61st), Saudi Arabia (62nd) and Iran (63rd) with scores below 26 points. The US re-joined the Paris Agreement in 2021, moving up to 52nd place in 2023 from last place, but its score (38.53) is still low. Hungary is ranked 53rd (Burck et al., 2022).

Current ratio of renewables in global primary energy supply (compared to 2°C below baseline scenario) 5%

Development of energy supply from renewable energy sources 5%

Current ratio of renewables in global primary energy supply 5%

Global primary energy supply per capita to reach 2030 target (below 2°C) 5%

Current global primary energy supply per capita compared to 2030 target (below 2°C limit) 5%

Former global primary energy supply per capita compared to 2030 target (below 2°C limit) 5%

Energy consumption20%

20%

Renewable energy to reach 2030 target (compared to below 2°C scenario) 5%

Climate policy 20%

Nationalclimate policy10% climateInternationalpolicy10%

Current energy consumption compared to 2030 targe (below 2°C limit) 5%

Source: Author’s editing, based on Burck et al. (2022)

Current GHG emissions per capita compared to 2030 target (below 2°C limit) 10%

GHG emission reduction compared to 2030 target (below 2°C limit) 10%

Former GHG emissions per capita 10%

Current GHG emissions per capita 10%

Figure 5.6 Structure of the Climate Change Performance Index (CCPI)

CONCLUSIONS

GDP is the most widely used indicator of economic performance, but by definition it cannot capture the sustainability of the economic performance it measures. At the same time, the recognition of the limits to growth has increased scientific, societal and policy demand for the development of sustainability indicators to measure current performance. These indicators can be grouped into three categories. One quantifies the damage caused by economic activity, and the benefits and other outputs not measured in GDP, following the principles of GDP calculation. These include the Measure of Economic Welfare (MEW), the Net Economic Welfare Indicator (NEW), the Index of Sustainable Economic Welfare (ISEW) and the Genuine Progress Indicator (GPI). The second group breaks away from the material calculation of GDP, and the composite indicators thus created include indicators measuring the different dimensions of social, financial, and environmental sustainability in addition to GDP. They typically give a value between 1 and 100 to show the relative level of countries compared to each other. These include the Sustainable Society Index (SSI), the Sustainable Development Goals (SDG) index and the Sustainable Development Report (SDR). The third set of sustainability indicators focuses on only one, mainly environmental, dimension of sustainability. These include the Ecological Footprint (EF), the Environmental Performance Index (EPI) and the Climate Change Performance Index (CCPI). All these indicators have correctly identified the problem, and even partly provided a solution. However, they have failed in replacing GDP or GNP (Table 5.2). Measures of general welfare are of great interest, but observing and evaluating the individual components included in the measures is a complex task, not without subjective calculation.

ISTVÁN TÓZSA

Currently used alternative indicators to measure welfare and well-being

“There must be a better way to make the things we want, a way that doesn’t spoil the sky, or the rain or the land.”

Paul McCartney

As we saw in Chapter 3, human well-being is influenced by a number of factors outside GDP. This includes our health, our security, our family and social relationships, our work-life balance, the state of our natural environment, and more subjective indicators such as simply our happiness and our ability to achieve our plans. GDP by its very nature does not include these aspects. However, without them we cannot judge the well-being of a country. Another indicator is therefore needed to measure well-being. This need has been raised before, but no clear solution has yet been found. The difficulty lies in the need to condense the many different aspects into one indicator, if possible, and the measurability of these aspects is itself questionable. As opposed to the dry but measurable accounts of GDP, how can we measure our happiness? Although the task is difficult, many attempts have been made by international institutions and researchers. In this chapter we present ten well-known projects that attempted to measure general human well-being beyond material welfare.

WELL-BEING AND WELFARE

It is the author’s personal experience that in 1989, the year of the regime change in Hungary, people stood in queues in shops with sullen faces, or hurried to their work, grim-faced and worried, hustling in the shortage economy, nervous, tired, working several shifts for their livelihood and the well-being of their families. They were noticeably unhappy. That same year in Sweden, in a society of plenty, we could meet polite, helpful, sophisticated-looking, kindly smiling, joking people. We can try quickly concluding the topic by saying that the reason is obvious, since the GDP per capita, the measure of living standards, according to the UN database, was only USD 3,100 for Hungarians and USD 25,600 for Swedes. This happiness from welfare, which is also visible on the man in the street, is understandable. Yes, but, also in the same year, in Cuba, through the walls of the poor “family homes” made of wooden planks on the beach, through the gaps, you could hear the merry banter, singing and guitar playing; Cuban families, neighbourhoods and street people seemed to be

much more carefree than even the Swedes, even though their per capita income that year was 600 dollars less than the Hungarian.

The fallacious correlation between material welfare and happiness had been already noted in classical antiquity: “happy is he who is happy with little money; unhappy is he who is unhappy with much money” (Democritus). The best-known saying survives from the Protestant Reformation: “money does not make man happy…” (Martin Luther). In economics, the first scientific study of this issue was by Richard Easterlin (1974), who showed empirically that material welfare and people’s subjective happiness increase linearly with each other up to a certain point, up to the level of elementary welfare, and then happiness starts to decline; this is the so-called Easterlin Paradox Beyond the welfare tipping point defined by Easterlin, the sense of happiness (Social Well-Being –SWB) divides into two, namely the hedonic happiness originally distinguished by Aristotle, i.e., happiness grounded in money, fame and beauty; and the eudaimonic happiness of inner self-actualisation and connection to human communities (Görög, 2015).

According to a simple survey, the world’s richest people rated their satisfaction with life at 5.8 on a scale of 1 to 7. The nomadic Eskimos of North Greenland and the nomadic Maasai of East Africa, who are as poor as beggars compared to them, also felt 5.8 percent satisfied with their lives. Below this, but perhaps less than we expected, was the satisfaction rate of 4.6 for slum dwellers in Calcutta (Diener and Seligman, 2004).

This has been a matter of debate among economists. Although research surveys showed for example that, between 1946 and 1989, in the USA, Japan and France, despite significant economic growth and a 150 per cent increase in per capita income, subjective happiness stagnated (Diener et al., 1999). There were also studies showing that subjective satisfaction rises in parallel with material welfare, especially in the Nordic countries and the developed Anglo-Saxon world (Hagerty and Veenhoven, 2003). Easterlin (2005) challenged

these results with the measurement methodological objection that happiness cannot be measured in the same way in different regions of the world, as it is also a culture-specific concept.

In the literature, the term well-being appeared alongside the term wealth or welfare, which, as a reflection of this, was also reflected in the Hungarian language by a new term for well-being that had not existed before: jóllét. According to this, welfare refers to a relatively easily measurable income, a financial situation that allows the availability of quality services necessary for a comfortable and carefree life, while well-being tries to quantify only the estimable, subjective feeling of being able to feel appreciation, including in terms of individual health, security, happiness, satisfaction, life and life goals.

Correlation analyses were also carried out in the global questionnaire survey of happiness and satisfaction, partly confirming the existence of the Easterling Paradox. But they partly also confirmed the view that rich countries are the happier (Inglehart and Welzel, 2005). In the correlation matrix of the so-called Inglehart–Welzel Cultural Map, the negative range on the horizontal axis is the conditions for survival and the positive range is individual selffulfilment. The negative range of the vertical axis shows the traditional national and religious values, and the positive range is the modern secular values. In this matrix, country clusters could be outlined (Figure 6.1). This research proved that happiness is not measured uniformly across the world; the eight clusters include at least sixteen different geographical and cultural entities or groups of countries.

Post-communist

Far East

Catholic Europe

Reformed Europe -- Protestant Europe

Africa

South Asia

Latin America

Anglo-Saxon

Note: The distinction between GDR-GSR is due to socio-economic differences that can be measured three decades after the division of the East-West German parts of the country. Source: Own editing, based on World Values Survey, 2022

“Let him who has no money drink wine, and all the wealth of the world will be his”, the Hungarian poet Sándor Petőfi wrote in one of his poems. In the words of American writer James Baldwin: “Money, it turned out, was exactly like sex, you thought of nothing else if you didn’t have it and thought of other things if you did.” Such quotations link the already regionally fragmented notion of happiness to the power of passions and also indicate how subjective and variable it is.

In this chapter, the methodology and lessons learned for measuring well-being are presented using ten indicators as examples. It is worth looking at several indicators because none of them has yet achieved the same recognition and acceptance status as GDP. All test methods have advantages and disadvantages, and their results vary considerably. These indicators do not take into account either the

Figure 6.1 Inglehart’s value axis regional clustering of the concept of happiness in individual countries

differences in values revealed by the regional Inglehart–Welzel Cultural Map or the dual qualitative content of “happiness” as indicated by the Easterlin Paradox. However, the assessment of the results can still give an idea of the perceived well-being in different countries, in different dimensions.

The Easterlin Paradox can be resolved according to Fromann (2010): after the satisfaction of elementary welfare, the well-being component of happiness may increase or decrease further with increasing wealth, depending on whether the factors of pleasure-seeking (hedonism) or self-actualisation (eudaimonia) are measured.

Well-being (SWB) happiness

Hedonic happiness

Welfare critical point

Eudaimonic happiness

Elementary welfare

Prosperous welfare

Welfare (GDP) Wealth

Source: Author’s editing, based on Fromann 2010

Human Development Index (HDI)

The Human Development Index (HDI) is a measure used by the United Nations to measure quality of life beyond material welfare. Two economists, led by Mahbub ul Haq, developed the first version in 1990, based in large part on Amartya Sen’s concept, for the UN Development Programme. Its three pillars are health, knowledge and well-being. It derives health from life expectancy at birth, education

Figure 6.2 The critical welfare point

from years of education, and welfare from financial status (GDP). HDI is the most widely used alternative well-being indicator backed by the United Nations. It is simple to calculate (it now covers 189 countries) and it has been available since 1993. However, it has the disadvantage of not addressing many areas of well-being, such as the state of the environment and social inequalities.

Between 2010 and 2021, Switzerland, the Nordic countries, Ireland, Australia, Germany, the Netherlands and Hong Kong led the HDI index in the top 10. Hungary is ranked 46th out of 189.

0.3850.962

Source: Human Development Reports

The Happy Planet Index (HPI) seeks to measure the ecological efficiency of well-being through subjective perceptions of ecological footprint, quality of life and well-being. It aims to show the extent to which people in each country can live a happy and sustainable life at the same time. This measure was developed by the New Economics Foundation in London on behalf of the UN.

Figure 6.3 Human Development Index (HDI) in 2021

Happy Planet Index (HPI)

The calculation of the Happy Planet Index is similar to HDI: quality of life is represented by life expectancy at birth (UN data), multiplied by a score on a 10-point scale of well-being showing life satisfaction (Gallup World Poll), then divided by the numerical ecological footprint in hectares (Global Footprint Network data). By taking the ecological footprint into account, the indicator also provides an answer to the question of how happiness and life satisfaction can be achieved at a health and environmental cost, and who can be happy (also) without putting less strain on the Earth’s ecosystem.

Source: Own editing, based on https://greennews.ie/opinion-forget-gdp-and-adopt-the-happy-planet-index/

The Happy Planet Index has the advantage of incorporating the environmental aspect, while its evaluation is made more difficult by the fact that one third of it is determined by a subjective questionnaire. The aim was to measure 152 countries, but due to the coronavirus epidemic 88 countries were included in 2020. The “ladder of life” questionnaire measuring subjective well-being is missing in the case of the remaining countries, and in many cases the ecological footprint is also missing.

If we look at the 10 “happiest” countries in the world, they are overwhelmingly the “poor” countries of Central and South America. Switzerland entered the top ten as the only European country no earlier than in the late 2010s. The V4 countries are in the middle,

Figure 6.4 Structure of the Happy Planet Index (HPI)

with roughly the same results. It is worth noting that Singapore, South Korea and China are also close to the V4 countries in terms of happiness, while the “rich” USA and the “rich” Arab states are in the bottom third of the list. This calculation method seems to support the Easterlin Paradox; in the words of the Hungarian novelist Mór Jókai, “the poor plutocrats”.

Better Life Index (BLI)

The Better Life Index (BLI) is developed by the OECD, the Parisbased Organisation for Economic Co-operation and Development. The Better Life Index covers the 38 OECD member countries, plus Russia, Brazil and South Africa. It is intended as an alternative to GDP that takes a number of well-being factors into account in addition to income.

The 11 factor groups of the BLI are: housing, income, workplace, community, education, environment, citizen participation, health, life satisfaction, safety and work-life balance. Despite its name, the index does not include an aggregate indicator or ranking. So, it is more of a collection of data. Based on our own calculation using the 7 indicators, in 2020 Hungary ranked 31st out of 40 in a list of predominantly developed countries. Among the Visegrád countries, the Czech Republic has the highest ranking (22nd), followed by Slovakia (26th) and Poland. However, this is only an estimate, because the OECD does not publish aggregate scores or rankings.

Index of Wealth to Well-Being (W2W)

The Wealth to Well-Being (W2W) indicator was introduced by the Boston Consulting Group to show how successful countries have been in putting economic development at the service of the welfare of their people (Beal et al, 2012). In the calculation, the Sustainable Economic Development Assessment (SEDA), which can also be interpreted as a standalone indicator, was compared to per capita income. The

resulting quotient is therefore a measure of well-being relative to economic development. It is one of the indices covering the largest number of indicators in terms of welfare and well-being (Mukherjee and Ahuja, 2018).

Income is measured by GDP; economic stability by inflation and GDP growth volatility; employment by the unemployment rate. The so-called investment indicators are calculated from the availability and quality of education and health services and the state of infrastructure. Social sustainability is also measured by a number of indicators, including income inequality and the strength of cohesion between NGOs, the level of civic activism and gender equality data. The quality of governance is measured in terms of efficiency, accountability (transparency), freedom of non-governmental and economic organisations. The environmental indicator is calculated from the quality and effectiveness of environmental policy, the extent of water pollution and load of transport.

The speciality of this coefficient is that it relates well-being to income, i.e., it measures the extent to which material wealth was converted into “real” happiness. The effect of the Easterlin Paradox can also be observed in this ranking: above a certain income level (roughly USD 25,000), well-being increases to a lesser extent and the curve flattens.

In 2020, Hungary was ranked 28th out of 141 countries, behind Poland (9th) but ahead of Slovakia (41st) and the Czech Republic (32nd).

Economics

Economicstability Income Environment Governance

Civil Society Equality Infrastructure

SEDA Health Education

Employment

Sustainability Investments

Source: Author’s editing, based on Beal et al. (2012)

Inclusive Development Index (IDI)

The Inclusive Development Index (IDI) was developed by the World Economic Forum (WEF) to measure not only economic development but also primarily its inclusiveness and sustainability. As with the concept of the BCG’s “wealth-to-well-being” coefficient, in addition to examining economic development, this indicator looks at how widely economic development is distributed in society. There are 3 domains and 12 indicators for the calculation of the IDI composite indicator (WEF, 2018).

1. Growth and development (GDP per capita, labour productivity, healthy life expectancy, employment).

Figure 6.5 SEDA assesses relative well-being across ten dimensions

2. Inclusion (net income and inequalities in wealth distribution with Gini coefficients, poverty, average income.

3. Intergenerational distribution and sustainability (adjusted savings, carbon intensity kg/GDP, public debt, young and old population as a percentage of working age population).

In the 2018 ranking, Hungary was ranked 23rd out of 103 countries surveyed. Among the countries in the region, the Czech Republic (15th) and Slovakia (20th) are ahead, while Poland (27th) is behind. Hungary is performing well in terms of rising living standards and wealth inequality. On the other hand, the level of public debt is above average, and the proportion of elderly people compared to the working age population is high.

The advantage of this indicator is that it gives priority to social aspects, though it essentially takes nothing else into account (state of the environment). However, it is one of the most suitable indicators for its own purpose.

World Happiness Report (WHR)

The World Happiness Report (WHR) is a publication of the Sustainable Development Solutions Network. The ranking of countries by subjective well-being is based on the Cantril Index survey. The following indicators provide a statistical explanation of the Cantril Index survey scores:

1. GDP per capita,

2 life expectancy,

3. generosity,

4. corruption,

5. freedom to make life choices,

6. social help, support and

7. vision of the future.

The publication is produced by a team of independent experts; the data for the analysis are provided by Gallup World Poll and Lloyd’s Register Foundation, based on questionnaire surveys, except for the first and second indicators (where World Bank and WHO data are used).

Scandinavia and Switzerland top the WHR list of “happiness”, as well as the index reflecting inclusion (IDI) (1st Finland, 2nd Denmark, 3rd Iceland, 4th Israel, 5th Netherlands, 6th Sweden, 7th Norway, 8th Switzerland, 9th Luxembourg, 10th New Zealand). In 2023, Hungary is ranked 51st out of 137 countries.

According to the survey, the most important factor for individual happiness is future expectations. The second most important is financial situation, followed by indicators measuring social cohesion and individual health and freedom.

Social support

Health Freedom

Corruption

LESS COMMON METRICS:

1. Weighted Index of Social Progress (WISP)

Generosity

Richard J. Estes, a professor at the University of Pennsylvania, also developed a model to measure quality of life: the Weighted Index of Social Progress (WISP) with scores ranging from 0 to 100 and

Figure 6.6 The order of importance of the factors contributing to the world’s happiness, based on the summation of measurements made in 137 countries

Source: Author’s editing, based on Helliwell et al. (2022)

a measure of deviation from the mean. This composite index can be constructed from 35 indicators covering 10 domains.

The analysis is particularly useful for measuring the situation of less developed countries. Several indicators (e.g., illiteracy, women’s rights, aid, assessment of armed conflicts) show consistently high levels in developed countries.

2. Physical Quality of Life Index (PQLI)

The Physical Quality of Life Index (PQLI) like the HDI, is an index with only three components: life expectancy, literacy and infant mortality. A significant overlap is assumed in the index between life expectancy and infant mortality. It was commissioned by the Overseas Development Council and developed in 1978 by Morris David Morris.

3. Life Quality Index (LQI)

The London-based Economist Intelligence Unit (EIU) produced the Life Quality Index (LQI), which, like many other indicators discussed so far, attempts to measure and rank which countries offer the best opportunities for a healthy, safe and happy life. The aspects covered by the survey are material welfare, life prospects, quality of family life, political freedoms, job security, climate, personal and physical safety, quality of community life, governance and gender equality.

4. Global Liveability Index (GLI)

Unlike the other indicators discussed so far, the Global Liveability Index (GLI) does not rank countries, but 173 major cities around the world. It focuses primarily on well-being and environment based on 30 indicators. It is also produced by the Economic Intelligence Unit (EIU) belonging to The Economist magazine. The “liveability” of the selected cities is assessed from the individual’s point of view, based on a score out of 100 compared to New York. The factors considered are:

• stability (crime, war, protests, terrorism),

• health (private, public, drugs),

• culture and environment (climate, corruption, religion, censorship, sport, culture, food supply, services),

• education (private, public) and

• infrastructure (transport, housing, utilities).

Because of the data collection, the sampling method and the qualifying factors, this indicator cannot be recommended as an alternative to GDP, especially since, as it focuses primarily on wellbeing, it completely ignores welfare indicators. This indicator is more relevant in surveys on urbanisation or marketing of settlements.

SUMMARY

International institutions and economists have already made significant attempts to overcome the GDP’s shortcoming that it only measures material income, while not being sensitive to the many other factors affecting our real well-being. To this end, complex indicators have been developed that account not only for GDP but also health, the state of our environment, our social relationships, social cohesion, self-actualisation and other factors (Table 6.1). None of these approaches have become as popular as GDP. Also, none of them could replace GDP in public discourse about development or as a compass in decision-making. Perhaps the closest to reaching this status is the Human Development Index (HDI), which is backed by the United Nations.

Table 6.1

Summary evaluation of welfare and well-being measurement indices according to their main criteria

In addition to the examples listed above, dozens of other measurement, indexing and ranking methods have been developed to quantify welfare and well-being. As can be seen from the examples above, each method is unique, and each tries to find a solution with scientific rigour and statistical expertise. They try to define the domains and measures of well-being beyond material conditions. It should be noted, however, that there is no index that satisfies all of the following criteria in all respects:

1. has a simple algorithm based on population data and/or a public survey,

2. covers all areas that affect well-being1,

3. has been prepared regularly with the same method for at least a decade,

4. covers roughly the same number of countries over at least a decade,

5. can take into account the fact that the interpretation of wellbeing is region-specific and culture-specific,

6. distinguishes between the criteria of hedonic and eudaimonic happiness.

Without exception, the indices of the surveys listed in this chapter produced different country rankings, which obviously follows from the fact that well-being is subjective. Islamic, Buddhist or Christian cultures have different interpretations of the components of happiness and satisfaction. This means that the same method could not be used to measure them, even if the same survey questions were used. However, beyond these cultural differences, the surveys also have shortcomings: lack of timeliness, constant revisions, countries left out. Each of these measurements may be more of a snapshot; however, when taken together, they draw a credible picture. By no means can we say that we have solved the problem of measuring well-being. Research is currently being conducted in several directions,

1 These are material welfare, health/quality of life, security, environment, employment opportunities, civic cooperation and freedom of expression, access to services, women’s equality and corruption.

partly in parallel, as is typical of modern scientific research. The next decades may reveal a winning approach and narrative it will be revealed whether a new indicator can take on a role in the social sciences and in social policy formation that equals the current role of the GDP in the economy.

PÁL BÓDAY AND ZSUZSANNA SZŐKÉNÉ BOROS

Sustainability indicators for the Hungarian economy

“We cannot choose between [economic] growth and sustainability – we must have both.”

Paul Polman

In the previous chapters, we have seen the limitations of GDP and the alternative measures that experts and international institutions have proposed in an attempt to overcome these limitations. It is important, however, that the international statistical community is continuously striving to improve GDP within the system of national accounts, to meet new challenges and expectations. This chapter summarises the developments in national accounts/GDP and related environmental accounts that are gradually coming into force, and thus providing increasingly more information within the national accounts system on the use of environmental resources, the state of the environment, and the progress of digitalisation and globalisation.

The complex phenomenon of sustainable development is linked to a number of processes and conditions that need to be monitored continuously in order to determine the extent to which the changes taking place around serve to ensure that the present generation, which is creating its own welfare, does not exhaust and deplete its resources, but preserves and even expands them in sufficient quality and quantity for future generations. To do this, we need indicators that allow us to compare the past and the present with the goals we set and the progress towards them.

The system of national accounts was created to describe the performance of the economy. Statistical methods and recommendations are being developed to describe the relationship of the economy with well-being and the environment, so that they can be systematically presented in a way compatible with the accounting system of national accounts. Therefore, the multiannual reviews of the national accounts system also cover these areas. The review addresses, among other things, the issues identified above as constraints to GDP. For example, it may include more detail on accounting for biological resources, introduce data as a new tool, and seek to take household labour into account. The new indicators derived from these, such as resource productivity or greenhouse gas intensity, help us to better understand the relationship between the environment and the economy.

INDICATORS OF SUSTAINABLE DEVELOPMENT IN HUNGARY

The Hungarian Central Statistical Office (HCSO) began publishing a set of indicators related to the phenomenon of sustainable development in the mid-2000s under the title “Indicators of Sustainable Development in Hungary”. The indicator system, which has been published regularly since then, has undergone continuous changes over the years in its content, structure and details and its relationship to related theoretical frameworks. The aim of continuous improvement is to ensure that the indicator system supports this difficult-to-measure set of phenomena as well as possible, with indicators that are aligned with the objectives as closely as possible, and that can satisfy the widest possible range of users.

Source: HCSO

The publications on sustainable development in Figure 7.1 were initially based on the EU list of indicators valid at that time, which was continuously supplemented with indicators that were more focused on domestic targets. It later adopted the resource-based grouping

Figure 7.1 Sustainable development publications

of the National Framework Strategy on Sustainable Development, which distinguishes between four resources: human, social, economic and environmental. Most recently, in addition to the revision of the indicator set, the indicator framework has been structured according to the national strategy and the UN Sustainable Development Goals (SDGs).

Two publications are published each year: the full set of indicators online, and a shorter summary available in pdf and print formats. The current set of indicators consists of 134 indicators, of which 33 are human, 25 are social, 23 are economic and 53 are environmental in terms of showing the status of economic resources.

The detailed publication includes, for each indicator, a so-called relevance, showing the relation between the indicator concerned and sustainability, and also includes a detailed definition of the indicator, an analysis of the phenomena described and an international comparison, if the indicator is available at international level. In addition, a textual assessment is included for each indicator. The indicators are accompanied by sub-indicators or supplementary indicators to better understand the phenomenon concerned. Links are provided to the data used, which are usually more detailed than those shown in the publication. Data and figures from the publication are also available for download.

The economic pillar of sustainability is discussed in a separate chapter of the publications. The indicators describing the link between sustainability and the economy are mainly found in this chapter. When looking at the UN Sustainable Development Goals, there are indicators linked to the economy in several areas. Goal 1: eradicate poverty; Goal 5: gender equality; Goal 8: decent work and economic growth; Goal 9: industry, innovation and infrastructure; Goal 10: reducing inequalities; Goal 12: responsible consumption and production and Goal 17: partnership for achieving the Goals; all of these have indicators under the economic pillar, measuring the sustainability of the economy.

As mentioned above, the set of indicators is constantly undergoing major and minor changes, and in the latest set of indicators for 2022,

the area of economic indicators was enriched with indicators related to green public procurement, environmental R&D activities and international development aid.

REVIEW OF INTERNATIONAL METHODOLOGIES FOR NATIONAL ACCOUNTS AND BALANCE OF PAYMENTS: BPM7/SNA2025

International methodologies for large systems describing macroeconomic processes are subject to regular review. The aim is to ensure that the systems are capable of tracking economic changes in the world and that the data produced by the methodologies (such as national accounts, including GDP and current account balance) reflect real world developments as realistically as possible. The practice to date has been to carry out major reviews every 15 years or so. The methodology currently in use, SNA2008 and the BPM6 (Balance of Payments Manual), was introduced in 2008. In the European Union, a more detailed, more rigorous set of rules based on the SNA (System of National Accounts) is in force and has the force of law, the latest version of which is the ESA2010 (European System of Accounts). This revision of methodologies has for the first time led to the harmonised development of national accounts and balance of payments methodologies at international level, in order to minimise the differences between the two statistics.

The introduction of SNA2008 and BPM6 did not mark the final closure of methodological issues. There remain a number of areas identified by the international expert group on methodologies identified as research topics for the next major methodological revision. However, the economic, environmental and political changes that have taken place in the almost ten years since the review and their accelerated and continuous nature have made it necessary to review the methodologies as soon as possible.

Recognising this external need, in March 2020 the UN Statistical Commission (UNSC) and the IMF BOPCOM (IMF Committee on

Balance of Payments Statistics) decided to revise both the SNA2008 and the BPM6. The steps and timeline are shown in Figure 7.2; the target date for the adoption of the two revised standards is 2025.

The Update Process

UNSC: launch update process

Development of guidance notes & country consultation and testing

2020-2023

UNSC: adopt recommendations

Draft 2025 SNA, incl. country consultation on new text

BOPCOM: launch update process

Research work, leading to draft annotated outline (AO)

2020-2022

BOPCOM: endorse draft AO after public consultation

including country consultation on new text

Committee (AEG and ISWGNA): approve 2025 SNA

UNSC: adopt 2025 SNA

BOPCOM: agree on BPM7

IMF Chief Statistician: approve BPM7

Source: United Nations Statistical Commission, Intersecretariat Working Group on National Accounts (ISWGNA)

Close cooperation was established between the professional bodies and professional groups that define the methodology of national accounts and balance of payments statistics at the global level in order to ensure that the review process is conducted in a harmonised manner across the areas concerned and that the

Figure 7.2 SNA and BPM review flow chart

methodologies in each area remain consistent. In addition, there is also close cooperation with other related areas (government finance statistics, environmental and economic accounts, International Standard Industrial Classification of all Economic Activities).

The review was based on previously identified research topics; these topics were revised to take account of new issues that had arisen in the meantime, and then prioritised. On this basis, thematic expert groups (Task Teams, TT) were set up. The expert groups bring together experts in different fields from the widest institutional spectrum (statistical offices, central banks, international institutions, research institutes). The Guidance Notes, which are drafted by the expert groups, include the possible solutions to the problem, the proposed solution and the methodological and practical aspects of its implementation.

PURPOSE OF THE REVIEW

A key objective of the SNA2008 review is to define a broader framework for the accounts system as a tool for better monitoring and analysis of well-being and sustainability.

The speed with which multinational companies are able to transform their operations at the global level, the impact of digitalisation on production and consumption models, and issues of equality and sustainability led to a legitimate demand from users and policy makers for these processes to be properly reflected also in official statistical methodologies. Accordingly, the methodological review in the field of national accounts focuses primarily on three major research areas:

(1) globalisation;

(2) digitalisation;

(3) well-being and sustainability; while in the area of balance of payments statistics the focus is on the following areas:

(4) general principles and structural issues;

(5) bank accounts;

(6) direct investments;

(7) issues relating to financial and payment systems.

These issues have a longer-term impact on the global and European economies so they will remain relevant for decades to come.

The drive to move the statistical accounting framework beyond GDP requires a rethinking of the relationship between the central framework of the SNA, the System of Environmental-Economic Accounting (SEEA), and the measurement of human well-being and the sustainability of social development.

The aim is not to redefine current macroeconomic indicators such as GDP, but to develop recommendations that encourage countries to produce statistics that provide policy makers with important information on the “beyond GDP” effects of decisions (such as who benefits from growth and employment and to what extent, or how the benefits of economic activity are distributed across businesses, households, individuals and geographical regions).

Key recommendations relate to the development of supplementary accounts and tables that include estimates of free services within the household and human capital, as well as health and social conditions. There is also a concerted effort to develop new net product and income indicators to take account of fixed capital consumption and the depletion of natural resources. The development and wider use of net metrics is a first step towards measuring sustainability, as it makes the value of the produced and natural resources used to produce the current period’s goods and services visible to users.

The revised SNA will be better aligned with the system of environmental and economic accounts by providing recommendations on the use of classification systems to make the link between the economy and the environment more visible, and by restructuring the management of biological assets and emissions trading schemes, as well as the valuation of natural resources. The renewed standard will also include a set of recommendations for measuring the informal economy, which is growing internationally.

During the review process, the expert groups develop a Guidance Note on the topic and submit it for global consultation, after which a proposed final version is produced. By the end of 2022, 67 Guidance Notes were formulated by the expert groups, of which 25 were endorsed after the global consultation, 28 were decided on in global consultation, 4 were in the stage of global consultation and 10 were about to be launched.

A novelty of the current review process is that, based on the approved Guidance Notes, there is a testing period during which statistical organisations can test the feasibility of the new methods in practice, according to the proposed final version. The results of these are used to finalise the new methodology in the manuals.

The first version of SNA2025 is to be followed by a revision of the European methodology, ESA. As ESA2010 covers a narrower and more socio-economically homogeneous group of countries than the SNA, and some of its indicators (GNI, EDP) are also used for economic policy purposes, the methodology itself and its application are a legal obligation for Member States. From a methodological point of view, this means adapting the SNA requirements to the European context, taking into account the need to ensure comparability between countries and practical feasibility. Therefore, it is possible that not all amendments to the SNA (especially those not related to core accounts) will be incorporated into the ESA, or that there are elements that it will not be compulsory to comply with in the first few years after implementation.

EXPECTED CHANGES

The expected changes fall into three types (Table 7.1):

CONCEPTUAL CHANGES

• Core accounts are affected

EXTENSION OF CORE ACCOUNTS

• D evelopment of new or extended satellite accounts

• Further breakdown of existing categories

CLARIFICATION OF SNA2008

• More precise and detailed elaboration of certain concepts and categories

• No change to core accounts

Source: Own editing

Conceptual changes affecting core accounts

There are relatively few changes that affect the essence or concept of the SNA2008. The following areas were identified:

• The impact of increasing globalisation on production: the possible impact on core accounts of treating marketing assets (excluding goodwill2) as productive assets.

• Establishing a closer link with environmental accounts.

• Detecting the spread of digitalisation in production and consumption: accounting for “data” as an asset in the national accounts.

• Aspects of well-being and sustainability, including aspects of the behaviour of economic actors beyond GDP. In particular, in terms of sustainability:

• Ownership of natural resources and their depletion;

2 Goodwill is not a productive asset under ESA2010; it should be recognised when its value can be established in the event of a change of ownership

Table 7.1 Types of predicted changes

• Accounting for emissions trading;

• Accounting for biological resources (possible extension of asset limits);

• Renewable energy sources (a possible new asset category).

“Data” could therefore be accounted for as a new asset in national accounts in the future.

The definition of data is defined in the approved Guidance Note as follows: “Information that results from the observation and analysis of a certain phenomenon; the information elements of these phenomena are recorded, organised and stored in digital form, thus providing economic benefits in the production process.”

Data can take many forms, and by the above definition, national accounts account for data that exist in digitised form and are used in production. As a result of the revision, the data is to be treated as a productive asset in the intellectual property asset category if it is generated as a result of a production process and is used in production for more than one year. Like any other asset, data has an economic owner, a value and depreciation, and can be sold. Own account data should be considered, just like other intellectual products (e.g., research and development). Treating the data as a produced asset also affects output, intermediate consumption, and thereby value added, gross fixed capital formation, export-import data and non-financial assets.

Extension of core accounts (e.g., new, modified satellite accounts)

The extension of the core accounts implies the development of new or extended satellite accounts or further breakdowns within existing categories in the following areas:

• Valuation and accounting of “free” products;

• Digitalisation supply and use tables;

• In the context of globalisation, a more detailed look at multinational companies, special purpose vehicles, global production value chains and trade in value added;

• Analysing specific areas of well-being with new satellite accounts (distribution of household income, consumption and wealth, household work done for own consumption, human capital, health and education conditions);

• Possible changes to the SNA classifications to more accurately reflect environmental accounts.

These allow for the accounting of details that were not previously covered in the national accounts and allow the national accounts system to be more in line with current technological and societal requirements than before.

Clarification of SNA2008

The revision involves a refinement of the current categories, which does not require supplementary tables and does not lead to changes in the main macroeconomic aggregates. The most important of these are:

• Price and volume measurement of products and services involved in digitalisation;

• Management of free digital products in the core accounts;

• Artificial intelligence;

• Cloud-based services;

• Digital intermediary platforms;

• Evaluation of mineral and energy resources;

• Promotion of the use of net indicators (NVA: net value added, NDP: net domestic product, NNI: net national income, etc.).

It follows from the above that in the review, the international statistical community does not attempt to create a hardly definable, debatable, composite measure that combines environmental impacts, well-being and all the effects of digitalisation with GDP. Rather, it seeks to build on the complexity, coherence and consistency of the national accounts system to expand and develop the areas concerned, for example by creating new asset categories, prioritising net indicators or strengthening links with existing and future satellite accounts.

SATELLITE ACCOUNTS

As early as 1991, the United Nations Statistical Commission proposed the addition of satellite accounts to national accounts, including the development of integrated environmental and economic accounts.

Satellite accounts, although linked to the central system, are not necessarily linked to each other. Their main aim is to complement the picture provided by the national accounts system.

Basically, we distinguish between two types of satellite accounts, internal and external. The internal satellite account follows the accounting rules and conventions of the national accounts, possibly using more extensive classifications, allowing for the accounting of complementary activities. It aims to provide a more detailed picture of the area covered than the central system, without overloading the central system. Such satellite accounts may be sectoral accounts, such as satellite accounts for agriculture or tourism, or, for example, environmental expenditure accounts, which measure the economic resources spent on preventing, mitigating and eliminating pollution and any other damage to the environment.

External satellites apply rules and sets of definitions that differ from the central system, widening the scope of accounting. Different classifications may be used here, but the main emphasis is on the

alternative approach: to complement the central system. Satellites of this type generally provide information on a broad range of socioeconomic activities and aim to be complete in this respect (Tűű, 1997).

The great advantage of satellite accounts, especially the external type, is that they provide an opportunity to try out new concepts and methodologies, with a much greater degree of freedom than the central system would allow. This is particularly true for integrated environmental and economic accounts. These areas are characterised by the fact that they require intervention, usually from government, for which the classifications of core accounts do not provide a direct, complex analysis, or only to a limited extent. The statistics describing the relationship between the economy and the society/environment and, more fundamentally, the system of environmental economic accounts, include such external satellite-type accounts.

Indicators based on the System of Environmental Economic Accounting (SEEA) can shed light on the relationship between the environment and well-being, which traditional indicators (such as GDP or national income) do not address.

The objective of the framework of environmental economic accounts is to make environmental and economic information available to users, and in particular to policymakers, in a coherent, systematic, easily interpretable and internationally comparable way, and as far as possible in its entirety. The system of accounts covers the following areas:

• the stock and stock changes of natural resources;

• the flow of materials and energy within the economy and between the economy and the environment;

• economic activities and transactions related to the environment.

NATURAL RESOURCE ACCOUNTS

Forest

Land and soil

Water reserve

Mineral and energy wealth

Fish and fishing

PHYSICAL AND MONETARY RESOURCE USE TABLES

Material flow

Emissions of air pollutants

Energy flow

Water flow

Emissions of water pollutants

Ecosystem Waste

Source: SEEA, own editing

ENVIRONMENTAL ECONOMIC ACCOUNTS

Environmental expenditure

Environmental products and services

Environmental taxes

Environmental subsidies

Environmentally harmful subsidies

Resource use and management

The introduction and methodological development of these accounts is ongoing, and in Hungary six “modules”, underlined in Table 7.2, are currently being prepared.

The indicators derived from the accounts can be used in a number of areas in addition to decision making. In addition to assessing the availability and use of natural resources and environmental pressures, the system of accounts also provides an account of economic activities undertaken to protect the environment, the results of government actions and guidance on the valuation of renewable and nonrenewable natural resources.

THE RELATIONSHIP BETWEEN THE ECONOMY AND THE ENVIRONMENT AND THE DIFFERENT RESOURCES

Since the 1970s, there has been a continuous demand for the development of statistics and indicators that are able to reflect the use of natural resources and the pressures on the environment in macroeconomic indicators. As early as 1971, Drechsler argued that,

Table 7.2 Classification of environmental economic accounts

although the need for and importance of environmental protection is undisputed, economic indicators do not adequately reflect the efforts made to this end, and that environmental activities are not accounted for, or not with the right sign, and that this is not only confusing but also to some extent hinders appropriate economic policy decisions (Bóday and Szilágyi, 2013).

Some examples are given below to illustrate the links between the performance of the national economy and the use of natural resources, based on environmental accounts data and GDP.

Resource productivity is the ratio of GDP to domestic material consumption (DMC). It shows how well a country is managing its resources. The indicator can be used to determine the extent to which the use of natural resources is increasing in line with economic growth. The increase in its value indicates an increase in efficiency in the use of available resources, allowing economic growth with less environmental damage.

Figure 7.3 Changes in resource productivity and its components, Hungary, 2000–2021 (domestic material consumption (DMC) and GDP, 2000=100)

The rate of change of environmental pressure indicators is usually compared to the rate of change of GDP. If they change at a similar rate, the resource productivity does not change. However, if their rates of change are different, resource productivity also increases or decrease, or in other words, diverge (Szabó, 2006).

In general, there is a strong (or absolute) divergence between consumption and output indicators if the environmentally important consumption variable is stable or decreasing while the economic indicator measuring output (GDP) is increasing. A weak (or relative) divergence is when the environmentally important variable is growing but its growth rate is below that of the economic indicator. In the case of Hungary (Figure 7.3), there was an absolute divergence between 2012 and 2014 and 2016 and 2019, followed by a relative divergence, so overall resource productivity increased. In 2021, we could produce 67 per cent more GDP using 24 per cent more resources than in 2000. Resource productivity improved by 34 per cent as a result of these two factors.

A similar environmental indicator to resource productivity is greenhouse gas intensity (GHG), which shows the amount of greenhouse gas emissions per unit of value added.

The indicator can be used to determine the extent to which the activities of certain sectors are carbon intensive. These sectors are not necessarily the largest emitters, but they require significant fossil energy use to be effective. For example, while in 2020 at the national economy level 1 million forints of value added was associated with 2 tonnes of GHG emissions (Figure 7.4), in agriculture it was 13 tonnes, showing that agriculture is a resource-intensive sector. A more important trend, however, is that the production of a unit of GDP is producing less and less CO2 emissions, which means that the carbon intensity of the Hungarian economy is decreasing.

Using similar logic, many similar indicators can be calculated using environmental accounts, such as energy intensity or waste intensity.

Other indicators in the environmental accounts can also help to explain the relationship between the economy, economic performance and the environment. Some examples are the proportion of environmental taxes (the tax base of which is a physical unit with a proven negative impact on the environment) in the tax system, or the amount of green investment and green jobs (the level of investment in environmental industries and related to services, the number of people employed).

With the ongoing development and introduction of environmental accounts, new tools will soon be available to describe the relationship between the environment and the economy.

Figure 7.4 Greenhouse gas intensity in national economic sectors with significant intensity, Hungary, 2000–2020 (GHG emissions per HUF 1 million (measured at 2005 prices) gross added value)

SUSTAINABLE GROWTH INDEX

ÁGNES NAGY AND ANDRÁS ZSOLT SZABICS

The concept of the Sustainable Growth Index

“The GDP tells you nothing about sustainability.”

Joseph Stiglitz

For the long-term sustainability of an economy, it is not sufficient to look at GDP or economic development trends alone. In addition to the real economy, the sustainability of financial, social and environmental factors and processes must also be taken into account. This is the only way to ensure the sustainable development, welfare and well-being of present and future generations, and the efficient and sustainable use of resources in the long term.

The MNB Sustainable Growth Index assesses the sustainability performance of our country in the EU through 64 indicators. Of the 64 indicators, GDP per capita is a prominent one, but this is complemented by 63 additional indicators in the 4 dimensions of sustainability in order to provide a picture of development and its sustainability. The analysis covers the period 2010–2022, and territorially the EU countries.3

METHODOLOGY OF THE SUSTAINABLE GROWTH INDEX

The Sustainable Growth Index is composed of a total of 64 indicators from 4+1 pillars, and this composite indicator is used to assess the sustainability of Hungary’s development in comparison with the EU. With the composite indicator, the MNB aims to create a ranking that takes sustainability into account by adjusting GDP per capita, which measures the development of the economy (Figure 8.1). The MNB identified four main areas that are fundamental to sustainable welfare: economy, finance, society and environment. Of the four key areas, 15 indicators were selected in the social domain and 16 in each of the other domains; with development there is a total of 64 indicators (Table 8.1). The sub-indices for each sustainability area complement GDP per capita, which alone represents the development pillar. The value of the main index is equal to the arithmetic average of the five areas under study, weighted equally.

ECONOMIC SUSTAINABILITY

20% weight, 16 indicators

FINANCIAL SUSTAINABILITY

20% weight, 16 indicators

SOCIAL SUSTAINABILITY

20% weight, 15 indicators

SUSTAINABLE GROWTH INDEX

ECONOMIC DEVELOPMENT

20% weight, 1 indicator

Source: MNB

ENVIRONMENTAL SUSTAINABILITY

20% weight, 16 indicators

The MNB used its proprietary methodology to compile the Sustainable Growth Index. The calculation methodology – first used in 2017 for the Banking Competitiveness Index, and later for the Competitiveness and Sustainability Indices – is also the basis for the new composite index. Countries score between 0 and 100 on the various indicators, depending on their performance. The best performing country receives 100 points, while the countries that rank lower in performance receive fewer points in proportion to the standard deviation (Asztalos et al., 2017). A key issue in the scoring is the definition of the optimal value (average, minimum, maximum, target), which varies from indicator to indicator and can express what is considered a sustainable long-term goal for a given indicator. Hungary’s performance is presented not only against the average of the EU nations, the Visegrád competitors and the Northern TOP5

Figure 8.1 Structure of the Sustainable Growth Index

(Denmark, Estonia, Finland, the Netherlands and Sweden), but also in terms of its time series performance by domain and in the aggregate index from 2010 onwards.

In the following chapters, the indicators used for the MNB’s Sustainable Growth Index and the results are demonstrated in the key sustainability areas, illustrated with detailed textual evaluation and figures. In addition to the textual evaluation of main areas, the framework developed by the MNB provides an opportunity to quantify the results as well as to analyse based on objective diagnosis. As a result, in Chapters 9–12 we show the indicators selected in the publication in the field of economic, financial, social and environmental sustainability, presenting the most significant with a historical figure. This makes the Hungarian performance easier to compare to the average of the EU, V3 and Northern TOP5 countries. After reviewing the indicators, Chapter 13 presents the aggregated results of the MNB Sustainable Growth Index.

ECONOMIC DEVELOPMENT

GDP per capita

ECONOMIC SUSTAINABILITY

Investment rate as a proportion of GDP

The proportion of intangible investments within GDP

Labour productivity

Domestic value added in production

SOCIAL SUSTAINABILITY

Total fertility rate

Life expectancy at birth

Healthy life years

Self-reported unmet needs for medical examination

Domestic value added content of gross exportsShare of mortality driven by behavioural risks

Economic Complexity Index (ECI)

Labour productivity of SMEs

Ratio of exporting SMEs

SMEs selling on e-commerce channels

Ratio of tertiary graduates

Participation in lifelong learning

Employment rate

Proportion of young people neither in employment nor in education and training

Table 8.1 Sustainable Growth Index indicators

ECONOMIC SUSTAINABILITY SOCIAL SUSTAINABILITY

Share of SMEs with product innovation

Expenditures on R&D as a percentage of GDP

Digital Economy and Society Index (DESI)

Ratio of GDP per capita of the most developed and least developed NUTS 3 regions

Ratio of knowledge-intensive employees

Number of new patent grants

Income Gini index

Wealth Gini index

Ratio of people at risk of poverty or social exclusion

Proportion of people living in households with mortgage, rent or utility bill arrears

Severe housing deprivation rate

Number of thefts

Unemployment rate -

FINANCIAL SUSTAINABILITY ENVIRONMENTAL SUSTAINABILITY

Return on equity

Cost-to-assets ratio

Loan-to-deposit ratio

Net non-performing loan portfolio as a percentage of the capital

Corporate sector's loan portfolio as a percentage of GDP

Household sector's loan portfolio as a percentage of GDP

Corporate bond market capitalisation to GDP

Gross public debt-to-GDP ratio

Ecological balance

Greenhouse gas emissions compared to its level in 1990

Proportion of pollutants in the air

Energy intensity of the economy

Carbon dioxide emissions per one unit of economic output

Net energy import as a share of gross available energy

Share of renewable energy sources in final energy consumption

Share of nuclear energy in the gross electricity production

Ratio of foreign holding within public debt Financial support for fossil fuels

Net external debt as percentage of GDP Recycling rate of municipal waste

Current account balance as a percentage of GDP

Cash holding as a percentage of GDP

Net financial assets to GDP ratio of households

Ratio of internet banking users

Share of people buying online

Ratio of payment card purchases

Source: MNB

Proportion of areas involved in organic farming

Total internal renewable water resources per capita

Circular material use rate

Government R&D expenditures for environmental purposes

Environmental tax revenues as a percentage of GDP

Expenditures on environmental protection as a percentage of GDP

ERZSÉBET ÉVA NAGY, PÉTER SAVANYA, ANDRÁS ZSOLT SZABICS, MIHÁLY SZOBOSZLAI AND VIKTOR DÉNES VARGA

Economic Sustainability

“Our biggest challenge in this new century is to take an idea that seems abstract – sustainable development –and turn it into a reality for all the world’s people.”

Kofi Annan

Sustainable growth depends not only on factors outside the economy (environmental conditions, demographics), but also on the renewed growth capacity of the economy itself. The main driver of economic growth is productivity growth, i.e., the increasingly efficient use of available resources. However, this requires complex developments, basic research, innovation and investment to integrate these into production, then well-organised production processes and finally the sale of products in a highly competitive market. In this chapter we look at these factors of the economy’s capacity to grow. Over the past decade, Hungary performed well in terms of average GDP growth above the EU average, and its labour productivity also improved. However, there is still room for significant improvement in the level of these indicators. The future productive capacity is largely determined by the investment rate, which was the highest in the EU in 2022, but the picture is nuanced by the fact that the value of modern intangible investments as a percentage of GDP is around half the EU average.

A key question for sustainable growth in the long term is the share of production that actually generates new value within national borders. Hungary’s domestic value added, both as a share of production and exports, increased over the past decade, but remains lower than the EU average. In terms of economic complexity, Hungary ranks 9th globally when taking into account the complexity and diversity of exports, but this is largely due to the know-how of multinational companies producing in Hungary. Domestic value added is more moderate in this high-tech segment. On the positive side, labour productivity in domestic SMEs increased significantly over the past decade, although it is still lower than in most European countries.

Innovation and digitalisation are important drivers of productivity and thus of sustainability. In terms of R&D expenditure, a key indicator of innovation activity, Hungary exceeds the regional average but falls short of the target, and efficiency indicators show that unfortunately, increasing expenditure does not translate into improved innovation

performance. The domestic digital infrastructure is competitive by international standards, but its utilisation leaves room for catching up.

Overall, Hungary ranks 20th in economic sustainability among the EU countries in 2022. The national index was 42.6 points in 2022, so Hungary’s performance in this area was better than the average for the other Visegrád countries (41.0 points). However, our performance was below the EU average of 50.3 points. Between 2010 and 2022, our country’s ranking improved by 4 places overall (Figures 9.1 and 9.2).

Figure 9.1 Results in the area of

High labour productivity helps sustainability by allowing the economy to produce more goods and services with the same use of resources. Economic growth in the developed world is constrained and faces a number of internal resource constraints (raw materials, labour, financial resources) and external challenges (epidemiological, geopolitical, trade risks), as well as increasing sustainability requirements (environment and energy, stock management) (MNB, 2022). Within these circumstances, the role of productivity, which is the basis for balanced long-term growth and sustainable convergence, becomes even more important.

Figure 9.2 Trends in economic sustainability rankings

Hungary’s labour productivity was the 4th lowest among EU Member States in 2022. The tax and labour market reforms introduced from 2010 resulted in a large increase in the number of economically active and employed people, but new entrants were typically less productive, so the negative composition effect initially reduced productivity. In a tightening labour market since 2017, economic growth has become increasingly capital-intensive and technologydriven, so labour productivity has also risen. In 2022, our country’s employment-based labour productivity was 74 per cent of the EU average, so there is a substantial reserve for productivity growth (Figure 9.3).

Figure 9.3 Employment-based labour productivity compared to the EU average

The productivity of small and medium-sized enterprises has a significant impact on the sustainability of the national economy because of their economic importance. In Hungary, SMEs employ twothirds of the workforce and produce more than half of value added. Labour productivity in SMEs increased substantially between 2010 and 2021, from 64 per cent to 80 per cent of the EU average (Figure 9.4).

Productivity of domestic SMEs is still lower than in most European countries, so there is room for improvement (MNB, 2022).

Figure 9.4 Labour productivity of SMEs compared to the EU average

QUANTITY AND QUALITY OF INVESTMENTS

On the financial side, investment is the basis for future production and efficiency gains. In addition to the size of capital, its structure and the relationship between capital and technology are of particular importance (Baksay et al., 2022).

The domestic investment rate has exceeded the EU average every year since 2017 and was the highest in the EU in 2022. In 2022, Hungary’s investment rate was 28.2 per cent, significantly higher than the EU average of 22.5 per cent, the V3 average of 21.2 per cent and the Northern TOP5 average of 24.3 per cent. In the case of Hungary, foreign direct investment (FDI) also contributed significantly to the high investment rate. However, the picture is clouded by the fact that, from 2019 onwards, the rapid rise in investment prices in Hungary was the main reason for the increase in the investment rate.

The digital transformation requires modern intangible and smart investments. Between 2010 and 2021, Hungary’s average intangible investment-to-GDP ratio was 2.8 per cent, close to the V3 average (2.5 per cent), compared to 4.2 per cent in the EU and 4.9 per cent in the Northern TOP5. (Figure 9.5). In 2022, the share of intangible investment in GDP in Hungary was 2.6 per cent, in the bottom third of the EU ranking.

DOMESTIC VALUE ADDED AND ECONOMIC COMPLEXITY

Domestic value added is a key factor in the sustainability of economic growth. The share of domestic value added in output indicates the value added per unit of gross output within a country’s borders. The Hungarian indicator in 2021 was close to 43 per cent, below the EU average (45 per cent) and the Northern TOP5 (around 47 per cent). On the positive side, the indicator mostly increased over the last decade until 2020 and was above the V3 average throughout (Figure 9.6). The improvement is driven by the increasing weight of the services sector, which has a higher domestic value added content (Várnai, 2023).

Figure 9.5 Intangible investment as a percentage of GDP

Growth beyond internal demand constraints is possible if an economy’s output is also competitive on foreign markets. Hungary is one of the most open economies in the EU, with a high export-toGDP ratio, but with a high import content of exports. The domestic value added content of our country’s exports was 52 per cent in 2020, 13 percentage points lower than the EU average (Figure 9.7).

Figure 9.6 Domestic value added in production

Despite the low domestic value added content of exports, Hungary ranked 11th out of 133 countries in the Economic Complexity Index of Harvard University in 2021. The indicator ranks countries according to the diversity and complexity of their export baskets. Our country’s position in the indicator is stable, fluctuating between 9th and 11th place since 2010. Among the regional competitors, the Czech Republic was the only one to perform better (6th place), Slovakia was 12th and Poland 25th. The complexity of export products and the moderate share of domestic value added in exports show that the former is largely due to the know-how of multinational companies producing here.

Figure 9.7 Domestic value added content of gross exports

Exports remain a concentrated activity in Hungary, with relatively few SMEs exporting. Of domestics SMEs, 5 per cent exported in 2020, below the EU average of 7 per cent and especially the Northern TOP5 average of nearly 10 per cent, but above the V3 average (4.5 per cent) due to the low Czech value. The highest shares of exporting SMEs are in Estonia and Slovenia, at over 15 per cent.

INNOVATION AND DIGITALISATION

Innovation and digitalisation are the most important sources of technological progress and thus of sustainable growth. The more advanced an economy is, the more innovation must drive growth, and innovation and knowledge are currently embodied primarily in digitalisation. In 2021, Hungary spent just over 1.6 per cent of its GDP on R&D (Figure 9.8). This level is above the average for countries in the region, but below the target set by Hungary for 2020 (1.8 per cent). The strategic target for the period 2021–2030 is 3.0 per cent. On the positive side, over the past decade, R&D expenditure has risen to a level close to the EU average, moving Hungary up from 17th to 13th place among EU Member States. However, the picture is clouded by the fact that only business spending as a percentage of GDP rose, while public and higher education spending fell. Low business R&D expenditure means that the share of Hungarian SMEs innovating products is in the bottom third of the EU ranking (Figure 9.9). On the positive side, the share of innovative SMEs doubled in a decade.

Source: Eurostat

Note: For Luxembourg, data for 2018 instead of 2020.

Source: Eurostat (2012), European Innovation Scoreboard (2020)

Figure 9.8 R&D expenditure as a percentage of GDP

Figure 9.9 Share of SMEs with product innovation

Despite increasing R&D spending, the number of registered patents in Hungary is one of the lowest in the European Union. Since 2013, the number of new patents registered in Hungary in a year has been steadily decreasing, averaging around 13 patents per million people between 2017-2021. The Hungarian indicator is well below the average of both the EU and Visegrád competitors, which have averaged around 90 and 50 patents respectively in recent years. The lower domestic value may be due to less practice-oriented research, but also to the fact that foreign-owned companies, even if they conduct research in Hungary, file new patents in their home country.

Hungary has a competitive infrastructure for socio-economic development based on digitalisation, but is not yet making sufficient use of it. The EU Digital Economy and Society Index (EU DESI) ranks Hungary 22nd in the ranking of Member States (Figure 9.10). Of the four pillars of the index, Hungary performs at the EU average level in terms of internet access (and among the leaders in terms of bandwidth), but is consistently in the bottom third of the EU in terms of digital readiness of the workforce, digital public services and integration of digital technologies at corporations. In Hungary, the share of knowledge-intensive employment was 24 per cent in 2021, similar to the regional average, which is the 5th lowest in the EU. The EU average is 26 per cent and the average of the northern countries is over 30 per cent. Overall, the domestic indicator improved by 1.5 percentage points compared to 2010.

The lack of adoption of digital solutions is one of the biggest contributors to the productivity gap between different sizes of enterprises (Szoboszlai, 2023). Digital solutions are also important to expand sales channels. While only 7 per cent of SMEs sold their products online in 2010, this was 13 per cent in 2019 and 20 per cent in 2022. The Hungarian rate is similar to the V3 average (17 per cent) and not significantly below the EU average (21 per cent). The experience of businesses that had to sell online as a result of the pandemic presumably made it possible to sustain the use of these solutions in the long term.

Figure 9.10 Digital Economy and Society Index in 2022

ÁRON ISTVÁN DRABANCZ, ZÉNÓ FÜLÖP, ZOLTÁN JENŐFI, BENCE MUHARI, ISTVÁN NEMECSKÓ, BALÁZS SISAK, MIKLÓS SZEBENY, NOÉMI VÉGH AND VIVIEN VIRÁGH

Financial Sustainability

“Finance is not merely about making money. It’s about achieving our deep goals and protecting the fruits of our labour.”

Robert J. Shiller

Financial sustainability, based on a stable and efficient financial system, and fiscal, macroeconomic and financial market balance, is an essential factor for sustainable convergence in the long term. Efficient, diversified, soundly structured financing and financial balance promote not only economic sustainability, but also social and environmental sustainability.

Within the financial system, a key priority for Hungary is the sustainability of the banking system, which improved over the past decade. In 2010, the high loan-to-deposit ratio of over 100 per cent and the high stock of non-performing loans indicated significant vulnerabilities, but these have fallen into a reasonable range by now. Private sector credit as a percentage of GDP declined significantly in the 2010s, leaving considerable room for prudent financial deepening, which could contribute to higher paced but still sustainable growth. In addition to the banking system, the efficiency and sustainability of the economy is also enhanced by a liquid and developed bond market, which has developed significantly in Hungary in recent years. Financial digitalisation and the rise of electronic payments not only contribute to making financial processes more efficient, but also reduce the environmental impact of financial activities.

The internal and external financial balance are essential ingredients for the long-term sustainable growth of economies. Hungary’s public debt ratio declined steadily and its structure improved significantly in the 2010s. The coronavirus crisis caused the debt ratio to increase for only one year, and it has since resumed its downward trend. Our country’s current account balance improved significantly from the imbalances before the 2008 crisis but turned into a deficit as a result of strong domestic demand and external crises in the 2020s. The reduction in our country’s vulnerability has been supported by a substantial reduction in net external debt in recent years.

In the financial sustainability pillar, Hungary ranked 22th in the European Union in 2022. Hungary’s score of 51.6 is below the average of both the EU countries (59.5) and the Visegrád countries (57.1). The Netherlands, Sweden and Luxembourg are the leaders in financial sustainability, while Greece, Cyprus and Romania are the laggards. Between 2010 and 2022, Hungary moved up from 26th to 22th place (Figures 10.1 and 10.2).

SUSTAINABILITY OF THE FINANCIAL SYSTEM

An efficient, stable and sustainable financial system, and in the case of Hungary, the banking system in particular, is an essential factor for sustainable convergence. In continental Europe, the banking system is the most important intermediary for financial resources and assets, and its sustainable functioning is key to balanced economic growth. In addition to the banking system, a liquid and developed bond market also supports the economy, which has become increasingly important in Hungary in recent years.

Figure 10.2 Trends in financial sustainability rankings

A sufficient capital adequacy ratio is conditional on the banking system’s ability to generate sufficient profits in excess of the cost of capital. If profits are too low, banks cannot build up sufficient capital, which reduces their resilience to shocks and their role in financing the economy. However, high profitability is not necessarily an advantage either, as high profits can also result from banks having a dominant position in certain sub-markets or taking excessive risks. We considered the long-term sustainable return on equity (RoE) to be around the 10 per cent average of the Visegrád countries. Between 2016 and 2019, the profitability of the domestic banking system exceeded this level by almost 5 percentage points, partly due to specific factors, putting it among the top performers in the EU. After a temporary decline in 2020, the profitability of the Hungarian banking system was again the highest in the EU in 2021, followed by 6th place in 2022.

The sustainability of the banking system also depends on the efficiency of its operations. In international comparison, the domestic operating expenses of 2.8 per cent as a ratio of total assets is significantly higher than the European average of 1.4 per cent and the average of 1.4 per cent in the region (Figure 10.3). At the end of 2022, the operating expenses of the Hungarian banking system as a ratio of total assets, net of the value of foreign subsidiaries and the impact of the bank tax and transaction levy was 2.1 per cent. The low cost-efficiency of the Hungarian banking system can be addressed by increasing the economy of scale of institutions and the widespread use of digital solutions.

Adequate capitalisation of the banking system contributes to its lending capacity and also increases its resilience to shocks. However, the assessment of capital adequacy also depends on the quality of the portfolio, as a high share of non-performing loans increases the risk of future capital erosion. These two factors can be taken into account simultaneously by the ratio of net (i.e., not covered by provisions) nonperforming loans (NPLs) to capital. For the domestic banking system, this indicator was around 50 per cent in 2010, well above the regional and European averages. In the following years, the indicator improved significantly: in 2021, the figure was 10.5 per cent. This is better than the EU average of 12.8 per cent, which is also indicative of the persistent NPL problem in some European countries from previous crisis periods, and is slightly higher than the average of 10 per cent for the regional countries. The value of the indicator in Hungary stood at 11.4% in 2022, after a minimal increase.

Figure 10.3 Operating expenses as a ratio of total assets

The loan-to-deposit ratio is an indicator of the funding risks of the banking system, showing how much of the loan portfolio is covered by bank deposits, which are considered a stable source of funding. A persistent ratio well above 100 per cent either reflects financing peculiarities (mortgage bond financing, high share of central bank refinancing) or indicates a high weight of interbank and foreign funding. A high share of these resources may entail refinancing risks, increasing the vulnerability of the banking system. At the time of the escalation of the financial crisis in 2008, the domestic loan-to-deposit ratio was close to 150 per cent, which was high in regional comparison. The indicator fell to close to 75 per cent by the end of 2016, after the crisis, mainly due to loan portfolio contraction, and after a few years of stagnation, it fell below 65 per cent during the COVID-19 crisis (Figure 10.4). After a historical low level in 2021, the value of the indicator rose to 71.2 per cent in 2022.

Figure 10.4 Loan-to-deposit

The development of the financial institutional system is a catalyst for future economic development, as long as the credit-to-GDP ratio does not reach a harmful level, is a catalyst for future economic development. A sustainable financial deepening, free from excessive volatility, would help Hungary’s social welfare to grow (Baksay et al., 2022). In our country, the loan portfolio of the household sector as a percentage of GDP declined significantly following the 2008 financial crisis. This is mainly due to the gradual and accelerated erosion of foreign currency loans, which were unsustainable in the early 2000s, through government measures (early repayment and settlement) (Matolcsy, 2020). After a significant decline, the indicator showed stagnation, with the domestic indicator (14.7 per cent) remaining well below the V3 average of 35 per cent at the end of 2022, leaving considerable room for prudent credit expansion. The corporate sector also experienced a balance sheet adjustment in the 2010s, though to a lesser extent than households. Corporate sector creditto-GDP stood at 27.4 per cent in 2010, while the indicator bottomed out at 16.5 per cent in 2016 (Figure 10.5). The Hungarian indicator of 17.9 per cent in 2022 is in line with the V3 countries, but there is still substantial room for financial deepening for all countries in the region.

In addition to the banking system, a liquid and developed bond market also increases the efficiency and sustainability of the economy as a whole. An efficient bond market allows for more diversified financing, helps access to funding in the event of a reduction in bank lending, can support recovery in the event of economic and financial shocks, and can facilitate companies’ access to international bond markets. In the European Union, the bond market appreciated following the 2008 financial and economic crisis, and over the past decade the central bank emerged as a buyer in many economies, including Hungary since 2019. Within the EU, the development of the bond market is mixed, with bond market size approaching 30 per cent of GDP in some countries (France, Sweden) and averaging less than 5 per cent in Central and Eastern European countries (Figure 10.6). In Hungary, the portfolio of corporate bonds as a percentage

Figure 10.5 Corporate sector credit as a percentage of GDP

of GDP grew from 1.5 per cent to 5.3 per cent between 2019 and 2021, supporting sustainability both through increased corporate transparency and by building an efficient market infrastructure and an appropriate regulatory environment that boosts investor confidence. Domestic bonds cover a broad spectrum of the economy, and several corporate issuances have already been made through green bond issuance, which is of particular importance from a sustainability perspective.

Figure 10.6 Development of corporate bond market portfolio as a percentage of GDP

INTERNAL AND EXTERNAL FINANCIAL BALANCE

The financial sustainability of the national economy is based on fiscal, macroeconomic and financial market balance. The stable availability of the resources to finance growth, the economy’s creditworthiness and its resilience to external shocks are key to economic growth and sustainability.

Fiscal sustainability is the ability of governments to maintain their spending, tax and other policies over the long term. The key indicator of a government’s financial position is the gross public debtto-GDP ratio, which is the most commonly used indicator to capture the sustainability of the budget and public finances (Baksay et al., 2016). However, in addition to the level of public debt, it is also worth looking at its structure, which is also an important indicator of the sustainability of public debt (Matolcsy, 2019).

Thanks to the fiscal transition in Hungary from 2010 onwards, the debt-to-GDP ratio continued to fall from 2011 until the coronavirus pandemic. Domestic debt-to-GDP ratio fell from 80.3 per cent in 2011 to 65.3 per cent, then spiked like other EU countries as a result of the handling of the coronavirus pandemic, but has been showing a downward trend again since 2021 (Figure 10.7). In 2022, the domestic debt ratio was 73.9 per cent, lower than the EU average (83.5 per cent) but above the average for the Visegrád and the Northern region (50.4 and 40.9 per cent, respectively).

The structure of government debt also improved significantly over the past decade. In 2011, foreign currency-denominated debt accounted for almost half of central government debt, falling to 25 per cent by 2022. The ownership structure of debt changed favourably, with foreign investors gradually being replaced by domestic sources, with foreign ownership at 64.7 per cent in 2011 and 34.1 per cent in 2022. The preference for longer-dated and fixed-rate bonds reduced the risk of refinancing debt.

Achieving and maintaining external balance is also a key element of financial sustainability. The current balance of payments shows the extent to which the economy’s current expenditure abroad is covered by income from abroad, thus giving an idea of the economy’s external balance and its reliance on external resources (Matolcsy, 2020). Hungary's current account balance improved significantly following the imbalances that existed before the 2008 crisis. In the early 2010s, the current account balance turned into surplus and was significantly above the EU average, but this was also favourable compared with its regional peers (Figure 10.8). After 2016, as investment rates rose, the current account surplus narrowed and turned into a slight deficit, typical of emerging countries. With the recovery from the pandemic, the current account deficit fell to below 4 per cent of GDP by 2021, with import levels rising above the deficits of the region’s countries.

Figure 10.7 Evolution of government gross debt-to-GDP ratio

In 2022, the rise in energy prices lead to a further deterioration in external balances, not only in Hungary, but in the region as a whole.

EU average

V3 average

Nothern TOP5 average

Note: Four-quarter values.

Source: Eurostat

In addition to the current account indicator, stock indicators also play a key role in assessing the long-term sustainability of external balance. During the 2008 crisis, it was clear that over-indebtedness to foreign actors poses external vulnerability problems, financing and refinancing risks. Net external debt excluding shareholder loans shows the amount of the country’s liabilities owed to non-residents after deducting receivables. During the 2008 crisis, Hungary’s net external debt was a multiple of the region’s level, posing a serious financial sustainability problem. By the end of the 2010s, the high financing capacity resulted in a substantial reduction in net external debt, which came close to the regional average. Net lending stopped declining

Figure 10.8 Current account balance as a percentage of GDP

and stabilised below 10 per cent of GDP, reflecting the decline in external financing capacity in recent years (Figure 10.9).

V3 average

Northern TOP5 average

An important component of macro-financial sustainability is the financial sustainability of households, with financial wealth as a key indicator. Net financial wealth, the difference between the financial assets and liabilities of Hungarian households as a percentage of GDP, increased significantly from 70 per cent to 105 per cent between 2010 and 2022 (Figure 10.10). The rise is partly the result of a sustained expansion in household income, which boosted the stock of financial assets as a percentage of GDP by 13 percentage points, up from over 110 per cent in 2010. The expansion of financial assets was driven by the favourable retail government security schemes. Meanwhile, the loan portfolio of households declined by more than 20 percentage points from above 40 per cent of GDP, which

Figure 10.9 Net external debt as a percentage of GDP

also contributed to the rise in net financial wealth. The net financial wealth of households as a percentage of GDP in 2022 was close to the EU average and ranks high among the region’s countries. The positive picture is tempered by the high share of cash holdings of households among their financial assets, which is one of the highest in the EU as a share of GDP and exceeds most of its regional peers. A shift of cash holdings into interest-bearing assets (e.g., bank deposits, government securities) would substantially improve the structure of the economy’s financing.

Figure 10.10 Net financial wealth of households as a percentage of GDP

FINANCIAL DIGITALISATION

Financial digitalisation not only contributes to more efficient banking processes, but also reduces the impact of financial activities on the environment. In addition to reducing the environmental burden and increasing efficiency, the widespread adoption of online banking services also promotes financial inclusion. In Hungary, the share of online banking users was 31 per cent in 2010, below the EU and V3 averages (51 per cent and 40 per cent, respectively). However, over the past decade, Hungary started to catch up, and by 2022 the majority of the population (68 per cent) used online banking services. This not only reduced the gap with the EU (72 per cent), but by 2022 Hungary surpassed the level of the Visegrád countries (68 per cent) in this indicator (Figure 10.11).

Figure 10.11 Share of people using online banking

Digital presence also shifted shopping habits away from traditional options, but the net sustainability impact of online shopping is not clear. On the one hand, consumers save energy by reducing their visits to retail stores, but on the other hand, the delivery and return of online purchases and the packaging materials used during delivery represent a new environmental burden compared to the traditional model. In 2022, the proportion of online shoppers in Hungary in the last 3 months was 78 per cent, similar to the EU and V3 averages (74 per cent and 81 per cent, respectively).

The rise of electronic payments supports the improvement of the sustainability of the national economy by increasing efficiency and reducing environmental pressure. The share of electronic payments is steadily increasing in EU Member States, including Hungary, mainly due to the development of the electronic payment infrastructure, including the rapid spread of the contactless card payment technology (Deák et al., 2022). The Hungarian indicator rose from 10 per cent in 2010 to 41 per cent in 2021, above the V3 average (36 per cent) and only slightly below the EU average of 44 per cent. The increased uptake of electronic payments was greatly helped by the preference for contactless and online purchases in the wake of the coronavirus pandemic, and the requirement to offer the possibility of electronic payment from 2021 in all retail stores that are required to use online cash registers (Deák et al., 2020).

As the share of electronic payments increases, the use of cash for transactions decreases, which contributes to improving the competitiveness of the national economy and reducing the ecological footprint of payments. With this in mind, the MNB gives priority to enabling electronic payments in all payment situations.

PÉTER HUGÓ ASZTALOS, CSABA LADOS AND ÁGNES NAGY

Social Sustainability

“Sustainable development requires human ingenuity. People are the most important resource.”

Dan Shechtman

The quantity and quality of human capital has a fundamental impact on social and economic sustainability. The quantity of human capital is primarily determined by demographic trends, its quality is influenced by the effectiveness of the education system, while the health system has an impact on both the quantitative and qualitative dimensions. These areas are not independent of each other: for example, individuals’ educational attainment and health status have an impact on their decisions whether to have children and on their life expectancy. In these areas, change is essentially a long-term process and requires a longer-term approach than in other areas of economics. For example, if a country has a successful family policy to increase the birth rate, the positive impact on the labour market will not be felt for at least two decades. In recent decades, European societies, including Hungary’s, have been characterised by unsustainable fertility rates and ageing populations.

In addition to the quantity and quality of human capital, the way in which it is used and rewarded by a society is also crucial, i.e. living conditions, the degree or inequality and the state of the labour market. In recent years, Hungary has approached full employment, which has significantly supported economic growth, but further employment growth requires the full utilisation of labour reserves. As labour market processes improved over the past decade, the proportion of people at risk of poverty or social exclusion has fallen significantly. Income and wealth inequality in Hungary is moderate by international standards, but social mobility is low.

In the area of social sustainability, we calculate that Hungary ranked 18th in the EU in 2022. Hungary scored 55.0 points in 2022, which is lower than the average of the other Visegrád countries (63.7 points), the Northern countries (62.8 points) and the EU (57.6 points).

Hungary’s ranking improved by 5 places between 2010 and 2022. Czechia is ranked after the best performing Northern countries, while Romania and Bulgaria have the lowest scores for social sustainability (Figures 11.1 and 11.2).

Figure 11.1

in the area of social sustainability

Hungary Germany V3 average Northern TOP5 average

A major challenge for EU countries is to reverse the current negative demographic trends. Low fertility and ageing populations are common features of developed countries, including Hungary. No EU country currently achieves the minimum fertility rate of 2.1 needed to maintain a sustainable population (Figure 11.3). The Hungarian fertility rate rose significantly over the decade from its historic low in 2011 (1.23) and exceeded the EU average (1.53) in 2021 (1.61). Population projections suggest that the working-age population will decline significantly in most EU countries in the coming decades (Eurostat, 2023), which, coupled with increasing life expectancy, will lead to an increase in demographic dependency ratios.

Figure 11.2 Trends in social sustainability rankings

Long-term sustainable economic growth is difficult to achieve with a declining population (Sharma, 2020). The decline in the working age population leads to a fall in labour supply, which holds back economic growth. The ageing population has a negative impact on the sustainability of public care systems, while also affecting the structure of the economy by changing consumption and saving patterns. In order to reverse the negative demographic trends, it is therefore worth pursuing social policies that can effectively promote childbearing and thus ensure sustaining the population size.

Figure 11.3 Total fertility rate

HEALTH STATUS

Maintaining good health is not just a personal and family matter, it is also a major national economy issue. Health is part of national wealth, because health affects a country’s economic performance and competitiveness through the quality and quantity of the available workforce. Chronic diseases reduce active working time and labour productivity, while premature deaths cause significant damage to the national economy. This is why maintaining health is beneficial to society from both an individual and an economic perspective (Magyar Nemzeti Bank, 2018). Healthy life expectancy in the European Union rose significantly in the second half of the last decade, but the coronavirus pandemic broke the positive trend in many countries (Figure 11.4).

Figure 11.4

TOP5

TOP5

Maintaining good health in the population is largely the responsibility of the individual, as in most cases the healthcare system only has contact with patients when they have a problem. Improving individuals’ health consciousness, proper nutrition and regular physical activity could have a positive impact on the health status of the population and on mortality rates. In Hungary, almost half of all deaths are attributable to a behavioural risk, the second highest rate among EU countries (Figure 11.5). The state has a vital interest in providing all possible support to help individuals maintain or regain good health, as preventing disease is much cheaper and more effective than treating it.

Figure 11.5 Mortality rates due to behavioural risks

EDUCATION AND TRAINING

Education has a significant impact on a country’s economic performance through the quality and productivity of the available workforce. Measuring the effectiveness of the education system is not easy, however, since in the case of a student with a university degree, we are talking about at least 18 years of education, starting from kindergarten, and in this area it is difficult to clearly define the exact added value of each level of education. However, investing in education pays off for both individuals and society (OECD, 2010). Those with higher education live longer, have better employment conditions and higher incomes, and pay more taxes.

The transition to a knowledge and technology-led growth model and hence the long-term growth potential is crucially influenced by the availability of a sufficient supply of highly skilled workers in the economy. Hungary is at a competitive disadvantage because only 32 per cent of young Hungarians have completed a tertiary degree, below the average of 38 per cent in the other Visegrád countries and 42 per cent in the EU (Figure 11.6). However, it would be equally important to strengthen participation in lifelong learning, as almost all EU countries, including Hungary, have the potential to make significant progress in this area. Between 2010 and 2022, the share of people in lifelong learning in the nation increased from 3 per cent to 8 per cent, but this is still lower than the EU average of 12 per cent and a fraction of the average of the Northern countries at around 27 per cent. It is in each countries’ best interest to continuously improve the knowledge of their population, as keeping up with global trends is essential to create an innovation-driven economic model.

LABOUR MARKET

Labour market processes fundamentally determine the sustainability of society and economic growth. The size and efficiency of the available workforce affects not only the growth of the national economy, but also the welfare and well-being of individuals. From a sustainability point of view, the most significant constraint on the quantity of the workforce is the unfavourable demographic trends (population shrinkage and ageing), while regarding the quality of the workforce, several megatrends (e.g. digitalisation, green transition, atypical work) are already causing challenges today, requiring significant adaptation by workers, companies and the state.

Figure 11.6 Share of people in the 25–34 age group with tertiary education

In Hungary the labour market approached full employment over the past decade, providing a substantial contribution to economic growth. Thanks to targeted government measures and favourable economic trends, activity and employment indicators increased at one of the fastest rates in the EU, with unemployment falling significantly. The coronavirus crisis in 2020 temporarily interrupted the positive trends, but with the rapid recovery of the economy, employment in 2021 had already surpassed pre-crisis levels. The Hungarian employment rate in the 15–64 age group in 2022 was 74.4 per cent, higher than the EU and Visegrád average (72–73 percent) (Figure 11.7). In parallel with the increase in employment, the unemployment rate has also improved significantly since 2010. It rose slightly (to 4.1 per cent) under the impact of the COVID-19 crisis, but fell to 3.6 per cent in 2022, the 6th lowest rate in the EU.

Figure 11.7 Employment rate in the 15–64 age group

With demographic constraints emerging, activating existing labour market reserves is also essential to maintain or further increase high employment. Activity rates for young people also improved over the last decade but remain below the EU average. The share of young people aged 15–24 not in education, employment, or training (NEET) was 10 per cent in 2022, slightly above the V3 and EU averages of around 9 per cent. Young people not in education, employment, or training represent a lost opportunity at both the individual and economic level, and inactivity can have negative long-term consequences.

INEQUALITIES AND LIVING CONDITIONS

The extent and evolution of inequalities is an important factor for economic and social sustainability. Inequality is a natural feature of the market economy and competition, as it encourages better performance and competition. However, excessive rates of it lead to significant welfare losses, as it negatively affects social cohesion and mobility, and can jeopardise the sustainability and inclusiveness of growth. Economic policies can reduce inequality through income redistribution, targeted subsidies, and adequate and widely available health and education systems (IMF, 2015) helyett (Dabla-Norris et al., 2015).

Hungary is among the countries with lower inequality, both in global and EU comparison. The Hungarian Gini index measuring income inequality rose from around 24–25 per cent in the aftermath of the 2008 economic crisis to 28 per cent, and was still at 27.4 per cent in 2022. The Hungarian indicator is better than the EU average of 29 per cent, but higher than the other Visegrád countries (24 per cent). Wealth inequality rose in most EU countries over the past decade, including slightly in Hungary (Figure 11.8). The Hungarian Gini index measuring wealth inequality was estimated to be 67.7 per cent in 2022, lower than the EU average but slightly higher than the V3 average (71 and 66 per cent, respectively). There is a negative relationship between wealth inequality and homeownership: in countries where

homeownership is the dominant factor, including Hungary, wealth inequality is on average lower (Briglevics et al., 2020).

Inequalityhas increased Inequalityhas decreased

The proportion of the population at risk of poverty or social exclusion in Hungary has fallen at one of the fastest rates in recent years. The Hungarian AROPE indicator fell from over 30 per cent in 2015 to 18.4 per cent (1.75 million people) in 2022, the largest decrease in the EU and already better than the EU average (Figure 11.9). For all three AROPE sub-indices – income poverty, severe deprivation, low work intensity – the proportion of people affected has decreased in recent years.

According to the OECD, the impact of the socio-economic background of parents on the school performance of children is one of the highest in Hungary (OECD, 2019). In the long term, this phenomenon can perpetuate inequalities, which is detrimental to social sustainability.

Figure 11.8 Wealth Gini index in 2010 and 2022

Housing can be considered sustainable if the broadest possible range of people in society have access to housing that meets their basic housing needs. A stock of good quality, affordable housing also supports economic growth and competitiveness by promoting the geographical mobility of workers and helping young people to become independent in life. Between 2010 and 2020, the proportion of people living in severely inadequate housing conditions in Hungary fell significantly from 17.7 per cent to 7.6 per cent, but still ranks 5th highest in the European Union (Figure 11.10). At the same time, the recovery from the 2008 crisis meant that fewer people had problems maintaining housing: in 2022, only 10.3 per cent of the Hungarian population lived in a household with mortgage, rent or utility bills in arrears, compared to 24.3 per cent in 2010. At the same time, the extraordinary rise in residential property prices in the second half

Figure 11.9 Percentage of the population at risk of poverty or social exclusion (AROPE)

of the decade significantly reduced the affordability of housing. In Budapest in 2022, 11.9 years of average net income in the capital city were needed to buy a 75-square-metre apartment, more than 3 years higher than in 2010 (Magyar Nemzeti Bank, 2023). An increase in the renewal rate of the domestic housing stock, which was just 0.45 per cent in 2022, would be key to ensuring both accessibility and decent housing.

Figure 11.10 Share of people living in severely inadequate housing conditions in the total population

CHAPTER 12

RÓBERT HAUSMANN AND ANDRÁS SULYOK

Environmental Sustainability

“The environment is everything that isn’t me.”

Albert Einstein

Long-term sustainability of the economy and society can only be achieved if environmental considerations are taken into account in the decisions we make. Ensuring the regeneration of resources is the only thing that can guarantee the welfare of future generations (Magyar Nemzeti Bank, 2021).

The long-term sustainability of energy management depends on striking a balance between three factors: environmental protection, security of supply and affordability. Expanding domestic, environmentally friendly energy sources would reduce Hungary’s dependence on energy imports and strengthen its environmental sustainability. Renewable and nuclear energy capacities account for a third of the Hungarian energy mix, which can be increased mainly by increasing solar, wind, geothermal and nuclear capacities. There is scope for reserve sustainability by further increasing energy efficiency, which improved by nearly a quarter between 2010 and 2021, and extending it to sectors of which energy efficiency have declined.

The green transition can only be made possible by conserving resources and building a circular economy. Compared to 1990, greenhouse gas emissions of Hungary fell by more than the EU average. The ecological balance is the 9th best in the EU, but further resource savings and investment are needed to achieve carbon neutral economy. This requires the expansion of green financial instruments, to which the green mandate of the MNB contributes.

In terms of environmental sustainability, Hungary ranked 18th in the EU in 2022. The Hungarian score is 42.4 points, slightly below the V3 average of 42.9 points and also lower than the EU average of 45.8 points. The best performing countries (Sweden, Finland, Estonia) in the area scored above 60 points. Among the Visegrád countries, Slovakia and the Czech Republic scored higher than Hungary. Ranking of Hungary improved strongly between 2010 and 2012, then stagnated, but deteriorated more significantly in 2018. Since then, Hungary hasn't managed to improve position in the EU ranking, thus the country's ranking has been the same in recent years as in 2010 (Figures 12.1 and 12.2).

Note: The environmental indicators are limited for 2022, so the results for 2022 are practically the same as for 2021.

Source: MNB

Note: Averages are the average of the rankings for individual countries. The environmental indicators are limited for 2022, so the results for 2022 are practically the same as for 2021.

Figure 12.1 Results in the area of environmental sustainability

Figure 12.2 Trends in environmental sustainability rankings

SUSTAINABLE ENERGY MIX

The sustainability of a country’s energy production is enhanced when the share of environmentally friendly and domestically produced energy sources in its energy mix increases. Investments in renewables and nuclear energy reduce energy dependence and environmental pressures, while improving external balances.

The domestic share of renewable energy sources is lower than the EU and Visegrád averages. The share of renewable energy sources in Hungary’s gross energy consumption was 14 per cent in 2021, the 6th lowest in the European Union (Figure 12.3). In addition to this, the Hungarian indicator increased at the 2nd lowest rate after Romania compared to 2010. If we include nuclear energy in the share of renewables, about one third of Hungarian energy use can be considered environmentally friendly.

V3 range

Hungary

EU average

V3 average

Northern TOP5 average

Figure 12.3 The share of renewable energy in total final energy consumption

Increasing the share of domestically produced environmentally friendly energy sources can reduce Hungary’s energy dependence, thereby improving security of supply and reducing greenhouse gas emissions. Increasing and diversifying the domestic share of renewable and nuclear energy has significant sustainability potential, and the integration of these energies into energy system has already started (Hausmann and Szalai, 2021). This included a more than 50-fold increase (from 1 to 5,407 megawatts) in installed domestic solar PV capacity between 2010 and 2022, exceeding 80 per cent of the 2030 target of around 6,500 megawatts (Innovációs és Technológiai Minisztérium, 2020). The further expansion of environmentally friendly energy sources could be facilitated by exploiting the potential of domestic geothermal and wind energy, and by building up the Hungarian green hydrogen value chain. All of these can contribute to a sustained reduction of the 50–60 per cent domestic net energy import ratio to below 50 per cent, and to achieving a zero-emission economy (Figure 12.4).

Figure 12.4 Net energy imports as a share of gross available energy

The energy use of the Hungarian economy per unit of output fell by nearly a quarter between 2010 and 2021, strengthening the country’s environmental sustainability. But looking at the main sectors of the economy separately, the picture is more complex. While the energy efficiency of industry and agriculture declined by 17 per cent and 15 per cent respectively over the period concerned, the energy efficiency of services doubled.4 In particular, investments to increase energy efficiency in industry and agriculture, and renovation of the households’ housing stock, could help to increase further energy efficiency at a higher rate.

The energy consumption per capita is moderately high compared to Hungary’s economic development. Compared to the economic development, Hungary’s energy overconsumption is the 10th highest in the EU, lower than the average of the other Visegrád countries but higher than the EU average (Figure 12.5).

Gross domestic product per capita at purchasing power parity (PPS/capita, 2021)

Note: Luxembourg’s energy consumption: 6.4 tonnes of oil equivalent per capita, development: 87,056 PPS/capita, Ireland’s energy consumption: 2.3 tonnes of oil equivalent per capita, development: 70,859 PPS/capita.

Source: MNB based on Eurostat data

4 Based on the methodological description of the Hungarian Energy and Public Utility Regulatory Authority on energy consumption statistics, a methodological change was introduced in 2013, so the comparability of energy intensity data at the economic sector and branch level for the years before and after 2014 is limited.

Figure 12.5 Relationship between energy consumption and economic development (2021)

The long-term sustainability of energy system depends on striking a balance between environmental protection, security of supply and affordability. Achieving this can be facilitated by a coordinated and systemic energy policy that ensures achieving climate protection goals, strengthens the country’s security of supply and keeps energy prices affordable. These challenges of finding a solution to all of these at the same time is referred to in the literature as the energy trilemma (Liu et al., 2022).

EMISSION-FREE ECONOMY

Ensuring that our natural resources are available for future generations is key to the sustainable convergence of our economy and society. We can only ensure the ecological sustainability of our planet and of individual countries if we do not exploit the natural resources available – water, air, land – but manage them sparingly and consciously (Meadows et al., 1972). In addition, to keep the global average temperature rise below 2°C compared to pre-industrial levels, major policy efforts are needed.

In Hungary, greenhouse gas (GHG) emissions decreased by 32 per cent between 1990 and 2021. This exceeds the EU’s GHG emission reduction (25 per cent) but is slightly lower than the reduction in emissions of the Visegrád competitors (33 per cent) (Figure 12.6). Around half of the domestic decline between 1990 and 2021 can be attributed to the transition period of the early 1990s, when the heavy industry sector was downsized and restructured. However, GHG emissions have been rising since 2014. The cyclicality of the economy and the variation in GHG emissions are interlinked, which could be moderated in the future by the mass integration of environmental considerations into business models. The European Union has set a target in the European Climate Law for Member States to reduce their GHG emissions by at least 55 per cent by 2030 compared to 1990. The EU’s objective is to achieve total carbon neutrality by 2050.

Carbon dioxide emissions per unit of domestic product are around 35 per cent lower than the average for Visegrád competitors and in line with the EU average. Comparing the change in energy use and carbon emissions per unit of output between 2010 and 2021, the domestic economy is decarbonising at a slightly faster pace than it is increasing its energy efficiency.

Hungary is in the top third of the European Union in terms of population exposure to air pollution. In addition to greenhouse gas emissions, pollutants are also released into the air that are not cleared from the lungs after inhalation, posing a serious health risk. In Hungary, the concentration of these substances in the air is 14 micrograms per cubic metre, which is lower than the average air pollution in the V3, but higher than the EU average (Figure 12.7). In 2019, the number of deaths due to air pollution was the 4th highest in Hungary.

Figure 12.6 Greenhouse gas emissions compared to 1990

CIRCULAR ECONOMY

Globally, we are overconsuming available natural resources, as shown by the fact that 1.7 Earths would be needed to meet global resource needs. A large proportion of the limited natural resources and environmentally damaging activities are available for free or cheaply to many actors in the economy, making it worthwhile for everyone to consume a little more of them than would be profitable and environmentally sustainable for society as a whole (Virág, 2019). The aim of the ecological balance of a country is to measure this for statistical purposes by showing how much of the natural resources available in a country (biocapacity) are used (ecological footprint). A deficit occurs when the ecological footprint exceeds the available biocapacity, i.e., the ecological balance is negative.

Figure

the

Ecological deficit of Hungary is lower than the average for the other Visegrád countries and EU countries. Between 2010 and 2019, Hungary had the 3rd largest increase in its ecological deficit among EU Member States. Only four – Northern countries – in the European Union have an ecological surplus (Figure 12.8).

2019 2010

Note: The ecological balance is the difference between a country’s biocapacity and its ecological footprint.

Source: Global Footprint Network, MNB calculation

The spread of the circular economy could become a key tool for saving resources. The circular economy is about extending the time of usage and life cycle of a product as much as possible, rather than consuming it once. The methods for this include repairing, refurbishing and, when we do not need them anymore, reselling

Figure 12.8 Ecological balance

a product which was purchased once. When a product reaches the end of its life, it is best to recycle its raw materials as much as possible.

The recycling rate of municipal waste in Hungary is lower than the EU and Visegrád averages. An intrinsic factor in the rise of the circular economy is what proportion of waste generated is recycled. Between 2010 and 2018, the share of recycled waste in Hungary increased by almost 18 per cent, approaching the EU average of 38 per cent, but in the following years its relative position worsened overall. The proportion of waste dumped untreated on the surface and in the soil is inversely related to the proportion of waste recycled. The former fell by 20 per cent between 2010 and 2018 as recycling increased, and in 2019–2020, when the share of recycled waste fell, the share of residual material going to landfill increased by a similar proportion. The low share (7 per cent) of materials participating in the circular economy as a share of domestic material use supplemented by net imports also underlines the untapped potential of domestic materials management.

GREEN FINANCING

Green financial instruments, supported by the MNB’s green mandate, help to facilitate the investments needed to strengthen environmental sustainability. Public spending on strengthening environmental sustainability could be financed by revenues from environmental taxes and the issuance of green government bonds. On the other hand, resources that can be mobilised on financial markets (green bonds, green loans, etc.) can support the green transformation of the private sector. The domestic development of green financial instruments is supported by the fact that the Hungarian Parliament gave the central bank (MNB) a green mandate in the summer of 2021, which is the first among European central banks with such

mandate. Closely linked to the green mandate is the MNB’s Green Home Programme, the development of the green toolkit strategy of the central bank, the announcement of the Green Preferential Capital Requirement Programme for commercial banks, and the revitalisation of the domestic green corporate bond market.

There is scope to increase revenues from Hungarian environmental taxes and to extend environmental spending (Baksay et al., 2022). In Hungary, environmental tax revenues as a percentage of GDP decreased by 0.6 percentage points between 2010 and 2021. Thus, in 2021, environmental tax revenues amounted to 2 per cent of GDP, lower than both the Visegrád and EU averages (Figure 12.9). However, domestic pollution taxes (a type of environmental tax), which account for 0.2 per cent of GDP, are the 2nd highest in the EU. These taxes are designed to make the biggest polluters in the economy pay for the use of public goods such as clean air and water. Environmental expenditure as a percentage of GDP has been falling in recent years, and in 2020 it accounted for 1.6 per cent of GDP in Hungary. The Hungarian indicator is lower than the other Visegrád countries, EU and Northern TOP5 averages. More than onethird to one-third of Hungarian environmental expenditure, or 0.60.6 percent of GDP, was contributed to companies and government, while one-quarter, or 0.4 percent of GDP, was contributed to households.

Source: Eurostat

Hungary is one of Europe’s leaders in terms of the portfolio of green government bonds issued. The share of green government bonds in total government bond holdings in Hungary was 3.8 per cent at the end of 2022, only Ireland (4.6 per cent) and the Netherlands (4.1 per cent) had larger shares in the EU. The first green government bond in Europe was issued by Poland at the end of 2016. Hungary issued green bonds in 2020 for the first time, first in euros and then in Japanese yen. This was followed in 2021 by a 30-year green bond issuance on the forint market. Hungary now regularly auctions its 10- and 30-year forint green bonds in the normal government bond auction process, and occasionally raises foreign currency for environmental sustainability expenditure through bond issuance.

Figure 12.9 Environmental tax revenue and expenditure as a percentage of GDP

ÁGNES NAGY AND ANDRÁS ZSOLT SZABICS

Outcomes of the Sustainable Growth Index

“We are using resources as if we had two planets, not one. There can be no Plan B because there is no Planet B.” Ban Ki-moon

Hungary was ranked 21st in the European Union in the Sustainable Growth Index in 2022. Hungary’s performance of 43.8 points in the index was lower than the EU average of 53.1 points and below the 47.4 points of its Visegrád competitors (Figure 13.1). The Czech Republic and Slovakia finished ahead of us in the region, while Poland was behind. Overall, Sweden, the Netherlands and Denmark were the best performing of the 27 Member States, while Bulgaria, Greece and Romania were the worst performers.

Hungary reached the best value of the Sustainable Growth Index in 2019. Between 2010 and 2019, the index increased by 4.7 points, then decreased by 2 points between 2019 and 2022, but still increased by 2.6 points overall since 2010. In Hungary, each of the four sustainability domains examined underperformed the EU average in 2022. However, since 2010, the nation has seen the 5th highest increase in the EU’s Sustainable Growth Index, up 3 places overall over the period. Over the past decade, Hungary made significant progress in social and financial sustainability, with environmental sustainability showing the least improvement since 2010.

Over the past decade, average GDP growth in Hungary exceeded the EU average and labour productivity also improved, but the latter still remains one of the lowest in the EU. Hungary’s domestic value added, both as a share of production and exports, increased over the past decade, but remains lower than the EU average. Innovation and digitalisation are important drivers of productivity and hence sustainability, where progress has been made in recent years, but further efforts are needed to achieve a knowledge and technologyled growth path.

Financial sustainability, based on a stable and efficient financial system and macroeconomic and financial market stability, is an essential factor for sustainable convergence in the long term. The sustainability of the banking system improved over the past decade. Hungary’s macro-financial balance and indebtedness improved substantially between 2010 and 2019, and then the coronavirus pandemic and the energy crisis led to a rise in the budget deficit, current account deficit and inflation.

Social sustainability is fundamentally determined by, among other things, demographic and labour market trends, the quality and accessibility of education and health systems, and the extent of inequalities. In recent decades, European societies, including Hungary’s, have been characterised by unsustainable fertility and ageing populations. Improving the health and education systems is essential to increase welfare (and well-being) and the quality of human capital. Hungary has been nearing full employment in recent years, but looking ahead, productivity needs to increase. Employment growth led to a significant reduction in the proportion of people at risk of poverty and social exclusion, and economic growth was achieved without increasing inequality.

Long-term sustainability of the economy and society can only be achieved if environmental considerations are taken into account in the decisions we make. Ensuring the regeneration of resources is the only thing that can guarantee the welfare of future generations. Compared to 1990, Hungary’s greenhouse gas emissions decreased and its ecological balance is the 9th best in the EU, but further efforts are needed to achieve carbon neutrality. Promoting a circular economy and a competitive transition in the agriculture and food industry would strengthen environmental sustainability. Renewable and nuclear energy capacities account for only a third of the Hungarian energy mix, and further increasing energy efficiency leaves room for catching up. The green transition can be supported by an expansion of green financial instruments and targeted improvements to the tax system. The process is also facilitated by the Magyar Nemzeti Bank through its sustainability mandate. The MNB was one of the first central banks to take meaningful measures to integrate environmental sustainability considerations into the regulatory framework of the banking system, reserve management, monetary policy, collateral management and data disclosure (Matolcsy, 2022).

In Hungary, each of the four sustainability areas examined underperformed the EU average. Figure 13.2 shows how the contribution of development and sustainability areas evolved in each country compared to the EU average performance. Both GDP per capita and sustainability indicators are below the average. However, in the sustainability areas, the gap is smaller than in the case of Poland, compared to which Hungary has an overall better performance despite a lower GDP per capita.

Figure 13.1 Overall results of the Sustainable Growth Index

Source: MNB

Development Economy

Finance

Society

Since 2010, Hungary has recorded the 5th highest increase in the Sustainable Growth Index among EU countries. The rising trend in the index from 2010 was followed by a decline from 2019, but overall the Hungarian score still increased by 2.6 points since 2010 (Figure 13.3).

Of the 27 EU Member States, 9 had a positive periodic balance, with only Lithuania, Latvia, Malta and Ireland ahead of Hungary in terms of dynamics. In Hungary, the larger increase in the index was supported by strong performance improvements in society (+8.9 points), finance (+5.7 points) and economy (+5.3 points). The environment area was considered to be lagging behind (+0.4 points) because the

Figure 13.2 Breakdown of the Sustainable Growth Index by pillar contribution in 2022

performance improvement at the beginning of the period gradually disappeared between 2014 and 2022.

Hungary was in the fourth out of five groups of countries in terms of the Sustainable Growth Index and economic development. GDP per capita in Hungary, the main measure of economic development, increased between 2010 and 2022, from 61.5 per cent of the EU average in 2022 to 76.1 per cent in 2022 at constant prices. The ranking remained relatively stable and in 2022 Hungary was ranked 21st in the development ranking. If both the level of relative development and the Sustainable Growth Index are taken into account, the countries

Figure 13.3 Hungary’s score in the Sustainable Growth Index and its five pillars from 2010 to 2022

of the European Union can be divided into five distinct groups of countries. Hungary is ranked in the fourth group (Figure 13.4).

Note: Ireland and Luxembourg are not included because of their outliers in GDP per capita. Source: Eurostat, MNB

Figure 13.4 Relationship between Sustainable Growth Index and economic development in the European Union in 2022

PROPOSAL FOR CALCULATING SUSTAINABLE GDP

ANDRÁS BALATONI, ÁDÁM MARTONOSI

Introduction to the methodology for calculating sustainable GDP

“Thinking about the implementation of sustainability, it is very easy to see what we have to give up and lose sight of what we could stand to gain. The reality is, however, that a sustainable world offers countless benefits.”

David Attenborough

To overcome the limitations of GDP described in the previous chapters, the Magyar Nemzeti Bank carried out two types of calculations to complement GDP with sustainability aspects. The second approach presented here adjusts the level of GDP in economic (i.e. nonstatistical) terms on the basis of the five factors of sustainability. By our definition, GDP is sustainable if it (1) has been or could have been generated while keeping balance of product and labour markets, (2) financial sector, (3) net lending and it (4) preserves ecological resources and (5) ensures a fair distribution of the goods and services produced.

We give the name sustainable GDP (sGDP) or sustainabilityadjusted GDP to the resulting indicator. For each of the five criteria, a key indicator was chosen to capture the deviation of the given area from the equilibrium level, i.e., the shorter and longer-term cycles, and then adjusted GDP for these deviations. It is therefore possible to calculate what the value of GDP would have been at each point in time if the economy had been on a sustainable path along the five examined dimensions. The result can be higher or lower than the GDP shown in the statistics. It is lower if the economy expanded faster than the sustainable path, which could lead to overheating and imbalances, and higher if the economy did not exploit its equilibrium growth potential.

The advantage of the methodology is that we obtained results that are comparable in time and space for all 27 countries of the European Union. The results are presented in international comparison, in fixed price PPS in euro (comparative prices, 2022 base), in terms of GDP per capita between 2000 and 2022. The approach includes a small number of indicators, but in calculating cyclical movements and deviations from equilibrium, we took into account a number of types of underlying data and information. The calculation draws on international practices (for example in estimating the output gap and the credit gap) but combines them in a new way.

THE FIVE DIMENSIONS OF SUSTAINABILITY CONSIDERED

1. The output gap captures the balance between macroeconomic supply and demand, i.e., the impact of growth on inflation. In this respect, growth is at equilibrium if demand and supply are growing at the same rate and the difference between them is minimal. Excess demand causes inflationary pressures, while oversupply causes deflation. The difference between supply and demand is quantified using the widely used output gap indicator. Disposable income, the economic outlook, the fiscal demand effect, the external business cycle and many other factors play an important role in shaping the demand side of the economy. The indicator we use captures the shortterm business cycle variation of GDP, it is filtered out when calculating sustainable GDP.

2. The sustainability of the economy depends on external financial balance. In the short run, the net lending position may temporarily deviate from the equilibrium level, but in the long run, any deviation in either direction should be closed. The external balance is captured in real economic terms by the external trade balance and, in a broader sense, by the current account balance, which includes financial flows. However, part of the flows with the EU are not included even in the broader indicator, so we used the current account balance supplemented by the capital account, i.e. balance of net lending, in our calculations. The equilibrium position was considered to be a balanced (zero) financing capacity, which means that neither net external debt nor receivables are accumulating, i.e., the stock variables are balanced.

3. The lending activity of the banking system is usually unsustainably strong in economic upturns and too weak in recessions. Lending flows are volatile by nature and the financial system tends to behave pro-cyclically: in good times, it overheats economic growth unsustainably by lending, and in recessions it restrains lending more than is justified, amplifying fluctuations in economic performance. Fluctuation in lending is not considered to be a state of equilibrium

and is therefore excluded from sustainability-adjusted GDP. Our calculations follow the international methodology for the equilibrium estimation of the private sector credit-to-GDP ratio, which takes into account the country’s development and the financial mediating system, its efficiency and digitalisation.

4. The social sustainability of economic growth is estimated through labour market processes. Economic growth can only be sustained if it benefits the widest possible section of society in a fair way. In contrast, excessive inequality leads to a weakening of social cohesion and wasting human capital capacity. Sustainable GDP is calculated by taking into account the probability of individuals with a given level of education finding a job.

5. The ecological aspect of sustainability is quantified by the extent to which available environmental capacities are used or overused. The ecological balance is the difference between the natural resources (biocapacity) available in a given area and the resources used from it (ecological footprint).

The following subsections briefly explain why the key variables we chose are important for sustainability and how we used them in our analysis. The results obtained using the five variables are discussed in detail in the final subsection.

SZABOLCS SZENTMIHÁLYI

Supply and demand balance: The output gap

“The only surprise about the economic crisis of 2008 was that it came as a surprise to so many.”

Joseph Stiglitz

The balance between macroeconomic supply and demand is an important condition for sustainable economic growth. In this chapter, we summarise how we measure the deviation of the supply/demand relationship from the level considered sustainable.

In calculating sustainable GDP, we take into account different macroeconomic variables, whose cyclical processes have different wavelengths. The shortest cycles of 5–10 years are called business cycles, which alternate between boom and bust periods and periodically divert the economy from its equilibrium – and therefore sustainable – growth path. During recessions and crises, real GDP levels are lower than what the supply side of the economy would produce, but higher during booms.

Cycles can be well described by the concept of the output gap, which is the difference between potential output and observed GDP. Potential output is determined by the supply capacity available in a given period. If the output gap is positive, measured GDP is higher than potential GDP, and if it is negative, it is lower. The result of this cyclical movement can also be observed in the evolution of inflation rates. In a period of weak demand, inflation falls and remains low, while above-equilibrium GDP implies accelerating price increases. Thus, if the current performance of the economy is just about equal to its potential level, GDP growth is sustainable from an inflation perspective.

A negative output gap raises and a positive gap lowers the level of sustainable GDP relative to actual GDP. When output is below potential, it would be possible to produce more output with the resources available. Conversely, when the economy overheats and the output gap is in positive territory, GDP sustainable in the long run is lower than real GDP.

MAIN FACTORS DETERMINING THE OUTPUT GAP

The current broad consensus is that long-term growth is determined by the supply side of the economy, i.e., potential output is essentially determined by population growth, capital accumulation and technological progress. If the rate of capital accumulation (determined by investment) is in line with population growth and technological changes, then the evolution of supply-side GDP depends on demographic and technological factors. By contrast, developments in business cycles are mainly determined by demand fluctuations and the economic policy.

When the economy is on its potential growth path, supply and demand are in balance. Many macro variables together shape this through complex interactions. The output gap indicator (Figure 15.1) is able to capture these using a single cyclical variable. Thus, the output gap includes, on the supply side, the growth of investment, the impact of innovation, digitalisation, R&D spending and the role of demography, among others. On the demand side, there is also household consumption, external demand from export markets and fiscal impulses.

The output gap expresses the relative relationship between macroeconomic demand and supply. Demand above equilibrium pushes GDP above its potential level, so the output gap will be positive. If, on the other hand, a shock reduces demand, the output gap could go into negative territory. In this case, companies cut production, leading to redundancies and unused capacity.

For central banks, however, it is not only the output gap per se that is important, but also the resulting inflationary effects. The relationship between inflation and the cyclical position of the real economy is known in economics as the Phillips curve. This implies that the output gap is related not only to unemployment and capacity utilisation but also to inflation. This latter relationship is of particular importance for monetary policy, as the output gap is one of the most important determinants of inflation over the time horizon over which

monetary policy affects inflation. Thus, if the current performance of the economy is equal to its potential level, this can be considered as sustainable GDP growth in terms of inflation, which is an important pillar of our sustainable GDP calculation.

Potential output growth can be broken down by the contribution of production factors (Giorno et al., 1995). When we do this, we assume that at the macroeconomic level, the output of the economy can be captured by the so-called production function, which establishes the link between production inputs (capital and labour) and economic output. The different factors of production can be substituted for each other, for example, in the case of automation, robotisation, the same output can be achieved by replacing labour with physical capital.

The supply side is determined not only by the capital and labour used but also by their productivity, which is influenced by a number of other factors. The state of education and of health basically determine what those skills and are what the health condition is that the working-age population needs to contribute to production. And the innovation ecosystem, the institutions that support it and the level of digitalisation of the economy are key elements in determining how efficiently companies can use all these factors (capital and labour) together to achieve the highest possible productivity from the resources available.

The sustainability of the workforce is influenced by demography on the extensive side and by technological progress and human capital on the intensive side. A stable and steady increase in human capital contributes to more efficient work by enabling production using more advanced technology, leading to higher productivity.

Macroeconomic demand is driven by household consumption, investment, external demand in export markets and the fiscal impulse. However, these are underpinned by a number of other factors, such as the labour market and income situation, perceptions of the economic outlook, lending conditions and fiscal space for manoeuvre.

The sustainability or expansion of potential growth is therefore a function of the factors of production available. Capital goods are

created through investment, while the gradual wear and depreciation of the existing capital stock must also be maintained through additional investment. The more modern a technology is, the faster it becomes obsolete, so the continuity and efficiency of production requires the constant renewal of capital goods. The past period showed that the level of investment and its structure are crucial for economic development. The role of “smart” capital, i.e., information and communication technology (ICT) and intangible assets, has appreciated. “Smart” capital stimulates the whole business sector and digitalisation improves productivity in manufacturing and service companies (Várnai, 2022).

EVOLUTION OF THE OUTPUT GAP IN THE EU AND HUNGARY

We interpret the output gap as the difference between observed GDP and the sustainable (potential) GDP estimated from the supply side of the economy. If current GDP is above the supply-side output level, then the output gap is positive and the economy is performing above its sustainable level. This means overuse of available factors, which is not sustainable, so sustainable GDP is lower than statistical GDP. Otherwise, if the output gap is negative, the economy is not fully utilising the resources available to it, and a higher level of output could be achieved, in which case sGDP is higher than GDP.

EU27 Hungary

Note: For Hungary, we used the output gap calculated by AMECO until 2001 and the MNB’s own Kalman filter-based estimate from 2002 onwards.

Source: AMECO, MNB calculation

The output gap in Hungary was similar to the gap estimated for the EU as a whole. The main differences are, on the one hand, faster closing of the gap compared to the EU in the period 2012–2014, higher overheating in the period 2017-2018 and a smaller negative swing in the output gap during the COVID-19 pandemic.

Figure 15.1 Output gap of the EU and Hungary

BALÁZS SISAK

External long-term sustainability

“Going too far is just as bad as not going far enough.”

Confucius

The long-term sustainability of the economy depends on the sustainability of the country’s external financing. But what does external sustainability mean for a country’s economy? The main indicator of external financial balance is the current account, which includes both external trade and income transactions with the rest of the world and reflects the country’s saving position vis-à-vis the rest of the world. The latter refers to whether the relative value of gross savings and investment results in an inflow of foreign funds (current account deficit) or, on the contrary, an outflow of funds (current account surplus). In this chapter, we analyse the evolution of the relationship between economic growth and sustainable GDP through current account developments.

ONLY THE EQUILIBRIUM POSITION CAN BE MAINTAINED IN THE LONG TERM

When estimating the equilibrium level of the current account balance, the cyclical position of the economy and country-specific characteristics should be taken into account. Some factors affect current account developments in the short term, while others have a long-term impact. Accordingly, current account imbalances may be the result of temporary shocks (such as higher imports due to soaring energy prices) or more permanent processes such as economic catching-up (Cubeddu et al., 2019).

International capital flows allow developing countries to catch up more quickly, and can thus justify persistent external imbalances that may last for a decade or two. Emerging countries may need more capital than domestically available savings, while in developed countries savings generate more capital than can be invested at high returns. In this case, capital flows between countries are, up to a certain level, mutually beneficial. This capital flow causes a current account surplus in the advanced country and a deficit in the emerging country (Figure 16.1). Developing countries benefit from this by seeing a surge in investment and productivity, accelerating economic catch-up. In principle, this process continues until the

capital stock in the emerging country also reaches a level where the return on surplus investment no longer exceeds that of developed countries.

PPS), for * 2021 data

Successful catching-up therefore results in the emerging country becoming one of the countries that invests more capital than it attracts. At the same time, the catching-up process turns from a negative current account balance into a current account surplus. At the level of the national economy, domestic savings by that time exceed domestic investment.

The excessive current account deficit is also hampering economic catching-up through a reduction in national income (GNI). Foreign capital invested demands profit and interest. These payments reduce the so-called gross national income (GNI) indicator. GNI, unlike GDP, is not the sum of goods and services produced within a country’s borders, but the sum of the incomes of the economic agents

Figure 16.1 Relationship between the current account balance and GDP per capita

belonging to that economy. The difference between the two (the GNI-GDP gap) is the result of the flow of profits, interest and workers’ income between countries. If more income flows out of the country than into it, this is reflected as an external imbalance in the balance of payments and reduces GNI relative to GDP. Growth financed from external sources therefore ultimately leads to an imbalance and is not sustainable. The different external positions of countries with different levels of development may also partly reflect their specific demographic situation. In advanced, ageing societies, external surplus is a natural consequence of looking ahead and saving for later in life. Similarly, in the case of countries with rapid population growth, higher consumption and investment demand also justify an initial current account deficit and the accumulation of external debt. Many people in a young society would take out a loan to improve their housing conditions or to start a business, for example.

The current account may therefore durably deviate from balance for structural reasons, but only a position around the balance can be sustained in the very long term. Taking into account the processes that cause persistent imbalances, it is not reasonable to assume that a country can maintain a unilateral relationship with the rest of the world over a very long period, even over many generations, in which its current account position remains negative or positive on an ongoing basis. Therefore, a current account balance around equilibrium appears to be desirable for sustainable growth in the long run, as it ensures that no large accumulation of international debt or claims occurs.

CURRENT ACCOUNT BALANCES OF SUCCESSFULLY EMERGING COUNTRIES IMPROVED

The experience of emerging countries also reflects the fact that successful catching-up cannot take place with a permanently negative current account balance. Globally, the experience of the past decades also provided examples of catching up with different states of current account balances. For example, South Korea’s external balance went from deficit to surplus in 1986 while China is catching up while having a steady surplus. The catching-up of Asian countries has been largely based on a high share of investment financed by domestic savings. At the same time, the Baltic countries achieved rapid growth in the two decades following the fall of the Iron Curtain with large current account deficits.

In the aftermath of the financial crisis, some EU countries were also characterised by a catching-up process with a positive external financial position. In the 2000s, before the financial crisis of 2007–2008, some EU countries experienced catching-up with high current account deficits, but this proved unsustainable for several Member States (Bakker and Gulde, 2010; del Hoyo et al., 2017). In contrast, in the 10 years from the adjustment following the financial crisis to the Covid crisis, the EU’s eastern Member States experienced a catchingup cycle characterised by a balanced or positive external net lending. Emerging countries within the EU are in a special position thanks to the resources from the EU’s Structural and Cohesion Funds. Some of these do not appear in the current account, but still help external financial balance. This means that, for the beneficiary countries, the sustainable level in the long term should not be the balanced current account, but the current account balance supplemented by EU-

funded transfers (the so-called capital account), i.e., the balance of net lending (Figure 16.2).

Current account balance

Capital account balance

Net lending

Source: MNB, Eurostat data

THE ROLE OF FINANCING EXTERNAL IMBALANCES

The sustainability of external imbalances depends on the country’s future net foreign income earning capacity, which is also strongly influenced by the financing of the deficit and the nature of external sources. A country that accumulates external debt has financial room for manoeuvre, but becomes vulnerable to investors’ judgement and changes in financial market conditions, which can lead to a crisis in the event of market turbulence (Catão and Milesi-Ferretti, 2013).

Figure 16.2 External balance indicators averaged over 2018–2022

In such a case, a stagnation in foreign inflows or a sudden reduction in foreign debt could result in a permanent growth sacrifice. In the case of equity finance, or FDI, foreign companies invest directly in the foreign country. In such cases, the investor usually brings not only capital, but also technology, business culture and contacts, so the indirect contribution of this is usually also beneficial to the country’s development and competitiveness. FDI is also beneficial for the stability of the foreign source, but it is a rather expensive form of financing and can tie up resources that could be used to develop a domestically-owned economy (Komáromi, 2008).

If a country finances its current account deficit through debt, then the resulting foreign reliance can make catching up more expensive, while FDI, though useful in many ways, raises dilemmas about the transfer of profits abroad. Thus, the characteristics of external financing can also be used to argue that a sustainable external position in the very long run can be considered to be an external position around equilibrium.

ZSOLT OLÁH AND TAMÁS NAGY

Sustainability of the financial system

“Where there is a will, there is a way. Financial crises are too costly for taxpayers. We cannot afford imprudence and negligence.”

Xavier Freixas, Luc Laeven and José-Luis Peydró

The financial cycle is generally understood to be a common, periodic and not necessarily regular co-movement of the main economic indicators of the financial system. These swings are two-way, with relatively long booms sometimes followed by a severe financial crisis (Borio, 2014).

The financial cycle is endogenous, i.e., it is caused by imperfections in the functioning of processes within the economy. Given that the cyclicality of the financial system can be mitigated by regulation, the question arises as to what would happen to the economy in a state where the harmful part of the cyclical fluctuations of the financial system is minimised. For example, what would the value of GDP be instead of what is observable now? This level of GDP could be considered sustainable in terms of the financial cycle, as it is not underpinned by excessive financial activity or held back by a financial crisis.

We need to make major simplifications in order to have at least some kind of rough idea of the level of GDP “adjusted” for the financial cycle for all 27 EU countries. Therefore, on the one hand, we restrict our approach to the cyclicality of lending, measured by the cyclical position of non-financial private sector (households and non-financial private corporations) credit-to-GDP. On the other hand, we make strong assumptions on the co-movement between credit and GDP based on the relevant empirical literature. In the following, these two simplifications are described in more detail.

CYCLICAL POSITION OF CREDIT-TO-GDP RATIO

The deviation of the non-financial private sector credit-to-GDP ratio from its own trend value is called the credit gap. Outstanding loans as a percentage of GDP is an indication of both the incomegenerating capacity of the loans disbursed and the debtors’ ability to repay the loans. Both interpretations suggest that positive credit gaps (i.e., unusually high credit-to-GDP ratios) indicate the presence

of excessive lending, which increases the likelihood and severity of future financial crises. Negative values, on the other hand, indicate that there is scope for further credit expansion without the risk of major financial instability. The trend values depend on the persistent conditions in the economy, such as the quality of government regulation, the development of the financial intermediation system or the openness of the economy. For this reason, the same credit-toGDP ratio may involve a positive cyclical position in one country and a negative cyclical position in another. There are also more informative indicators of the financial cycle than the credit gap, which can capture developments regarding banks, their clients, property markets, financial optimism and other relevant phenomena. Accordingly, their ability to predict a crisis is generally better than that of credit gaps (see for example Galán and Mencía, 2018; Lang and Welz, 2018; Lang et al., 2019). However, the data needed for these indicators are not available in a uniform way across the 27 EU countries.

There are many ways of calculating credit gaps, and it is not clear which of these best measures the credit cycle, and furthermore, credit gaps are only moderately able to capture the evolution of the financial cycle (for a brief review of the relevant literature, see Hosszú and Lakos, 2021, some of the main references are Detken et al., 2014; Tölö et al., 2018; and Lang et al., 2019). Credit gaps can differ in at least four ways. The loan portfolio considered can be broad or narrow, depending on whether only loans granted by the domestic banking system are taken into account or a wider range of credit-type transactions. The calculation of credit gaps often requires an assumption on the length of the credit cycle, which, according to the literature, can vary between roughly 10 and 30 years, depending on the country group, time period and estimation procedure (Borio, 2014; Aikman et al., 2015; Galati et al., 2016; Jordà et al., 2016; Hiebert et al., 2018). The most popular method of trend-cycle decomposition for credit gaps is the Hodrick–Prescott filter, but there are several alternatives (Hamilton, 2018; Galán, 2019; Barrell et al. 2020; Beltran et al., 2021). Finally, there is also the question

of whether the credit gap value for a given date (typically a quarter) is calculated by taking into account the entire credit-to-GDP time series (two-sided approach) or only up to the date concerned (onesided approach). The latter makes sense if we want to monitor the current evolution of the credit gap, which is typically required by macro-prudential regulation.

The European macro-prudential regulatory framework recommends that, for monitoring the booming phase of the financial cycle, the credit gap should be constructed with the widest possible loan portfolio and a one-sided HP filter that takes into account even the longest financial cycles (BCBS, 2010; ESRB, 2014). We also used this credit gap for our calculations with one modification. We used an HP filter with a maximum financial cycle length of 22 years (i.e., the lambda parameter was set to 125,000 instead of 400,000).

The data were obtained from four different data sources. Fourquarter rolling sum of current price GDP data in the denominator of the credit-to-GDP time series are from Eurostat. The bottleneck was the ECB credit data, which are available for all 27 EU countries, but in many cases only with short time series. The calculated creditto-GDP time series were extended from the BIS credit database (for 17 countries), and where this was not possible, from data of national macroprudential authorities (for 4 countries). The credit gap time series for each country are traced back to at least 2000, and in the case of data gaps, we estimated values based on credit gaps for similar countries.

The different specifications of credit gaps can differ significantly (Figures 17.1 and 17.2). This also implies that the adjustment of GDP by the credit cycle can only be done with considerable uncertainty. These differences can also be observed in the trend values of credit gaps, and it is also striking that only a lower level of non-financial private sector indebtedness in Hungary can be considered sustainable compared to the EU for the time being. Despite the differences, the evolution of all credit gaps clearly reflects the excessive lending in the period

preceding the Global Financial Crisis, partly caused by inadequate regulation of the financial system. In line with the severity of the crisis, a significant and protracted negative cyclical position then emerged, and the renewed economic policy toolbox which also drew on the lessons of the crisis played a significant role in its reversal.

Baseline

Narrow definition of credit Longer cycle

Two-sided filtering Christiano–Fitzgerald filter

Note: Each credit gap differs from the baseline version only in the indicated characteristics. Fourth-quarter values from quarterly time series, except for the 2022 data for the credit gap calculated with narrow definition of credit, where the third-quarter value is shown.

Source: BIS, ECB, and Eurostat data

Figure 17.1 Hungary’s credit gaps based on different filtering methods

Note:

Baseline Longer cycle Two-sided filtering Christiano–Fitzgerald filter

METHOD OF ADJUSTING FOR THE FINANCIAL CYCLE

The sustainable GDP was calculated by adjusting the GDP and the loan stock accordingly, until the credit gap was zero. This is based on empirical results on the typical co-movement of loans and GDP. These imply that a 1 per cent annual increase in the outstanding loans of the non-financial private sector loan portfolio is associated with an annual increase in nominal GDP of roughly 0.2–0.7 per cent per year (international findings: Hristov et al., 2012; Bijsterbosch and Falagiarda, 2014; Gambetti and Musso, 2016; Hungarian findings: Tamási and Világi, 2011; Székely, 2020). To be conservative, we chose a value from the lower half of this range for our calculation: 0.3. The financial cycle

Figure 17.2 Credit gaps for the EU-27 based on different filtering methods

is also linked to other types of cyclical fluctuations in the economy, usually in mutually reinforcing ways (Rünstler and Vlekke, 2018). The lower value chosen was also an attempt to dampen the multiple inclusion of the joint effects of the cycles in the adjustment of GDP for cyclical effects.

In the case of a positive credit gap, the adjusted GDP is smaller than the current one, and in the case of a negative credit gap, it is larger. The higher the absolute value of the credit gap, the higher the absolute value of the gap between adjusted and current GDP.

ANNA NASZÓDI AND ÁDÁM MARTONOSI

Social inequality as a determinant of sustainable GDP

“Social justice demands that we fight against the causes of poverty: inequality and the lack of labour, land, and lodging; against those who deny social and labour rights; and against the culture that leads to taking away the dignity of others.”

Pope Francis

Moderate levels of social inequality are an important criterion for sustainability. There is no optimal level of inequality. However, neither the extreme high nor the extreme low values have been stable throughout history. In this chapter, we summarise how we measure the social inequality underlying our sustainable GDP indicator. The basis of measurement is the cyclical nature of social inequality.

A wide variety of indicators are used in the literature to measure social inequality. The main reason is that inequality is multidimensional. This is reflected, for example, in differences in income and wealth of different groups, social mobility and employment opportunities. In addition to economic dimensions, differences between the relatively advantaged and the relatively disadvantaged people can be seen in differences in education, training opportunities, and opportunities for the preservation of health and recovery. The list of dimensions could go on almost endlessly.

Another relevant aspect of the measurement of inequality is that, within a certain limit, certain forms of inequality are socially acceptable, while beyond a certain limit and in certain forms of inequality they are not sustainable due to lack of social acceptance. Finally, a further consideration in the choice of inequality index is that the active role of the state is expected in reducing certain types of inequalities, while in other areas it is not in consideration. Typical expectations include security, access to basic education and healthcare, and a healthy environment. However, the state, for example, is not expected to provide its citizens with a suitable spouse and a long, happy life. Nevertheless, we can track historical changes in social inequality from changes in marriage patterns and life expectancy, as well as from trends in indicators that can be directly influenced by the state (see Case and Deaton, 2021; Naszodi and Mendonca 2021, 2022, 2023).

SUSTAINABILITY MEASURED BY THE EMPLOYMENT GAP

To calculate sustainable GDP, we use an inequality index based on differences in employment opportunities. This indicator is the employment gap, defined as the difference between the employment rates of the highly educated (those with at least a college degree) and the low educated (those without a high school diploma).

Employment opportunities are closely related to other dimensions of inequality (e.g., income, health, life expectancy) and the strength of social cohesion. The data show that the employment gap has similar pattern to indicators derived from other labour market data (e.g., wage distribution), thus confirming our view that the indicator chosen to calculate sustainable GDP captures social inequality in a sufficiently comprehensive way.

We use a statistical approach and historical data to determine the extent of social inequality calculated in employment gap, which is the basis for our calculation of sustainable GDP. The extent of the employment gap which is compatible with sustainable GDP was defined by examining the fluctuation of the indicator over time and looking for a value sufficiently far from extreme highs and lows. Since the low value is typically around zero, the central value is defined as half of the maximum value recorded during the period under review.

It should be stressed that the central value defined in this way was taken by the cyclically fluctuating gap indicator only occasionally, as illustrated by the Hungarian data in Figure 18.1. However, in the years when the gap indicator was precisely equal to it, we were relatively far away in time from the turning points.

The employment gap indicator has the advantage that, unlike other social inequality indicators, it is based on relatively easily accessible data and can be produced for a wide range of countries and for a longer period relevant to the analysis. The employment data for the 27 EU Member States were downloaded from the Eurostat website, which are produced by Eurostat on the basis of the Labour Force Survey. Thus, we improve the comparability of our indicators from different years or for different countries by calculating it using data on young men aged 25–29. This avoids any strong influence by differences among or changes in the pension rules or parental leave rules over time. However, if this data was not available for a particular country and a particular year, we replaced it with the unemployment gap, calculated in a similar way to the employment gap, or with data for a wider age group (e.g. 25–39 year olds).

Figure 18.1 Comparison of the employment gap and the wage distribution indicator

Malta Hungary

Spain Finland Luxemburg

EU27 Sweden

Slovakia

Austria

Portugal Greece

Italy

France

Romania Belgium

Our approach is consistent with research that shows that excessive social inequality has negative effects on the economy. According to Ostry et al. (2014), rising social inequality also shortens the favourable period of the economic cycle when GDP is growing. We used their empirical findings to calculate the contribution of sustainable levels of social inequality to sustainable GDP (see Figure 18.2).

Figure 18.2 Contribution of the employment gap indicator to sustainable GDP in in 2022

NORBERT CSORBA

Role of environmental factors in calculating sustainable GDP

“Nature provides a free lunch, but only if we control our appetites.”

William Ruckelshaus

Since the first industrial revolution, the historically unprecedented growth in the world’s economy and population resulted in increased utilisation of the available natural resources. As a result, the depletion of environmental resources has increased in past decades and has now become a tangible barrier to long-term sustainable growth. Natural resources are not merely input factors of production, but also serve as a framework for it. The volume of available resources is finite, and thus – with a view to ensuring sustainable growth – efforts should be made to use resources efficiently also in ecological terms (Virág, 2019). In this chapter, we summarise how we measure the deviation of environmental resource use from the level considered sustainable.

Of the five key variables considered in the calculation of sustainable GDP, the ecological indicator has the longest cycle. There is a strong argument that we are in the first long, and deteriorating, global cycle in terms of ecological balance since the industrial revolution. Although it is difficult to quantify all environmental resources and their use in a single indicator, the data point in the direction of a global ecological footprint that significantly exceeds the Earth’s carrying capacity. It is estimated that we currently use as much environmental resources each year as the Earth produces in 1.8 years (Global Footprint Network, 2022b). The pursuit of ecological sustainability is therefore both a necessity and an opportunity for new technologies, investments and jobs. Ecological sustainability is not only a goal but also a major economic driver in all walks of life (Baksay et al., 2022).

ECOLOGICAL SUSTAINABILITY IS MEASURED BY THE ECOLOGICAL BALANCE

The ecological balance is the difference between the natural resources (biocapacity) available in a given area and the resources used from it (ecological footprint) (Global Footprint Network, 2022a;

Magyar Nemzeti Bank, 2022). Biocapacity is the sum of all biologically productive areas (both terrestrial and aquatic) that are needed to meet human needs and to reproduce. The ecological footprint is the amount of natural resources used to meet needs and the amount of waste generated.

The common unit of measurement is the so-called global hectare. The global hectare is the average biological and natural resource per hectare on the planet. The results vary considerably from country to country: for example, in good soils the value is higher, while in deserts and urbanised areas it is lower. Each country’s own resources per capita can then be compared with the resources it uses. In addition to the direct environmental burden of production, the ecological footprint also tries to take into account the exported and imported environmental burdens, which is usually a major challenge in sustainability analyses. Data were obtained from the Global Footprint Network and York University (Canada), which are general references on the subject.

THE ECOLOGICAL BALANCE IN THE EUROPEAN UNION IS NEGATIVE

Like most European countries, Hungary’s ecological footprint exceeds its biocapacity, thus the ecological balance is in deficit (Figure 19.1). This means that more biocapacity or lower use of ecological resources is needed to meet current needs, as we are currently overusing our resources.

Note: From 2019 we use York University baseline data, which form the basis of the GFN time series. 2021 and 2022 preliminary data release.

Source: Global Footprint Network, York University (Canada)

Hungary’s ecological balance compares favourably with the EU and the region and was better than the world average for most of the 2010s (Figure 19.2). In the first half of the 2000s, the Slovak ecological balance was better than the Hungarian ecological balance in environmental terms. Since 2005, however, the ecological footprint of Hungary has been decreasing, which has been accompanied by an improvement in the ecological balance. With the improvement of the Hungarian balance, and the simultaneous worsening of the world average, by the 2010s, Hungary’s value was already better than the world average. The Czech, Polish and EU average were all below the Hungarian ecological balance over the whole time horizon.

Figure 19.1 Evolution in Hungary’s biocapacity, ecological footprint and ecological balance

Note: From 2019, we use York University baseline data, on which GFN time series are based, 2021 and 2022 are preliminary data releases.

Source: Global Footprint Network, York University (Canada)

The impact of each country’s ecological balance on sustainable GDP was calculated on the basis of natural endowments and development. Significant differences can be identified between the geographic endowments in each country. The Scandinavian countries tend to have a high proportion of forested and untapped natural capacity, resulting in high biocapacity and a positive ecological balance, in contrast to countries with small areas and high population density (e.g., Benelux), which have a high proportion of built-up areas, low biocapacity and a highly negative ecological balance.

Figure 19.2 The ecological balance of the Visegrád Four, the European Union and the world

In order to quantify the impact of the ecological gap on sustainable GDP, we estimated country-specific parameters for our study due to the different geographic endowments. Several different methodologies were used to determine this in different estimations: time series, cross-sectional and panel examination. To estimate individual, country-specific variances, we fitted OLS (Ordinary least squares) models to time-series data for the countries and performed the process for period averages on the cross-sectional sample. Finally, we constructed a pooled OLS model on a panel database built from time series and cross-sectional data of the European Union Member States.

The more advanced an economy is, the less its ecological balance is affected by a unit of additional economic growth (Figure 19.3). In the early stages of economic development, growth goes hand in hand with more intensive pollution of the environment and greater use of resources. However, later, when a certain level of development is reached, environmental protection becomes more important, and innovations to use resources more efficiently, as well as green investments are given more attention (Zorkóciová et al, 2021). These can help to achieve further economic growth without significant additional environmental pressures (Dinda, 2004). This process is supported by the shift in emphasis from industrial production to the services sector in developed countries, which is lower in emissions and less energy intensive.

Note: Development is calculated as GDP per capita, based on fixed price purchasing power parities in 2022.

Source: MNB calculation based on Global Footprint Network and Eurostat data

Figure 19.3 Relationship between the development of the EU countries and the ecological parameter

ÁDÁM MARTONOSI

Sustainable GDP indicator (s GDP) results

“Sustainable development is the pathway to the future we want for all. It offers a framework to generate economic growth, achieve social justice, exercise environmental stewardship and strengthen governance.”

Ban Ki-moon

In this chapter, we present the results of our estimates for the calculation of the sustainable GDP indicator (sGDP), based on the details presented above. Sustainable GDP is an economically adjusted alternative measure of GDP that shows the economic output that would be generated if the product and labour market, the financial sector, the balance of financing capacity and the conservation of ecological resources were maintained, while ensuring a fair distribution of the goods and services produced. Another important aspect in the construction of the indicator is that it should be comparable over time and cross-section, so as to show the main trends over the last two decades.

Our results show that in Hungary, sustainable GDP exceeded GDP in the 2010s, but fell below GDP in 2021 and remained below GDP in 2022. In the 2000s, sustainable GDP was significantly lower than statistically recorded GDP, which is explained by the fact that a significant part of economic output was generated by unsustainable external indebtedness. Sustainable GDP has exceeded actual GDP since 2012, partly due to the adjustment of the economy and partly due to the new type of economic policy reforms introduced since 2010. Between 2015 and 2017, sustainable GDP was around 15 per cent higher than actual GDP, suggesting that there was still room for sustainable GDP growth. However, after 2017, sustainable GDP declined, which may be a consequence of the COVID-19 pandemic and the energy crisis, as well as the lack of reforms.

WHAT METHODOLOGY WAS USED TO CALCULATE SUSTAINABLE GDP?

Our approach is to measure the deviation of economic, social and ecological processes from the equilibrium level in five areas, and to adjust GDP levels for this deviation (Figure 20.1). The five areas and their key indicators:

1. Output gap: This shows the relationship between macro demand and supply in the economy. A positive value indicates an excessively high level of demand and hence inflationary effects.

A negative value indicates that demand is below the level that can be generated by the supply side, so the economy is performing below its potential.

2. Current account: This shows whether the economy’s external balance with other countries is in balance. A deficit means that the economy is using more financial resources than it has available. This may stimulate growth in the short term but is unsustainable in the long term. If the current account is in surplus, the country is allocating its savings abroad, indicating limits to internal growth potential.

3. Credit gap: This measures the internal financial balance. A positive value indicates that the banking system is lending more to the economy than the sustainable level. As with other imbalances, this can boost economic growth in the short term, but it is unsustainable in the medium term and usually leads to a financial crisis that completely erases the previous growth surplus. In the case of a negative credit gap, the banking system lends less than it could, given its own development and the state of the economy, which slows down investment and thus economic growth.

4. Employment gap: This measures social inequality. It is the difference in employment rates between the highly educated and the low educated. In almost all countries, highly skilled people find jobs more easily than less skilled people. However, if this gap becomes too high, it indicates that low-skilled people are not getting access to adequate education (and possibly health care), social mobility is severely restricted, income gaps are high and social cohesion is damaged. There is no optimum level of social inequality, so we compare each country to its own level of inequality that seems sustainable.

5. Ecological balance: This is a sign of a country’s environmental sustainability. The ecological balance is the difference between the natural resources (biocapacity) available in a given area and the resources used from it (ecological footprint). If it is negative, the national economy uses more resources than are available in its territory in a renewable way. With the exception of the sparsely populated Nordic countries, EU countries typically have ecological deficits.

Source: MNB editing

Our concept of sustainable GDP is based on actual GDP figures, adjusted by deviations from equilibrium values. The key indicators measuring the five dimensions of sustainability and their deviation from the equilibrium level have been presented in the previous chapters. Adjustments are subtracted or added to the level of GDP by assigning appropriate parameters to each key variable to determine the level of sustainable GDP (sGDP). The limited number of variables allows us to make these calculations over long time series (2000 to 2022) and for broad international comparisons (all 27 EU Member States).

The sGDP indicator was designed to be comparable with the GDP per capita indicator at purchasing power standard. GDP per capita at purchasing power parity is a key indicator for measuring economic development. Converting the total GDP of the national economy to GDP per capita helps to eliminate differences in size

Figure 20.1 The sGDP indicator takes into account five sustainability aspects

Sustainable lending environment

Sustainable inflation

Sustainable external balance

Sustainable ecology

Sustainable social welfare

between countries. The purpose of purchasing power parity is to remove distortions due to different price levels in different countries. Our main outcome variable is sustainable GDP per capita, which we construct on a fixed basis and at purchasing power standard prices (2022 base, PPS euro).

The level of sustainable GDP that we calculate shows what the value of GDP would be if there were no imbalances in the economy and all key variables were on a sustainable trend. If this is the case, i.e., if there is no significant difference between GDP per capita at purchasing power parity and the sGDP indicator we calculate, then economic performance is sustainable at that level.

For many countries, sustainable GDP levels are significantly below or above actual GDP levels for longer or shorter periods, suggesting that countries are experiencing significant imbalances. The two indicators can become closer to each other in several ways. If the level of sGDP is below the level of actual GDP, it indicates that the economy is reaching its current level of development by sacrificing equilibria, which is not sustainable. If this tendency does not change in time, the level of GDP is expected to converge towards the level of sGDP (i.e., decline in relative terms). But if a country can improve its sustainability processes, sGDP could catch up with the higher GDP level. In periods when the level of sustainable GDP is higher than actual GDP, the equilibrium factors would allow for higher economic development than the development actually achieved. In this case, with appropriate reforms, the level of actual GDP could reach the level of sGDP without weakening sustainability.

MEASURING AND COMPARING ECONOMIC DEVELOPMENT

Our results show that sGDP per capita in Hungary exceeded the GDP level in the 2010s, but fell below it in 2021 (Figure 20.2). In the 2000s, sustainable GDP per capita was significantly lower than the GDP indicator shown in the statistics. The reason is that economic growth was only possible at the cost of large imbalances before the

2008–2009 financial crisis (Matolcsy, 2020). In the mid-2000s, sGDP was on average about 25 per cent below the level of actual GDP. This trend changed significantly after 2008, first as a result of the economic crisis, and then from 2010 as a result of economic and competitiveness reforms. The level of sustainable GDP reached the level of actual GDP in 2011–2012 and then gradually increased thereafter. The vast majority of economic reforms had already been completed by 2015, which raised the level of sGDP, so that between 2015 and 2017, sGDP was around 15 per cent higher than actual GDP. This indicated that there is still room for sustainable catching up. However, between 2017 and 2019, sGDP growth slowed and then declined from 2020, partly due to the economic crises. Statistical GDP recovered quickly after the COVID-19 crisis, but sGDP did not, and the latter fell back below the level of actual GDP in 2021–2022.

Figure 20.2 Trends in GDP per capita and the sGDP indicator in Hungary, 2000–2022

Looking at the same thing, a different picture emerges in two European countries that are very different from Hungary (Figure 20.3). In the case of Germany, we can see that it was able to gradually correct its internal imbalances without a significant decline in economic performance. In the 2000s, GDP in Germany also exceeded its sustainable level by more than 20 per cent, but the gap gradually closed over the period under review, narrowing to 5–7 per cent by the end of the period. The German economy was also able to reduce its long-cycle imbalances (ecological balance and social inequality). Greece underwent a characteristically different process over the past two decades. The sGDP time series highlights the unsustainable performance of the Greek economy in the first half of the 2000s. The initial gap of around 25 per cent between the two indicators reached its widest in 2007–2008, at around 35 per cent. Subsequently, the gap between the two indicators closed very quickly, partly due to the sharp downturn in the Greek economy and partly due to the rise in sustainable GDP resulting from the significant adjustment. Together, the two effects closed the gap between the two indicators between 2011 and 2012, and the gap has since been negative in the last decade, with neither per capita development nor sustainable GDP showing any significant growth. The last two decades in Greece illustrate how dynamic growth and sustainability processes can change in a small emerging economy when dominated by shorter business cycles.

GDP per capita (Greece)

sGDP per capita (Greece)

GDP per capita (Germany)

sGDP per capita (Germany)

Sources: AMECO, Eurostat, Global Footprint Network, York University, IMF, BIS, ECB, MNB calculation

FACTORS DETERMINING THE EVOLUTION OF SUSTAINABLE GDP

With the two sets of statistics, the difference between the time series of actual and sustainable GDP can be broken down and the direction and extent to which each of the five key variables is responsible can be determined.

A decomposition of the Hungarian sGDP adjustments shows that the domestic economy was characterised by over-indebtedness in the period before the financial crisis, which is reflected in external imbalances and lending imbalances (Figure 20.4). In the years preceding the financial crisis, sustainable GDP was around 25 per cent below actual GDP, with the five variables playing roles to different extent. The most significant shortfalls were in the financing capacity,

Figure 20.3 Trends in GDP per capita and sGDP in Germany and Greece, 2000–2022

the credit gap and the ecological balance. The financial crisis brought about a significant degree of forced adjustment also in the case of Hungary, which went hand in hand with a rise in social inequality, while financing and lending flows were quickly restored to a level that could be considered equilibrium.

The domestic level of sustainable GDP peaked between 2015 and 2017. The recovery from the financial crisis in Europe took years, but after 2012 the economy gradually recovered. Sustainable GDP growth was mainly driven by improvements in financing capacity and credit flows. The current account gradually turned into surplus, with the result that the financing capacity contributed positively to sGDP. The improvement in the credit gap is also significant. Excessive lending was replaced by equilibrium, and by the middle of the decade it appeared that lending could be increased even while maintaining equilibrium. Improvement in social inequality was mirrored in employment growth. Employment increased by more than 850,000 jobs between 2010 and 2022, which also significantly improved the employment chances of the low-skilled (with employment rates above the EU average). The ecological balance deficit temporarily narrowed but remained in deficit. The output gap fluctuated close to its equilibrium level.

From 2017 onwards, the level of Hungarian sGDP declined and was lower than statistically measured GDP in 2021-2022. The financing surplus disappeared and the credit gap gradually closed. The outbreak of the coronavirus pandemic was followed by a significant economic downturn, reflected in a positive contribution of the output gap in 2020, while the ecological deficit increased slightly. On the positive side, however, social inequality contributed positively to sustainable GDP at the end of the period under review, explained by near full employment and a tight labour market. In 2021, the level of sustainable GDP fell below actual GDP and remained there in 2022, suggesting that economic catching-up requires an improvement in sustainability.

External financing gap

Loan gap

Social gap

Ecological balance

Total difference

It is important to stress that the decomposition of sGDP shows a very different picture for European countries with different economic structures. International experience shows that there is a significant gap between more developed European countries and emerging economies. While for the former we see smaller differences between the two GDP calculations, for developing countries the shifts are significant. As we have seen, differences in geography and economic structure also cause significant differences in the evolution of sGDP levels, in particular in the ecological balance indicator.

Figure 20.4 Breakdown of the difference between sGDP and GDP in Hungary, 2000–2022

HUNGARY’S SUSTAINABLE DEVELOPMENT IN A EUROPEAN COMPARISON

As with GDP per capita, sGDP per capita varies significantly compared to the EU average, with Hungary ranking 25th in 2022 and its relative position worsening compared to the beginning of the period (Figures 20.5 and 20.7). Among the countries in the region, Austria (7th) and the Czech Republic (15th) are in the best position, Poland is 18th, Slovenia 20th, Romania 23rd and Slovakia 26th.

At the level of sGDP, Ireland and Luxembourg stand out in line with most other economic statistics because of their specific economic structure, followed by the developed countries of Western Europe and the Nordic countries. In Denmark, the Netherlands and Germany, it is true that their sustainable GDP relative to the EU average improved compared to 2000, while the other developed countries saw a slight deterioration, mainly due to the performance of the emerging countries that are catching up dynamically.

In terms of sGDP per capita, Poland made the biggest improvement in the Baltic region. Estonia is ranked tenth, partly due to its favourable ecological balance. The role of the ecological balance also makes a significant contribution to sustainability in other, typically Northern, countries, with untapped biological capacity improving sGDP to a lesser extent in Latvia and to a large extent in Finland and Sweden.

Sources: AMECO, Eurostat, Global Footprint Network, York University, IMF, BIS, ECB, MNB calculation

Hungary’s sGDP per capita indicator relative to the EU average reflects the domestic gap between sGDP and GDP (Figure 20.6). GDP per capita at purchasing power standard (PPS) is an important measure of economic development relative to the EU average, and similarly the sGDP per capita indicator can be calculated relative to the sustainable EU average.

In the 2000s, until the onset of the financial crisis, domestic sustainable development lagged substantially behind that measured by traditional methodologies. The difference was around 10 percentage points over this period. However, after the onset of the financial crisis in 2008, there was a significant improvement in sustainable development of around 25 percentage points compared to the EU average until 2017, which represents an relevant convergence of around 3 percentage points per year on average. This was partly explained by the forced economic adjustment during the financial

Figure 20.5 sGDP per capita in Europe (EU27=100), 2000 and 2022

crisis, which removed some of the existing imbalances, and partly by the economic policy turnaround in the post-crisis period, which put the Hungarian economy on a more sustainable growth path. The latter was also reflected in the development of GDP but increased the level of sGDP even more.

In the years 2015-2018, domestic sustainable development reached 80 per cent of the EU average, which is about 10 percentage points higher than the domestic development calculated on the basis of actual GDP over this period.

However, after 2018, the level of sustainable GDP relative to the EU average started to decline gradually and fell below the level of actual GDP by the end of the period under review. The slowdown is mainly explained by the cyclical closing of the financing capacity and the credit gap, which significantly reduced the level of sustainable GDP over a few years.

Figure 20.6 Trends in Hungary’s development and sustainable development (EU27=100), 2000–2022

The evolution of sustainable development relative to the EU average can also be seen in Hungary’s position in the EU ranking (Figure 20.7). In terms of actual GDP per capita, Hungary slipped from 19th to 23rd place in the EU ranking from the mid-2000s, and then gradually moved up from 2012 to 21st place in 2019, and held the same position in 2022. The ranking based on sustainable GDP is slightly different, although the main trends are similar. On the one hand, at the beginning of the period, Hungary’s ranking was worse than 19th, it was rather in the 21st–22nd position in the ranking. Subsequently, the Hungarian economy slipped back to 24th place during the financial crisis. With the dynamic growth of sustainable GDP Hungary's ranking improved to the 21st place till 2015. However, since 2019, the negative trends seen in sustainable GDP were also reflected in Hungary’s ranking. After losing multiple positions, Hungary was in 25th place by the end of the period, which is already below the worst position seen at the trough of the financial crisis.

Figure 20.7 Hungary’s development ranking among EU countries in terms of GDP per capita and sGDP per capita

ACKNOWLEDGEMENTS

The authors and editors of the book would like to thank MNB Governor György Matolcsy for formulating the ideas behind the book and for initiating its creation, and Deputy Governors for their encouraging support.

Special thanks to the authors of the papers in this volume, namely to: Péter Hugó Asztalos, András Balatoni, Lilla Sarolta Bánkuty-Balogh, Eszter Baranyai, Gábor Bartus, Pál Bóday, Magdolna Csath, Norbert Csorba, Áron István Drabancz, Zénó Fülöp, Róbert Hausmann, György Ádám Horváth, Zoltán Jenőfi, Csaba Kandrács, Csaba Lados, Ádám Martonosi, György Matolcsy, Bence Muhari, Ágnes Nagy, Erzsébet Éva Nagy, Anna Naszódi, István Nemecskó, Zsolt Oláh, József Popp, Tibor Princz-Jakovics, Raekwon Chung, Péter Savanya, Balázs Sisak, András Sulyok, András Zsolt Szabics, Miklós Szebeny, Szabolcs Szentmihályi, Mihály Szoboszlai, Zsuzsanna Szőkéné Boros, István Tózsa, Viktor Dénes Varga, Noémi Végh, Barnabás Virág, Vivien Virágh; and thanks for their suggestions on individual chapters and for their support of the authors’ work to: Dániel Babos, Bálint Dancsik, Ágnes Halász, Gergely Kicsák, Katalin Kis, Péter Koroknai, Géza Rippel, Péter Sajtos, Gábor Dániel Soós, Ákos Szalai, Kristóf Takács, Lóránt Varga and Sándor Winkler.

The discussion paper was edited by Gergely Baksay, György Matolcsy and Barnabás Virág.

The authors and editors would especially like to thank Rajmond Csikár for the editorial and coordination work, as well as Márta Puklus for the readers’ editorial assistance and Soma Szabó for his page layout work.

The graphic design of the volume is the work of the Budapest Metropolitan University. The authors would like to thank Katinka Cseh, Szilvia Dóra, Paula Lévay, Maja Bajcsy and László Fejér for their printing and logistical support, and László Körtvélyesi for coordinating the online publication, which were essential for the completion of this publication.

APPENDIX

References

Glossary

List of figures and tables

Abbreviations

Index of names and terms

REFERENCES

2008 SNA Update, Digitalization Task Team [DZTT] (2008) DZ. 6 Recording of data in National Accounts. Inter-secretariat Working Group of National Accounts. Downloaded from: https://unstats.un.org/ unsd/nationalaccount/RADOCS/ENDORSED_DZ6_Recording_of_Data_ in_NA.pdf (Date of download: 22 June 2023).

Acemoglu, D. (2011) Introduction to modern economic growth Princeton: Princeton University Press.

Aikman, D., Haldane, A. G. and Nelson, B. D. (2015) ‘Curbing the credit cycle’, The Economic Journal, 125(585), pp. 1072–1109.

Asztalos, P., Horváth, G., Krakovský, Š. and Tóth, T. (2017) ‘Ellentétek feloldása a bankrendszerek versenyképességének mérésében: Az MNB bankrendszeri versenyképességi indexe’ [Resolving mismatches in the measurement of banking system competitiveness: the MNB Banking System Competitiveness Index], Hitelintézeti Szemle / Financial and Economic Review, 16(3), pp. 5–31.

Bakker, B. B. and Gulde, A-M. (2010) The Credit Boom in the EU New Member States: Bad Luck or Bad Policies?. IMF (Working Paper No. 2010/130).

Baksay, G., Kicsák, G. and Szalai, Á. (2016) ‘Államadósság’ [Public debt] Budapest: Magyar Nemzeti Bank (Handbooks, Vol. 4) Downloaded from: https://www.mnb.hu/letoltes/mnb-oktatasi-fuzetek-2016-4szamallamadossag-2016augusztus.pdf (Date of download: 22 June 2023).

Baksay, G., Matolcsy, Gy. and Virág, B. (ed.) (2022) Új fenntartható közgazdaságtan. Globális vitairat. [New sustainable economics. Global discussion paper]. Budapest: Magyar Nemzeti Bank. Downloaded from: https://www.mnb.hu/web/sw/static/file/uj-fenntarthatokozgazdasagtan-single.pdf (Date of download: 22 June 2023).

Barrell, R., Karima, D. and Macchiarelli, C. (2020) ‘Towards an understanding of credit cycles: Do all credit booms cause crises?’, The European Journal of Finance, 26(10), pp. 978–993.

Barro, R. J. and Sala-I-Martin, X. I. (1995) Economic growth. New York: McGraw Hill.

Bartus, G. and Szalai, Á. (2014) ‘Környezet, jog, gazdaságtan: Környezetpolitikai eszközök, környezet-gazdaságtani modellek és joggazdaságtani magyarázatok’ [Environment, law, economics: environmental policy instruments, environmental economic models and explanations for economic analysis of law]. Piliscsaba: Pázmány Péter Catholic University Faculty of Law and Political Sciences (‘Jogtudományi Monográfiák 6.’ [Law Monographs 6]).

BCBS (2010) Guidance for national authorities operating the countercyclical capital buffer. Basel Committee on Banking Supervision, Bank for International Settlements. Downloaded from: https://www.bis.org/publ/bcbs187.htm (Date of download: 22 June 2023).

Beal, D., Rueda-Sabater, E. and Espírito Santo, T. (2012) From Wealth to Well-Being. Introducing the BCG Sustainable Economic Development Assessment. The Boston Consulting Group. Downloaded from: https:// web-assets.bcg.com/img-src/From_Wealth_to_Well_Being_Nov_2012_ tcm9-165787.pdf (Date of download: 22 June 2023).

Beça, P. and Santos, R. (2014) ‘A comparison between GDP and ISEW in decoupling analysis’, Ecological Indicators, 46, pp. 167–176. doi: http:// dx.doi.org/10.1016/j.ecolind.2014. 6.10.

Beltran, D. O., Jahan-Parvar, M. R. and Paine, F. A. (2021) Optimizing credit gaps for predicting financial crises: Modelling choices and tradeoffs. Washington: Board of Governors of the Federal Reserve System (International Finance Discussion Papers 1307).

Bijsterbosch, M. and Falagiarda M. (2014) Credit supply dynamics and economic activity in euro area countries: A time-varying parameter var analysis. Frankfurt am Main European Central Bank (ECB Working Paper Series No. 1714).

Bóday, P. and Szilágyi, G. (2013) ‘A környezeti számlák szerepe a fenntarthatóság mérésében’ [The Role of Environmental Accounts in Measuring Sustainability], Statisztikai Szemle / Hungarian Statistical Review, 91(8–9), pp. 870–889.

Borio, C. (2014) ‘The financial cycle and macroeconomics: What have we learnt?’, Journal of Banking and Finance, 45, pp. 182–198.

Boye, K. (2009) ‘Relatively Different? How do Gender Differences in Well-Being Depend on Paid and Unpaid Work in Europe?’, Social Indicators Research, 93, pp. 509–525.

Briglevics, T., Nagy, Á., Sisak, B. and Szalai, Á. (2020) ‘Gazdasági növekedés és alacsony vagyoni különbségek: Egy fontos lépés a fenntarthatóság felé’ [Economic growth and low wealth inequality: an important step towards sustainability]. Budapest: Magyar Nemzeti Bank. Downloaded from: https://www.mnb.hu/letoltes/briglevitstamas-nagy-agnes-sisak-balazs-szalai-akos-gazdasagi-novekedes-esalacsony-vagyoni-kulonbsegek.pdf (Date of download: 22 June 2023).

Brynjolfsson, E. and Collis, A. (2019) ‘How should we measure the digital economy?’, Harvard Business Review, November–December. Downloaded from: https://hbr.org/2019/11/how-should-we-measurethe-digital-economy (Date of download: 22 June 2023).

Burck, J., Uhlich, T., Bals, C., Höhne, N., Nascimento, L., Tavares, M. and Strietzel, E. (2022) Climate Change Performance Index 2023. Bonn/Berlin Germanwatch e.V., Cologne: New Climate Institute, Bonn: Climate Action Network International. Downloaded from:

https://ccpi.org/download/climate-change-performance-index-2023/ (Date of download: 22 June 2023).

Case, A. and Deaton, A. (2021) ‘Life expectancy in adulthood is falling for those without a BA degree, but as educational gaps have widened, racial gaps have narrowed’, PNAS, 118(11) e2024777118.

Catão, L. A. V. and Milesi-Ferretti, G. M. (2013) External Liabilities and Crises. IMF (Working Paper 2013/113).

Cobb, C., Halstead, T., and Rowe, J. (1995) The genuine progress indicator: Summary of data and methodology. San Francisco: Redefining Progress. Downloaded from: https://www.academia. edu/2130369 (Date of download: 22 June 2023).

Conceição, P. and Bandura, R. (2008) Measuring Subjective Wellbeing: A summary review of the literature. New York: Office of Development Studies (UN Development Programme).

Costanza, R. et al. (1997) ‘The value of the world’s ecosystem services and natural capital’, Nature, 387, pp. 253–260.

Coyle, D. (2014) GDP: A brief but affectionate history. Princeton and Oxford: Princeton University Press.

Cubeddu L. M. et al. (2019) The External Balance Assessment Methodology: 2018 Update. IMF (Working Paper 2019/65).

Cummins, R. (2001) ‘The subjective well-being of people caring for a family member with a severe disability at home: A review’, Journal of Intellectual & Developmental Disability, 26(1), pp: 83–100.

Dabla-Norris, E. et al. (2015) Causes and Consequences of Income Inequality: A Global Perspective. International Monetary Fund.

Downloaded from: https://www.imf.org/external/pubs/ft/sdn/2015/ sdn1513.pdf (Date of download: 22 June 2023).

Daly, H. E., Cobb, J. B. and Cobb, C. W. (1989) For the Common Good: Redirecting the Economy Toward Community, the Environment, and a Sustainable Future. Boston: Beacon Press.

Daly, H. E. (2005) ‘Economics in a full world’, Scientific American, 293(3), pp. 100–107.

Daminger, A. (2019) ‘The Cognitive Dimension of Household Labor’, American Sociological Review, 84(4), pp. 609–633.

Daniels, A. (1987) ‘Invisible Work’, Social Problems, 34(5), pp. 403–415.

Dasgupta, P. (2021) The Economics of Biodiversity: The Dasgupta Review. London: HM Treasury. Downloaded from: https://assets. publishing.service.gov.uk/government/uploads/system/uploads/ attachment_data/file/962785/The_Economics_of_Biodiversity_The_ Dasgupta_Review_Full_Report.pdf (Date of download: 22 June 2023).

De Neve, J-E., Diener, E., Tay, L. and Xuereb, C. (2013) ‘The Objective Benefits of Subjective Well-Being’, in Helliwell, J., Layard, R., and Sachs, J.: World Happiness Report. New York: UN Sustainable Development Solutions Network, pp. 54–79.

Deák, V., Kajdi, L., Nemecskó, I. and Végső, T. (2022) ‘Az idő pénz: Fizetési módok társadalmi költségének felmérése’ [Time is Money: A survey of the social cost of payment instruments], Hitelintézeti Szemle / Financial and Economic Review, 21(2), pp. 5–36. Downloaded from: https://www.mnb.hu/letoltes/hsz-21-2-t1-deak-kajdi-nemecsko-vegso. pdf (Date of download: 22 June 2023).

Deák, V., Nemecskó, I., Végső, T. and Bódi-Schubert, A. (2020) ‘A koronavírus járvány hatása a magyarországi pénzforgalomra 2020-ban’

[Impact of the coronavirus pandemic on Hungary‘s payment turnover in 2020]. Budapest: Magyar Nemzeti Bank. Downloaded from: https:// www.mnb.hu/letoltes/a-koronavirus-jarvany-hatasa-a-magyarorszagipenzforgalomra-2020-ban.pdf (Date of download: 22 June 2023).

del Hoyo, J. L. D., Dorrucci, E., Heinz, F. F. and Muzikarova, S. (2017) Real convergence in the euro area: a long-term perspective. Frankfurt am Main European Central Bank (ECB Occasional Paper Series No. 203.).

Detken, C. et al. (2014) Operationalising the countercyclical capital buffer: indicator selection, threshold, identification and calibration. European Systemic Risk Board (Occasional Paper Series No. 5.).

Diener, E., Seligman, M. E. P. (2004) ‘Beyond money: Toward an economy of well-being’, Psychological Science in the Public Interest, 5(1), pp. 1–31.

Diener, E., Suh, E. M., Lucas, R. and Smith, H. (1999) ‘Subjective well-being: Three decades of progress’, Psychological Bulletin, 125(2), pp. 276–302.

Diener, E., Oishi, S. and Tay, L. (2018) ‘Advances in subjective well-being research’, Nature Human Behaviour, 2, pp. 253–260.

Dinda, S. (2004) ‘Environmental Kuznets curve hypothesis: a survey’, Ecological Economics, 49(4), pp. 431–455.

Drabancz, Á. and Berde, É. (2021) ‘Széllel szemben?: A magyar fertilitás jövőbeli kilátásai’ [Against the wind? – Future prospects of Hungarian fertility], Demográfia, 64 (4), pp. 317–338.

Dudás, G. and Boros, L. (2019) ‘A közösségi gazdaság (sharing economy) definiálásának dilemmái’ [Dilemmas of defining the sharing economy], Tér és Társadalom, 33(1), pp. 107–130.

Easterlin, R. A. (1974) ‘Does economic growth improve the human lot? Some empirical evidence’, in David, P. A., Reder, M. W. (eds.) Nations and households in economic growth: Essays in honour of Moses Abramowitz. New York: Academic Press, pp. 89–125.

Easterlin, R. A. (2005) ‘Feeding the illusion of growth and happiness: A reply to Hagerty & Veenhoven’, Social Indicators Research, 74(3), pp. 429–443.

Eichengreen, B. and Hausmann, R. (1999) ‘Exchange Rates and Financial Fragility’, in New Challenges for Monetary Policy. Denver: Federal Reserve Bank of Kansas City.

EIB (2021) EIB Investment Report 2020/2021: Building a smart and green Europe in the COVID-19 era. European Investment Bank.

ESRB (2014) Recommendation of the European Systemic Risk Board of 18 June 2014 on guidance for setting countercyclical buffer rates (ESRB/2014/1), Official Journal of the European Union, C 239/1, pp. 1–10. Downloaded from: https://www.esrb.europa.eu/pub/pdf/ recommendations/140630_ESRB_Recommendation.en.pdf (Date of download: 22 June 2023).

European Commission, Directorate-General for Mobility and Transport, Essen, H., Fiorello, D., El Beyrouty, K. et al. (2019) Handbook on the external costs of transport – Version 2019 – 1.1, Publications Office of the European Union. Downloaded from: file:///D:/Downloads/ handbook%20on%20the%20external%20costs%20of%20transportMI0320275ENN.pdf (Date of download: 22 June 2023).

Fleurbaey, M. (2009) ‘Beyond GDP: The Quest for a Measure of Social Welfare’, Journal of Economic Literature, 47(4), pp. 1029–1075.

Fleurbaey, M. and Blanchet, D. (2013) Beyond GDP: Measuring Welfare and Assessing Sustainability. Oxford: Oxford University Press.

Fromann, R. (2010) ‘Nemzetek boldogsága és annak forrása az Easterlin-paradoxon tükrében’ [Happiness of nations and its source in the light of the Easterlin Paradox], in Prazsák, G. (ed.) ‘Nemzetek Európában’ . Budapest: ELTE TÁTK Társadalmi Konfliktusok Kutatóközpont, pp. 95–120. Downloaded from: https://tatk.elte.hu/ content/nemzetek-europaban-online-kotet.t.3450 (Date of download: 22 June 2023).

Galán, J. E. (2019) Measuring credit-to-GDP gaps. The Hodrick-Prescott filter revisited. Banco de España Occasional Papers No. 1906.

Galán, J. E., Mencía, J. (2018) Empirical assessment of alternative structural methods for identifying cyclical systemic risk in Europe. Banco de España Working Paper No. 1825.

Galati, G., Hindrayanto, I., Koopman, S. J. and Vlekke, M. (2016) ‘Measuring financial cycles in a model-based analysis: Empirical evidence for the United States and the euro area’, Economics Letters, 145, pp. 83–87.

Gambetti, L. and Musso, A. (2017) ‘Loan supply shocks and the business cycle’, Journal of Applied Econometrics, 32(4), pp. 764–782.

Giorno, C., Richardson, P., Roseveare, D. and van den Noord, P. (1995) Estimating Potential Output, Output Gaps and Structural Budget Balances. OECD Economics Department Working Papers 152.

Global Footprint Network (2022a) Earth Overshoot Day. Downloaded from: www.overshootday.org (Date of download: 22 June 2023).

Global Footprint Network (2022b) National Footprint Accounts

Downloaded from: www.footprintnetwork.org (Date of download: 22 June 2023).

Görög, Á. (2015). ‘Hedonikus és eudaimónikus boldogság’ [Hedonic and eudaimonic happiness], Downloaded from: https://tacit.blog. hu/2015/11/14/hedonikus_es_eudaimonikus_boldogsag ( Date of download: 22 June 2023).

Hagerty, M. and Veenhoven, R. (2003) ‘Wealth and happiness revisited. Growing wealth of nations does go with greater happiness’, Social Indicators Research, 64(1), pp. 1–27.

Hamilton, J. D. (2018) ‘Why you should never use the Hodrick-Prescott filter’, Review of Economics and Statistics, 100(5), pp. 831–843.

Hanley, N. and Atkinson, G. (2003) ‘Economics and sustainable development: What have we lernt, and what do we still need to learn?’, in Berkhout, F., Leach M., and Scoones I. (eds) Negotiating Environmental Changes: New Perspectives from Social Science. Cheltenham: Edward Elgar.

Hardin, G. (1968). ‘The tragedy of the commons’, Science, 162(3859), pp. 1243–1248.

Hausmann, R. and Szalai, Á. (2021) ‘New Measurement System for Sustainability – MNB’s Sustainability Report and Index’, Prosperitas 8(2), 3.

Helliwell, J., Huang, H., Wang, S. and Norton, M. (2022) ‘Happiness, Benevolence and Trust During COVID–19 and Beyond’, in World Happiness Report 2022 . Downloaded from: https://tacit.blog. hu/2015/11/14/hedonikus_es_eudaimonikus_boldogsag ( Date of download: 22 June 2023).

Heys, R. (2022) Inclusive measures of growth – How ONS is moving beyond GDP. Office for National Statistics. Downloaded from: https:// blog.ons.gov.uk/2022/11/11/inclusive-measures-of-growth-how-ons-ismoving-beyond-gdp (Date of download: 22 June 2023).

Hiebert, P., Jaccard, I. and Schüler, Y. (2018) ‘Contrasting financial and business cycles: Stylized facts and candidate explanations’, Journal of Financial Stability, 38, pp. 72–80.

Hoekstra, R. (2019) Replacing GDP by 2030. Cambridge: Cambridge University Press.

Hosszú, Zs. and Lakos, G. (2021) ‘Early warning performance of univariate credit-to-GDP gaps’. MNB Occasional Papers No. 142.

Hristov, N., Hülsewig, O. and Wollmershäuser, T. (2012) ‘Loan supply shocks during the financial crisis: Evidence for the Euro area’, Journal of International Money and Finance, 31(3), pp. 569–592.

IMD (2022) IMD World Competitiveness Yearbook 2022. Lausanne: Switzerland.

Inglehart, R. and Welzel, C. (2005) Modernization, Cultural Change and Democracy: The Human Development Sequence. New York: Cambridge University Press.

Innovációs és Technológiai Minisztérium (2020) ‘Nemzeti Energia- és Klímaterv’ [National Energy and Climate Plan]. Downloaded from: https://energy.ec.europa.eu/system/files/2020-01/hu_final_necp_main_ hu_0.pdf (Date of download: 22 June 2023).

Jordà, Ò., Schularick, M. and Taylor, A. M. (2016) ‘Macrofinancial history and the new business cycle facts’, NBER Macroeconomics Annual, 31, pp. 213–263.

Kahneman, D., Kruger, A. B., Schkade, D. A., Schwarz, N. and Stone, A. A. (2005) ‘A Survey method for Characterizing Daily Life Experience: The Day Reconstruction Method’, Science, 306(5702), pp. 1776–1180.

Kim, J.-H. (2017) ‘Social Media Use and Well-Being’ in Maddux, J. E. (ed.) Subjective Well-Being and Life Satisfaction. New York: Routledge, pp. 253–271.

Komáromi, A. (2008) ‘A külső forrásbevonás szerkezete: Kell-e félnünk az adóssággal való finanszírozástól?’ [The structure of external financing: Is there a reason to worry about financing through debt?], MNB Szemle / MNB Review, April 2008, pp. 14–23.

Kopp, M. et al. (2004) ‘Vallásosság és egészség az átalakuló társadalomban’ [Religion and health in a changing society], Mentálhigiéné és Pszichoszomatika, 5(2), pp. 103–125.

Kowalski, S. and Veit, W. (2020) Sustainable Society Index. Summary Report 2018. Technology Arts Sciences TH Köln. Downloaded from: https://ssi.wi.th-koeln.de/documents/summary-ssi-2018.pdf (Date of download: 22 June 2023).

Kulig, A., Kolfoort, H. and Hoesktra, R. (2010) ‘The case for the hybrid capital approach for the measurment of the welfare and sustainability’, Ecological Indicators, 10, pp. 118–128.

Lang, J. H. and Welz, P. (2018) Semi-structural credit gap estimation. ECB Working Paper No. 2194.

Lang, J. H., Izzo, C., Fahr, S. and Ruzicka, J. (2019): Anticipating the bust: A new cyclical systemic risk indicator to assess the likelihood and severity of financial crises. ECB Occasional Paper No. 219.

Larson, R. and Csíkszentmihályi, M. (2014) ’The Experience Sampling Method’, in Csíkszentmihályi, M. Flow and the Foundations of Positive Psychology. Dordrecht: Springer.

Liu, H., Khan, I., Zakari, A. and Alharthi, M. (2022) ‘Roles of trilemma in the world energy sector and transition towards sustainable energy: A study of economic growth and the environment’, Energy Policy, 170(113238).

Lucas, R. et al. (2004) ‘Unemployment alters the set point for life satisfaction’, Psychological Science, 15(1), pp. 8–13.

Magyar Nemzeti Bank (2018) ‘Növekedési jelentés 2018’ [Growth Report 2018]. Downloaded from: https://www.mnb.hu/letoltes/novekedesijelentes-2018-digitalis.pdf (Date of download: 22 June 2023).

Magyar Nemzeti Bank (2021) ‘Fenntarthatósági jelentés 2021’ [Sustainability Report 2021]. Downloaded from: https://www.mnb. hu/letoltes/fenntarthatosagi-jelentes-2021-hun-0518.pdf ( Date of download: 22 June 2023).

Magyar Nemzeti Bank (2022) ‘Termelékenységi jelentés’ [Productivity Report]. Downloaded from: https://www.mnb.hu/letoltes/ termelekenysegi-jelentes-2022-julius.pdf (Date of download: 22 June 2023).

Magyar Nemzeti Bank (2023) ‘Lakáspiaci jelentés’ [Housing Market Report 2021]. Downloaded from: https://www.mnb.hu/kiadvanyok/ jelentesek/lakaspiaci-jelentes/lakaspiaci-jelentes-2023-majus (Date of download: 22 June 2023).

Matolcsy, Gy. (2019) ‘A sikeres válságkezelés a 12 gazdasági fordulat tükrében’ [Successful crisis management in the light of the twelve economic turnarounds], Polgári Szemle / Civic Review Journal of Economic and Social Sciences, 15(1–3): pp. 15–45. Downloaded from:

https://polgariszemle.hu/aktualis-szam/163-gazdasagi-es-penzugyiinnovaciok/1017-a-sikeres-valsagkezeles-a-12-gazdasagi-fordulattukreben (Date of download: 22 June 2023).

Matolcsy, Gy. (2020) ‘Egyensúly és növekedés, 2010–2019: Sereghajtóból újra éllovas’ [Balance and growth, 2010–2019: From the bottom of the league to the top again]. 2nd edn. Budapest: Magyar Nemzeti Bank.

Matolcsy, Gy. (2022) ‘A gazdasági, a társadalmi, a pénzügyi és a környezeti fenntarthatósági szempontok megjelenése a Magyar Nemzeti Bank gyakorlatában’ [The Appearance of Economic, Social, Financial and Environmental Sustainability. Aspects in the Practices of the National Bank of Hungary], Pénzügyi Szemle / Public Finance Quarterly, 3, pp. 319–337.

Mazzucato, M. (2018) The Value of Everything: Making and Taking the Global Economy. London: Penguin Books.

McKeown, L. (2022) Measuring Progress: GDP & Beyond. Office of National Statistics. Downloaded from: https:/blog.ons.gov. uk/2022/08/12/measuring-progress-gdp-beyond/ (Date of download: 22 June 2023).

McKinsey & Co. (2021) Getting tangible about intangibles: The future of growth and productivity? June 16, 2021. Discussion paper. Downloaded from: https://www.meckinsey.com/capailities/growth-marketing-andsales/our-insights/getting-tangible-about-intangibles-the-future-ofgrowht-and-productivity (Date of download: 22 June 2023).

Meadows, D. H., Meadows, D. L., Randers, J. and Behrens, W. W. (1972) The Limits to Growth. New York: Universe Books. Downloaded from: http://www.donellameadows.org/wp-content/userfiles/Limits-toGrowth-digital-scan-version.pdf (Date of download: 22 June 2023)

Mukherjee, P. and Ahuja, K. (2018) A Comparative Assessment of Sustainable Economic Development among the G20 Countries. 7th International RAIS Conference on Social Sciences, pp. 72–86.

Nakamura, J. and Csíkszentmihályi, M. (2014) ‘The Concept of Flow’, in Csíkszentmihályi, M. Flow and the Foundations of Positive Psychology. Dordrecht: Springer.

Naszódi, A. and Mendonca, F. (2021) ‘A new method for identifying the role of marital preferences at shaping marriage patterns’, Journal of Demographic Economics, 89(1), pp. 1–27.

Naszódi, A. and Mendonca, F. (2022) ‘Changing educational homogamy: Shifting preferences or evolving educational distribution?’, Cambridge University Press [online publication] (Journal of Demographic Economics).

Naszódi, A. and Mendonca, F. (2023) A new method for identifying what Cupid’s invisible hand is doing. Is it spreading color blindness while turning us more “picky” about spousal education?

National Council for Sustainable Development [NFFT] (2020) ‘Útmutató a fenntartható jövőhöz’ [Guidelines for a Sustainable Future]. Downloaded from: https://www.nfft.hu/dokumentumok (Date of download: 22 June 2023).

NCSD (2020) ‘Útmutató a fenntartható jövőhöz’ [Guidelines for a Sustainable Future]. National Council for Sustainable Development. Downloaded from: https://www.nfft.hu/dokumentumok (Date of download: 22 June 2023).

Nordhaus, W. D. and Tobin, J. (1972) ‘Is Growth Obsolete?’, in Nordhaus, W. D. and Tobin, J. (eds.) Economic Research: Retrospect and Prospect, Volume 5, Economic Growth. NBER. Downloaded from:

https://www.nber.org/system/files/chapters/c7620/c7620.pdf (Date of download: 22 June 2023).

OECD (2010) The High Cost of Low Educational Performance. The Long-run Economic Impact of Improving PISA Outcomes. Downloaded from: https://www.oecd.org/pisa/44417824.pdf (Date of download: 22 June 2023).

OECD (2013) OECD Guidelines on Measuring Subjective Well-being. Paris: OECD Publishing.

OECD (2018) Beyond GDP: Measuring what counts for economic and social performance. Paris: OECD Publishing.

OECD (2019) PISA 2018 Results: Where all students can succeed Volume II. Downloaded from: https://www.oecd.org/pisa/publications/ pisa-2018-results-volume-ii-b5fd1b8f-en.htm (Date of download: 22 June 2023).

OECD (2020) How’s Life? 2020: Measuring Well-being. OECD Biannual Report.

Ostry, J. D., Berg, A. and Tsangarides, C. G. (2014). Redistribution, Inequality, and Growth. International Monetary Fund. Downloaded from: https://www.imf.org/external/pubs/ft/sdn/2014/sdn1402.pdf (Date of download: 22 June 2023).

Palotai, D. and Virág, B. (2016) ‘Versenyképesség és növekedés’ [Competitiveness and Growth]. Budapest: Magyar Nemzeti Bank.

Pew Research Center (2018) The Age Gap in Religion Around the World. Downloaded from: https://www.pewresearch.org/religion/2018/06/13/ the-age-gap-in-religion-around-the-world/ (Date of download: 22 June 2023).

Roth, F. (2022) ‘Social Capital, Trust and Economic Growth’, in Intangible Capital and Growth. Springer, pp. 167–185.

Rünstler, G. and Vlekke, M. (2018) ‘Business, housing, and credit cycles’, Journal of Applied Econometrics, 33(2), pp. 212–226.

Sachs, J., Lafortune, G., Kroll, C., Fuller, G. and Woelm, F. (2022) Sustainable Development Report 2022: From Crisis to Sustainable Development: the SDGs as Roadmap to 2030 and Beyond. Cambridge: Cambridge University Press.

Sahay R. et al. (2015) Rethinking Financial Deepening: Stability and Growth in Emerging Markets. International Monetary Fund.

Downloaded from: https://www.imf.org/external/pubs/ft/sdn/2015/ sdn1508.pdf (Date of download: 22 June 2023)

Samuelson, P. A. and Nordhaus, W. D. (1987) Közgazdaságtan [Economics], I. Budapest: Közgazdasági és Jogi Könyvkiadó.

Schimmack, U. (2008) ‘The structure of subjective well-being’, in Eid, M. and Larsen, R.J. The science of subjective well-being. New York: The Guilford Press, pp. 97–123.

Schneider, F. (2022) ‘New COVID-related results for estimating the shadow economy in the global economy in 2021 and 2022’, International Economics and Economic Policy, 19, pp. 299–313.

Downloaded from: https://link.springer.com/article/10.1007/s10368022-00537-6 (Date of download: 22 June 2023).

Schoenaker, N., Hoekstra, R. and Smits J. P. (2015) ‘Comparison of measurment systems for sustainable development at the national level’, Sustainable Development, 23, pp. 285–300.

Sharma, R. (2020) The 10 Rules of Successful Nations. New York: W.W. Norton & Company.

Sen, A., Fitoussi, J.P. and Stiglitz, J. E. (2010) Mismeasuring our lives. New York, London: The New Press.

Solow, R. (1987) We’d better watch out. New York: New York Times Book Review.

Stiglitz, J. E. (2013) ‘In No One We Trust’, The New York Times. Downloaded from: http://archive.nytime.com/opinionator.blogs. nytimes.com/2013/12/21/in-no-one-we-trust/ (Date of download: 22 June 2023).

Stiglitz, J. E., Sen, A. and Fitoussi, J-P. (2009) Report by the Commission on the Measurment of Economic Performance and Social Progress. Downloaded from: https://ec.europa.eu/eurostat/ documents/8131721/8131772/Stiglitz-Sen-Fitoussi-Commission-report. pdf (Date of download: 22 June 2023).

Stiglitz, J. E., Fitoussi, J. and Durand M. (2018) Beyond GDP: Measuring What Counts for Economic and Social Performance. Paris: OECD Publishing.

Szabó, E. (2006) ‘A környezetterhelés és a gazdasági fejlődés szétválása’ [Decoupling of environmental pressures and economic development], Területi Statisztika 9, 46(4), pp. 393–410.

Székely, B. (2020) Funding for lending schemes should prioritize SME lending. MNB Occasional Paper No. 138.

Szlávik, J. (ed.) (2007) ‘Környezetgazdaságtan’ [Environmental Economics]. Budapest: Typotex Kiadó.

Szoboszlai, M. (2023) ‘Meg kell előzni a digitális dualitás kialakulását’ [We must prevent the emergence of digital duality]. Budapest: Magyar Nemzeti Bank. Downloaded from: https://www.mnb.hu/kutatas/ pareto-muhely/osszes-elemzes/meg-kell-elozni-a-digitalis-dualitaskialakulasat (Date of download: 22 June 2023).

Tamási, Á. (1934) ‘Ábel Amerikában’ [Abel in America]. Budapest: Ifjúsági Könyvkiadó.

Tamási, B. and Világi, B. (2011) Identification of credit supply shocks in a Bayesian SVAR model of the Hungarian Economy. MNB Working Paper No. 2011/7.

Tay, L., Herian, M. N. and Diener, E. (2014) ‘Detrimental Effects of Corruption and Subjective Well-Being: Whether, How, and When’, Social Psychological and Personality Science, 5(7), pp. 751–759.

TH Köln (2022a) SSI historical data. Downloaded from: https://ssi.wi.thkoeln.de/historical_data.html (Date of download: 22 June 2023).

TH Köln (2022b) SSI latest data, Data Set 2018, Country charts and tables. Downloaded from: https://ssi.wi.th-koeln.de/latest_data.html (Date of download: 22 June 2023).

Tölö, E., Laakkonen, H. and Kalatie, S. (2018) ‘Evaluating indicators for use in setting the countercyclical capital buffer’, International Journal of Central Banking, 14(2), pp. 51–112.

Tűű, L.-né (1997) ‘A szatellit-számlák’ [The Satellite Accounts], Statisztikai Szemle / Hungarian Statistical Review, 75(4–5), pp. 434–436.

UNECE-OECD-EUROSTAT (2008) Measuring Sustainable Development: Report of the joint UNECE/OECD/Eurostat working

group in statistics for sustainable development. New York, Geneva: United Nations.

United Nations (1987) Our Common Future. UN General Assembly document A/42/427. World Commission on Environment and Development, United Nations.

United Nations (2015) Transforming our world: the 2030 Agenda for Sustainable Development, UN General Assembly document A/RES/70/1, Downloaded from: https://www.refworld.org/ docid/57b6e3e44.html (Date of download: 13 July 2023).

United Nations (2022). The Sustainable Development Goals Report. New York: United Nations. New York: United Nations. Downloaded from: https://unstats.un.org/sdgs/report/2022/The-SustainableDevelopment-Goals-Report-2022.pdf (Date of download: 22 June 2023).

Várnai, T. (2022) ‘A tőke és a gazdasági növekedés kapcsolata: a mennyiségi szemléletből a minőség felé’ [Relationship between capital and economic growth: shifting the focus from quantity to quality], in Baksay, G., Matolcsy, Gy. and Virág, B. (ed.) ‘Új Közgazdaságtan a Fenntarthatóságért’ [New economics for sustainability]. Budapest: Magyar Nemzeti Bank, pp. 203–229. Downloaded from: https://www.mnb.hu/web/sw/static/file/az-ujfenntarthato-kozgazdasagtan-hun.pdf (Date of download: 22 June 2023).

Várnai, T. (2023) ‘Résekben naggyá nőni: a kreatív ipar súlya Magyarországon’ [Growing big in market niches: weight of creative industry in Hungary]. Budapest: Magyar Nemzeti Bank. Downloaded from: https://www.mnb.hu/kutatas/pareto-muhely/osszes-elemzes/ resekben-naggya-noni-a-kreativ-ipar-sulya-magyarorszagon-1 (Date of download: 22 June 2023).

Virág, B. (ed.) (2019) ‘A jövő fenntartható közgazdaságtana’ [The sustainable economics of the future]. Budapest: Magyar Nemzeti Bank.Downloaded from: https://www.mnb.hu/kiadvanyok/mnbszakkonyvsorozat/a-jovo-fenntarthato-kozgazdasagtana (Date of download: 22 June 2023).

Wackernagel, M. and Rees, W. E. (1996) Our ecological footprint: reducing human impact on the earth. Gabriola Island, BC; Philadelphia: New Society Publishers.

Wang, B. and Chen T. (2022) ‘Social progress beyond GDP: A principal component analysis (PCA) of GDP and twelve alternative indicators’, Sustainability, 14(6430).

WEF (2018) The Inclusive Development Index 2018. Summary and Data Highlights – World Economic Forum. Downloaded from: https://www3. weforum.org (Date of download: 22 June 2023).

Wendling, Z. A. et al. (2018) Environmental Performance Index. New Haven: Yale Center for Environmental Law & Policy. Downloaded from: https://epi.yale.edu/ https://epi.yale.edu/downloads/ epi2018reportv06191901.pdf (Date of download: 22 June 2023).

Wolf, M. J. et al. (2022). 2022 Environmental Performance Index. New Haven: Yale Center for Environmental Law & Policy, p. 206. Downloaded from: https://epi.yale.edu https://epi.yale.edu/downloads/ epi2022report06062022.pdf (Date of download: 22 June 2023).

Wooden, M. et al. (2009) ‘Working Time Mismatch and Subjective Wellbeing’, British Journal of Industrial Relations, 47, pp. 147–179.

World Values Survey [WVS] (2022) Findings and Insights –Inglehart-Welzel Cultural Map. Downloaded from: https://www. worldvaluessurvey.org (Date of download: 22 June 2023).

Zorkóciová, O., Palusková, H. and Danisková, S. K. (2021) ‘Regression analysis of the relationship between selected variables of economic growth and sustainable development’, Ad Alta: Journal of Interdisciplinary Research, 11(2).

Recommended reading

Basel Committee on Banking Supervision (2010) Guidance for national authorities operating the countercyclical capital buffer. Basel: Bank for International Settlements.

Costanza, R., Hart, M., Posner, S. and Talberth, J. (2009) Beyond GDP: The Need for New Measures of Progress. Boston: Pardee Center for the Study of the Longer-Range Future (Pardee Paper No. 4).

Dickinson, E. (2011) ‘GDP: A Brief History’, Foreign Policy, 2011. január 3. Downloaded from: https://foreignpolicy.com/2011/01/03/gdp-a-briefhistory/ (Date of download: 22 June 2023).

Diener, E., Sandvik, E., Seidlitz, L. and Diener, M. (1993) ‘The relationship between income and subjective well-being: relative or absolute?’, Social Indicators Research, 28(3), pp. 195–223.

Diener, E., Suh, E. and Oishi, S. (1997) ‘Recent Findings on Subjective Well-Being’, Indian Journal of Clinical Psychology, 24(1), pp. 25–41.

Easterlin, R. A. (1995) ‘Will raising the income of all increase the happiness of all?’, Journal of Economic Behavior and Organization, 27(1), pp. 35–47.

Eurostat (2023) ‘Population projections (EUROPOP 2023)’. Downloaded from: https://ec.europa.eu/eurostat/data/database (Date of download: 22 June 2023).

European Commission, Directorate-General for Mobility and Transport, Essen, H., Fiorello, D., El Beyrouty, K., et al. (2020)  Handbook on the external costs of transport : version 2019 – 1.1. Publications Office.

European Systemic Risk Board [ESRB] (2014) ‘Recommendation of the European Systemic Risk Board of 18 June 2014 on guidance for setting countercyclical buffer rates (ESRB/2014/1)’, Official Journal of the European Union, C 239/1, pp. 1–10.

Freixas, X., Laeven, L. and Peydró, J.-L. (2015) Systemic risk, crises, and macroprudential regulation. Cambridge: MIT Press.

Gaspar, V., Medas, P. and Perrelli, R. (2021) ‘Global Debt Reaches a Record $226 Trillion’, IMF blog. Downloaded from: https://www.imf. org/en/Blogs/Articles/2021/12/15/blog-global-debt-reaches-a-record226-trillion (Date of download: 22 June 2023).

Helliwell, J. F., Bonikowska, A. and Shiplett, H. (2016) Migration as a Test of the Happiness Set Point Hypothesis: Evidence from Immigration to Canada. NBER Working Paper 22601.

Inglehart, R. and Klingemann, H-D. (2000) ‘Genes, culture, democracy and happiness’, in Diener, E. and Suh, E. (eds.): Subjective well-being across cultures. Cambridge: MIT Press, pp. 165–183.

Központi Statisztikai Hivatal [KSH] (2022) ‘A fenntartható fejlődés indikátorai Magyarországon [Indicators of sustainable development in Hungary], 2022. Downloaded from: https://www.ksh.hu/s/kiadvanyok/ fenntarthato-fejlodes-indikatorai-2022/fenntarthato_fejlodes_ indikatorai_2022.pdf (Date of download: 22 June 2023).

Kubiszewski I. et al. (2013) ‘Beyond GDP: Measuring and achieving global genuine progress’, Ecological Economics, 93, pp. 57–68.

‘Mi a különbség a jólét és a jóllét között? [What is the difference between welfare and wellbeing?], OzoneTV, 2020. 06. 25. Downloaded from: https://ozonetv.hu/cikkek/2020/06/25/mi-a-kulonbseg-a-jolet-esa-jollet-kozott (Date of download: 22 June 2023).

National Council for Sustainable Development [NFFT] (2013) ‘Nemzeti fenntartható fejlődési keretstratégia’ [National Framework Strategy on Sustainable Development]. Downloaded from: https://www.nfft.hu/ nffs (Date of download: 22 June 2023).

NCSD (2013) ‘Nemzeti fenntartható fejlődési keretstratégia’ [National Framework Strategy on Sustainable Development]. National Council for Sustainable Development. Downloaded from: https://www.nfft.hu/

nffs (Date of download: 22 June 2023) Oishi, S., Graham, J. and Galinha, J.C. (2013) ‘Concepts of Happiness Across Time and Cultures’, Personality and Social Psychology Bulletin, 39(5), pp. 559–577.

Szentmihályi, Sz. and Világi, B. (2015) ‘A Phillips-görbe: elmélettörténet és empirikus összefüggések’ [The Phillips curve – history of thought and empirical evidence], Hitelintézeti Szemle / Financial and Economic Review, 14(4), pp. 5–28.

United Nations [UN] (2015) Transforming our World: The 2030 Agenda for Sustainable Development. Downloaded from: https:// ensz.kormany.hu/download/7/06/22000/Vil%C3%A1gunk%20 %C3%A1talak%C3%ADt%C3%A1sa%20Fenntarthat%C3%B3%20 Fejl%C5%91d%C3%A9si%20Keretrendszer%202030.pdf ( Date of download: 22 June 2023)

United Nations (2022) Updating the System of National Accounts (SNA). Department of Economic and Social Affairs, Statistics Division, United Nations.Downloaded from: https://unstats.un.org/unsd/ nationalaccount/snaUpdate.asp (Date of download: 22 June 2023).

United Nations (2022) SDG Indicators: Global indicator framework for the Sustainable Development Goals and targets of the 2030 Agenda for Sustainable Development. Department of Economic and Social Affairs, Statistics Division, United Nations. Downloaded from: https:// unstats.un.org/sdgs/indicators/indicators-list/ (Date of download: 22 June 2023).

United Nations (2022) The 17 goals. Department of Economic and Social Affairs, Sustainable Development, United Nations. Downloaded from: https://sdgs.un.org/goals (Date of download: 22 June 2023).

United Nations Environment Programme, International Union for Conservation of Nature and World Wide Fund For Nature [IUCN-UNEPWWF] (1991) ‘Caring for the Earth: A Strategy for Sustainable Living. Gland. Downloaded from: https://wedocs.unep.org/20.500.11822/30889 (Date of download: 22 June 2023).

Waas, T., Hugé, J., Block, T., Wright, T., Benitez-Capistros, F. and Verbruggen, A. (2014) ‘Sustainability assessment and indicators: Tools in a decision-making strategy for sustainable development’, Sustainability, 6(9), pp. 5512–5534.

Waterman, A. S. (1993) ‘Two Conceptions of Happiness: Contrasts of Personal Expressiveness (Eudaimonia) and Hedonic Enjoyment’, Journal of Personality and Social Psychology, 64 (4), pp. 678–691.

GLOSSARY

At risk of poverty or social exclusion, AROPE: the proportion of people in the population experiencing at least one of the following: relative income poverty or severe material and social deprivation or very low work intensity. AROPE is the main indicator for monitoring the EU’s target on poverty and social exclusion.

Balance of payments: balance of payments statistics present transactions between residents and non-residents. Real economy transactions are recorded in the current and capital account, while financial transactions are recorded in the financial account. The balance of payments is statistics on an accrual basis, so transactions are always recorded at the change of ownership.

Better Life Index, BLI: an OECD indicator that includes data on quality of life in 41 developed countries across 11 dimensions, such as housing, jobs, income, satisfaction, safety and environment.

Biocapacity: the natural resources available in a given area, the sum of all biologically productive areas (both terrestrial and aquatic) that are needed to meet human needs and to reproduce.

Capital account: includes asset movements related to unreciprocated and non-produced, non-financial assets between residents and nonresidents.

Circular economy: the circular economy is about extending the life of a product, its life cycle, as much as possible, rather than consuming it once.

Climate Change Performance Index, CCPI: the assessment uses 14 indicators in four categories (GHG emissions, renewable energy, energy use and climate policy) to compare the climate ambition

and progress of the countries under review in order to increase the transparency of international climate policy.

Creative destruction: a concept introduced by Joseph Schumpeter, whereby new innovations and solutions take the place of older products and services in the market.

Credit gap: an indicator measuring the current state of cyclical fluctuations in the aggregate loan portfolio of the non-financial private sector, i.e., households and non-financial corporations. It is also a measure of the financial cycle. The credit gap is usually quantified by the absolute (i.e. percentage point) deviation of the credit-to-GDP ratio from its trend value. These credit gap indicators differ in the method used to estimate unobservable and time-varying trend values. Significantly positive credit gaps are considered to be a moderately reliable early predictors of financial crises occurring in the medium term, i.e., within 1–5 years. They also have a prominent place in the macro-prudential policy monitoring system.

Current account: the current account includes the external trade (goods and services) balance, the income balance and unrequited current transfers among payments.

Data: information that results from the observation and analysis of a certain phenomenon; the information elements of these phenomena are recorded, organised and stored in digital form, thus providing economic benefits in the production process.

Domestic value added content: the share of domestic value added in output indicates the value added per unit of gross output within a country’s borders.

Easterlin Paradox: Empirical studies by Richard Easterlin (1974) show that as material welfare increases, happiness increases for a while, but declines beyond a certain “welfare tipping point”. The resolution

of this is that, beyond the level of elementary welfare, well-being only increases with “hedonic” (pleasure-induced) happiness, while the “eudaimonic” (self-actualizing) happiness identified by Easterlin stagnates and then declines.

Ecological balance: the difference between biocapacity and ecological footprint. It shows how much of the natural resources available in a territorial unit (biocapacity) is used (ecological footprint). If the ecological balance is negative, it indicates overconsumption of available resources.

Ecological Footprint, EF: expresses the amount of fertile land a society needs to sustain itself and absorb the waste produced, given the level of technological development, taking into account the ecological carrying capacity of the land. First, we calculate the consumption of a person in different product categories, and then we assess the amount of land needed to produce the consumed products. The quotient of the two indicators indicates the amount of land “expropriated” in the given product category. Finally, we aggregate the data for the different product categories and multiply this by the number of inhabitants to obtain the ecological footprint of the given municipality or region.

Ecological sustainability: for natural resources, a sustainable state is when the environmental impacts of economic activities are within the carrying capacity of the Earth’s ecosystem (‘safe operating space’).

Economic complexity index: a team of researchers at Harvard University uses the volume and structure of exports to estimate a country’s knowledge capital and rank 133 countries around the world. The scoring system reflects the economic strength of countries through export diversification. A more complex export structure could lead to higher economic growth, according to the index.

Ecosystem services: all the tangible and intangible goods and services that result from the natural or human-induced functioning of ecosystems and contribute to the maintenance and enhancement of the well-being of society and individuals within it. Such services include clean water, food, clean air, soil formation, or even the aesthetic value of an area.

Employment gap (by education level): the difference between the employment rate of the highly educated (i.e. those with at least a college degree) and the low educated (i.e. those without a secondary school diploma).

Employment-based labour productivity: the most commonly used indicator in productivity calculations is work (labour) productivity, defined either as value added per person employed or per hour worked. Employment-based labour productivity refers to the value added per employee.

Energy dependency rate: shows the share of imported energy in a country’s energy consumption. Its measure is the net energy import ratio, which is the difference between the energy imported and exported in a given year (net imports) divided by the energy available (concluded from net changes in inventories).

Energy intensity: energy use per unit of economic output. The higher it is, the more energy it takes to keep the economy running.

Energy mix: the breakdown of a country’s energy use by energy source.

Energy trilemma: triple challenge for energy policy. A concept referring to the difficulty and consequential policy challenges of simultaneously achieving (i) energy dependency reduction, (ii) energy affordability and (iii) an environmentally aware energy supply.

Environmental Performance Index, EPI: an effective tool for measuring the UN’s Sustainable Development Goals (SDGs), as it calculates an aggregate index between 0 and 100 from 11 core indicators of different weights in three target areas (reducing the impact of the environment on human health, improving the viability of ecosystems and reducing climate change), calculating the value of each indicator of a given country from the deviation from the targets.

Environmental tax: a tax levied specifically on polluting activities (production or consumption). Green or environmental taxes are economic policy instruments that can be used to achieve a more favourable overall social supply-demand balance than at present, thereby reducing the polluting activities of economic operators. Revenue from green taxes is still a fraction of gross output and total tax revenue in developed countries.

External debt: debt-type liabilities (loans, bonds) of the whole economy (private sector and treasury) to the rest of the world.

Fertility rate: one of the most important demographic indicators. The fertility rate expresses how many children a woman will give birth to in her lifetime at the age-specific birth rate for a given year.

Financial crisis: a disturbance in the functioning of the financial system that is substantially damaging to the economy as a whole. In other words, it is a sudden and rapid realisation of the contraction phase in the financial cycle. Its main features are a dramatic deterioration in expectations about the future, a sharp fall in credit supply, a drop in risk appetite, a surge in demand for liquid financial assets and a rapid depreciation of other financial assets. This phenomenon on a smaller scale is called a financial stress situation.

Financial cycle: a common, periodic and not necessarily regular co-movement of the main economic indicators of the financial system. In the expansion phase, economic activity in the financial

system (lending, insurance, securities trading, payments, etc.) picks up, expectations about the future become optimistic, risk appetite increases and the value of financial assets rises. In the contraction phase, all this is reversed. The cyclical fluctuations of the financial system are harmful beyond a certain level, because they limit the financial system in performing its basic functions: the processing of payments, the allocation of financial resources, and the sharing and diversification of risks. A full financial cycle typically lasts at least 10 and up to 30 years.

Financial development and financial deepening: financial development and its “deepening” are typically measured by the level and change in a country’s credit-to-GDP ratio. Comparing the variables, it can be observed that economically developed countries are also financially developed and that the development of the financial mediating system precedes and has a positive impact on the development of the real economy.

Financial stability: the state of the financial system in which it can smoothly perform its basic functions (processing payments, allocating financial resources, sharing economic risks) while keeping the chances of a financial crisis occurring to a minimum.

Financial system: the subsystem of the economy that creates money, makes it possible to pay with it, and trades it between different points in time and between different possible outcomes in the uncertain future. Typical examples of the latter are the coordination of savings and borrowing, and the sharing of risks through insurance schemes. The most important parts of the financial system are financial intermediary institutions (e.g., banks, insurance companies, pension funds, investment funds), financial markets (e.g., money markets, foreign exchange markets, capital markets) and institutions that provide the infrastructure for and/or supervise and regulate the former (e.g., central banks, stock exchanges, clearing houses).

Foreign Direct Investment, FDI: foreign investments where an investor resident in one country has a lasting interest in a company resident in another country. Typically, investments with a foreign ownership stake of 10 per cent or more are included.

Genuine Progress Indicator, GPI: an indicator of social and environmental welfare with a total of 26 indicators, where economic, social and environmental costs and benefits are subtracted and added, taking into account the depletion of natural and social capital.

Gini-index: a common measure of income and wealth inequality. Its value lies between 0 and 1 (or 0 and 100 percent), where 0 means perfectly uniform distribution, i.e., complete equality, and 1 means complete inequality.

Global hectares: a standard unit of account for ecological footprint and biocapacity. Different land types (e.g., forest, meadow, arable land) have different productivity, and the productivity-weighted average of these areas is the global hectare.

Global Liveability Index, GLI: the Global Liveability Index, developed by the Economic Intelligence Unit, ranks 173 major cities around the world on the basis of 30 indicators representing safety, health, culture and environmental quality, education and infrastructure.

Greenhouse gas, GHG: the natural and anthropogenic constituents of the atmosphere that partially absorb the long-wave radiation emitted by the Earth’s surface, a process known as the greenhouse effect. The greenhouse effect is beneficial to some extent; without it the average temperature of our planet near the surface would be -18°C instead of +15°C, and life on the planet would probably be extinct. The most important greenhouse gases are water vapour and carbon dioxide, but also methane, nitrous oxide, tropospheric ozone and other gases in lower concentrations.

Gross National Income, GNI: an indicator derived from GDP, by taking into account primary income between residents and non-residents, i.e. compensation of employees, capital and interest income, and EU-related primary transfers. It measures the income generated by domestic operators.

Happiness: there is no generally accepted definition, it is understood differently in various cultures and times. In scientific works, it is sometimes used as a synonym for subjective well-being or as the net balance of positive and negative emotions. In its everyday meaning, it is a concept closely related to good luck in many countries, but in the modern American definition, for example, this meaning is completely absent.

Happy Planet Index, HPI: a United Nations indicator based on a Gallup survey, which assesses happiness in consideration of the least burden on the Earth’s ecosystem, in terms of life expectancy, welfare, satisfaction and ecological footprint.

Healthy life expectancy: the number of years an average person can expect to live at a given age without any limitation due to health.

Hedonic treadmill theory: a biological-psychological theory that the body and mind strive for a state of equilibrium. In terms of well-being, satisfaction with life returns to a stable baseline even after emotional outbursts.

Human capital: among the factors of production, capital can be basically divided into two parts: physical and human capital. In a broader sense, human capital is the knowledge embodied in the individual, the skills, competences and attributes that facilitate the creation of personal, social and economic welfare. In a narrower sense, human capital stock is the stock of knowledge, competences and other economically relevant attributes that the working-age population possesses.

Human Development Index, HDI: the most widely used, easy-tocalculate alternative UN indicator of well-being, ranking 189 countries, but only on the basis of their health, education and welfare (income).

Inclusive Development Index, IDI: a World Economic Forum indicator that looks at how broad sections of society are affected by indicators of economic development such as income, life expectancy, health, welfare and sustainability.

Inclusive society: a system of socio-economic institutions that provides opportunities and services for members of society in a wide scale, without discrimination and guaranteeing equal opportunities as far as possible, which help everyone to make the most of their talents and working abilities for the benefit of others.

Index of Sustainable Economic Welfare, ISEW: one of the most comprehensive sustainable measures of economic welfare, calculated by adjusting the MEW (measure of economic welfare), which starts from personal consumption but also takes into account the welfare effects of changes in consumption inequalities by adding or subtracting 22 indicators of welfare (economic, social and environmental damages and benefits), while accounting for the depletion of natural and social capital.

Inglehart’s axis of values: in the correlation matrix showing the existence of the Easterlin Paradox on a regional basis, the negative range of the X-axis is the subsistence value and the positive range is the self-fulfilment value. Traditional global values are in the negative range of the Y-axis and modern global values in the positive range. A diagonal axis of values divides the matrix in the negative range for scarcity and in the positive range for abundance; the countries under study are shown as regional clusters.

Intangible investment, intangible assets: investment in intangible activities (e.g., knowledge, skills development, reputation building)

and the intangible value created by these investments (e.g., higher education/qualification level, more positive market perceptions, stronger trust levels).

Intangible investments: investments in computer software and databases, research and development, mineral exploration, licensing and know-how.

Investment rate: the ratio of gross fixed capital formation to gross domestic product (GDP).

Life Quality Index, LQI: the Economist Intelligence Unit’s Quality of Life indicator, calculated from 11 composite measures of healthy, safe and happy living conditions.

Lifelong learning: refers to learning activities typically in adulthood, pursued in parallel with work, not within the in-school education and training at young age. For statistical purposes, a lifelong learner is defined as someone who received any kind of education or training (formal or non-formal) in the four weeks preceding the survey.

Loan-to-deposit ratio: the loan-to-deposit ratio compares the total amount of loans granted by banks to their customers with the total amount of deposits of their customers. In other words, it shows the share of bank deposits, which can be considered a stable source of funding, in the loan portfolio.

Macroprudential policy: the part of public intervention to maintain financial stability that deals with preventing and, where necessary, mitigating excessive build-up of systemic financial risks. In other words, it is a system-wide regulation that seeks to prevent and dampen financial crises without unduly restricting the functioning of the financial system.

Measure of Economic Welfare, MEW: in addition to understanding the relationship between economic growth and welfare, the indicator also provides information on sustainability, such as factors that are outside the scope of traditional GDP or GNP calculations (e.g., the value of leisure, non-market goods and services, and the disadvantages of urbanisation).

National capital: the sum of the economic, natural, human and social assets that a country possesses.

Natural capital: the elements of the Earth’s living and non-living (biogeochemical) resources that provide ecosystem services, such as minerals and energy carriers.

Natural resources, natural capital: the elements of the physicalchemical-biological living and non-living environment in which humanity lives, whose existence is essential for human survival, health and pursuing human activities.

NEET rate (Not in Education, Employment or Training): the share of young people not in employment, (formal or non-formal) education, or training in the population of the same age.

Negative externality: when the incremental costs of producing or consuming a product are not reflected in its producer or consumer price, but are spread across other actors in the economy.

Net Economic Welfare, NEW: adds to GNP some key elements of wealth (e.g., household labour, leisure, value of the informal economy) and deducts unpaid costs associated with pollution and the disadvantages of modern urbanisation.

Net external debt: the ratio of external debt-type liabilities (loans, bonds) of the total economy (private sector and treasury) minus debttype assets.

Net financial assets/position: stock indicator; the difference between household financial assets and liabilities.

Net lending/net borrowing: net financing capacity (net financial savings) is the part of disposable income that is not spent by economic operators, i.e., not used for consumption or accumulation. If the difference between income and domestic consumption is negative, i.e., the sum of the national economy’s capital accumulation (investment and changes in inventories) and consumption expenditure exceeds the country’s disposable income, then there is a financing need. The net lending/borrowing is the sum of the current account and the capital account.

Non-renewable energy sources: some natural resources are finite from a human perspective;, it takes millions of years for them to form but they are exploited at a faster rate than they are re-produced. This includes natural gas, oil, coal and uranium.

Operating expenditure: includes personnel expenses, other administrative expenses and depreciation. The majority of personnel expenses are payroll expenses, while other administrative costs include IT costs, rent, marketing costs, insurance premiums and professional fees. The latter item also includes bank levies that cannot be included in the income tax category (e.g., special tax on financial institutions, financial transaction levy, extra profit surtax). Depreciation includes depreciation of property, plant and equipment, and amortisation of intangible assets.

Output gap: the difference between the current level of GDP and potential output. It aims to determine the current cyclical position of the economy. It is an important indicator of inflationary pressures from the real economy.

Phillips curve: an empirical economic relationship between the growth rate of nominal wages and the level of unemployment. In essence, the lower the unemployment rate, the faster wages rise.

Physical Quality of Life Index, PQLI: the Overseas Development Council’s Physical Quality of Life Index is defined by life expectancy, literacy and infant mortality.

Pooled OLS model: an econometric modelling procedure where observations are regressed on a cross-section (without time dimension) using the ordinary least squares method.

Production function: establishes the link between production factors (capital and labour) and economic output.

Public debt: the total of the government sector’s debts and accounting liabilities accumulated in the past.

Purchasing Power Parity, PPP: an economic method for calculating an alternative exchange rate between two currencies. Purchasing power parity measures how much goods and services can be bought in one currency against another, taking into account different prices in different countries. The reference currency used by PPP is the US dollar.

Purchasing Power Standard, PPS: identical in methodology and use to purchasing power parity. This indicator is produced by Eurostat and uses the euro as the reference currency.

Ratio of electronic bill payments: the ratio of the annual amount of card purchases to annual household consumption.

Renewable energy sources: a group of energy carriers that are renewable on a human timescale, i.e., do not run out, unlike nonrenewable energy sources. Renewable energy sources include direct thermal and photovoltaic solar energy, biomass, wind energy, hydropower, ocean wave energy, geothermal energy and tidal energy in connection with the Moon.

Resiliency: the characteristics of systems to maintain their ability to function in the face of external disturbances and shocks, either by adaptations or by changing the way the system operates so that its main, essential functions and objectives can still be met.

Resource: the sum of material and non-material factors used to create economic goods, products and services. The set of inputs (initial, things used) that can be combined to produce a given good. Contemporary economic thinking divides resources into four groups: physical-economic resources, human resources, social resources and environmental resources.

Return on Equity, RoE: one of the most widely used profitability indicators, showing how much profit after tax a company made in a given period, based on its equity. Since the value of equity can change during the year, in practice the average value of equity calculated for a given period, usually a financial year, is taken and compared with the current period’s profit after tax.

Satellite accounts: they detail, modify or supplement the tables and accounts in the central system to meet specific data requirements. Satellite accounts, although linked to the central system, are not or not necessarily linked to each other.

Share of people living in severely inadequate housing conditions: the proportion of people living in a dwelling characterised by at least one of the characteristics of inadequate housing conditions and classified as overcrowded. Inadequate housing conditions can include a lack of bathroom or indoor toilet, a leaky roof or excessively poor lighting. Crowded conditions are determined by the number of rooms available to the household, the size of the household, and the age and marital status of its members.

Sharing economy: a business model in which the owner and the user are separated, the number of users is high and the same asset is used

by several people in alternating time periods. Typical examples are car-sharing networks. In principle, fixed costs are borne by the owner and variable costs by the users. Asset utilisation is typically higher than if owner and user were the same.

Social capital: value derived from good relations between people, strong social bonds, trust.

Social cohesion: the capacity of a society to ensure the general welfare of its members by limiting the extent of inequalities and banishing the practice of social exclusion.

Social inequality: the different position in society of individuals and families and social groups defined according to various criteria (e.g., different levels of education, labour market activity, family background) according to several dimensions (e.g., income, life expectancy) and the difference in their chances of moving into more favourable social groups.

Supply and consumption tables: the central elements of the input-output framework are the supply and consumption tables at current and previous year prices. The framework is complemented by symmetric input-output tables, which can be derived from the supply and consumption tables using assumptions or additional data. The supply and consumption tables are matrices describing the value of transactions in products in the national economy, broken down by product type and sector. These tables show the following: the structure of production costs and the income generated in the production process; the flow of goods and services produced in the national economy; the flow of goods and services between the domestic economy and abroad; in order to analyse the EU context, it is necessary to distinguish between flows within the EU and those with non-EU countries.

Sustainability: the long-term quantitative and qualitative state of resources that enables societies to sustainably secure, at least maintain, but more importantly increase, their outputs and the creation of their well-being in the broad sense. Sustainability has many aspects. In this book, it is understood primarily in economic, financial, social and ecological terms.

Sustainable Development Goals (SDG) Index and Sustainable Development Report (SDR): indicates pro rata progress on social and environmental sustainability against the SDGs over time, on a scale of 0–100 points, using around 120 indicators. In recent years, the global SDG index has been on the decline, with particularly substantial lagging in poverty eradication, decent work and economic growth.

Sustainable development: progress is understood in both quantitative and qualitative terms. Development is sustainable if it does not run into obstacles in the foreseeable future, i.e., if it can continue without any substantial intervention.

Sustainable finance: first defined in the 1987 Brundtland Report as development that meets the needs of the present without compromising the ability of future generations to meet their own needs. Today, this concept is the basis of the United Nations (UN) 2030 Agenda for Sustainable Development and its seventeen Sustainable Development Goals (SDGs), which aim to eradicate poverty, protect the planet, and promote peace and prosperity for all.

Sustainable Social Index, SSI: one of the most comprehensive sets of indicators, measuring social, environmental and economic sustainability across 7 categories with 21 indicators, concluding that, as social and economic sustainability improves, environmental sustainability is deteriorating.

System of Environmental Economic Accounting, SEEA: an international statistical standard that takes a systematic approach to combining economic and environmental information to measure the contribution of the environment to the economy and the impact of the economy on the environment. The SEEA uses a structure and classification consistent with the System of National Accounts (SNA) to facilitate the development of indicators and analyses the relationship between the economy and the environment.

Telic theories: the psychological theories of human behaviour along the dimension of target orientation. The telic personality is characterised by problem-focused, target- and planning-oriented coping strategies, which show a positive correlation with subjective well-being.

Transfer price: in the case of a company with several subsidiaries or establishments, the supply/flow of goods/services at non-market prices between the different segments. Often used to reduce the tax base.

Value added content of exports: shows the percentage of gross exports that come from domestic production.

Value chain: a representation of how much new value is created at each stage from the conception of a product/service to its delivery to the customer.

Wealth to Well-being, W2W: a Boston Consulting Group indicator that relates the SEDA (Sustainable Economic Development Assessment) indicator of sustainable economic development to per capita income.

Weighted Index of Social Progress, WISP: a quality of life measure developed at the University of Pennsylvania to measure differences

between less developed countries (e.g. women’s rights, illiteracy, armed conflicts).

Welfare:  was understood a few decades ago as the possession of material goods, wealth and financial security. Today, both in policymaking discourse and in academic work, there is a growing emphasis on well-being, which goes beyond the material status.

Well-being: the two main dimensions of (subjective) well-being are life satisfaction (cognitive) and the net balance of emotions (affective). Instead of objective measures, the focus is on the subjective perception of individuals, how they experience and value their life and activities. In addition to material welfare, it also includes other dimensions such as family happiness, health, the state of our environment, the possibility and ability to achieve self-fulfilment, a meaningful life (eudaimonia), personal freedom, etc.

World Happiness Report, WHR: a ranking of “happiness” based on the Gallup survey published by the Sustainable Development Solutions Network; it is based on wealth, life expectancy, generosity, corruption, freedom of choice, helpfulness and vision.

INDEX OF NAMES AND TERMS

2008 financial crisis 180

2050 109, 111, 211

A

ability to predict a crisis 249

additional environmental pressures 266

ageing 62, 192–195, 199, 221, 242

Agenda 21 12

aggregation 90–92

air pollution 44, 64, 80, 212

Annan, Kofi 159

AROPE indicator (percentage of the population at risk of poverty or social exclusion) 202

artificial intelligence 144

Asian countries 243

atypical work 199

automation 236

autonomy 68

autotelic personality 71

average income 126

B

balance of payments 36, 137–139, 184, 242

balance of subjective well-being 72

balance sheet adjustment 180

Baltic countries 243

Ban, Ki-moon 269

bank tax 177

Banking Competitiveness Index 155

banking system 174, 176–181, 220–221, 231, 249, 271

basic education 256

basic research 160

Benelux countries 265

Better Life Index (BLI) 123

biocapacity 107, 213–214, 232, 262–265, 271

biologically productive area 263

BIS 250–252

bond market 174, 176, 181–182, 216

boom and bust periods 234

BPM6 137–138

budget deficit 47, 220

business cycle 231, 234–235, 275

Ccapital account 231, 244

capital accumulation 31, 235

capital adequacy 177–178

car sharing 53, 324

Carbon Capture and Storage (CCS) 27

Carbon Capture, Use and Storage (CCUS) 27

carbon footprint 107

carbon intensity 126, 149

carbon mitigation strategy 27

carpooling 53

cash holdings 187

catching-up 33, 240–243, 277

CCUS (

central bank 13, 139, 179, 181, 215–216, 221, 235

central bank refinancing 179

China 66, 109, 123, 243

circular economy 206, 213–215, 221

climate and social crises 16

Climate Change Performance Index (CCPI) 111–113

CO₂ emission 14–15

Commission on the Measurement of Economic Performance and Social Progress 42

competitiveness 49, 155, 189, 196, 203, 245, 274

competitiveness index 155

composite indicator 88, 109, 125, 154

composite indicators 83, 88, 113

composite sustainable development indicators 92

composition effect 163

Confucius 240

contactless card payment technology 189

convergence 162, 174, 176, 211, 220, 280

coronavirus pandemic 183, 189, 196, 220, 277

corporate bond market 182, 216

correlation matrix of the Inglehart–Welzel Cultural Map 118

cost-efficiency 177

country-specific parameter 266

COVID-19 crisis 179, 200, 274

Coyle, Diane 45

creative destruction 42

credit cycle 249–250

credit gap 230, 248–253, 271, 277, 281

Credit Suisse 202

Croatia 46

cross-sectional/longitudinal research 72

current account 36, 137, 174, 184–185, 220, 231, 240–245, 271, 277

current account deficit 36, 184, 220, 240–245

cyclical position 235, 240, 248–251

cyclical processes 234

DDaly, Herman 32, 95, 98

demography 29, 194, 235–236

dependency ratio 30, 194

depreciation 50, 81, 97–98, 143, 237

developed country 107

differences in wealth

Digital Economy and Society Index 171–172

digitalisation 40, 134, 139, 142–145, 160, 169, 171, 174, 188, 199, 220, 232, 235–237

DIW Econ 164

domestic value added 160, 166–168, 220

dwindling resource supplies 32

Eearly repayment 180

Easterlin Paradox 117–124

Easterlin, Richard 117

ECB (European Central Bank) 250

ecological balance 107, 206, 213–214, 221, 232, 262–279

ecological footprint (EF) 13, 106–107, 113, 121–122, 189, 213, 232, 262–264, 271

ecology 20

Economic Complexity Index 168

economic cycle 259

economic development

12, 35, 40–41, 60, 85, 109, 123–125, 154–156, 171, 180, 210, 224–225, 237, 266, 272–273, 280

economic resources 136, 145

economic stability 124

economic sustainability 21, 102, 159, 161, 174, 192

Economist Intelligence Unit (EIU) 128

ecosystem services 24, 80

education 29–31, 41, 45, 48, 64, 67, 80–81, 84, 97, 101, 104–105, 115, 120–125, 144, 169, 192, 198–201, 221, 232, 236, 256, 271

education system 31, 81, 84, 192, 198, 201, 221

Einstein, Albert 19, 205

electronic payments 174, 189

emerging country 240–241

emission 14–15, 27, 44, 104, 106, 109, 111, 140, 143, 149–150, 206, 209, 211–212, 221, 266, employment gap 257–258, 271

employment rate 65, 77, 124, 200, 257, 271, 277

energy consumption 208, 210

energy dependence 208

energy efficiency 206, 210, 212, 221

energy from renewable sources 103

energy intensity 150, 210

energy mix 206, 208, 221

energy trilemma 211

environmental expenditures 157

environmental factors 32, 58, 63, 72, 99, 154, 261

Environmental Performance Index (EPI) 108, 113

environmental pressures 109, 147, 208, environmental burden 188–189, 263

environmental protection 105, 148, 206, 211, 266

environmental quality, quality of the environment 21

environmental sustainability 20, 102, 104–105, 113, 156, 174, 206–207, 210, 215, 217, 220–221, 271

environmental taxes 150, 215–216

ESA 2010, European system of national and regional accounts 137, 141 EU farmers’ market (crowdfarming) 53

EU’s Structural and Cohesion Fund 243

eudaimonic happiness 117, 131

European Commission 23, 102, 108

European Union 137, 171, 175, 181, 196, 203, 208, 211–214, 220, 225, 230, 263, 266

EU Emissions Trading System (ETS) 14

Eurostat 81, 194, 250, 258

excessive lending 249–250, 277

experimental and interventional methodologies 72 exports 160, 167–169, 220

external balance 33, 36, 168, 184–185, 208, 231, 243, 271

external debt 36–37, 174, 185, 231, 242, 244

external financing 186, 240

external imbalance 240, 242, 244, 276

external indebtedness 36, 270

external position 242, 245

FFDI (Foreign Direct Investment) 36, 165, 245

financial assets 186–187

financial wealth 186–187

financial crisis 9, 36, 179–180, 243, 248, 251, 271, 274–282

financial cycle 248–252

financial deepening 174, 180

financial digitalisation 174, 188

financial instability 249

financial market stability 220

financial optimism 249

financial room 244

financial sustainability 33, 36–37, 173–186, 220

financial system 34, 174–176, 220, 231, 248, 251

fiscal impulse 235–236

fixed capital consumption 140

flow 22, 26, 50, 72, 105, 146, 231, 240, 242, 277

flow metrics 50

foreign currency loan 180

foreign currency-denominated debt 183

fossil energy use 149

fourquarter rolling sum of current price GDP 250

France 117

full employment 192, 200, 221, 277

future indebtedness 86

GGallup World Poll 122, 126

GDP 12–35, 38–99, 113, 116, 121–129, 132, 134, 137, 140, 142, 145–149, 154, 160, 165, 167, 169, 174, 180–187, 216–237, 240–242, 248–262, 265, 269–282

GDP growth 35, 44, 47, 51, 59, 124, 160, 220, 234, 236, 242, 270, 274, 277

GDP per capita 50–51, 55, 99, 116, 125–126, 154, 222, 224, 230, 272–282

GDP-B indicator 54

gender equality 105, 124, 128, 136

Genuine Progress Indicator (GPI) 100, 113

geothermal energy 209

GFN (Global Footprint Network) 107, 122, 262–263

Gini coefficient 126

Gini index 201

global hectares 107

Global Liveability Index (GLI) 128

GNH (Gross National Happiness) 13

GNI-GDP gap 242

government regulation 249

GPI (Genuine Progress Indicator) 100

green bonds 215, 217

green corporate bond market 216

green financing 215

green hydrogen 209

green investments 16, 266

green loans 215

green transition 199, 206, 221

greenhouse gas emissions 149, 206, 209, 212, 221

greenhouse gas intensity 134, 149

greenhouse gases (GHG) 27, 111, 149, 211

gross domestic product (GDP) 33, 76, 79

gross national income (GNI) 241

gross public debt 34, 183

growth sacrifice 245

HHappy Planet Index (HPI) 121–122

Harvard University 168

health care 30–31, 41, 80, 271

health care system 30–31

healthy environment 256

healthy life expectancy 125, 196

hedonic happiness 117

Heys, Richard 42

higher education 67, 101, 169, 198

high-tech sector 47

Hodrick–Prescott filter 249

Hoekstra, Solow 52, 91

household consumption 98, 235–236

human capital 20, 28, 30–31, 38, 50, 97, 140, 144, 192, 221, 232, 236

Human Development Index (HDI) 13, 91, 120–122, 128–129

human resources 28–29, 80

Hungarian Central Statistical Office (HCSO) 29–30, 135

IDI composite indicator 125, 127

IMF BOPCOM - Committee of Experts on Balance of Payments Statistics 137

import content 167

imports 206, 215, 240

Inclusive Development Index (IDI) 125, 127 income inequality 29, 106, 124, 201

income poverty 202

index of Net Economic Welfare (NEW) 97

Index of Sustainable Economic Welfare (ISEW) 98–101, 113

Index of Wealth to Well-Being (W2W) 123

indicator for inclusive development 13

individual factors 66

inequality 28–29, 41, 63–64, 77, 98, 106, 124, 126, 192, 201–202, 221, 232, 255–259, 271, 277

infant mortality 128

inflation 34, 65, 77, 124, 220, 231, 234–236, 270

inflation rate 234

innovation 20, 32, 38, 42, 48, 54, 106, 136, 160, 169, 198, 220, 235–236, 266

innovation ecosystem 236

input and output indicators 31

intangible assets 237

intangible investments 48–50, 160

interest 34–36, 93, 113, 187, 197–198, 241–242

international capital flows 240

intrinsic reward 71

investment 14–16, 20, 24, 31, 35–36, 44, 47–50, 76, 79–82, 85–86, 97, 124, 140, 150, 160, 165, 184, 206, 208, 210, 215, 235–243, 262, 266, 271

investment rate 160, 165, 184

invisible work 61, 69

KJapan 66, 117

know-how 160, 168

knowledge and technology-led growth 198

knowledge-intensive employment 171

Kuznets, Simon 12, 41 L

Labour Force Survey 258

labour market 54, 163, 192, 199–201, 221, 230, 232, 236, 257, 270, 277

labour market reserves 201

labour productivity 125, 160–164, 196, 220

lambda parameter 250

length of the credit cycle 249

Life Quality Index (LQI) 128

lifelong learning 67, 198

Lloyd’s Register Foundation 126

loan portfolio 179–180, 186, 249–252 loans as a percentage of GDP 248, credit-to-GDP 248–249

loan-to-deposit ratio 174, 179

long-term sustainability 12–13, 16, 100, 154, 185, 206, 211, 221, 239–240

low work intensity 202

M

macroeconomic aggregates 144

macroeconomic and financial market balance 174, 183

macroeconomic supply and demand 231, 234

macroprudential authorities 250

Magyar Nemzeti Bank (MNB) 20, 41, 92, 154–156, 162, 164, 189, 194, 204, 206, 215–216, 221, 230, 263, 283 market turbulence 244

marriage pattern 256

Measure of Economic Welfare (MEW) 96–97, 113 Millennium Ecosystem Assessment 24

MNB’s green mandate 215

MNB’s Green Home Programme 216

MNB’s Green Preferential Capital Requirement Programme 216

monetary policy 221, 235–

monetised value 81, 88

monetised, economic value of resources 81

mortgage bond financing 179

N

national assets 50

National Council for Sustainable Development 30, 93

National Framework Strategy on Sustainable Development 136

natural capital 20–22, 32, 76, 84, 86–87, 91, 93 natural resources 21–22, 25, 28, 80, 84, 87, 91, 104, 107, 140, 142, 146–148, 211, 213, 232, 262–263, 271

negative externality 23

net energy imports 209

net external debt 36–37, 174, 185, 231

net lending 185, 230–231, 243–244

net national income 145

net value added 145

network economy 54

network effect 54

New Economics Foundation 121

no emissions or natural sequestration by trees 27

non-financial private sector 248, 250, 252

non-performing loans 174, 178

Northern TOP5 countries 156

nuclear energy 206, 208–209, 221

number of people employed 150

Oobjective and subjective factors 77

OECD, the Organisation for Economic Co-operation and Development.

13, 41, 66–69, 81, 104, 123, 198, 202

Ordinary least squares (OLS) model 266

online banking 188

online cash register 189

online purchase 189

output gap 230–238, 270, 277

patent 171

personal agency 68

Phillips curve 235

Physical Quality of Life Index (PQLI) 128

pleasure-seeking (hedonism) 120

population growth 235, 242

population projection 30, 194

potential output 234–236

production function 236

productivity 12, 32, 53, 55, 125, 134, 148–149, 160–164, 172, 196, 198, 220–221, 236–237, 240

productivity gap 172

productivity of labour profit 36, 45, 51–52, 177, 241–242, 245

profit repatriation 52

property market 249

public debt ratio 34, 174

purchasing power parity (PPP) 59, 272–273

QQuality of Life Indicator 13

RR&D (Research and Development) 48, 137, 143, 160, 169 R&D spending 171, 235

real economy 154, 235

recession 38, 231, 234

recycling 215

reference point 63, 70

refinancing risk 36, 179, 185

reliance on foreign currency debt 35

renewable and non-renewable natural resources 147

renewable energy sources 143, 208

renewal rate of the domestic housing stock 204

resilience to shocks 177–178

resource allocation 16

resource productivity 134, 148–149

resource use, use of resources 154, 162, 262, 266

resource-intensive sector 149

retrospective 32, 72

Return on Equity (RoE) 177

Rio Earth Summit 12

robotisation 236

room rentals (Airbnb) 53

S

satellite accounts 13, 144–146

satisfaction 51, 58–59, 63, 67–68, 70, 72, 77–78, 82, 117–123, 131

savings 90, 126, 206, 240–243, 271

Scandinavia 127, 265

Schumpeterian Dream 42

security of supply 206, 209, 211

SEEA, System of Integrated Environmental and Economic Accounting 140, 146

self-actualisation (eudaimonia) 120

services sector 166, 266

severe deprivation 202

share of young people not in education, employment, or training (NEET) 201

sharing economy 53–54

Shechtman, Dan 191

Shiller, Robert J. 173

smart investment 48, 165

SME (small and medium-sized enterprises) 160, 164, 169, 172

social and labour rights 255

social capital indicator 54

social cohesion 28, 127, 129, 201, 232, 257, 271

social inequality 63, 255–259, 271, 275, 277

social justice 255, 269

social mobility 192, 256, 271

social resources 84

social sustainability 124, 191–194, 201–202, 220–221, 232

socially inclusive and ecologically green investments 16

South Korea 123, 243

SPI, Social Progress Index 13, 90

Stiglitz, Joseph 42, 54, 83, 153, 233

subjective well-being 58–73, 122

supply of renewable energy 32

sustainability 33–34, 36–40, 51, 76, 82–89, 91–97, 100–106, 113, 124–126, 133, 136, 139–140, 142, 155–166, 173–177, 181–194, 199–217, 220–222, 228–232, 236–240, 244, 247, 256–257, 262–263, 271–279

Sustainable Development Goals, SDGs 28, 104–105, 108–109, 136

sustainability indexing 92

sustainable convergence 162, 174, 176, 211, 220

sustainable development 12–13, 20, 28, 30, 38, 50, 86, 89, 93, 96, 104–105, 108–109, 113, 126, 134–136, 154, 159, 191, 269, 279–282

Sustainable Development Report (SDR) 104, 113

Sustainable Economic Development Assessment (SEDA) 123

sustainable GDP 13, 15–16, 227, 229, 231–241, 252, 255–266, 269–282

sustainable GDP paradigm 15–16

sustainable growth 20, 44, 50, 85, 151–156, 160, 169, 174, 219–225, 242, 262, 281

Sustainable Growth Index 151–156, 219–225

Sustainable Social Index (SSI) 102

System of National Accounts (SNA) 13, 91, 137–144

Ttaxi driving with own car (Uber) 53

technological progress 32, 97, 169, 235–236

technology-led (growth) 198

telic theories 68, 71

temporary shock 240

tightening labour market 163

total factor productivity 32

total national wealth (TNW) 81

tragedy of the commons (Hardin) 23

transaction levy 177

transfer pricing 40, 52, 54

transfers 244

trend-cycle decomposition 249 U

UK Office for National Statistics 42

uneconomic growth 32

unemployment rate 65, 77, 124, 200

United Nations Organisation (UN) 12–13, 20, 28, 104–105, 120–121, 129, 145

unused capacities 53

urbanisation 97–101, 129

USA 109, 117, 119, 123

Vvalue added

countries

Wwage distribution 257

waste intensity 150

water retention capacity 84

wavelength 234

wealth inequalities 50–51, 77,

welfare 23–24, 28, 33, 47, 58, 64, 77–79, 96–102, 113–124, 128–134, 154, 180, 199, 201, 206, 221

Weighted Index of Social Progress (WISP) 127

well-being 17, 30, 41–43, 51, 55–73, 76–85, 88, 91, 102, 104–105, 115–125, 128–131, 134, 139–140, 142, 144–146, 155, 199, 221

wind energy 209

working-age population 194, 236

World Bank 126

World Economic Forum (WEF) 125

World Happiness Report (WHR) 126

Y

York University 263

ABBREVIATIONS

AROPE (At Risk of Poverty or Social Exclusion): percentage of the population at risk of poverty or social exclusion

BLI: Better Life Index

BOPCOM: Committee of Experts on Balance of Payments Statistics

BPM6, BPM7 (Balance of Payments and International Investment Position Manual 6th/7th Edition): the international methodological rules for balance of payments statistics, as revised in recent years

CCPI: Climate Change Performance Index

CCS (Carbon Capture and Storage): Carbon Capture and Storage (CCS) is the capture, transport and storage of greenhouse gases from fossil fuel power plants, energy-intensive industries and gas fields, by injecting the captured greenhouse gases back into the ground.

CCUS (Carbon Capture, Use and Storage): Carbon Capture, Use and Storage (CCUS) is the capture of carbon dioxide (CO2) emissions from fossil energy production and industrial processes for storage or reuse deep underground.

DESI: Digital Economy and Society Index

DMC: Domestic Material Consumption

EF: Ecological Footprint

EIB: European Investment Bank

EPI: Environmental Performance Index

ESA2010: The European System of National and Regional Accounts

ETS: European Union Emissions Trading System

FDI: Foreign Direct Investment

GDP: Gross Domestic Product

GHG: Greenhouse gases

GLI: Global Liveability Index

GNH: Gross National Happiness

GNI: Gross National Income

GPI: Genuine Progress Indicator

HDI: Human Development Index

HPI: Happy Planet Index

IDI: Inclusive Development Index

ICT: Information and Communications Technology

ISEW: Index of Sustainable Economic Welfare

ISWGNA: Intersecretariat Working Group on National Accounts

HCSO: Hungarian Central Statistical Office

LQI: Life Quality Index

MEW: Measure of Economic Welfare

NDP: Net Domestic Product

NEET (Not in Education, Employment, or Training): the share of young people not in employment, (formal or non-formal) education or training in the population of the same age.

NEW: Net Economic Welfare

NCSD: National Council for Sustainable Development

NNI: Net National Income

NPL: Non-Performing Loan

NUTS 3 regions (Nomenclature of Territorial Units for Statistics): the common nomenclature of territorial units for statistics established by the European Union, which divides the Member States into 3 levels. The NUTS 3 level is the smallest of these administrative units, in the case of Hungary, the level of counties.

NVA: Net Value Added

NW: National Wealth

OECD: Organisation for Economic Co-operation and Development

PPP: Purchasing Power Parity

PPS: Purchasing Power Standard

PQLI: Physical Quality of Life Index

R&D: research and development

RoE: Return on Equity

SDG: (the UN’s) Sustainable Development Goals

SDR: (the UN’s) Sustainable Development Report

SEEA: System of Integrated Environmental and Economic Accounting

sGDP: sustainable GDP

SME: micro, small and medium-sized enterprises

SNA: System of National Accounts

SSI: Sustainable Social Index

SWB: Subjective Well-Being Index

TNW: Total National Wealth

UNSC: United Nations Statistical Commission

W2W: Wealth to Well-Being Index

WHR: World Happiness Report

WISP: Weighted Index of Social Progress

“The drawback of GDP as the main statistical measure of economic performance has become increasingly evident, as it ignores the significant externalities that many economic activities bring to the environment and the society. I applause the MNB’s work that delivers a comprehensive re-evaluation of the traditional GDP indicator and proposes options to structure a sustainable measure of GDP.”

JUN MA, President, Beijing Institute of Finance and Sustainability.

“We need new metrics to assess environmental sustainability; the objective and subjective dimensions of wellbeing not captured by GDP; the digital economy; and the inter-generational dimensions of fiscal policy and finance. This new volume of the MNB offers a comprehensive overview of the issues. I strongly recommend this book, which will contribute to the worldwide effort to move beyond GDP.”

JEFFREY D. SACHS, Director, Center for Sustainable Development, Columbia University.

“Sustainable GDP is a long-awaited breakthrough pioneered by the Central Bank of Hungary to reconcile long-term sustainability with short-term GDP that will open up a paradigm shift critical especially for Net Zero 2050. Sustainable GDP is a must read for all those who are interested in improving the sustainability quality of GDP.”

RAEKWON CHUNG, Board Director, Ban Ki-moon Foundation for a Better Future.