Issue 19

ISSUE 19 October 2018

TOP STORY

DARCY, GATSBY or WONKA WHO’S THE WEALTHIEST?

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Dear Readers, On behalf of the NER team, it is our pleasure to present the 19th issue of the Nottingham Economic Review. The NER continues to offer students the opportunity to engage with a variety of economic and political themes and prides itself on allowing each individual writer to showcase their own unique style on a topic of their choosing.

We have been particularly impressed with the ability of our editors to create both fascinating and insightful perspectives on a range of topics. Our editors were chosen based on their ingenuity in proposing an unparalleled article titled, “Brexit” and as editors-in-chief we were amazed to read such compelling, amusing and refreshing ideas. We are immensely proud to showcase this raw talent in the NER. This issue includes an incredible assortment of articles. Artificial intelligence and the increased usage of contactless payments are just a couple of the themes explored and we are delighted to publish a journal with such an immense range of topics. We would like to extend our biggest congratulations to this year’s Gainsborough Prize Award winner, Anna Howell, for her incredible article “Darcy, Gatsby or Wonka – Who’s the Wealthiest?” and of course to our two runners up, Daniel Light and Rosie Mahoney. These articles, along with many others, are proudly displayed in this issue and we hope you will enjoy reading them as much as we enjoyed writing them. We also invite you to look at our website and Instagram page to keep updated on all NER activities and perhaps apply for a role for our 2018/19 edition!

It takes a village to create something as worthwhile as the NER and so we would like to extend our deepest gratitude to the many people who make it possible through their unwavering support and dedication. The school of economics, in particular Frances Twiddy, Suzy Howe, Louise Hemming, John Gathergood, Paul Mizen and of course, Philip Watson. The NER would not exist without Philip, a University of Nottingham alumnus and we thank him sincerely for the wonderful opportunity he allows us to keep having.

Finally, for some of our editors this was their final edition of the NER as many graduated this summer. We have loved working with you over the past year and wish you all the best in the future but we look forward to welcoming our next editorial team!

NER Editors in Chief

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The NER Team About Us The Nottingham Economic Review is a student-run annual journal, backed by the School of Economics, whose purpose is to showcase undergraduate research and promote ongoing advancements in economic thought. Our editorial team strive to create provoking, insightful and topical content, while simultaneously capturing the interest of our readers. We also welcome external submissions and publish those that add value to our magazine.

Editors in Chief

Magazine Design

Shamima Manzoor Paige Portal Swati Raipancholia (Marketing) Rosie Mahoney

Daniah Al Mounajim Flora Wordie

Special thanks to Associate Editors Ashley Brumfield Oliver Clark Zhongwei Ho Anna Howell Chih Han Hsueh Charles Anthony Ibbett Yap Ke Li Georgina King Daniel Light Richard Palmer Mark Richardson Gaurav Suri

Prof. John Gathergood Louise Hemming Suzy Howe Prof. Paul Mizen Frances Twiddy Phillip Watson

Contact team@neronline.co.uk neronline.co.uk issuu.com/nottinghameconomicreview

Please contact us for details on how to be a part of our next issue!

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Letter from the Editors The NER Team Contents

Special Feature

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“Brexit, Uncertainty Shocks and the Decision Maker Panel” Charles Anthony Ibbett, Economics

Features

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#DeleteFacebook Shamima Manzoor, Economics Trapped Behind Bars Paige Portal, Economics Privacy: Priority or Pointless Practice? Swati Raipancholia, Economics The Future of Forecasts Oliver Clark, Economics Marxism Economics Chih Han Hsueh, Philoshopy, Politics and Economics The Robot Revolution Georgina King, Economics The Rise of Contactless Payment Richard Palmer, Economics The Global Water Crisis Gaurav Suri, Economics The Economics of Internet Retailing and Amazon’s Success Mark Richardson, Economics The Second Amendment Yap Ke Li, Economics Interest on Excess Reserves Ashley Brumfield, Economics Fintech Zhongwei Ho, Finance, Accounting and Management A Brief Event of Live - Event Ticket Markets Charles Anthony Ibbett, Economics

External Submissions

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What are the Determinants of Child Marriage in India? Sharmee Shah, Economics Korean Peace Toby Howard, Economics

Gainsborough Prize Winner/Top Story

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Darcy, Gatsby or Wonka - Who’s the Wealthiest? Anna Howell, Economics

Gainsborough Prize Runners up

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Time’s up on Trident Daniel Light, Economics Is a Graduate Tax the Answer to Our Prayers? Rosie Mahoney, Industrial Economics

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SPECIAL FEATURE

“BREXIT, UNCERTAINTY SHOCKS AND THE DECISION MAKER PANEL”

This article does not represent the views of the Bank of England; the views expressed in this article are my own.

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Charles Anthony Ibbett, Economics rexit represents an “uncertainty shock”, twice as strong as any other of the past twenty years (1). It will see businesses delay investment and employment in the UK, and euro-area, until the uncertainty is resolved. In response, the Decision Maker Panel (DMP) was set up by Paul Mizen (University of Nottingham) and Nick Bloom (Stanford University) in collaboration with the Bank of England. The project is based on the respective research of both Professor Paul Mizen and Professor Nick Bloom. This initiative aims to quantify uncertainty across a diverse sample of UK businesses after Brexit and to support the appropriate policy response by the Bank and UK Government (2). In order to understand why the DMP is useful, both now and in the future, we must first understand the affects of uncertainty.

Uncertainty increases significantly following major economic and political shocks such as potential trade wars and financial crises (3). It can also be split into short-run or long-run uncertainty, and this differentiation is important. Investment and R&D growth tend to be more sensitive to long-run uncertainty, while employment may have a more equal response to both. The source of long-term uncertainty seems to be empirically linked to slow-moving and more radical risks like those inherent to policy uncertainty (4). The Brexit vote and its aftermath have given rise to significant policy uncertainty - long-run uncertainty resultantly rose and is still higher than pre-vote values. This, as we have seen, is important for both employment and investment decisions within the economy.

Typically, a firm will hire and invest when conditions are sufficiently good, and fire and disinvest when conditions are sufficiently bad. Between these two thresholds no action will occur. When uncertainty rises, firms become more cautious which is represented by an increased separation

The Decision Maker Panel (DMP) was set up by Paul Mizen (University of Nottingham) and Nick Bloom (Stanford University) in collaboration with the Bank of England between the two thresholds (3). Firms will be less likely to take action as investment projects are put on hold till calmer times.

In the time following a major crisis, aggregate inaction can be a

problem. If too many firms have adopted a cautious stance, then growth will remain low and the recovery will never take off. The longer-run will also be affected if there is reduced investment in capital goods, product development, and worker training.

So far, some of the short-run symptoms of an uncertainty shock can be witnessed in the UK economy with the 2016 Brexit vote and its ongoing aftermath. Many firms have delayed investment projects until our future relationship with the EU becomes

The Brexit vote and its aftermath have given rise to significant policy uncertainty and therefore long-run uncertainty resultantly rose and is still higher than pre vote values uncertainty more certain (5). This delay has prevented the UK’s recovery from the financial crisis, with growth rates forecasted to remain much lower than other OECD economies. Until the future relationship with the EU is clear (regardless of the form) policy uncertainty will remain relatively high and investments decisions will be delayed. Although the symptoms are detectable, the uncertainty present and its effect on companies’ decisions is not easily quantifiable. It is also not possible to determine how well-informed decision makers are of uncertainty within the economy. These problems are addressed with the DMP. The DMP has been a key source of information to policy makers over the past year, as they have assessed how leaving the European Union may affect the behaviour of UK firms (2). Indeed, currently it is used to brief the Bank’s Monetary Policy Committee (MPC) prior to their rate setting meetings.

The DMP consists of a short survey to be taken by Chief Financial Officers of selected UK businesses, in the areas of: investment and borrowing; employment and costs; and sales and prices - rotating through the pairs every month so that all are covered each quarter (2) In addition to these general questions, others are included that focus on specific and current events - for example Brexit. At this time, policy questions from HM Treasury, the Department for Exiting the EU and the Bank of England have fed the survey but this is flexible. It has the potential to include questions from academics for research purposes and to adapt to fit future scenarios. The end goal is for the information gathered to be used to generate a monthly index of business uncertainty which will be a new resource for academics, financial firms, and financial data providers (6) - for which it has already proved

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popular. The DMP also has the potential to be used for policy analysis through its economic impact assessments on investment, sales and hiring rates (on almost real-time data).

References 1. Nicholas Bloom, Scott R. Baker, Steven J. Davis, 2012. Europe Monthly Index. [online]Available at: http://www.policyuncertainty.com/europe_monthly.html [Accessed: 16 July 2018]

Teams of analysts at the University of Nottingham and Bank of England work to recruit new buisnesses with a goal of achieving at least 8000 firms

2. 2017. “Quarterly Bulletin (2017 Q2): Tracking the views of British Businesses – Evidence from the Decision Maker Panel”. London: Bank of England.

3. Nicholas Bloom, “The impact of uncertainty shocks”, Econometrica, Volume 77, Issue 3, 2009, 623-685 4. Jose Maria Barrero, Nicholas Bloom, Ian Wright, 2017 “Short and long run uncer-

The initiative is based on the research of both Professors, Bloom and Mizen, who covered 5500 firms in August 2018.

This number is continuing to grow rapidly at a rate of 200 new firms per week. Teams of analysts at the University of Nottingham and the Bank of England work to recruit new businesses with a goal of achieving at least 8000 firms. Firms are selected based on their industry, region and firm type (e.g. small, young) which will allow the comparison between different regions of the UK or sectors of the UK economy. This comparison is useful in a number of ways. For example, via comparison, the Government (or BoE) can identify the industry or region that is most exposed to an uncertainty shock and then can act most effectively. Comparison can also highlight the different response that exporters and importers have to these types of shock.

tainty”, NBER working paper series, working paper no. 23676, National bureau of

In the uncertain times we currently face and those of the future, the Decision Maker Panel will provide current and precise information that quantifies uncertainty and its resultant effects. It gains much of its strength as a data resource from its flexibility. It has incredible potential which is spread over a variety of fields. It will be interesting to see how this information aids government, academics, financial firms, and more, in making the uncertain times a little more certain.

review, American economic association, Volume 97, Issue 2, 2007, 250-255.

I would like to thank Professor Paul Mizen for accepting an interview, it was a tremendous help in the formulation and direction of this article.

Maker Panel (2017 Q4)”. London: Bank of England.

If you’re a University of Nottingham Student and wish to get involved in the Decision Maker Panel, they are currently hiring new analysts. For more information contact Julia Leather at: lezjel@exmail.nottingham.ac.uk

economic research 5. Gavin Jackson, 2018. “What the evidence says about post-Brexit investment in the UK”. The Guardian, [Online] 2 April 2018. Available at: https://www.ft.com/content/d1f155f2-3683-11e8-8b98-2f31af407cc8.[Finance]. [16 July 2018].

6. University of Nottingham, 2017. “New Bank of England Decision Maker Panel Established”. CFCM, [Online] 2 February 2017. Available at: https://www.nottingham. ac.uk/cfcm/news/new-bank-of-england-decision-maker-panel-established.aspx.

[Finance]. [16 July 2018].

Nicholas Bloom, Stephen Bond and John Van Reenen “Uncertainty and investment dynamics”, Review of economic studies, Volume 74, 2007, 391-415 Nicholas Bloom, “Uncertainty and the Dynamics of R&D”, American economic Scott R. Baker, Nicholas Bloom, 2013 “Does uncertainty reduce growth? Using disasters as natural experiments”, NBER working paper series, working paper no.

19475, National bureau of economic research.

Scott R. Baker, Nicholas Bloom, Steven J. Davis “Measuring economic policy uncertainty”, The quarterly journal of economics, Volume 131, Issue 4, 2016, 1593-1636 2017. “Agents’ Summary of business conditions – and the results of the Decision 2018. “Agents’ Summary of business conditions – and the results of the Decision Maker Panel (2018 Q1)”. London: Bank of England.

2018. “Agents’ Summary of business conditions – and the results of the Decision Maker Panel (2018 Q2)”. London: Bank of England.

#DELETEFACEBOOK The Scandal Facilitated by Big Data Shamima Manzoor, Economics Facebook, a popular social networking website, has become one of the world’s largest technology companies. Its growth has been facilitated through its use of “Big Data”, as the data of its 2.2 billion monthly users (Facebook, 2018) provides the company with lucrative advertising opportunities. However, it has been recently revealed that user data has been manipulated to influence global politics, which many feel is a step too far, thus prompting the #DeleteFacebook movement.

As our lives become increasingly digitalised and social media usage becomes more widespread, the amount of data we produce is growing at an exponential rate. Facebook has over 300 petabytes, which is 300,000 terabytes, of data (Chan, 2013) stored in 11 enormous data centres (Mortenson, 2017), and there are plans for further expansions and new constructions. Its Lulea centre in Sweden alone contains 27,000 square feet of servers (DataCenter Knowledge, 2013), an incomprehensible amount of hardware. Facebook needs a massive operative environment to support new

capabilities such as live video and 360-degree photos and videos, and to handle the huge stream of live data from all over the world - simply to load a user’s home page, hundreds of servers and thousands of individual pieces of data are processed within seconds (DataCenter Knowledge, 2010).

Facebook has over 300 petabytes (300,000 terabytes) of data

The buzzword “Big Data” describes data used for analytical purposes. It has a multitude of applications within business environments, some of which include identifying new growth opportunities, enhancing cybersecurity, improving consumer loyalty, and even predicting stock market trends. According to Whishworks’ survey, 18% of companies in the UK have fully implemented Big Data, with 76% of companies investigating it or starting

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implementation; of these, 100% have said that Big Data initiatives are proving to be successful (Bobs Guide, 2018).

As an influential company that has access to billions of people’s personal data, Facebook has a responsibility to use this data appropriately; in fact, its business model relies on data mining. As shown on Chart 1, Facebook’s revenue is predominantly from advertising. User data, suchas income group, region, religion, and political affiliation, is used to generate tailored advertisements, and this advertising revenue is essentially what runs Facebook. This benefits both advertisers who can target their products more effectively, and users who are more likely to be shown content they are interested in. In essence, there is a trade-off between your privacy, and free access to the services provided by a technology company, whether it be Facebook, Amazon, or Google. Every time you engage with them, you add to their growing mine of data.

election, where they were paid $5.9 million by Donald Trump (Nussbaum, 2018) to help predict and influence voting. Algorithms were created to target voters with personalised political advertisements, using insights from Kogan’s Facebook data on where it would be best to advertise and which voters Trump was most likely to attract.

This is a prime example of the use of Big Data to influence democracy, and has left many people feeling uncomfortable. It has been revealed that the Facebook information of up to 87 million people, mostly in the US, may be in the hands of Cambridge Analytica (Schroepfer, 2018).

However, what if this data was misused, or expoilted without our consent?

Chart 2 Number of people whose Facebook information may have been improperly shared with Cambridge Analytica, by geographic location (Schroepfer, 2018)

Chart 1 Quarterly Facebook Revenue in $USD (millions) from Q4 2015 to Q4 2017 (Facebook, 2018) Facebook offers development tools and application programming interfaces to help developers create web and mobile apps to be hosted on Facebook’s platform, from which Facebook receives a fee. Aleksandr Kogan, a psychology professor at the University of Cambridge, was one such developer – but the use of the data he collected led to one of the most controversial data breaches in recent history, prompting the #DeleteFacebook movement.

Kogan created a personality test application called “thisisyourdigitallife”. To download it, users were required to express permission for the developers to access personal information such as their “likes”, their location, and crucially, information about their Facebook friends. From the 270,000 people who downloaded the app, Kogan therefore accrued data on over 50 million unsuspecting people (Nussbaum, 2018) as he had access to the data of the app users’ Facebook friends. However the key point is that although users gave developers access to the data, they did not give permission as to how this data was to be used.

Kogan sold the data to Cambridge Analytica, a firm who uses Big Data and psychological profiling to influence audience behaviour. Their political offering focuses on data-driven campaigns, and they have worked on presidential races and congressional and state elections around the world, including the 2016 US general election, where they were paid $5.9 million by Donald Trump (Nussbaum, 2018) to help predict and influence voting. Algorithms were created to target voters with personalised political advertisements, using insights from Kogan’s Facebook data on where it would be best to advertise and which voters Trump was most likely to attract. 2016 US general

The #DeleteFacebook movement is supported strongly

by Brian Acton, co-founder of WhatsApp, and Elon Musk, tech billionaire and the Chief Executive of SpaceX and Tesla. The hashtag trended on Twitter, as users vented their frustration at their information having been exploited without permission, and the large-scale influence it has had on politics. Just two weeks after the revelations, Facebook’s stock market value plummeted by $80 billion USD, and Mark Zuckerberg lost $14 billion USD from his personal net worth (Dike, 2018).

Another way in which Facebook facilitated Trump’s campaign was through its method of pricing and ranking advertisements. Posts that are expected to gain more attention are placed nearer the top of user’s feeds, and additionally, a post’s visibility is increased the more times people interact with a post.

So how can Big Data be used in political marketing – and can targeted advertising really determine a voters’ behaviour?

Can targeted advertising really influence democracy?

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Advertising is a method used with the intention of promoting sales. In the past, and still in most cases today, everyone receives the same advertisements for a product, whether it be on television, leaflets, billboards, or radio. It was assumed that there is one superior way to sell a particular product, which would attract as many people as possible – but why not split the public by demographics and target them all differently, which may improve sales even more? The economic concept of price discrimination recognises this, describing how firms in imperfect markets charge different prices for the same good or service to different consumers. The greater the amount of asymmetric information, the higher the potential for audience segmentation – and an area ripe with an imbalance of information is politics.

commercial value it holds. At the same time, social media sites like Facebook are likely to become even more popular due to networking economies of scale, regardless of privacy concerns, because we now rely on technology for so many aspects of our lives – so how viable is it to #DeleteFacebook?

Prior to supporting Trump, Cambridge Analytica worked for Senator Ted Cruz, one of his opponents. Initially, people barely knew of him, but he ended up being the only real contender against Trump. Speaking at the 2016 Concordia Annual Summit, Cambridge Analytica’s CEO, Alexander Nix, described the power of Big Data in global elections and how it was used to support Cruz (Concordia, 2016).

They recognised that although people may share the same age, gender, or ethnicity, this does not guarantee that they will all respond the same way to the same message. Certainly, demographics will influence their view, but model (openness, conscientiousness, extrav psychographics and personality are more important. Psychographic data includes lifestyle data like what magazine you read, what car you own and what shops you go to. Above this, they deemed personality to be the key driver of voting behaviour. They developed the OCEAN ersion, agreeableness, neuroticism) to predict the personality of millions of adults in the USA. It is clear to see therefore, how Big Data can potentially influence not only democracy but every aspect of the world we live in.

Big Data can potentially influence every aspect of the world we live in This is not the first time Facebook has been targeted for its Big Data potential. Insurance company Admiral, through its product “firstcarquote”, sought to analyse user’s personalities to determine how likely they are to be a safe driver (Ruddick, 2016). For example, if a user set a specific time for a meeting, rather than just saying “tonight”, they would be deemed a safer driver. However the product was terminated just hours before launch, due to privacy concerns, as it could change how people use social media if they are wary of their actions leading to discrimination.

GDPR (General Data Protection Regulation) is a law that was enforced in May 2018, addressing data protection and privacy for all individuals within the European Union. Companies who fail to report data breaches will be subject to fines of up to 4% of global revenue; for Facebook, this could mean a hefty $1.6 billion (Spangler, 2018). The new regulations will give consumers more information about what companies know about them and what data is used.

References Bobs Guide. “WHISHWORKS reveals results of UK Big Data survey”. 29 March 2018. http://www.bobsguide.com/guide/news/2018/Mar/29/whishworks-reveals-resultsof-uk-big-data-survey/ Chan, Lydia. “Presto: Interacting with petabytes of data at Facebook”. November 6, 2013. https://www.facebook.com/notes/facebook-engineering/presto-interacting-with-petabytes-of-data-at-facebook/10151786197628920/ Concordia. “The Power of Big Data and Psychographics”. Filmed September 2016 at the Concordia Annual Summit, New York. Video, 11:00. https://www.youtube.com/ watch?v=n8Dd5aVXLCc DataCenter Knowledge. “Inside Facebook’s Lulea Data Center”. 2013. http://www. datacenterknowledge.com/inside-facebooks-lulea-data-center DataCenter Knowledge. “The Facebook Data Center FAQ”. Sep 27, 2010. http://www. datacenterknowledge.com/data-center-faqs/facebook-data-center-faq Dike, Jason. “Facebook Loses $80 Billion USD in Stock Market Value”. Hypebeast.

March 28, 2018. https://hypebeast.com/2018/3/facebook-lose-80-billion-stockmarket-value Facebook. “Q4 2017 Results”. Accessed April 2018. https://s21.q4cdn. com/399680738/files/doc_financials/2017/Q4/Q4-2017-Earnings-Presentation.pdf Lomas, Natasha. “Facebook data misuse scandal affects ‘substantially’ more than 50M, claims Wylie”. TechCrunch. March 27, 2018. https://techcrunch. com/2018/03/27/facebook-data-misuse-scandal-affects-substantially-more-than50m-claims-wylie/ Mortenson, David. “2017 Year in review: Data centers”. Facebook Code. December 11, 2017. https://code.facebook.com/posts/392743124493876/ Nussbaum, Matthew. “Trump campaign sprints away from Cambridge Analytica”. Politico. March 20, 2018. https://www.politico.eu/article/cambridge-analytica-trump-campaign-tries-to-distance-itself-from-scandal-ridden/ Ruddick, Graham. “Facebook forces Admiral to pull plan to price car insurance based on posts”. The Guardian. November 2, 2016. https://www.theguardian.com/ money/2016/nov/02/facebook-admiral-car-insurance-privacy-data Schroepfer, Mike. “An Update on Our Plans to Restrict Data Access on Facebook”.

April 4, 2018. Facebook Newsroom. https://newsroom.fb.com/news/2018/04/restricting-data-access/ Spangler, Todd. “Facebook Under Fire: How Privacy Crisis Could Change Big Data Forever”. Variety. Accessed April 2018. http://variety.com/2018/digital/features/facebook-privacy-crisis-big-data-mark-zuckerberg-1202741394/

Facebook have announced the implementation of a whole host of controls to protect user data in response to the breach (Schroepfer, 2018). For instance, developers no onger have access to the data of friends who use an app, and users will be able to see all the information that is shared with any apps they use. Apps will also need to abide by stricter requirements before they can access user data. Despite increased awareness of the issues alongside increased regulatory action, it is unlikely that companies will stop looking for ways to exploit Big Data given the high

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TRAPPED BEHIND BARS The UK’s Toxic Criminal Justice Cycle Paige Portal, Economics Since 2011, crime rates have been steadily rising, with police figures reporting a 14% year-on-year increase in offences (Travis 2018). Annual crime costs are exceeding £32bn and planned police budget cuts of £700m have imposed a catastrophic impact on the ability of police to tackle increasingly complex criminal activity. An increase in prison numbers has strained the maintenance of the UK’s current regime ‘with over 60,000 adults per year receiving custodial sentences of less than 12 months’ (National Audit Office, 2010). Government statistics show that 68% of prisons have populations above Certified Normal Accommodation (CNA), raising concerns that the UK penal system has reached toxic levels (Bulman 2017). It is, therefore, unsurprising that in May 2018 the UK’s Justice Secretary, David Gauke, said that short term prison sentences do not work.

Government intervention had sought to correct the market failures associated with crime, but imperfect information and consumer sovereignty make it problematic/controversial for the government to identify/do what is in the public interest and thus will continue to make economic policy decisions that are sub-optimal. The assumption that an intervening government will always be welfare improving, gives it the power to fund harmful intervention. The role of public choice theory is centralised around a logical economic application to political science (Mueller 2003). However, the government has completed the development of the controversial “titan prisons” and deserted the proposed “Rehabilitation Revolution”. Public pressure has clearly influenced legislation to the point where effective choices have been practically abandoned and inefficient tactics, favoured.

One of the mechanisms employed to cope with the increased pressure on offender management and to modernise the public sector has been the development of “Titan jails” to replace ineffective and outdated institutions.

This is a slight deviation from tradition as past Conservative governments have reduced the scale of the public sector through a series of privatisations (Flynn and Asquer, 2007).

However, strategic changes have aimed to save taxpayers around £300m a year as part of a new and innovative approach with the objective of achieving greater efficiency (Travis, 2015). This is not a surprising policy considering liberal market economies, such as the UK and US having seen almost universally striking increases in the imprisonment rate (Lacey 2008). Nevertheless, in 2009, the proposed development of “Titan jails” was scrapped after continuous opposition from penal reformers suggested it was a disproportionate solution and had political motivations. An upfront cost of £1.2bn was committed to “Titan jails” in 2007, yet this figure later rose to £2.3bn. Nine years on, the development of Wrexham jail with an operational capacity of 2,500 inmates has been completed and in March 2017, the construction of four slightly smaller ‘supersized’ prisons were sanctioned by the Justice Secretary. The initial policy was justified by Lord Carter’s report ‘Securing the Future’ recommending ‘significant acceleration and expansion of the current building programme to meet unprecedented demand’ (Prison Reform Trust (PRT) 2007). However, the proposal was almost universally condemned with the arguments of decreased re-offending and better value for money having no substantial evidence (PRT 2007).

The economic rationale behind “titan jails” is an attempt to expand the current regime instead of transforming it but there has been no evidence of combining the effectiveness of small prisons with the efficiency of scale of large prisons

(PRT 2007). Mergers of these smaller prisons solicit economic theory that prison institutions will benefit from economies of scale. In the US, states such as Washington didn’t open penitentiaries for women until the 1970s due to the small number of female offenders. The rationale for exclusion from policy was that they would not meet the requirements on a cost-benefit basis (Durham 1994). It can therefore be regarded that rising prison populations have justified the development of “Titan prisons” as the costs can be minimised through an expansion in production, as in a matter of equity it is increasingly difficult to condone withholding resources (Durham 1994). Nick Herbert, former shadow Justice Secretary exclaimed that…

If these monstrous warehouses ever get built, projections show that they will be overcrowded by almost a third from day one. Old habits certainly die hard. (Herbert 2008).

However, the Government has succeeded in its pursuit of ongoing action despite opinion that titan prisons are a titanic waste of money. In my interview with Andrea Albutt in February 2018, she stated that the government’s failure to drive policy away from short-term prison sentences can be attributed to public pressure.

Continuing on this path is expected to further destabilise the criminal justice system and cause future overcrowding crises and higher reoffending rates (PRT 2008). The PRT (2007) recommended that for many short-term sentenced offenders, community punishment was more effective and economically efficient (PRT 2007) and although “Titan jails” were not completely disregarded, alterations to improve effectiveness were attempted in criminal justice policy.

In another attempt to modernise the criminal justice system, former justice secretary, Chris Grayling (2012) introduced a radical package of reforms known as the “Rehabilitation Revolution”, one of which intended to reduce the recidivism attached to short-term custodial sentences and alleviate the cycle of criminality with the increased use of community based sentences. However, six years on evidence suggests that the “Rehabilitation Revolution” has effectively been abandoned. The efforts to privatise initiatives were doomed to fail due to the ‘payment by results’ system (Heard 2015). The ambition to improve the efficiency of community sentences did not account for the falling number of community based punishment seen since 2009.

In essence, fewer offenders are now being referred to Community Rehabilitation Company (CRC), leading to falls in CRC income to significantly below the levels expected (Gyimah 2017). The private probation companies have thus made substantial losses and required a bail out of £342 million.

To rectify this, Mr Gyimah said an adjustment was made to the payment mechanism within the CRC contracts so it better reflected the fixed costs and made the CRC income less sensitive to changes in demand. Yet, the enforcement by private probation companies of community-based court sentences, has recently been assessed as “poor” by the HM Inspectorate of Probation. The target for the successful allocation of an offender in accommodation to a resettlement service was 90%, but the actual average performance was 69.8% with lows of 42.5% in some authorities.

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Prison sentences are generally defined as being a costly and ineffective approach to criminal punishment when the associated costs and re-offence rates are considered. Despite the positive externalities of current criminal justice proceedings, there are reasons to suspect that punishment outcomes will deviate from neoclassical definitions of optimality’ due to social dynamics (D’Amico 2017). It therefore becomes reasonable to adjust our expectations of imprisonment and divert our attention to other forms of punishment as prisons, a public good, may not always be allocatively efficient if the wider social costs and benefits are thoroughly analysed. So why haven’t we observed a drastic movement away from short term prison sentences? To victims of crime the incarceration of a perpetrator for protection has massive benefits.

Mitchell (2005) states that this can discourage productive choices so the forgone benefit from other expenditure opportunities is expected to be substantial. Although this is the case with any public good, Mohensi (2012) identifies economic costs sourced from prisons that are not standard consequences of other public good provisions. She lists human resource loss, jobs discontinuity, reduction of per capita income and family financial poverty as just a handful of negative economic liabilities induced by prison sentences.

This would counteract the contextualisation of prisons as a public good as the costs outweigh, or are equal to, the marginal benefits. Lacey (2008) argues that the difficulties associated with deciding the best form of punishment can be characterised as a ‘prisoner’s dilemma’ in which institutions have created a situation where the strategic capacity for political and economic coordination to achieve an optimal outcome is lacking. Thus, deciding how to effectively deter criminality is problematic. Carter (2003) exclaims that the increasing interaction between the public and the criminal justice process, through media and exerted pressure, could instead be the cause of increased sentencing severity and prison numbers. This has trapped our criminal justice system behind bars. An economically efficient shift in criminal justice policy, towards community sentences, would be too controversial for many office-seeking policy makers. Although ‘Government research shows that community sanctions are more effective than short prison sentences in reducing reconvictions’ (Heard 2015), perhaps that same government has abandoned economic reasoning and bowed instead, to public pressure.

References Bulman, Mary. 2017. “Two Thirds Of Prisons Overcrowded Prompting Warnings UK Penal System Has Reached ‘Toxic’ Levels”. The Independent, , 2017. https://www.independent.co.uk/news/uk/home-news/prisons-overcrowding-prisoners-ministry-of-justice-howard-league-a7685641.html.

Carter, Pat. 2003. Managing Offenders, Reducing Crime A New Approach. Strategy Unit.

D’Amico, Daniel J. 2017. “The Social Provision Of Punishment And Incarceration”. American Journal Of Economics And Sociology 76 (5): 1107-1132. doi:10.1111/ajes.12197.

Durham, Alexis. 1994. Crisis and Reform: Current Issues In American Punishment. Ebook. Bostom: Little, Brown and Co. Flynn, Norman, and Alberto Asquer. 2007. Public Sector Management. 5th ed.

Grayling, Chris. 2012. The Rehabilitation Revolution - next steps. GOV.UK. https://www. gov.uk/government/news/the-rehabilitation-revolution-next-steps.

Gyimah, Sam. 2017. Justice Update:Written statement - HLWS84. Ministry of Justice.

Heard, Catherine. 2015. Community sentences since 2000: How they work – and why they have not cut prisoner numbers. Centre for Crime and Justice Studies.

Herbert, Nick. 2008. Opposition Day Debate on sentencing policy and the early release of offenders. Nick Herbert MP. https://www.nickherbert.com/speeches/2018/1/15/opposition-day-debate-on-sentencing-policy-and-the-early-release-of-offenders.

Lacey, Nicola. 2008. The Prisoners’ Dilemma. Leiden: Cambridge University Press.

Mitchell, Daniel. 2005. The Impact of Government Spending on Economic Growth. Executive Summary Backgrounder. Heritage Foundation.

Mohensi, Reza Ali. 2012. “The Sociological Analysis Of Prison: Costs And Consequences”.

Journal of Law And Conflict Resolution 4 (1): 13-19.

Mueller, Dennis C. 1979. Public Choice. Cambridge [England]: Cambridge University Press.

National Audit Office. 2010. “Managing Offenders On Short Custodial Sentences”. National Audit Office.

Prison Reform Trust. 2007. “Titan Prisons: a gigantic mistake”. Prison Reform Trust.

Prison Reform Trust. 2008. Two thirds of prisons officially overcrowded http://www.prisonreformtrust.org.uk/PressPolicy/News/ItemId/38/vw/1.

Travis, Alan. 2018. “Rise In Recorded Crime Is Accelerating In England And Wales”. The Guardian. https://www.theguardian.com/uk-news/2018/jan/25/knife-and-gun-risessharply-in-england-and-wales.

Travis, Alan. 2015. “UK’s first ‘supersized’ Titan jail to be run by public prison service”. the Guardian. https://www.theguardian.com/society/2015/feb/24/uks-first-supersizedtitan-jail-to-be-run-by-public-prison-service

PRIVACY: PRIORITY OR POINTLESS PRACTICE? Swati Raipancholia, Economics Last Summer, I took on an internship for a well-known retail company in the digital marketing department. I was shocked to see the extent to which different software such as Facebook for Business, Google Analytics, and Hubspot, allow enterprises to track your every move online.

A promotional email is sent out. A digital marketing executive has the opportunity to see if YOU, specifically, opened it, unsubscribed, or weren’t sent the email due to a lack of interest (based on your previous records). Using a laptop I’ve never used before and simply logging into my email means advertisements from sites I’ve visited on my laptop at home are automatically displayed for me. I can’t be the only one who finds this constant infiltration somewhat frightening? This isn’t just the case for emails, it can also be done on social media and other websites. For an economics aficionado like myself, this begs the question, what are the economic consequences of this alarming lack of online privacy?

The fundamentals of the economics of privacy are simple:

There is a trade-off between customers and enterprises’.

The reduction of the cost of storing and manipulating information has led organisations to capture increasing amounts of data about individual behaviour. The hunger for customisation and usability has led individuals to reveal more about themselves to other parties. [More recently], individuals want to avoid the misuse of the information they pass along to others, but they also want to share enough information to achieve satisfactory interactions; organisations want to know more about the parties with which they interact, but they do not want to alienate them with policies deemed as intrusive.’ (1) As customers’ thirst for easy browsing and customisation grows in a technology-driven world, most customers are more than happy to share their personal information in exchange for a more personalised buying and browsing experience. As stated by Alessandro Acquisti in his academic paper on the topic, personal information is an economic good, as it holds value and its use carries an opportunity cost; the sacrificing of privacy. There is the issue of asymmetric information between customers and enterprises, as customers may not know how long their information will be used for, and moral hazards and negative externalities also arise from information sharing. (1)

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Programmatic advertising, in layman’s terms, is a means of online advertising based on customers’ past buying or browsing history powered by an algorithm. When you were looking at makeup tutorials on YouTube and suddenly start seeing makeup advertisements on Facebook and wonder how they knew, that’s how. Tracking is simply used to ‘improve a consumer’s online experience.’ (2). Real time bidding is a prime example of this. It refers to companies such as Facebook and Google running ad exchanges on any third party website you may visit. (3) This is considered beneficial on a microeconomic scale, as customers are shown similar preferences to previous purchases and recent interests, which could lead to a purchase. Though it may sound too small and too fast to make an impact on the business’s sales, we must remember that billions of these ads are put out every day, and programmatic advertising has been described as the future of marketing. Showing the customers what they want and reducing the internet’s equivalent of retail shoe leather costs increases consumer welfare. (4) In addition to the advantages present for customers and their buying patterns, programmatic advertising also helps businesses. Programmatic advertising enables advertisers to target individuals with highly specific online activities, with results that can be directly measured, and can be less expensive than larger non-targeted campaigns (5).

On the other hand, the effectiveness of traditional marketing channels can be more difficult to assess. This, again, delivers benefits on a microeconomic level, as businesses grow. Up and coming companies, who can’t afford huge billboards or extensive TV campaigns can now become as prominent as the likes of Nike and Apple. These new ways of using personal data to promote products allow markets to become highly productive and more competitive, and allowing customers access to more choice, which is typically economically desirable. Targeted advertising is said to generate thrice the revenue per ad compared to non-targeted advertising according to a study by the Network Advertising Initiative in 2009.

On the other hand, insufficient privacy can be damaging to customers in many ways. A basic example is discrimination. In a blog post by LSE’s Media Policy Project, a study on discrimination in the workplace is explained. (6) By creating fictional online accounts and profiles for potential employees and measuring the response rate of employers (7), it is found that in conservative states in the US, Christian candidates are 6 times more likely than Muslim candidates to receive a callback. Religion and other similar personal attributes aren’t legally allowed to be used as a reason to not hire an individual, so employers use standard justifications to get away with discriminating. This proves a lack of online privacy or ease of viewing people’s personal information can be damaging to career prospects of an individual. This can affect businesses in a roundabout way, as they may not be reaching their full potential due to discrimination preventing the employment of the best worker with the most appropriate skill set. This is merely one example of how breaches of online privacy can impact an individual’s life directly, their career and economic state of affairs.

Consumer surplus (the difference between what a consumer pays for a good compared to what they’re originally willing and able to pay, and the added benefit derived from this) can be reduced in the long-term as a result of a lack of privacy. Given various algorithms and tracking devices in place, coupled with customers accepting a low level of online privacy, it doesn’t take much for online firms to get a clear idea of a customer’s price point. The more information organisations have about customers, the more effectively they are able to price discriminate. Eventually, they know exactly how much each customer is willing to pay for a good, and will charge exactly that price, a phenomenon known as perfect price discrimination. (4)

transaction without the slightest glance or hesitation. So, what incentive do enterprises have to provide favourable privacy terms to customers? (7) There may be various drawbacks of the lack of privacy online, but as customers, do we really do anything to stop it? Does that mean we don’t really care?

There are cases, of course, where we don’t willfully choose to have full disclosure of our information. For instance, in the case of programmatic advertising, this is an automated function encountered by the majority of users with a social media account, or even an email address. Perhaps information about something as seemingly inconsequential as our shopping preferences isn’t considered particularly personal. But then, where does it end?

After all is said and done, you always have the option to unsubscribe from emails, leave a website, or have your personal data removed from social media if you feel the lack of privacy borders on intrusive, but remember, they’ll know it’s you.

References Alessandro Acquisti. ‘The Economics of Privacy’ Heinz College, Carnegie Mellon University, 2012. Available from: http://www.heinz.cmu.edu/~acquisti/economics-privacy.htm [Accessed on 2 August 2017]

John Ebbert. ‘If A Consumer Asked You, “Why is Tracking Good?”, What Would You Say?’ AdExchanger, 2011. Available from https://adexchanger.com/online-advertising/why-is-tracking-good/ [Accessed on 2 August 2017]

‘Real-time Bidding’ Wikipedia. Available from https://en.wikipedia.org/wiki/Real-time_bidding [Accessed on 2 August 2017]

David Jevons. ‘Too much information? The Economics of Privacy’ Oxera, 2014. Available from: http://www.oxera.com/Latest-Thinking/Agenda/2014/Too-much-information-The-economics-of-privacy.aspx [Accessed on 2 August 2017]

Know Online Advertising. Available from: http://www.knowonlineadvertising.com/ programmatic-buying/advantages-of-programmatic-buying/ [Accessed on 2 August 2017]

Alessandro Acquisti. ‘The Economics of Privacy’ LSE Media Policy Project Blog, 2016.

Available from: http://blogs.lse.ac.uk/mediapolicyproject/2016/07/27/the-economics-of-privacy/ [Accessed on 2 August 2017]

Alessandro Acquisti & Christina M. Fong. ‘An Experiment in Hiring Discrimination via Online Social Networks’ SSRN, 2012. Available from: https://papers.ssrn.com/sol3/ papers.cfm?abstract_id=2031979 [Accessed on 2 August 2017]

Alessandro Acquisti, Curtis Taylor, Liad Wagman. ‘The Economics of Privacy’ Available

from:

https://pdfs.semanticscholar.org/ce1c/842385e0d302b618be02c0b-

ca77a952ca10d.pdf [Accessed on 2 August 2017]

In many cases, we may casually choose to disclose personal information, even if we’re theoretically opposed to it. The

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THE FUTURE OF FORECASTS Oliver Clark, Economics I think that the people of this country have had enough of experts from organisations with acronyms - saying that they know what is best and getting it consistently wrong.

When Michael Gove uttered these words during his interview with Faisal Islam on Sky News on the 3rd June 2016, it only entrenched further the divisions between the two sides of the EU Referendum Debate. Those in favour of Remain honed in on the ‘had enough of experts’ soundbite that re-enforced their views that the Brexiteers did not have the evidence to prove that their upbeat post-EU vision was more than just fantasy. Those on the Leave side saw Gove’s comments as the validation they needed to reject the arguments made by the supposed intellectual elites of the IMF, the OECD and HM Treasury, who all predicted dire immediate consequences after a Brexit vote. Nottinghamshire’s own MP for Broxtowe, Anna Soubry, stated ‘people did not vote to become poorer’. But in reality, there was a clear consensus across the vast majority of the field of economics that Brexit would be damaging for the UK Economy in the long run and devastating in the short run. Yet 17.4 million people voted to leave the European Union, the largest democratic statement in British Political History.

Project Fact or Project Fear?

Prior to the referendum, Treasury analysis painted Brexit as an act of economic suicide. Indeed, George Osbourne claimed that Brexit would be a ‘DIY recession’ with ‘immediate effect’. The long term forecasts anticipated that GDP per capita would be £4,300 lower by 2030 in comparison to a Remain vote. However, it is the short term forecasts which I would like to initially focus on. The Treasury conducted two studies to evaluate the impact of Brexit within the first two years of the vote (i.e. by 23rd June 2018), The Shock Scenario (anticipating a Free Trade Agreement with the EU), and the Severe Shock Scenario (SSS), which anticipated a No Deal Scenario, and a reversion to WTO rules.

The former stated that GDP would be 3.6% lower, unemployment would rise by 520,000, the value of the pound would fall by 12%, and inflation would increase by 2.3%. In the latter study, the forecasts were even more grim, with a 6% reduction in GDP, unemployment soaring by 820,000, the value of the pound falling by 15% and a 2.7% rise in inflation. The SSS included even more dramatic statistics, such as House Prices falling by 18% and average real wages falling by 4%.

So how much of this economic armageddon has actually come to fruition, now that we are nearly two years on from the referendum?

The UK defied all the odds and was the fastest growing economy in the G7 in 2016, based on strong Q3 and Q4 growth. Although it then followed this up by being the worst performing country in the group last year, clocking in a growth rate of a measly 1.4% over the 12-month period, this has been far from the four quarters of negative growth anticipated by the Treasury. Inflation has indeed risen, peaking at 3.1% in November of last year. This was mainly caused by the devaluation of the pound against a number of currencies since the referendum vote, making British imports more expensive to consumers. However, the

pound has greatly recovered in the last 12 months, with it now almost reaching its pre-referendum value against the dollar (albeit not against the Euro). Yet many economists, such as at the IMF, believed that the pound was overvalued prior to the referendum (making our exports less competitive). But has the devaluation really been that damaging?

If we are assuming that the Bank was keeping to its 2.0% inflation target for the year, Treasury predictions suggested that inflation would border on 5% two years on from the vote, yet the rate at the time of writing is 3%, a single percentage point above the banks target, which it had failed to meet since 2014.

Unemployment is the area in which the forecast’s legs are swept out from underneath it. As opposed to the 520,000820,000 job losses which were forecast, caused by a large number of companies reducing or outright halting production in the UK due to Brexit-uncertainty, over 800,000 jobs have been created in the last two years, with the unemployment rate hitting its lowest level in nearly 40 years, falling as low as 4.3% in September of 2017. It can be argued that many of these jobs are temporary/zero hour contract jobs, but what is unarguable is that the significant rise in unemployment anticipated has not happened in any form.

Real wages (wages adjusted for inflation) have been stagnant in recent years, but the news from earlier this year that UK productivity is at its highest level in six years is a welcome sight. If this productivity rise does indeed drive wages up, real wages will certainly not fall, at the current rate of inflation.

If enough people say the same thing, does it become the truth?

The Treasury were not alone in their gloomy outlooks in the short run post-Brexit. The International Monetary Fund (IMF) were even more negative in their prospects, saying that as much as 5.5% could be wiped off of UK growth within two years of the vote to Leave. Christine Lagarde, the Managing Director of the organisation, had made earlier interventions before the vote, stating that there could be a stock market and house price collapse. As can be seen in Figure 1, the FTSE 100 has seen no such collapse, and the Office for National Statistics records for average house prices show a significant rise in the average house price since June 2016. In the Financial Times’ (FT) annual poll of more than 100 leading thinkers, not one thought a vote for Brexit would enhance UK growth in 2016, with 66 expecting negative growth by the end of the year. The Confederation of British Industries (CBI), anticipated as many as 950,000 fewer jobs by 2020. Many financial commentators expected the City of London to become a barren wasteland of empty office blocks as all of the big banks fled the Brexit-apocalypse for Europe, yet in spite of some posturing from the occasional CEO, it has not come to be.

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At the end of 2017, London was voted as the number one place for banks to operate in the world, in the Global Financial Centres Index. To put this into perspective, comparing with our EU counterparts, where it was insisted these banks would flee to in a post-Brexit world, only Frankfurt (11th) and Luxembourg (14th) made it into the top 20, with Paris all the way down in 26th.

We should be thankful that the forecasts of recession by the Treasury, amongst others, did not come to pass. However, with the short-run realities being so far from the great majority of economic studies, forecasts and thinking, Gove’s comments about the failures of these acronymed ‘experts’ resonate to this day. How are the public meant to believe that, in spite of their university degrees and lofty salaries, these economists know any better than the man on the street corner about the economic future of the country, when their forecasts are so far from the truth?

Many of these same organisations said that the UK would be left behind if it did not join the Euro, and yet we see today a single currency that has become an economic and political disaster across the continent. The most startling thing about this is the fact even basic economic models which are taught at the university level show that with a fixed exchange rate, or in a monetary union, austerity has massive negative impacts on the level of GDP. This was evidently not factored into ‘experts’ considerations. Clearly it would have been very difficult to foresee the magnitude of problems with the currency union but there were some early signs of issues whenno eventual Euro countries met the convergence criteria required before the creation of the Euro. This fact was also clearly not considered by experts, which is puzzling as it is vital information that one would assume would be necessary to include when looking into the future.

Voters rejected the arguments of the economic experts along with their poor track record and their failure the recognise clear patterns and signals when they voted to leave the European Union. The fact that the predictions made about Brexit were wholly wrong in the short run simply adds to the poor track record and exacerbates the problems of credibility that the profession faces.

When will we learn?

One could argue that the lack of historical precedent and the numerous variables made forecasting the aftermath of Brexit as near upon impossible. Indeed, the forecasts conducted by the majority of these organisations falsely assumed that Britain would trigger Article 50 immediately (a process which eventually took nine months) and that British consumer confidence would fall drastically in the event of a Leave vote. However, with these two ‘small’ assumptions, these two year economic models and forecasts which they produced can now be thrown out of the window. In December, Tom Scholar, Permanent Secretary to HM Treasury, stated that the analysis from the treasury was no longer ‘useful’. Yet less than two years on from these forecasts at the Treasury, civil servants are now pulling together reports and impact assessments which look at post-Brexit economic growth up to 2030, 12 years from now.

By 2030, we will have seen two general elections (assuming that the parties learn to not throw away a working majority with an early election a la Theresa May last year), four FIFA World Cups and Justin Bieber will likely be married with children. Looking backwards, 12 years ago we did not have the luxuries of the iPad, Spotify, WhatsApp and Uber. What I am trying to get at is that in 12 years the world will have changed in ways which we cannot currently comprehend or even hope to anticipate. In January of last year, Simon Kirby of the National Institute for Economic and Social Research stated that ‘the actual important impact from leaving the EU will not be known for another 10, 15, 20 years’.

If Economists had their forecasts made so inaccurate by assumptions of consumer confidence in a two-year period,

are we realistically going to claim that twelve year forecasts are worth more than the paper they are written on?

In an isolationist, self-sufficient autarky of centuries gone by, that may well have been the case. But in an ever more integrated and globalised world, changes can and do come from out of nowhere almost every day. What if tensions between the USA and North Korea or Russia escalate to an untenable point? What if the ever-growing number of Eurosceptic voices across the continent leads to another country withdrawal from the EU or the Eurozone? What if there is another asset bubble such as the housing market in 2007 which causes a global recession? All three of these could feasibly happen within the next 12 years, and would have devastating effects on global and domestic growth.

Economists use counterfactual projections (i.e. the projected growth if an event does not happen) to compare their economic analyses to. But in the increasingly integrated and ever changing world which we live in, I must ask, are these counterfactual projections and assumptions not just as variable as the things that we are trying to forecast?

By 2030, we will have seen two general elections, four FIFA World Cups and Justin Bieber will likely be married with children

What can we do?

The Civil Service, those who work at the Treasury, and at organisations such as the IMF, are prided on their impartiality when conducting these reports. Yet while accepting the Nobel prize for economics, Friedrich Hayek admitted that not only were economists unsure about their predictions, but their tendency to present their findings with the certainty of the language of science was misleading and “may have deplorable effects”. During the EU Referendum debate, analyses were branded as fact or faction depending on who was producing them and what they said. Earlier this year, Steve Baker MP, former leader of the European Research Group and now Minister at the Department for Exiting the EU, was asked whether he had heard claims that Treasury officials had ‘deliberately developed a model to show that every model other than staying in the (EU) customs union were bad and that officials had used this as a means to influence policy”. Baker told MPs that the account was ‘essentially correct’ but was later forced to apologise.

Yet when the public look at the profession of economics, hear the same voices making the same mistakes, time and time again, how are they meant to react other than to assume that these experts have a vested interest, and cannot be believed? Another possible reason is the concept of group thinking. In a study conducted by Prakash Loungani of the IMF, it was found that economists had failed to anticipate 148 of the last 150 recessions in their forecasts. In his research, Loungani found that the downside of getting a prediction wrong was more damaging than the upside of getting one correct (thus explaining the group-think mentality which was witnessed during the referendum), where deviating from the consensus would just be met with ridicule if proved wrong, and minor applause if proved right.

Although economics has been present since the dawn of civilisation, it has only really been treated as a science for the last two to three centuries. I am just a first year Economics Student at the University. Maybe after years of teaching and experience, I will have a better understanding of how these forecasts are constructed, how variables are decided and how assumptions are made. Maybe in a few years time, economists will have refined their methods so as to produce more accurate models and forecasts.

But from my current point of view, I believe that the field

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economics has some questions to answer, with great urgency we need to take GDP forecasting with a pinch of salt, and invest more resources into individual economic variables, such as unemployment. Maybe there needs to be a deeper understanding between the economic profession and the business world, where economists distinguish between what a business CEO says he will do in the event of a decision such as Brexit, and what he actually decides to do. Maybe we need to scrap long run economic

forecasting all together, or assign probability values to each potential as happens with the weather. I do not have these answers, but that is why I implore readers of the Nottingham Economic Review to contact me at my university email, leyoc1@nottingham.ac.uk, to tell me where we as a profession are currently going wrong, and what we must do to improve in the future and regain our credibility as experts once more.

MARXISM ECONOMICS In the Era of the Internet Chih Han Hsueh, Philosophy, Politics and Economics Karl Marx is one of the most influential and maybe controversial economists in history. He lived in the era just after the industrial revolution and developed his theory to involve lots of analysis as well as critique toward the era of industrialization. Today, the era of the Internet is often regarded as the third industrial revolution (Rifkin, 2011) and many changes to the market seems to encounter a structural transformation similar to that faced by Marx in his own era. Therefore it is useful to observe how Marx may think about these transformations.

By examining the structural transformation of the market in the era of the Internet, it is useful to distinguish two aspects in order to become more specific: social media and sharing economy. The reason for distinguishing is that Marx also analyzed the capitalism market by two aspects: labour market and goods market (Walker, 1978). Hence distinguishing aspects of the internet is useful in a similar manner. By analyzing the social media and sharing economy perhaps we can have a brief idea about why Marxism Economic Theory might help us to understand the economic structure in the era of the Internet.

Today, the era of the Internet is often regarded as the third industrial revolution Social Media and Labour Before directly looking at economics structure in the context of Marx, it is worthwhile to think about the fundamental market structure of social media. Take Facebook for example. Who is the consumer and who is the supplier? Who are the labour in the context of Facebook and what is the market force behind this market? Traditional economic theory might have difficulty in answering this question. For instance, we could assume all the users of Facebook are the labour and the information generated by Facebook as output. According to the law of diminishing returns, by implementing more labour, Facebook should have lower marginal utility of the labour and have higher marginal cost of output. However, in reality, each additional user involved in Facebook will bring higher utility than the previous one-creating an increasing rate of return.

Besides that, creating extra unit of information for Facebook will not need to increase extra cost. For example, Facebook does not need to increase any cost in order to encourage the to encourage the users to post more comments. And we know that total cost is the sum of fixed cost and variable. Since there is no increase in the variable cost for Facebook to increase its information and fixed cost is fixed, the average cost of Facebook is decreasing

marginal cost is zero when Facebook increases its output, namely information. In fact, Jeremy Rifkin describes this situation as a “zero marginal cost society” (Rifkin, 2014).

The Classical Economic Theory would find it difficult to provide an explanation for, or to analyze this phenomenon.

However, Marx may be able to provide an explanation for this phenomenon. Marx states that the market should make the labour realize their own value. According to Marx, labour can fulfill their lives and be creative when they are producing their own products because when the labour are producing the output, and they are also creating the true value of themselves. However, as long as the labour cannot understand their own value from their own products, they will be alienated from their own products (Marx, 1844).

Since the labour is alienated from its own products, the utility of the labour will ultimately decline. In terms of social media like Facebook ,YouTube or Instagram, the users are not alienated from their own products. For example, when we share a picture or post a comment with our friends, we feel that we are the contributors of the products. By applying this theory, we can somehow find out why some social media such as Facebook will lose fits attraction among teenagers. As long as the users of Facebook do not feel like they are creating their true value on the Facebook, the users will be alienated from using Facebook. When commercial ads are introduced onto the platform and parents get involved on Facebook, the users cannot feel their true value. Hence, these users might feel alienated and leave Facebook so they are no longer a user.

The same thing could also happen on YouTube or Instagram, and Marx provides the solution for this social media phenomenon. The idea of labour alienation is something these social media platforms could focus on in order to maintain the advantage of having a “zero marginal cost”.

Sharing Economy Marx clearly points out the foundation of the capitalism is based on manufacturing and consuming. However,

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he also claims that the manufacturing cost will always increase the profit earned by the producers will decrease.

Furthermore, the capitalism market will face its end since there is no more value that can be earned to encourage the producers to continue production. Thereafter, Marx argues that we will one day enter the stage of communism where people share goods with each other and focus on the exchange value of the goods rather than then the monetary value of the goods. It seems like the argument of Marx corroborates the emergence of a sharing economy. By using Uber and Airbnb, the participants in this market does not create something new but is instead sharing something they already own. As Morozov points out, the sharing economy has been framed both as part of the capitalist economy and as an alternative of the capitalist market (Morozov,2013). The scale of the sharing economy, like the idea of communism, does not really need to exclude the idea of capitalism. It can not only involve the function of the capitalist market but also escape the problem of the pure capitalist market. Take Airbnb for example. Those who provide their house on Airbnb can also be a consumer instead of solely a supplier, but it could also be the case that they are simply suppliers of the house without being consumers.

This allows the users on the Airbnb to value their house at its exchange value rather than its money value, and it could be the case that someone can stay in an expensive house whilst paying a relatively small amount of money. The same thing applies to Uber, as the users of Uber can have the chance to be driven in a Mercedes-Benz or Ferrari without paying expected expensive monetary value of these cars.

Instead, they only pay the exchange value to take the drive.

By applying the idea of Marx, it can be argued that the sharing economy would be the next step of a capitalist society since it enables us to experience the exchange value of goods rather than the monetary value of the goods.

Conclusion The emergence of new economic activities such as social media and the sharing economy is indeed changing the world we are living in presently. The new classical economy theory lacks the explanation to fully enable us to understand what is going on within the markets of these phenomena. However, by examining the theory of Karl Marx, we find out an alternative method to look at these activities. Karl Marx himself does recognize that a capitalism economy has huge benefits but he also believes that there would be a new and better stage following the capitalism economy. However, Marx does not know what this new stage might look like, so his theory only provides the problem inside the sphere of the capitalism economy. In the era of the Internet, we do have an alternative to the capitalism economy but it remains to be seen how this will work fully. Therefore, by looking retrospectively at the theory of Marx, we may be able to predict how these new markets will work.

References Evgeny Morozov, 2013,” The ‘sharing economy’ undermines workers’ rights”, The Financial Times, assessed 3/10/2018.URL: https://www.ft.com/content/92c3021c34c2-11e3-8148-00144feab7de Jeremy Rifkin, 2011, “The Third Industrial Revolution: How Lateral Power Is Transforming Energy, the Economy, and the World”, Palgrave Macmillan Jeremy Rifkin, 2014” the zero marginal cost society: the internet of things, the collaborative commons, and the eclipse of capitalism”, Palgrave Macmillan Karl Marx, 1959,”Economics&Philosophic Manuscripts of 1844”, Translated by Martin Mulligan, Moscow: Progress Publishers,

THE ROBOT REVOLUTION Georgina King, Economics Artificial Intelligence (AI) has become one of the most highly debated and anticipated topics of recent years. Technological advancement on this scale could have vast impacts – the coming change to the world similar to that brought by the advent of the electricity. But, what exactly is the Robot Revolution? And are AI robots the friends or foe of humankind?

What is Artificial Intelligence?

Artificial Intelligence is the term used to describe machines which have developed the ability to learn from experience, making them able to make decisions and perform human-like tasks. AI absorbs the knowledge provided by large amounts of data and identifies patterns within this data, allowing it to train itself to accomplish certain tasks. The implications of this technology are vast as it can be applied to multiple industries, and a variety of tasks these industries. Already AI is used by many of us through devices such as Amazon Alexa or Siri. Industries such as Banking use the machine-learning property to identify unusual behaviour in transactions, aiding in combatting fraud. The potential uses of AI as it grows from its current infancy are infinite, but to observe where potential growth is likely to lead, let’s first look at where it began.

The History of AI ‘Artificial Intelligence’ was coined in 1956 by John McCarthy at a Dartmouth University Conference. Initially discussion favoured the future of AI being top-down control, pre-programming robots with instructions. By the 1990s, a lack of

expected progress saw a reverse in engineering to focus on the bottom-up approach to AI. Using neural networks, robots would simulate brain cells and learn behaviours, rather than them being pre-programmed. Modern-day AI has evolved more rapidly since the introduction of this new approach.

Just as technology has developed, the catchall term of Artificial Intelligence has evolved to include not only mimicry of humans, but machine learning and then deep learning. Deep learning uses networks of unstructured data to train machines to work unsupervised – the machines essentially learn to “think” and process uncategorised data.

In 1997, IBM developed a Deep Blue Computer that was able to beat Russian Chess Master Garry Kasparov in a game of chess, through mimicking human decision-making (machine learning). In 2011, IBM’s Watson was able to beat humans on US game show Jeopardy, which was far harder than beating a human opponent at chess, as the required answers were far more complex – an example of deep learning in AI. Whilst AI was proving its learning capabilities in games, more practical applications were developed by Google. In 2008, the Apple iPhone featured a speech recognition app, powered using multiple computers running neural networks which analyse masses of spoken data. At 80% accuracy, this was already a massive AI breakthrough, but accuracy has since risen to 92% as of 2015. Google didn’t stop there, investing billions of dollars in driverless car technology with Waymo – the driverless-car subsidiary – having autonomous vehicles on the road in Phoenix, Arizona in 2017.

The history of AI is relatively recent, thus the future

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spectrum of AI-induced change is vast and unpredictable.

Developments in AI have a domino effect on each other and cause a continual expansion of its potential uses.

As this occurs, global economies invested in this technology will reap the rewards, but not without some negative consequences.

Industry Impacts and Microeconomic Analysis AI has the potential to boost rates of profitability by up to 38 percentage points, totalling $14 trillion in gross value added to 16 different industries by 2035. Three sectors in particular are likely to benefit most grossly from AI: Manufacturing, Financial Services, and Information and Communication.

The benefits are obtained through intelligent automation, whereby analysis of data can streamline supply, production and sales and predict for future issues in order to mitigate their impacts. Also, innovation diffusion will lead to reductions in production costs and faster product development which will increase revenue. Furthermore, labour and capital augmentation will increase business efficiency through identifying how to maximise the potential use of assets, as well as freeing labour away from low value-added tasks so that workers are more productive in their main tasks. All these features reduce the total costs incurred by a business during production and distribution, making them more profitable and generating revenue for further investment.

The boost to productivity will create more job opportunities. Based on economic theory, employers hire their workforce up to the point where the marginal productivity of labour is equal to the wage divided by the price (MPL = W/P).

The MPL is diminishing, so an additional worker is not as beneficial to productivity as the previous worker. As labour becomes more productive, the marginal product of the original last worker rises thus more labour will be employed to meet the MPL which will satisfy the theory equilibrium.

However AI, in the case of many manual low-skill tasks, will become a substitute for the current labour workforce. A utility function depicts the substitutability between capital and labour through the gradient of its slope. It is a dynamic function and the curvature and slope can change over time. In the case of AI, the utility function flattens out as the relationship between labour and capital (AI) changes to become more substitutable.

This dynamism in the marginal rate of substitution has historic evidence. Marshall’s rules outline that the greater the elasticity of substitution (of capital and labour), the more elastic the demand for labour (price elasticity). Perfect substitutes have an elasticity of substitution equal to infinity, thus as machines and workers become more substitutable, the demand for labour becomes more elastic meaning that small changes to price cause more than proportional changes to the workforce size – implying lessened job security. During the industrial revolution, some factory workers took to machine destruction and rioting to stop the sudden increased substitutability that threatened their job security. Known as Luddites, they destroyed textile machines in factories in Nottinghamshire and other midlands textile-production regions as they blamed the machines for their livelihood decline. Will people begin to sabotage AI for the sake of job security? Now we have far stricter laws and regulations in the labour force, as well as greater unionisation, so this is a less likely but still a possible dilemma.

AI also poses a threat to gender inequality. Higher proportions of women work in administrative roles in offices – one of the first positions likely to be replaced by AI in the near future. Furthermore, heavily gender imbalanced industries such as engineering and architecture will experience greater levels of job creation, with these roles being filled by more men than women due to the gender disparity in STEM graduates. Gender inequality

will be one of the biggest challenges facing industry following the adaptation of AI into business practice.

The Effect on the Macroeconomy Globally, the economic boost of AI is predicted by PwC and Accenture to amount to $15.7 trillion. For comparison, that’s 13 times the size of Australia’s GDP of $1.21 trillion in 2017. This boost is the summation of improvements to labour productivity ($6.6trn) and increased consumer demand ($9.1trn). Macroeconomic theory states AD = C + I + G + X - M, so an increase in consumer demand translates to an increase in Consumption (C) which increases Aggregate Demand (AD) and therefore GDP. AI will encourage a greater variety of products, which have the potential to be personalised to meet the needs of the consumer, and therefore will induce greater demand from consumers and provide greater output opportunity for industries. The greatest impact of AI is likely to be in China, who aim to lead the world in AI technologies by 2030 which will boost GDP by an expected 26%.

AI’s impacts will expand across multiple industries hence increasing the overall productive capacity of the economy, as well as making the economy more efficient. This is represented within economics on a Production Possibility Frontier (PPF) which shows a movement towards the PPF line itself (from orange to yellow) as an efficiency improvement, and a shift of the PPF (from 1 to 2) as an expansion of the productive capacity of an economy in multiple industries.

This allows for even more efficiency gains as the economy could move to a point beyond the original PPF (to green) that would not have been possible, shown across.

But, along with the myriad of potential for AI there are some unsavoury possibilities. Discrimination and inequality are undeniably prevalent in the current economy at regional, national and international levels. For example, in addition to industry effects, gender inequality may be exacerbated by the technology itself. The machine-learning capabilities of AI means it absorbs vast amounts of information; underlying social bias and discrimination within this has the potential to be absorbed and reiterated by the machines themselves. Preventing stereotypes from seeping into the algorithms and programming behind AI will be necessary to halt any discriminatory behaviour that many nations are working to mitigate.

Furthermore, the burden of occupational vulnerability, generated from the potential of being substituted for AI, falls most on those with medium-skill jobs. Low-skilled jobs are too expensive to automate, and high-skilled jobs are often too complex for AI. The resulting effect is “job polarisation” where median wages will stagnate whilst low- and high-skill jobs expand with a clear wage disparity between these workforce bicategories. This is a cross-industry macroeconomic effect, which could exacerbate wage inequality and increase the 90/10 wage ratio of developed nations.

The Future of AI Few developments can claim to have as vast an impact as AI, but the realised potential of AI will be to what extent?

And how quickly? It is not possible to predict for certain despite many published papers forecasting the future of

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Artificial Intelligence. The World Economic Forum met in Davos in January 2018 and concluded that whilst the advancements are “significant for humanity”, an inability for industries to adjust, and the subsequent instability and job losses, pose a significant threat. Conversely, history provides evidence that technology tends to create more jobs than it destroys, by increasing demand for non-automated occupations; there has been some evidence in support of this pro-job effect within already-deployed AI. Undoubtedly, we are entering a robotic revolution. The impacts of this?

No-one knows for sure.

References Accenture. n.d. HOW AI BOOSTS INDUSTRY PROFITS AND INNOVATION. https:// www.accenture.com/us-en/insight-ai-industry-growth.

BBC. n.d. AI: 15 key moments in the story of artificial intelligence. http://www. bbc.co.uk/timelines/zq376fr#z2rxp39.

Bloy, Marjie. n.d. The Luddites 1811 - 1816. http://www.victorianweb.org/history/ riots/luddites.html.

Carey, Scott. 2017. How UK banks are looking to use AI and machine learning.

December 6. https://www.computerworlduk.com/galleries/data/how-uk-banksare-looking-embrace-ai-machine-learning-3657529/.

Delaney, Kevin J, Jenny Anderson, Jason Karaian, Eshe Nelson, and Heather Timmons. 2018. Artificial intelligence and climate change will ruin us, but blockchain and women will save us. January 26. https://qz.com/1190800/artificial-intelligence-and-climate-change-will-ruin-us-but-blockchain-and-women-will-saveus/.

Desjardins, Jeff. 2017. AI will have an enormous impact on the future economy. August 22. http://uk.businessinsider.com/infographic-ai-effect-on-economy-2017-8?r=US&IR=T. Furness, Dyllan. 2017. AI Experts Warn About Automation and “Job Polarization”. May 15. https://www.techemergence.com/more-ai-experts-warn-aboutautomation/.Hayasaki, Erika. 2017. Is AI Sexist? January 16. http://foreignpolicy. com/2017/01/16/women-vs-the-machine/.

Investopedia. n.d. Deep Learning. https://www.investopedia.com/terms/d/ deep-learning.asp.

Lumen. n.d. Demand for Labor. https://courses.lumenlearning.com/boundless-economics/chapter/demand-for-labor/.

PwC. n.d. How will artificial intelligence affect the UK economy? https://www. pwc.co.uk/services/economics-policy/insights/the-impact-of-artificial-intelligence-on-the-uk-economy.html.

Saeed, Farhan. 2017. 9 POWERFUL EXAMPLES OF ARTIFICIAL INTELLIGENCE IN USE TODAY. January 16. https://www.iqvis.com/blog/9-powerful-examples-of-artificial-intelligence-in-use-today/.

SAS. n.d. Artificial Intelligence. https://www.sas.com/en_us/insights/analytics/ what-is-artificial-intelligence.html#.

The Economist. 2016. Automation and anxiety. June 25.https://www.economist. com/news/special-report/21700758-will-smarter-machines-cause-mass-unemployment-automation-and-anxiety.

Waters, Richard. 2017. Google owner tests first driverless car on city streets. November 7. https://www.ft.com/content/397134f8-c36c-11e7-a1d2-6786f39ef675.

Wikipedia. 2015. Hicks–Marshall laws of derived demand. June 23. https:// en.wikipedia.org/wiki/Hicks%E2%80%93Marshall_laws_of_derived_demand.

THE RISE OF CONTACTLESS PAYMENT Richard Palmer, Economics It’s been more than 10 years since Barclaycard rolled out their first contactless cards and since then, the use of contactless payment has rocketed, with even the Church of England trialling the use of the ‘tap and go’ system for donations last summer. Back in April 2017, the UK Card Association found that there were 108.4m contactless cards issued in the UK, a 20.6% increase from the year before (“Contactless Payments - Key Statistics & Figures| The UK Card Association” 2017). Initially the technology was just limited to card payments but Apple and Android quickly jumped on the bandwagon with the introduction of Apple and Android pay, allowing users to pay via mobile devices. Many were sceptical at first due to the danger of fraud, however this has not hampered the growth of contactless with Barclaycard claiming that an astonishing 51% of transactions under £30 are now undertaken using contactless.

The same study also claims that contactless saves you an extra seven seconds every time you use it instead of the now outdated Chip and Pin (“Contactless Now The Favoured Way To Pay For British Shoppers” 2017). This saving may seem minimal but in a world where patience is wearing thin and people expect everything instantly, the system has proved a huge success.

Many predict that we will eventually live in a cashless society where the only form of payment is through certain cards and it’s clear to see just why they would think that with the many benefits that contactless payment brings.

Firstly, if you just consider convenience, contactless takes away the need for an individual to visit an ATM to withdraw money or have to count out the correct amount required for the transaction, speeding up the whole process. The benefit isn’t just limited to the buyer either with firms able reduce labour costs through implementing self-service systems in their shops. Electronic payment also provides much more stability in the economy with it’s ability to allow the

smoothing of consumption. Put simply, credit eliminates the need to wait for paydays or certain payments, meaning transactions aren’t held up by such time restrictions.

The government can also benefit from the increased use of electronic and contactless payment as it will be able to collect more tax revenue where it wasn’t previously able to due to the ‘grey area’ of the economy where people favour ‘cash-in-hand’ deals purely to avoid being taxed.

Despite this being a seemingly natural progression in technology, it has to be considered just how much of an impact this could have on the economy as a whole. The combination of a speedier transaction and the elimination of the need to be in possession of cash has had a big impact on consumer spending habits. In essence, the system makes both the decision and the process of spending money much easier by removing the psychological constraint of physically having to hand over any currency.

This was noted by the Bank of England back in June 2017 (Bank of England 2017) who cited the rise of contactless payments as a large contributor to the growing levels of consumer debt. However, if you take a broader look at the impact of the system, it could be argued that contactless could actually be boosting the economy rather than just adding to the huge levels of debt brought about through poorly thought out spending. This is a view given in Mark Zandi’s (Zandi et al. 2016) paper that looks at how contactless has changed the world economy. He describes the system as a promoter of spending which acts in a way similar to which

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a fiscal injection would. The process would essentially be a cycle, where, as consumers spend more money due to contactless payment, firms look to meet this rising demand by producing more and in order to produce more, they look to take on more workers which in turn creates jobs, leading to rising incomes which allows consumers to spend more and the cycle begins again. The evidence is there to back this up too, with the study finding that increased card penetration was responsible for 0.4% of the increase in consumption and an average increase of 2.6 million jobs from 2011-2015.

It isn’t all over for cash just yet though, with Brexit reportedly leading to a mini-comeback as UK consumers look to hoard cash due to a combination of a lack of trust in high street banks and a desire to hoard money in the event that a ‘rainy day’ finally arrives. Many also worry about what electronic payments mean for their privacy, adding to the feeling that their every move is increasingly being logged and tracked. Fraud remains very problematic too, with £5.6m being lost to contactless fraud in just the first six months of 2017 (“Contactless Card Fraud Is On The Rise – Which? News” 2018). However, although this is a large and growing figure, it still only represents a very small percentage of the overall spending through contactless payment, so remains at a relatively small scale for now at least.

Contactless payment has seen an incredible rise to fame in the last decade and has undeniably had a massive impact on both day-to-day life and the economy. As time goes on this is only likely to continue to be the case with Barclaycard claiming that 37% of consumers would favour an increase in the cap to £50 (“Time Is Money” 2017). Master card did some research of their own too finding that over a quarter of UK shoppers are ready to make payments

contactless wearable devices (“More Than A Quarter Of UK Shoppers Prepared For Wearable Contactless Payments” 2018), begging the question, just how far is this phenomena going to go?

References Bank of England. 2017. “Financial Stability Report”. Bank of England. https:// www.bankofengland.co.uk/-/media/boe/files/financial-stability-report/2017/ june-2017.pdf?la=en&hash=EB9E61B5ABA0E05889E903AF041B855D79652644.

“Contactless Card Fraud Is On The Rise – Which? News”. 2018. Which? News. https://www.which.co.uk/news/2018/02/brits-lose-over-5-6m-to-contactlesscard-fraud/.

“Contactless Now The Favoured Way To Pay For British Shoppers”. 2017. Home.

Barclaycard. https://www.home.barclaycard/media-centre/press-releases/contactless-now-the-favoured-way-to-pay-for-british-shoppers.html.

“Contactless Payments- Key Statistics & Figures| The UK Card Association”. 2017.

Theukcardsassociation.Org.Uk. http://www.theukcardsassociation.org.uk/contactless_contactless_statistics/.

“More Than A Quarter Of UK Shoppers Prepared For Wearable Contactless Payments”. 2018. Computerweekly.Com. http://www.computerweekly.com/ news/252435637/More-than-a-quarter-of-UK-shoppers-prepared-for-wearablecontactless-payments.

“Time Is Money”. 2017. Home.Barclaycard. https://www.home.barclaycard/media-centre/press-releases/Contactless-payments-to-save-shoppers-almost-1bn. html?utm_source=Triggermail&utm_medium=email&utm_campaign=Post%20 Blast%20%28bii-payments%29:%20SumUp%27s%20European%20expansion%20could%20threaten%20competitors%20—%20The%20UK%20loves%20 contactless%20payments%20—%20Alipay%20brings%20biometrics%20to%20 KFC&utm_term=BII%20List%20Payments%20ALL. Zandi, Mark M., Sophia Koropeckyj, Virendra Singh, and Paul Matsiras. 2016.

“The Impact Of Electronic Payments On Economic Growth”. https://usa.visa.com/ dam/VCOM/download/visa-everywhere/global-impact/impact-of-electronic-payments-on-economic-growth.pdf.

THE GLOBAL WATER CRISIS Gaurav Suri, Economics

W

ater is everywhere. It flows through our streams, rivers and oceans and at first sight, it is difficult to see how we could ever be in shortage of it. However, the global water crisis is currently one of the greatest threats facing mankind and this shall continue to be the case unless an active, coordinated global effort is made to manage our water supplies more effectively and curtail our usage.

over the coming decades. Water stress is defined as being when ‘the demand for water exceeds the available supply a certain period or when poor quality restricts its use’ (European Environment Agency, 2018). The World Resources Institute, a global research organization, ranked 167 countries, and found that 33 will face extremely high water stress by 2040 (Maddocks, Young and Reig, 2015). Below, I discuss the main threats to future global water security.

The problem is that water, although covering 71% of the earth’s surface, is only useful to us if it is present in abundance exactly where it is needed, in the right form and at the right time.

Around 97% of water on the planet is saltwater and is therefore useless to us. Just 3% is freshwater, which is replenished through seasonal rainfall or is stored underground in aquifers. In the past, humans settled close to plentiful supplies of water, such as along riverbanks, but influenced by other economic forces, people are inclined to move to areas of greater water scarcity. Furthermore, human activity is currently massively inefficient in its usage and management of water, from wasteful agricultural practices to careless disposal of industrial waste. As the world’s population continues to expand from 7.6 billion to an estimated 10 billion by 2050, the situation will only worsen (The Economist, 2016).

Figure 1 shows the growing prevalence of water stress

Figure 1 Threats to global water security

Agriculture and Food

Higher demand for water over the coming years will come from greater demand for agricultural products, manufactured goods and electricity, all of which are extremely water intensive to produce. The heaviest user of freshwater is the agricultural sector. Vast amounts of water are used

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for irrigation and to support livestock, often using wasteful techniques. For instance, growing one kilogram of wheat requires 1,250 litres of water and producing one kilogram of beef uses 12 times more than that. In fact, agriculture accounts for a colossal 70% of total global freshwater withdrawals (The Economist, 2016).

reservoirs and aquifers can replenish their supplies. As the atmosphere becomes warmer, it will hold more moisture making sudden heavy downpours more likely which can lead to flash flooding (McIntyre, 2012). This will lead to increased amounts of sedimentary material in rivers and reservoirs, impacting both water quality and storage capacity.

Population growth and economic growth

Underpinning all of the above is the world’s rapidly increasing population along with rising incomes. People will directly demand more water as they get richer. However, population and income increases also place indirect pressure on water supplies, as agricultural activity will have to rise in line with population to meet future global food demand (it is also the case that as people become wealthier, they demand more meat products).

Figure 2 Figure 2 shows how agricultural water usage has increased over the previous few decades, most notably in India. Part of the problem is that developing countries do little to restrict the quantity of water that farmers can pump from underground aquifers and if rules do exist, they are often poorly enforced. It is estimated that around 20% of the world’s aquifers are over-exploited, which is clearly unsustainable (The Economist, 2016).

A further part of the problem is extravagance. Much more food is produced by farmers than is consumed, with some estimates citing that around a third of all food produced doesn’t even have the chance to be consumed, wasting as much water as flows down the Volga River in Russia in a year.

The production of energy also demands large volumes of water. For example, in electricity generation, water is essential for the functioning of coal-fired power stations and for cooling turbines and the reactor cores in nuclear power stations. Over 40% of America’s water withdrawals are used for cooling power stations (The Economist, 2016). To meet the future domestic and industrial energy demand, energy production will therefore also have to rise, further straining our limited water supplies.

Rethinking water pricing The global supply of water is clearly under great stress and the situation is likely to worsen. It is therefore important to consider how we price and ration this precious resource.

Should a resource so essential for our survival and that is becoming increasingly scarce in many parts of the world be available so cheaply?

Underpinning these issues is the fact that agricultural water use remains heavily subsidized in many countries, encouraging inefficient usage. Recent OECD reports indicate that industrial and household users may pay more than 100 times as much as agricultural users, although such comparisons should not be taken too literally due to the different water quality needs of the different users (Jones, 2003). Nevertheless, the agricultural sector pays significantly lower prices for water than other sectors in most OECD countries.

Pollution Excessive water pollution also poses a threat. Water pollution comes from a variety of sources including pesticides and fertilizers from agricultural activity, untreated human wastewater and industrial waste (WWF, 2018). Chemicals and harmful waste products are carelessly discarded into streams and rivers, destroying vital ecosystems and further straining water supplies. For example, in China, over a third of waterways have been polluted by industrial effluent (The Economist, 2016).

Climate change

The growing threat of climate change is likely to exacerbate any other risks to global water security. A warmer climate will lead to a speeding up of the global water cycle, affecting rainfall patterns and causing wet regions to receive even more precipitation and dry regions to become even drier Drought events and floods will become more severe when they occur, placing further pressure on water supplies.

Late or light rainy seasons will impact the speed at which

Why is water so cheap?

This can be explained by considering Adam Smith’s so-called paradox of value: ‘Why do diamonds cost more than water?’

Water is far more useful, yet diamonds command a much higher market price. Simple economic theory provides an answer through the concept of diminishing marginal utility (Goetz, 2013). The prices of the two commodities are determined not by their total usefulness to society, but rather the usefulness of each unit of water or diamonds. The total utility of water to people is immense as it is essential for survival. However, since water is (or has in the past been) in such abundant supply, the marginal utility of water is low (see Figure 3). As the supply of water increases, each unit of water becomes worth less. Diamonds, however, are much more limited in supply so the ‘usefulness’ of one additional diamond is much greater than the ‘usefulness’ of one additional glass of water. Therefore, people place grater value on diamonds.

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Why should water be priced higher?

The problem with low water prices is that they signal abundance and this is clearly not the case. There is no incentive for consumers to conserve it and investors have little incentive to construct pipes and other infrastructure to transport it to where it is most needed. As water scarcity grips the planet, it may be time to rethink how we price water and allocate it to where it is needed the most.

Economists often speak of the marginal cost of water but as pointed out by Robert Glennon, a water expert at Arizona University, when referring to America, “in very few places in the country are people even paying for the marginal cost”. Without real prices and measurements that would determine cost, there’s no incentive to conserve consumption. Also, the prices we use to allocate water today were set in a time when water shortage wasn’t a huge issue and therefore are outdated and in need of revision (Lam, 2015).

There is a significant economic case for raising water prices from their artificially low levels in order to signal scarcity and hence encourage more responsible water usage.

Why might it be difficult to raise the price of water?

If the price of water was raised all over the world, there would be a clear disparity between poor households who may be unable to afford even the basic quantity of water they need and richer households whose usage could go unperturbed. This may lead to greater inequality, as price increases will hit the poor the hardest. Furthermore, clean drinking water has been recognized by the UN as an essential human right and should therefore be available to everyone with no distinction between citizens. Whilst this is goal has clearly not been met, as approximately 780 million people around the world do not have access to clean drinking water, many politicians are afraid of charging higher prices for something so essential as water, meaning it is often underpriced even in areas of great scarcity.

Pricing solutions

A flat increase in the price of water at all levels of consumption may therefore not be the most sensible approach to encouraging more efficient usage. Since drinking water is a fundamental human right, a basic level of water should be guaranteed to all citizens at a subsidized price or even for free. However, usage in excess of this quantity should be faced with steep price increases (see Figure 4). This protects low-income households as they can meet their minimum water usage needs at a low price and penalizes high-usage households and wasteful users. This pricing system is designed to reduce demand rather than cover costs. Revenues paid by excessive or high-usage households would cover the costs of low-volume users. Any excess profits can then be reinvested to improve the quality or quantity of the water supply (Zetland, 2008).

An alternative is to introduce increasing block rates, meaning each subsequent ‘block’ of water consumption is priced at a higher rate than the previous. Previously, urban water was priced at a decreasing rate due to economies of scale, meaning a lower per unit price for high-volume users (Lam, 2015). But now, to conserve supplies, perhaps only the first block should be subsidized and beyond this, price increases should be sharp to cut usage. However, this solution is not without problems and is likely to face strong political resistance. For example, in areas such as California, where approximately 70% of water usage is outdoors such as on swimming pools, lawns and golf courses, people would face extremely high water bills as such activities require large volumes of water.

Other solutions Clever pricing does have the potential to reduce demand for drinking water but it must be used in combination with other solutions. The following solutions are aimed at cutting back water usage and improving the efficiency with which it is used. Most of them have been implemented in countries around the world but to varying degrees. Furthermore, they have tended to be implemented piecemeal rather than in a co-ordinated global effort to preserve the world’s water resources.

Being such a heavy user, the agricultural sector is an important target for implementing better water management strategies. In many developed countries, farmers are already starting to use water more efficiently. For instance, precision planting and the use of hybrid seeds that require less watering, among other technologies, have been widely implemented already. Wasteful irrigation techniques are also starting to be replaced by methods such as drip irrigation, which allows water to drip slowly to the roots of plants rather than being spread indiscriminately over large areas of land. It is estimated that drip irrigation can cut usage by around 30-70% (Sanwal, 2015). Harvesting rainwater by collecting it in tanks is also being used to reduce pressure on aquifers. The recycling of wastewater also has huge potential. Israel, for example, recycles an impressive 86% of its sewage, far higher than any other country in the world (Tal, 2016). However, politicians do not express much enthusiasm for this approach, as they dislike the idea of letting people drink recycled waste.

Another major problem is leaky pipes in urban areas. This issue causes some large Asian and Middle Eastern cities to lose over half of their water. However, this is not just a developing world problem as London still wastes around 30% of its supply through leaks. Plugging these leaky pipes is likely to go a long way towards conserving water supplies.

In the past, this was fairly tedious and expensive but fixing pipes will soon become much simpler and cheaper. Robotic systems capable of detecting and repairing leaks by sensing pressure changes around them are currently being piloted in order to effectively deal with this issue and can be used even while the pipes are still in use (Chandler, 2017).

Water scarcity has driven many dry countries around the world to construct desalination plants to convert seawater into drinking water. However, desalination is much more expensive than practically all other methods of supplying freshwater due to the large amounts of electricity required, making it unviable for most developing countries. This being said, it has been successfully implemented in certain countries, for example, Israel’s largest desalinisation plant, Sorek, supplies over 1.5m people, meeting around 20% of municipal demand (The Economist, 2016). A problem with desalination plants is securing the money needed for investment in them - many private investors are unwilling to risk huge sums of money for uncertain returns that span decades into the future. Desalination also involves a high ecological cost as delicate ecosystems may be damaged by the intake of seawater and the outflow of large quantities of brine. Therefore, whilst suitable for some countries, it is not the most ideal option.

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Conclusion

Lam, Bourree. 2015. “Water: The Price Is Wrong”. The Atlantic. https://www.theatlantic.com/business/archive/2015/03/finding-the-right-price-for-water/388246/.

With smarter pricing, worldwide implementation of water conservation techniques and cooperation between countries and the different users of water, we can better use and manage our supplies and alleviate the threat of water scarcity. We should be constantly reminded by the words of Ismail Serageldin, speaking in 1995 – “if the wars of this century were fought over oil, the wars of the next century will be fought over water”. Fortunately, this has not yet happened. However, failure to act now moves us dangerously close towards this becoming a reality.

“Liquidity Crisis”. 2016. The Economist. https://www.economist.com/news/briefing/21709530-water-becomes-ever-more-scant-world-needs-conserve-it-use-itmore-efficiently-and?zid=298&ah=0bc99f9da8f185b2964b6cef412227be.

Maddocks, Andrew, Robert Young, and Paul Reig. 2015. “Ranking The World’S Most Water-Stressed Countries In 2040 | World Resources Institute”. Wri.Org. http://www.wri.org/blog/2015/08/ranking-world%E2%80%99s-most-waterstressed-countries-2040. McIntyre, Neil. 2012. “How Will Climate Change Impact On Water Security?”. The Guardian. https://www.theguardian.com/environment/2012/nov/30/climate-change-water.

References

Sanwal, Mukul. 2015. The World’s Search For Sustainable Development. Cambridge University Press.

Tal, Alon. 2016. “Rethinking The Sustainability Of Israel’s Irrigation Practices In The Drylands”. Water Research 90: 387-394. doi:10.1016/j.watres.2015.12.016.

Chandler, David. 2017. “Finding Leaks While They’Re Easy To Fix”. MIT News. http://news.mit.edu/2017/robot-finds-leaks-water-pipes-0718.

“Water Scarcity | Threats | WWF”. 2018. World Wildlife Fund. Accessed February 25. https://www.worldwildlife.org/threats/water-scarcity.

Goetz, Melanie K. 2013. “The Paradox Of Value: Water Rates And The Law Of Diminishing Marginal Utility”. Journal - American Water Works Association 105 (9): 57-59. doi:10.5942/jawwa.2013.105.0147.

“Water Stress”. 2018. European Environment Agency. Accessed February 25. https://www.eea.europa.eu/themes/water/wise-help-centre/glossary-definitions/ water-stress.

Jones, Tom. 2003. “Pricing Water - OECD Observer”. Oecdobserver.Org. http:// oecdobserver.org/news/fullstory.php/aid/939/Pricing_water.html.

Zetland, David. 2008. “Forbes Welcome”. Forbes.Com. https://www.forbes. com/2008/07/14/california-supply-demand-oped-cx_dz_0715water.html#7da4be6137c9.

THE ECONOMICS OF INTERNET RETAILING AND AMAZON’S SUCCESS Mark Richardson, Economics Earlier this year, Jeff Bezos overtook Bill Gates to become the richest man in the world. The CEO of Amazon took advantage of the ‘Internet Business Boom’ during the 1990s by working on an idea that would eventually make him one of the most successful businessmen on the planet. To quantify the company’s triumph, if you had invested $1,000 into Amazon back in 2007, that investment would be worth over $12,000 today (CNBC, 2017). But why has the Internet retailing industry been so profitable for Bezos and other E-Commerce tycoons?

that consumers are likely to purchase from them again long run profits will be large. We can see this in practise when looking at the exponential rise in profits that Amazon has obtained during the 21st century (Statista, 2018).

How did Amazon become so powerful in today’s market?

Jeff Bezos entered the uncertain and volatile Internet retailing industry by following his ‘regret minimization framework’.

Leaving a Vice-President position at a Wall Street firm seemed nonsensical to most, but he didn’t want to get to the age of 80 and wonder ‘What could have been?’

The convenience of online shopping for consumers is the main reason web retailers are finding their ventures to be remunerative. Within minutes you can complete your weekly grocery shop or buy numerous items of clothing, which including travel time would usually take at least an hour if you were to journey to high-street supermarkets and retail stores. The efficient nature of the market is a key reason why Internet sales as a percentage of total retail sales have increased from 2.9% to 17.1% between April 2007 and January 2018 (Statista, 2017).

However, the online retailing industry is difficult to break into due to the pivotal role that consumer confidence plays. A major hurdle every firm faces initially is to try and entice buyers to complete their first purchase with them, which is where non-price competition is key. Amazon, Ebay and other Internet retailing companies use incentive schemes such as free delivery trials and promotions to encourage first time buyers. These digital monopolies are confident their reliable customer service will mean

Amazon started as an online bookstore, but it swiftly became a business that sold a vast variety of goods when customers started writing to them asking for other products to be sold.

Using a risk it all strategy, Amazon was an early entrant to the online market which helped Bezos benefit from first-mover advantages. This meant Amazon could perfect its service through ‘learning by doing’ and create a strong name, with its global brand value reaching $139.29bn in 2017. (Statista, 2017) The company prides itself on its high quality service, which was vital in gaining a large customer base at the beginning of the 21st century. Trust in the company grew and it has been able to consistently exploit large network economies of scale. The additional revenue earned relative to the extra cost of adding another user to the network has been immense,

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simply because they have gained more users and the fixed for each consumer have fallen drastically.

With technology rapidly becoming a necessity for people, the digital monopoly is able to enjoy the rewards of ‘The Spiral Effect’. Due to online stores gaining a higher number of shoppers, more sellers are flocking to Amazon, which is increasing the number of customers it receives even further. At the end of 2017, the company had over 300 million active users, with 44% of web shoppers going directly to Amazon for their product searches (Statista, 2017).

What’s next for Amazon?

It seems as if Amazon can’t stop innovating. Amazon Prime Air has been a major focus in the last few years, with the first delivery drone successfully delivering popcorn and a TV streaming stick to a trial customer in 2016. If the idea continues to take off, we could be seeing drones flying into London by 2020. Talk of Amazon also bidding for Premier League Football TV rights in order to rattle the Sky-BT duopoly emerged earlier this year. Given the current lucrative nature of the premier league, a successful bid in the next few years could see Amazon reap huge financial rewards.

Amazon’s global brand reaching $139.29bn in 2017 (Statista, 2017)

stores such as Amazon and eBay, otherwise unsuccessful Internet searches by consumers may lead them to believe that the product is not being sold. Secondly, click and collect purchases from large retail stores can help smaller, close-by shops.

When a consumer travels to pick up an item bought online from a department store, they may visit the shops around them to carry out spontaneous purchases. Little shops that sell items such as souvenirs and newspapers may sit uate themselves next to superstores to gain a larger customer base which in-turn will increase their own profits.

The future of Internet Retailing and E-Commerce The market share in the industry is unlikely to change dramatically. The online retailers that have been profitable since the Internet arrived have created high barriers to entry. Potential entrants are de-incentivised by the sunk and fixed costs of the operating systems needed to perform in this market, and the monopolies are going to keep growing. New technologies and brighter minds will cause the Internet retailing sector to carry on developing, with companies continuing to find new ways of providing online customisation of products that will meet the exact needs of every consumer. It’s probable that we will soon be living in a world dominated by search engines and next day deliveries.

References After buying the ‘Whole Foods Market’ chain last year, Amazon is looking to revolutionise the supermarket industry with its new ‘grocery store of the future’. The checkout-free store, which tracks what shoppers are buying using cameras and sensors, is being used in Seattle to cut waiting times in grocery stores. Waiting in line in a supermarket can be a major inconvenience for many consumers, so a company that can end these issues will have a serious competitive advantage.

This innovation is going to be tricky to implement globally, but given the prosperous nature of the company, you wouldn’t bet against the project being profitable.

Other industry implications Consumer’s expectations of convenience are growing fast.

There is a worry that online retailing is cutting jobs for people working in high-street retail. Businesses are being forced to adapt and invest more into their online operations, which is reducing the amount of in-store jobs available. Retail employment in the UK fell by 2% during 2017 (ONS, 2017) and the trend is expected to continue this year; however, these problems in the retail sector could potentially be offset by gains in the Transport and Storage industry. During the same time period, employment in this sector has increased by 6.7% due to the vast increase in warehouse and postal jobs in the UK. Therefore, the main concern is whether skills can be transferable across these two industries and in many cases, they aren’t. Luckily, face-to-face customer advice is never likely to go out of fashion, with many people still preferring to go into stores to test the product/item of clothing before they buy it. Subsequently, for a significant majority of people working in high-street retail, job availability and security should still remain high.

“Amazon: annual revenue 2017.” Statista. 2017. https://www.statista.com/statistics/266282/annual-net-revenue-of-amazoncom/.

“Amazon: brand value 2017 | Statistic.” Statista. 2017. https://www.statista.com/ statistics/326086/amazon-brand-value/.

“Amazon total active users 2013-2016 | Statistic.” Statista. 2017. https://www.statista.com/statistics/476196/number-of-active-amazon-customer-accounts-quarter/.

Carter, Shawn M. “If you invested $1,000 in Amazon 10 years ago, here’s how much you’d have now.” CNBC. December 29, 2017. https://www.cnbc.com/2017/11/28/ifyou-put-1000-in-amazon-10-years-ago-heres-what-youd-have-now.html.

“Dataset:EMP13: Employment by industry.” Office for National Statistics. 2017. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/employmentbyindustryemp13.

“Statistical bulletin:Internet access – households and individuals: 2017.” Office for National Statistics. 2017. https://www.ons.gov.uk/peoplepopulationandcommunity/ householdcharacteristics/homeinternetandsocialmediausage/bulletins/internetaccesshouseholdsandindividuals/2017.

“Time series:Internet sales as a percentage of total retail sales (ratio) (%).” Office for National Statistics. 2017. https://www.ons.gov.uk/businessindustryandtrade/retailindustry/timeseries/j4mc/drsi.

Furthermore, you may assume that the online retail industry is harming small high-street stores, but some small businesses are in fact benefiting greatly from Internet retailing for two main reasons. Firstly, smaller firms can now access specific customer groups that they may otherwise not be able to obtain. In 2017, 90% of households in the UK had Internet access (ONS, 2017) and when searching for a less common good, most people will look online to see if the product is in stores. This is why it is beneficial and essential that smaller companies selling untypical items display them on online

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THE SECOND AMENDMENT Yap Ke Li, Economics

Previous efforts of gun regulations

well regulated militia being necessary to the security of a free state, the right of the people to keep and bear arms shall not be infringed.” Many might know it as the fundamental basis of resistance against gun control. When gun advocates of America refuse to allow bills regarding gun regulations to pass, they do so by claiming that they are merely protecting their rights to bear arms, as written in the national constitution by their founding fathers. To law-abiding gun bearers in the US, the right to own and possess firearms is as sacred as their very freedom of speech.

In 1994, the American government passed the ViolentCrime Control and Law Enforcement Act, prohibiting the sale, manufacture, importation, or possession of a number of specific types of assault type weapons for a ten-year period. Somewhat miraculously, there was significantly less mass-shootings than had previously occured. However, when the ban expired in 2004, and failed to be reauthorised in Congress, mass shootings were once again on the rise.

The bill, that was solely intended to reduce mass-shootings, was allowed to expire following gun enthusiasts’ argument that it did little to reduce overall gun violence.

“A

That being said, gun control activists who are drastically pushing for gun reform believe that the second amendment did not stand the test of time. When it was written, framers of the constitution intended to empower states by allowing them to have an armed militia as a form of protection against the federal government (if it ever needed to be called upon). The lack of relevance of its purpose to states today is what aggravates gun protesters the most, since no American state has the same sort of militia that existed in the 1780s. Modern-day gun supporters have moved on to interpret their right to bear arms as a right to self defense.

This, in turn, is largely subject to debate, as it is not explicitly cited in the original text.

The influence of the NRA The resistance from the National Rifle Association, a progun advocacy group backed by rich corporations, is often the reason why the process of passing gun reform laws resembles a painfully slow tug-of-war. The NRA is often accused of buying its political support by making direct campaign donations to candidates whose political interest seem to align with their own. Many Republican representatives are often questioned if their ability to decide commonsense laws is compromised by the financial backing of said special interest lobby group. In a recent town hall debate held in the wake of the Marjory Stoneman Douglas High School mass shooting, Sen. Marco Rubio was heavily criticised by his failure to deny that he would never accept a single donation from the NRA in his future campaigns.

Although, if one was to dig a little deeper into the NRA’s expenditure, one would realise that their real political influence does not come from donations to political candidates, but from their outside spending aimed at running television and internet ads overemphasising the “fear” of having their right to bear arms taken away. In the 2018 Election Cycle, the NRA spent about $1.7mil (6 times more than donations) on convincing the American population that voting for politicians that support stricter gun regulations meant endangering their own livelihoods. A prime example of the NRA’s success was Sen. Mary Landrieu defeat in her next election after she had supported a bill that closed off a loophole regarding gun purchases by expanding federal background checks.

American citizens, both pro and anti-gun laws need to start clarifying and understanding the relationship between money and political influence in this context if they want to start having conversations on the true core of the issue and move forward from there, instead of accusing each other of conspiracies.

After the incident of Sandy Hooke, a bi-partisan piece of legislation called the Manchin-Toomey Amendment was proposed but voted down in Congress, missing just 6 votes to have been passed. The unusual joint effort by both parties was meant to further regulate gun purchases by requiring universal background checks on most private party firearm sales. Unfortunately, the defeat of this bill just went to show Americans that the safety and security of their children was secondary to the representatives’ fear of losing political support over a certain population group.

A glimmer of hope today The most recent school shooting at Parkland, Florida has sparked a movement called #NeverAgain, of which victims of the devastating incident have decided to take matters into their own hands by pushing the government to take action. The growing popularity of this movement continues to pressure lawmakers into taking steps towards tighter gun regulations. Possibly due to its widespread media attention, the Trump administration announced on the 10th of March 2018 that it has started the process of banning bump stocks, a device that enables guns to fire many rounds at once like a machine gun.

Despite opposition from the NRA and many furious gun owners, the Justice Department was ordered by President Trump to classify bump stocks under machine guns, which are illegal under federal law. The decision took the nation by surprise as prior to this, Trump has infamously seemed to propose more guns as a solution to gun violence. Nevertheless, gun control activists all over the country are hopeful that this might just be the beginning of stricter gun regulations that the nation has been long anticipating.

References “America’s Complex Relationship with Guns”, Pew Research Centre, Source: Survey of US adults conducted March 13-27 and April 4-18, 2017, Accessed March 3, 2017

http://www.pewsocialtrends.org/2017/06/22/americas-complex-relation-

ship-with-guns/psdt_2017-06-22-guns-00-09/ “Profile for 2018 Election Cycle”, Source: Centre of Responsive Politics, Accessed February 23. 2017 https://www.opensecrets.org/orgs/summary.php?id=D000000082&cycle=2018 Mark Gius, “The impact of state and federal assault weapons bans on public mass shootings”, Applied Economics Letters, 22:4 (2014) 281-284, DOI: 10.1080/13504851.2014.939367

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INTEREST ON EXCESS RESERVES An important policy tool and a possibly dangerous political weapon Ashley Brumfield, Economics A decade on from the 2008 Financial Crisis and one of the most important policies that helped deal with the crisis still remains - it is causing a debate amongst economists and politicians alike. The interest rate on excess reserves (IOER) has been a key policy for the Federal Reserve in the time since the Crisis due to the unique monetary situation which they found themselves in. The initial idea of an interest rate on excess reserves was brought about over four decades ago by Milton Friedman (federal reserve bank of San Francisco, 2013), who suggested the implementation of the policy would allow the Federal Reserve to have a better level of control over the short term interest rate, a very attractive quality for policy makers.

The interest on excess reserves clearly allows better control over money supply for the central bank and ‘since IOER was first introduced, in October 2008, the Fed’s practice has been to set its IOER rate above, if not substantially above, corresponding market rates, and to thereby encourage banks… to pile-up as many reserves as the Fed sends their way’ (George Selgin, 2017).

It was not until the 2008 Financial Crisis that the power to pay an interest rate on excess reserves was granted. The federal reserve needed to offer commercial banks the incentive to hold more reserves above their required levels.

Without this incentive all the new money that had been flowing into the system from QE programmes would have meant interest rates stayed low for a long time and monetary policy would have been virtually impossible to manage.

This proves that granting the power to pay interest on excess reserves was a well thought out and much needed policy.

According to the median estimates of the Federal Reserve, reserve interest rates should be increasing to 2.125% Congress granted this power in order to give the Federal Reserve more control over the economy after the shock of such a large scale crisis. Since this moment, the interest rate on excess reserves has been a keystone in the Federal Reserve’s monetary policy. Virtually every time the fed has changed interest rates it has done so by altering the interest rate on excess reserves.

It is also worth noting that an interest rate on excess reserves was due to be introduced even before the crisis began. Therefore, it should be considered a monetary policy tool rather than just a reaction to one of the biggest financial crises of all time. This is important to note as it shows the policy has validity and should not be discarded or used as a political tool, as it possibly could be in the coming years.

Because of this policy, Banks hold roughly $2.2 trillion in excess of what they are required to with the Fed (Curtis Dubay, 2018). Last year, the Fed paid $30bn (Business Insider, 2018) to the banking sector in excess reserves interest payments. It is because of these huge amounts of money that this vital monetary tool could soon become a political issue.

Some people will be confused as to why rich banks, who put the world economy through so much trouble are getting huge pay outs while economic conditions over the last 10 years have negatively impacted many people’s incomes.

Figure 1

The interest payments made to banks under the interest on excess reserves scheme, The Economist As we can see in Figure 1, as interest rates increase there will be an increase in the interest rate on excess reserves and thus greater interest repayments to the banks. At this vast level of repayments, it could be difficult to explain to the public just what the objective of the policy is. It may also be difficult to make people realise that these repayments will sharply fall after they have peaked at around $50bn, and so the policy could be difficult to sustain and be archived before it has properly completed its job.

The effects of interest rates on excess reserves are plentiful. In addition to what was previously mentioned, incentivising banks to hold more reserves has clearly helped to reduce the leverage of some banks. This was obviously a major problem before and during the financial crisis. A lack of liquidity disrupted the entire payments system and brought economies to a halt when the credit crunch hit.

Avoiding another serious episode such as this one is vital in the future. As well as this, it has also been important in maintaining a low level of inflation in the time since the crisis. The massive amounts of reserves pumped into the system via various QE programmes threatened to reduce overnight rates to zero. This would have caused a spread between what banks could borrow and lend at, therefore allowing profits to be made and facilitating unnecessary risk. This is clearly not an option after the experience of 10 years ago. Increased lending would have also driven inflation which would have reduced confidence in the economy even further, prolonging the recession even more.

While economies have been struggling to recover over the last 10 years and interest rates have been low, the relative cost of interest payments to banks has also been low. However, this could all be about to change, as interest rates look to be on the (steady) rise once more. This is certainly the expectation of investors and finance professionals as seen through the stock market decline over the early months of 2018. The world economy is doing better, but that is by no means a cause to do away with the interest on excess reserves policy.

According to the median estimates of the Federal Reserve,

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reserve interest rates should be increasing to 2.125%, creating interest rate payments of up to $47Bn (Curtis Dubay, 2018). This is clearly a huge amount of money and it is likely that this figure would draw politicians to call for an end to the programme of interest on excess reserves. But, once more, just because the economy has begun to recover does not mean that we no longer need this monetary tool. In fact, it is the case that the rate on reserves policy is needed now just as much as ever before, in order to maintain this positive growth and maintain economic conditions for improving consumer confidence, finally breaking the spell of years of uninspiring economic performance.

With increasing interest rates and a reduction in QE activity, it is in fact the case that monetary policy is becoming increasingly difficult to manage. ‘Because of QE, the banking system is awash with reserves. Banks have more cash on deposit at the Fed than they need to settle customer deposit withdrawals (payments), and they therefore don’t need to borrow funds from each other as they would in normal times. Because of this, the Fed Funds rate – the rate at which banks borrow from each other – no longer influences bank behaviour. It has fallen to zero’ (Frances Coppola, 2015).

Any calls to stop using the interest on excess reserves would cause huge problems for central banks. It is essential that the amount of money that is lent by banks is controlled in some way by the Federal Reserve. Without this sort of regulation, it would be extremely difficult for the Fed to manage the federal funds rate and market interest rates would simply collapse, meaning that money would be easily available once more.

Any change in this delicate system could have a major impact on the tax payer. The assets on the federal reserves balance sheet are essentially funded by the tax payer. Rejecting the IOER policy would cause, as previously mentioned, a collapse in the interest rate, the Federal Reserve would have to sell off its assets to help raise interest rates and restrict the money supply. This process would create an unprecedented fire selling of assets and reduce the value of the assets. This cut in value would then be at the expense of the tax payer.

Clearly central banks and politics do not mix well. This could therefore prove problematic if they decide to continue with the IOER policy in the face of political pressure.

People may begin to lose the trust in the central bank. A lack of trust would reduce the effectiveness of monetary policy and would make it harder still to manage the economy. This could undo all the good work of the independent central bank system. At the extremes (which should be considered in this case as they provide a good barometer for measuring reality), it could be the case that people completely ignore the central banks announcements.

Since ‘Some commentators … indicate that the Federal Reserve’s liquidity facilities have been ineffective in promoting the flow of credit to firms and households’ (Todd Keister

and James McAndrew, 2009) It is also very important that commercial banks play their part in promoting the policy, by making the public aware that they are still willing to lend to them. Credible announcements are needed in order to increase the confidence of borrowers and to get the economy moving forward with saving and borrowing. (Curtis Dubay, 2018).

With the central bank and commercial banks working together there should be enough information available to ward off any potential issues for the interest on excess reserves policy and the public will be acutely aware of the importance of this policy as well as the fact that it does not disrupt the normal functioning of financial markets.

There are obviously other major issues that could act to make it even more difficult for central banks. Uncertainty surrounding the Brexit negotiations and their outcomes as well as other antiglobalisation rhetoric could damage the worldwide economy. Monetary policy at this point could then become important in helping the economy to grow. If interest rates can’t remain low due to the abolition of interest on excess reserves, then it will be the case that private investment will shrink. This would be problematic as the economy would need investment and a confidence boost in order to prevent a possible recession.

A lack of private investment could leave the burden of propping up the economy to the government, thus impacting tax payers further. This demonstrates why the situation is so delicate. On the one hand tax payers feel aggrieved that they are seeing large sums of money go to the banks.

However, they would also suffer if taxes were to increase further in the event of a collapse.

Overall, it is clear that many people feel uncomfortable and even angry at the consequences of the financial crisis. They feel banks are being compensated for their own wrong doings. However, it is clear that political intervention in monetary policy is something that could have extremely negative consequences for the tax payer, for the banks and for the financial system as a whole. It is natural for people to be unsure about policies they have never seen before, especially ones that seem to be rewarding those who should be punished for their actions. However, individuals also need to be aware of the positive impact of the interest rate on excess reserves and also realise that the repayments to banks only account for 2% of bank income in the USA (The Economist, 2017). While this policy may be unusual, it certainly helps rather than hinders the economy and so should be celebrated as an economic success and a demonstration of policy makers adapting to new and complex situations in order to protect the wellbeing of the public. As a result of this, the public and politicians should have renewed optimism in these dynamic policy makers, and trust them more to reach the correct decisions for the health of the economy, instead of attempting to turn one of the success stories of recent monetary policy into a political, toxic weapon.

FINTECH Zhongwei Ho, Finance, Accounting and Management On the 23rd June 2016, Brit’s morning was ruined not by the sun that never came out, but by UK’s major blunder in its political history since the appeasement. A staggering 51.9% of the UK electorate voted to leave the EU, putting the UK in the spotlight for the wrong reasons. Just

when we thought that KFC’s chicken shortage brought a seismic shock to the country, Britain’s move to leave the EU would resonate throughout the economy even more so.

With the due date for the UK to leave the EU coming up really soon, this article seeks to find out if the UK economy will still be a world leading economy through its financial sector, while focusing primarily on fintech.

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Origins of Fintech What is Fintech? Fintech is the combination of the two words – “finance” and “technology”. Originally, the term only applied to the back-end of established consumer and financial trade institutions. However, at the end of the first decade of the 21st century, the term has since expanded to include any technical innovation in the finance industry (Investopedia 2017). With the recent interest around block chains, especially Bitcoin, the interest around the Fintech industry has never been higher. Moreover, with the recent push to digitize data and improve customer satisfactions, big commercial banks have also started to experiment with different fintech applications to lure younger customers. A great example of this would be the mobile banking application that everyone loves, or hates, depending on how much you have left in your current account.

Britain’s stance in Fintech Britain stands to be the leading market for fintech in the world, with Singapore and New York being the second and third most popular hubs for fintech respectively. The UK’s fintech industry has an estimated £20bn in annual revenue and this figure continues to grow. The majority of revenue is generated by what we term ‘Traditional Fintech’ and in the order of 18% is generated by Emergent Fintech. Of the £20bn in annual revenue generated by the fintech sector, £10bn comes from the payments; £3.8bn comes from financial data and analytics; £4.2bn comes from financial software; £2.0bn comes from platforms.

For years, Britain has always been a key player in the Fintech industry. A few examples of fintech industries that the UK are global leaders in are peer-to-peer platforms, aggregator platforms and data and analytics product (EY 2017). London in particular, is a coveted hub that is viewed amongst fintech companies as the number one destination to set up their company. This is because the business environment in the UK makes it desirable for companies to relocate there.

Permanent roles in the fintech sector have exploded rising by a staggering 732 per cent year-on-year.

When the UK is voted as a powerhouse of fintech, this comes as no surprise. (It came as no surprise to see the UK voted as a powerhouse of fintech). One of the reasons the UK is so desirable for fintech companies is that London has a high concentration of financial services and technology companies that are in close proximity to each other. This gives fintech companies easy access to capital and talent pools that are needed to propel their company forward. To them, it’s like walking through the chocolate aisle of Tesco Extra, only to be bombarded with the amount of choices they get to make and acquire.

The second reason is London is blessed with sympathetic policy makers and regulators. The FCA (financial conduct authority) and The Bank of England are innovative and progressive. For example, through the implementation of “Project Innovate”, the “Regulatory Sandbox” and Bank of England’s work on cryptocurrencies and distributed ledger technology (Burges Salmon 2016). Project Innovate is a scheme by the FCA that offers innovative support and services to innovative fintech businesses. The regulatory sandbox allows companies to trial their new products without having the burden of getting full authorization, while also maintaining customer protection.

Spicy competition Countries in the EU have begun taking notice of the UK’s blissful relationship between their regulators and financial companies. Berlin and Paris for example, have been mounting aggressive promotion campaigns to lure

fintech startups to their home turf. The inward investment team have even said they have been contacted by startups in London that are considering moving there, due to the significantly cheaper rent and benefit of being part of the EU. Other cities in the EU such as Zurich may try to win startups to set up in their country. Zurich, Deloitte found, “has nurtured a thriving financial service and fintech sector, and boasts excellent infrastructure, a solid legal system and protection for consumers” (Hurley 2017). Zurich might very well be well positioned to be the next global financial hub.

The incumbents such as Credit Suisse and UBS among others, are working closely with emerging fintech startups. The Swedish capital, meanwhile, is second only to Silicon Valley in producing the most highly valued technology startups per capita.

However, these cities in the EU may not be able to surpass London as the next global financial hub. This is because even though they may have access to free movement of talent through the common market, countries such as Berlin suffers from being dislocated from its financial hub in Frankfurt. The symbiotic relationship between fintech firms and London’s financial centre is what makes it such an appealing place for fintech startups. Furthermore, New York could be a close competitor for London. However, due to the nature of the US complex regulatory environment, with 50 states, federal agencies and law enforcement to deal with, it’s like a wild west for fintech startups out there.

The end is near?

On the 29th of March 2017, the UK government triggered article 50, which gives the UK until the 29th of March 2019 to leave the EU. As the UK is halfway through packing its bags to say adios to its fellow brothers in the EU, the fintech sector in the UK remains unfazed by the uncertainty that is presented. However, the most pressing question is whether the UK will be a world leader in the fintech sector post brexit. With the current situation, the UK’s fintech sector might be able to navigate post Brexit with a lot of confidence. This is partly due to the fact that the UK is blessed with a high density of financial institutions for fintech companies to work together with. Furthermore, the UK is also has innovative regulators and government working alongside them. The Chancellor of the Exchequer, Philip Hammond, announced a myriad of plans for the fintech sector in the coming years at the inaugural International fintech Conference just last year. According to the Chancellor, “Our tech sector already contributes a bigger proportion of our GDP than any other country in the G20” (Treasury and MP 2017). With a £7 billion revenue sector, which employs over 6,000 people at hand, the government has introduced 3 important things that ensures the UK fintech sector will stay competitive post Brexit.

Firstly, in response to fintech companies’ concern, the government has “provided £400 million of new capital to the British Business Bank to leverage £1bn of investment in UK technology businesses” (Treasury and MP 2017). This inflow of cash into fintech businesses is much appreciated, as capital injection into businesses allow them to spend more on acquiring better talents or even purchasing newer equipment so that they can become more productive.

Secondly, the UK government will be implementing T levels, which is an equivalent to A levels. The T levels will be taught from 2020, and the first 3 subjects that have been announced are Digital, Construction, and Education and Childcare (Education and MP 2017). Compared to traditional A levels, T levels equip students with high quality experience like education by partnering leading companies such as Rolls-Royce, Fujitsu and EDF. By equipping students with these skills, the productive potential of the economy will rise in the future. Not only that, it will also create a culture

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of entrepreneurism and forward-thinking employers. This is vital for the growth of the fintech sector as these are exactly the type of employees they need. Thirdly, the Chancellor mentioned that through a report from EY, they found that many fintech firms want to expand into Asia. As a result, the UK government and FCA have been actively building bridges with Asian countries such as Hong Kong, Singapore, China and many more. Government and financial institutions from both sides have been actively collaborating to advance fintech. Post Brexit, this will benefit the UK a lot as they will be able to lend their expertise, as a leader in the industry, to up and coming fintech businesses in Asia.

Conclusion The UK has nothing to lose from relying on its fintech sector to navigate post Brexit. However, uncertainty between the EU and the UK regarding the flow of labour might hinder talent acquisition for the fintech industry, possibly slowing down its growth. However, this is offset by active collaboration between financial regulators and the government, which ensures that the industry will not be neglected and will continue to be world leaders.

Close competition could not come close to the degree of closeness UK fintech firms have with their financial institutions and regulators. However, in the long term, other countries might catch up, but it might take a lot of time as financial restructuring of an economy is an arduous

process and it doesn’t happen overnight. The success of the UK happens to be the bricks it laid centuries ago that ensured that it would have a solid foundation.

References EY. 2017. Landscaping UK Fintech. Report, EY, EY. Accessed January 7, 2018. http://www.ey.com/Publication/vwLUAssets/Landscaping_UK_Fintech/$FILE/ EY-Landscaping-UK-Fintech.pdf.

Investopedia. 2017. Investopedia. Accessed January 8, 2018. https://www.investopedia.com/terms/f/fintech.asp.

Hurley, James. 2017. Raconteur. April 23. Accessed January 17, 2017. https:// www.raconteur.net/finance/will-london-still-be-the-global-fintech-hub-postbrexit.

Burges Salmon. 2016. Burges Salman. July 13. Accessed January 18, 2018. https://www.burges-salmon.com/news-and-insight/legal-updates/the-impactof-brexit-on-fintech-in-the-uk/.

Treasury, HM, and The Rt Hon Philip Hammond MP. 2017. “International fintech conference.” April 12.

Education, Department for, and The Rt Hon Justine Greening MP. 2017. GOV.UK. October 11. Accessed Febuary 8, 2017. https://www.gov.uk/government/news/ education-secretary-announces-first-new-t-levels.

A BRIEF OVERVIEW OF LIVE-EVENT TICKET MARKETS Charles Anthony Ibbett, Economics Ticket touts have been considered the bane of live-event ticket markets for long time. They take advantage of the limited supply and the excess demand, in the market, reselling tickets at inflated prices.

In an ideal world with perfect information, markets for these tickets would set prices that equate demand and supply - at the market clearing price. In reality, ticket markets are quite opaque and before sale opens the demand for tickets is very difficult to gauge.

Still, for some events, where supply is dramatically exceeded by demand, prices are surprisingly low. Ticket touts take advantage and resell tickets for multiples of the original price - most dramatically from £140 to over £8000 for Harry Potter: The Cursed Child (listed on viagogo) . This free lunch begs the question: why are the primary market prices not higher? Surely the event-organisers should increase the prices in the primary market closer to that of the market clearing price. This would increase their profits and it would force the scalpers they detest out of a business.

Why are ticket prices so low?

The low prices are a product of the complex preferences of artists, teams and box offices. To most teams and artists, it is crucial that their venues/events are sold out . The ability to state you sold out sends a strong signal of how in demand the experienced good (the ticket) and the artist is. Secondly, the presence of a sell-out

would maximise, secondary, complementary revenue e.g. parking, concessions, but also TV exposure . In order to guarantee a sell-out prices are set artificially low, as it is highly improbable that demand, and by proxy the equilibrium price, would be known.

t is also evident that an important social preference of box offices is the availability of tickets to consumers at moderate prices3. These lower prices allows venues to be filled by more enthusiastic, regular fans, rather than solely the rich.

It allows the artist or team to generate more sustainable income as the majority of fans are not wealthy CEOs but are blue collar workers. Artificially low prices thereby have the ability to appeal to these workers and widen the fan base which facilitates a sustainable future income.

Moreover, there is an apparent difference in the respective agents profit maximisation functions. While the box office displays a preference for this sustainable profit, the ticket reseller does not, and maximises profit in the short run.

Thus the box office will lower prices to provide a higher consumer surplus while the touts have no such restraints and charge the market clearing price.

Who are ticket resellers?

Ticket resellers’ goal is simply to buy low and sell high and therefore make a sizeable profit on the difference. They act as middle men between people who want to sell their ticket and those wishing to buy. These resellers can be broken down into two general types: scalpers and brokers. Ticket scalpers are not licensed and tend to buy and sell tickets on the day, within the hours or minutes leading up to the event. However, ticket brokers are licensed to resell tickets, they tend to resell tickets significantly in advance of the event. Both are important for closing and clearing the market.

Many fans that want a ticket may not have the time to stand in lines or call the box office or get online during a ticket sale. Enter the resellers. They facilitate the acquisition of tickets by those who value them highly but may have been unable to acquire them on the initial purchase.Ticket brokers acquire their share of tickets sometimes in bulk by either paying people to stand in line or calling the box office when the tickets go on sale. This is where a problem arises.

The aggressive method that the ticket resellers employ can block the actions of regular fans who wish to purchase the ticket for consumption rather than resale. Does this means

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that the efficient allocation of tickets is compromised?

Economically, no, the ticket resellers actually increase allocative efficiency . A study has shown that allocative efficiency is improved by a small amount in markets where ticket resellers are active, compared with markets where ticket resellers are not. However, there is a trade-off between efficiency and equality that traditional economics ignores. A blue collar worker who is willing to use more than a day’s wages to purchase a ticket evidently values the ticket more than a CEO who is only willing to spend less than an hour’s .

The measure of allocative efficiency fails to capture this but it would be nigh impossible to measure anyway.

Government regulation The actions of ticket touts are seen by some (if not many) as unethical and there have been calls for regulations to be enacted in order to bring them under control. There are two main actions that are called for: complete bans of the reselling and price controls.

Firstly, banning the ticket resale market would be economically inadvisable - it would be damaging for all parties. This secondary market allows ordinary resale of unwanted tickets and therefore offers insurance to those who hold a ticket but are unable to attend. This insurance reduces the risk associated with ticket acquisition and this would increase ticket prices in the primary market (Spindler 2003) as a result. Therefore, the banning of secondary markets removes this insurance for consumers and the higher profits for the artist, team or box office.

Hamilton tried two methods, which I will dub the US and UK methods, with different effectiveness. In the US the producers suffered through a year with tickets being resold on the secondary market at over 3x the price on average ($475 to $1810). To combat this they decided to “[take] from the rich and give to the poor” . They increased prices on premium seating (from $475 to $849) which allowed them to decrease prices on more moderately priced seating. This action reduced the possible mark-up gained by ticket resellers and as a result: the average number of listings for each performance halved on reseller Stubhub and the size of the mark-up profit made reduced from $1335 to $95210.

Although not entirely effective, it has been successful in reducing the ticket reselling activity surrounding the experience. Despite this, it is worth noting that this method has been employed for ticket market where demand was not totally opaque: the event had been running a year and the creators and producers used online secondary market sales to gauge the market clearing price. In the UK the producers took their ambition to reduce ticket touting, to a new level. The UK method entailed multiple new restrictions. It involved a paperless system where ticket holders had to go to the theatre on the of the performance with a confirmation email, the bank card used for the booking and photo ID . It is also worth noting that: by this time ticket purchasers were limited to four tickets maximum and any tickets found to be resold were rendered void (Both UK and US). Despite these additional restrictions, tickets found their way onto the secondary market two hours after initial sale. The prices for those listed were high but there were relatively few listed, which suggests that the system employed had some effect.

Where do we go from here?

Ticket resellers’ goal is simply to buy low and sell high and therefore make a sizeable profit on the difference.

Alternatively, price controls in certain countries e.g. Hong Kong , may have popular support, but they still may not be the best decision, economically. Demand would continue to drastically outstrip supply and the market would still be ridden with inefficiencies. There also have been suggestions that the presence of scalpers actually informs box offices of the real market clearing price in Williams (1994) and Hamilton most recently.

Moreover, if the market is regulated in either way, activities may shift underground which would result in further inefficiencies. Market agents would be less protected against fake tickets and therefore resources would be allocated to policing it.

Modern methods As government regulation is not effective and does not promote efficiency, companies and distributers have tried new approaches in order to ensure tickets reach those who value them. The three methods focused on here are Ticket master’s Verified Fan and Hamilton’s two methods.

Ticket Master describe their Verified fan system as a “big robot to protect fans from the thousands of little scalper bots trying to scoop up tickets” . The public responses to this have been mixed, while overall results have been remarkable. For the 60+ tours that Verified Fan has been used for, less than 5% of the tickets have gone on to be resold on the secondary market. However, when an event is incredibly popular and the stakes are high enough then Verified Fan can seem impotent against bots. Tickets for a recent string of Bruce Springsteen concerts that used Verified Fan were being sold for $10000 (up from $75).

The last two sections highlight the difference in effectiveness of regulation on public or private levels. If our goal is the efficiency of the market considering the preferences of the agents involved then there is a clear solution.

The first is to define and differentiate the roles of government and private agents in this market. The government’s legislative role should not be in market interference but in market efficiency. As we have seen, government regulation of total bans or price controls result in negative externalities for a few or potentially all parties involved. Therefore, their legislative focus should not be on removing the secondary market but reducing risk and uncertainty through guarantees and licensing. On the other hand, private creative parties/agents should be responsible for private regulation of their own market. Partly this is due to their preference to introduce the inefficiency in the first place but partly this is also due to their better knowledge of their own market. An artist or team opening a highly demanded show/event should be able to use the available technology to limit the dispersion of the tickets. This could be completed by taking inspiration from Hamilton’s UK Method and/ or possibly employing technology similar or the same to Ticketmaster’s “Verified Fan”.

The scenario proposed will not eliminate ticket touts in totality, for they will always exist so long as the mark-up gained is greater the value of effort exerted. However, the restrictions imposed will increase the effort required and therefore reduce resale activity that is profit-focused. This scenario would be more efficient overall as along as resale is offered by the private agent (artist, team, box office) or an associated party (both of which are more and more regular). This scenario would also set a good ground work for policy when the market becomes even more complicated in the next section which I will explore briefly.

The Power of the Status quo In this exploration we have implicitly assumed a single supplier that originates and disperses the tickets. We therefore

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References “A Muggle’s Game”, The Economist, Published: 20/08/2016, Accessed: 10/03/2018, https://www.economist.com/news/britain/21705288-curse-market-forcesmakes-ticket-reselling-tough-manage-muggleu2019s-game Paul, Krugman, ‘Thinking Outside the Box Office”, SLATE, Published: 13/05/1999, Accessed:

10/03/2018,

http://www.slate.com/articles/business/the_dismal_sci-

ence/1999/05/thinking_outside_the_box_office.html, James, Atkinson, “The Economics of Ticket Scalping”, Jimmy Atkinson, Published: 03/05/2004, Accessed: 10/03/2018, http://jimmyatkinson.com/papers/the-economics-of-ticket-scalping/ Andrew T. Williams, “Do anti-ticket scalping laws make a difference?”, Managerial and Decision Economics Journal, Volume 15, Issue 5, 1994, 503-509 Philip, Leslie, and Alan, Sorenson, “The Welfare Effects of Ticket Resale”, N/A, Published: 07/2018, Accessed: 10/03/2018, http://faculty.haas.berkeley.edu/wolfram/ InnovSem/PapersF08/resale.pdf Yashvardhan, Bardoloi, “Are ticket scalpers actually good for economic efficiency

have ignored the different players within the actual supply chain. If the different agents of the supply chain are introduced, then conflicting incentives and further information disparity must also be introduced. This is exemplified in the supply chain of concert tickets.

In the concert supply chain, the main agents are: the artist, their manager, the promoter, the venue (operators) and the “primary” ticket sellers (such as ticketmaster). Ticket sellers such as ticket master charge a transaction fee (e.g.

15%) on sales. This transaction fee allows the initial vendor to ‘double-dip’ in both the initial sale but also the resale in order to increase its profit. In this situation this actor has a reduced incentive to enforce or aid in enforcement of any regulation, even its own.

The artist, of whom we have heard only of their desire to under-price their tickets for their fans also benefits from this status quo. Their manager is incentivised to make the artist as much money as possible due his cut of earnings generally being based on the artist’s. The promoter is incentivised to pay enough to ensure that the event goes forward. Therefore, for certain events, artists are paid as if the ticket price was between actual retail price and market clearing price. The promoter still is able to make money by engaging in the secondary market via a ticket broker.

or equality?”, Young Post, Published: 10/11/2016, Accessed: 10/03/2018, http:// yp.scmp.com/over-to-you/columns/article/104824/are-ticket-scalpers-actually-good-economic-efficiency-or-equality Unknown, ‘Press Releases”, N/A, Published: 21/05/2014, Accessed: 13/03/2018 http://www.info.gov.hk/gia/general/201405/21/ P201405210465.html Ticket Master, “Verified Fan: Frequently Asked Questions”http://help.ticketmaster. com/verified-fan/ Stephen, Dubner, “Why Is The Live-Event Ticket Sale Market So Screwed Up”, Freakonomics, Published: 06/12/17, Accessed: 09/03/2018, http://freakonomics.com/ podcast/live-event-ticket-market-screwed/ Joanna, Kao and Anna, Nicolaou, “‘Hamilton’ raises broadway ticket prices to foil scalpers”, Financial Times, Published: 01/02/2017, Accessed: 12/03/2018, https:// www.ft.com/content/81e13906-e43b-11e6-8405-9e5580d6e5fb Hannah, Ellis-Petersen and Rob, Davies, “Hamilton West End tickets appear on resale sites despite anti-tout measures”, The Guardian, Published: 16/01/2017, Accessed: 12/03/2018, https://www.theguardian.com/stage/2017/jan/16/hamilton-west-endtickets-found-on-resale-sites-viagogo-despite-anti-tout-measures Stephen, Dubner, “Why Is The Live-Event Ticket Sale Market So Screwed Up”, Freakonomics, Published: 06/12/17, Accessed: 09/03/2018, http://freakonomics.com/ podcast/live-event-ticket-market-screwed/

In this situation, where “everybody’s making money on scalping” the status quo is incredibly difficult to change.

In fact, when a new firm Tixfan approached members of the supply chain in order to conduct anti-botting and anti-scalping for free. “No one was interested”12. Milton Friedman called this the power of the status quo.12 The power of the status quo is currently held in the opacity of the supply chain to: each of the other respective agents of the supply chain; the government and the consumers.

Therefore the answer to improving economic efficiency of this market will be found in improving the transparency of the supply chain. In order to achieve this goal, government regulation will have to play a part.

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WHAT ARE THE DETERMINANTS OF CHILD MARRIAGE IN INDIA? Sharmee Shah, Economics, 2019 Globally, of the women alive today, more than 700 million were married off as child brides (UNICEF, 2016). The Convention On The Rights Of The Child (UN, 1989) defines child marriage as a formal marriage or informal union where one or both spouses are under the age of 18 years. Child marriages are argued to be “forced” marriages since the children are too young to make well informed, calculated decisions about their potential spouses or the timing of their marriages. Less than 5% of the women examined by the India Human Development Survey (2005) had a primary role in choosing their husbands (Desai and Andrist, 2010). In most cases, parents, guardians or caregivers arrange their children’s marriages. Their motivations in doing so are rooted in a spectrum of individual, household, sociodemographic and cultural characteristics.

The occurrence of child marriage is disproportionately larger for females as compared to males, hence the analysis is focused on female child marriage. In Mali, for example, the ratio of child brides to child grooms is 72:1 (World Policy Analysis Centre, 2014). Due to India’s large population (1.324 billion people), it accounts for 33% of child brides globally (World Bank, 2016; UNICEF, 2014). Child marriage leads to increased risks of contracting HIV/AIDS, maternal and infant mortality and a less educated female population, which in turn perpetuate the poverty trap. Despite these negative implications the hazard still persists.

Econometric analysis on data from a 2014 household survey complied under ‘Young Lives: An International Study of Childhood Poverty- India’ which covers a sample of 486 Indian females, aged 18-19 years old, found that after controlling for various socio-economic characteristics, females belonging to the backward classes, living in a rural region, experiencing hypergamy, spending a shorter amount of time travelling to school/work and having a father with low literacy levels lower the fe male’s age at marriage and increases the probability that she experiences child marriage.

There is a significant positive relationship between a female’s father’s education levels and her age at marriage, where an additional year of education attained by him increases his daughter’s expected age at marriage by

1 month and 5 days, ceteris paribus. This supports the theory that children of less educated parents experience a higher likelihood of child marriage as parents may not see the economic benefits of providing further schooling for their daughter (Kamal, 2011). Less-educated adults (parents) may also have lower levels of human capital and hence are more likely to receive lower incomes (Mincer 1974) which leads to poorer parents being unable to meet the costs associated with educating their daughter. They thus look at marriage as a reasonable ‘next step’ in planning their daughter’s future or simply as a tool to rid them of the cost of further raising her. Mother’s education levels are insignificant in influencing her daughter’s age at marriage due to female members holding relatively low or no power in the decision making processes within the patriarchal cultures where child burdening cost of further raising her or because they are unable to access further education opportunities due to caste-based discrimination.

Alternatively, it could be the case that poor, lower caste parents see hypergamy - the action of marrying an economically wealthier/higher caste groom - for their daughter as her way out of the poverty cycle. Females who experience hypergamy married 3 years, 5 months and 15 days earlier, on average, as compared to those who do not, ceteris paribus. Furthermore, a female marrying into an economically better off household faces an average increase in the probability of experiencing child marriage by 44 percentage points, ceteris paribus. Theoretically this is because parents are also incentivised by the traditional dowry custom. Dowry is wealth transferred from the bride’s household to the groom or his household. The younger the bride, the smaller the dowry paid by her par ents as grooms highly demand young brides and are hence willing to settle for a smaller payment (Chowdhury, 2010).

It is hence economically beneficial for parents to marry off their daughters earlier. In caste-based societies, as wealth disparities increase, dowry payments become larger (Anderson, 2003). In India (a caste-based society), hypergamy has led to parents having to pay more dowry for an upper class/caste groom to compensate for what would have otherwise been an improper alliance since miscegenation is looked down upon. Hypergamy has caused inflation in dowry payments and has infiltrated into communities that

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were previously unaware of the custom (Anderson, 2003).

To tackle this inflation in dowry payments, parents desiring a wealthier/upper caste groom for their daughter will marry her off at a younger age in order to get away with paying less in dowry to the upper caste/class groom.

A significant positive relationship exists between the time taken for a female to travel to her main activity for the day (work/school) and her age at marriage, where increasing a female’s travel time by 1 minute, increases her age at marriage by 7 days, ceteris paribus. Patriarchal households that associate their female members’ chastity/purity with honour (Caldwell, 2005) tend to restrict their female members’ mobility. Hence, a larger distance covered everyday puts the female at a higher risk of experiencing premarital sexual activity (consensual), unwanted pregnancies, miscegenation, rape and sexual violence (especially in disaster and conflict zones) which would consequently bring ‘dishonour’ to the household and leave the female ineligible for marriage. This fear incentivises parents to arrange their children’s marriages early (Maloney et al., 1981). Hence households whose females travel for a lengthier time may signal detachment of household honour from her chastity showing that the household is liberal, hence females are able to make autonomous decisions concerning their marriage timing and are allowed greater mobility to continue their further education. Females living in rural regions marry 1 year, 4 months and 17 days earlier as compared to those living in urban areas, ceteris paribus. In rural India high held customs and traditions and the lengthy distances to the sparse secondary schools force females to drop out and increases the probability of child marriage occurring.

In patriarchal societies that blame the victims of sexual violence for bringing ‘dishonour’, regions with low crime rates against women may also allow greater female mobility and the opportunity to attend further schooling, thus delaying the female’s age at marriage.

In 2006, Indian policy makers replaced a 77 year old Act with the new Indian Child Marriage Prohibition Act (Gazette of India, 2006) that enforced stricter policies such as punishment for grooms and individuals solemnising and permitting child marriage. Child marriage prohibition officers have also been appointed to educate the community on the risks associated with child marriage and bring about a positive change in the culture around the treatment of a female child. Whilst these policies may help lessen the prevalence of child marriage, there is still a lot of progress to be made in widening the aims of policies to tackle the determinants of child marriage evidenced in this article. Local law enforcement officers may be compromised and also conform to the same cultural norms of arranging

early marriage for females, leading to inconsistent dowry, thereby nullifying the positive relation between the amount of dowry paid and the age of the bride. Educational policy should aim to provide more proximate schools in rural areas, thus lessening the time taken to travel to school. Law enforcement and social policies should also aim to eradicate crime against women and the dominant patriarchal ideology (with the support of village councils) respectively, thereby giving females autonomy and greater mobility to higher education institutions that are sparse and far, instead of having to drop out and marry early.

References ‘Reaching every child: The promise of equity’, (2016), The State of the Worlds Children, UNICEF 1(1), 38-39.

‘The United Nations Convention on the Rights of the Child’, (1989), 1(1), 1-4.

Desai, S., & L. Andrist (2010), Gender Scripts and Age at Marriage in India. Demography, 47(3), 667–687.

‘World Policy Forum Fact Sheet- Child Marriage’, (2014), World Policy Analysis Centre, 1(1).

World Bank, Population Data (2016) ‘Ending Child Marriage: Progress and prospects’, (2014), UNICEF, 1(1) 2-4.

Boyden, J., T. Woldehanna, S. Galab, A. Sanchez, M. Penny, L. T. Duc (2016), Young Lives: an International Study of Childhood Poverty: Round 4, 2013-2014, UK Data Service.

Kamal, S. M. M. (2011), Socio-economic determinants of age at first marriage of the ethnic tribal women in Bangladesh, Asian Population Study, 7(1), 69-84.

Mincer, J. (1974), Schooling, Experience and Earnings. New York: National Bureau of Economic Research.

NCBC Act 1993, National Commission for Backward Classes, Ministry of Social Justice and Empowerment, Government of India.

Chowdhury, A. (2010), Money and Marriage: The Practice of Dowry and Brideprice in Rural India, 1-21.

Anderson, S. (2003), Why Dowry Payments Declined With Modernisation in Europe but are Rising in India, Journal of Political Economy, 111(2), 269–310.

Caldwell B. K. (2005), Factors affecting female age at marriage in South Asia, Asian Population Studies, 1(3), 283-301.

Maloney, C., K. M. A. Aziz & P. C. Sarkar (1981), Beliefs and Fertility in Bangladesh.

Monograph Series No. 2, International Centre for Diarrhoeal Diseases Research, Dhaka Bangladesh 85-88.

The Prohibition of Child Marriage Act 2006, The Gazette of India, Published by Authority, New Delhi, Government of India.

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KOREAN PEACE Toby Howard, Economics, 2020 Peace, finally? For almost 68 years the Korean states have been at war following the invasion of the South by the North in 1950. Armed conflict ended in 1953 with the signing of an armistice and the recognition of a demilitarised zone, but without a peace treaty the two states have technically been at war ever since. Relations between the two have remained frosty at best, with several incursions and overt acts of military aggression by the North resulting in the deaths of around 50 South Korean soldiers and several civilians.

It is estimated that an economically unified Korea would generate $8.7 trillion in 2055, 1.7 times the projected size of South Korea itself (Dreyfuss, 2018)

91% of North Korean imports come from Asia with 85% from China (Simoes and Hidalgo 2011). This abnormally weighted trading profile stems from its aggressive dealings with other states surrounding their nuclear weapons program and horrific human rights record, and has led to many international organisations slapping the state with severe trade sanctions (Alfred 2014). It is undeniable that the state’s restricted trade in combination with its woefully mishandled economy has stunted their growth since the division of Korea in 1948. An oft cited natural experiment used to isolate the effects of economic management and institutions from other factors, such as geography and culture, is a night time photograph of the Korean Peninsula.

The disparity in the development of the two countries is starkly demonstrated by their night-time lighting. It can be convincingly argued that the South’s free market principles of secure property rights, an effective judiciary, contestable government, low levels of inequality, widespread access to education, and a transparent bureaucracy among other qualities has allowed innovation to explode and make South Korea the eleventh largest economy in the world

(Acemoğlu and Robinson 2013). The North contrasts the South in every aspect of that list and is estimated to have an economy just one fiftieth of its neighbour’s size. (“South Korea Vs. North Korea - Economy Comparison” 2018).

In recent weeks considerable progress has been made towards a peace agreement which will officially end the war between the two nations, with denuclearisation one of the key terms. In conceding to the world’s assertions that the North end its escalating nuclear programme it is likely that they will ameliorate relationships sufficiently to open up new trading opportunities. In light of these considerations, is it right to say that the North is going to be the real winner as a result of the pending peace deal? On first glance one would assume so, as the benefit to the North of opening up trading opportunities with the rest of the world would outweigh that to the South (and every other state) of a single extra trading partner. However, I would argue that any economic advantage to the North would be diminished, if not completely extinguished, by a system which actively disincentivises innovation and capital accumulation.

The recent economic history of China provides some insight. They have been a communist state since 1949 which for a long period hindered their economic growth. In the years following the death of Mao in 1977, a sub-elite of illuminated party leaders began putting into place free market economic institutions not ordinarily associated with communist rule. It is usually observed that exclusive political institutions such as communism will exclude good economic institutions, but China has been able to go against this trend. As a result, China has become one of the world’s fastest growing economies and a hub of foreign investment. Nevertheless, in their book ‘why nations fail’, Acemoglu and Robinson cast doubt over whether such a positive economic outlook is sustainable for a country which has such repressive political institutions, as these will tend to encourage exclusive and arbitrary economic institutions which themselves discourage investment and innovation. As such one would expect that North Korea, without any impetus for a change from the current system of bad political institutions, would continue

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on the path on which China began and fail to take full advantage of the opportunities that peace will bring them.

References

There is a general consensus that the South would benefit from a more closely integrated Korea. In the most idealistic situation of an economically unified Korea, it is estimated that the combined economy would generate $8.7 trillion in 2055, 1.7 times the projected size of South Korea itself (Dreyfuss 2018). An unpredictable political landscape discourages foreign investment and harms the South’s credit rating, so stability in the region would reduce the effects of these issues and encourage further growth for the state (Lee 2018). Additionally, a report by Morgan Stanley suggests that the effect of ‘unification’ between the two states would be similar to that resulting from the fall of the Berlin wall They predict a jump of 15% in local stocks in the best scenario with more conservative estimates at 8% (Heeb 2018).

UK.

It is hard to conclude whether these mitigations to the North’s benefits diminish them enough that the South will take more from the peace. What can be concluded, however, is that all parties will reap economic benefits from peace in Korea.

ical Tool for Understanding the Dynamics of Economic Development. Workshops

Alfred, Charlotte. 2014. “How North Korea Became So Isolated”. Huffpost https://www.huffingtonpost.co.uk/entry/north-korea-history-isola-

tion_n_5991000.

Dreyfuss, Joel. 2018. “North Korea-South Korea Summit May Be Kim Jong Un’s First Attempt At Bridging The Economic Divide”. CNBC. https://www.cnbc. com/2018/04/26/korean-summit-may-be-first-step-to-bridge-economic-divide. html. Heeb, Gina. 2018. “Here’s What Could Happen To South Korea’s Currency If The Country Reunifies With North Korea”. Business Insider. http://uk.businessinsider.com/korean-reunification-what-could-happen-to-south-koreas-currency-2018-4.

Lee, Jiyeun. 2018. “North Korea Would Benefit Most, By Far, From Peace On Peninsula”. Bloomberg.Com. https://www.bloomberg.com/news/articles/2018-04-24/ korea-peace-dividend-would-flow-mostly-to-impoverished-north.

Simoes AJG, Hidalgo CA. 2011. The Economic Complexity Observatory: An Analytat the Twenty-Fifth AAAI Conference on Artificial Intelligence. (2011) “South Korea Vs. North Korea - Economy Comparison”. 2018. Indexmundi.Com. https://www.indexmundi.com/factbook/compare/south-korea.north-korea/ economy.

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GAINSBOROUGH PRIZE WINNER/TOP STORY

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Darcy, Gatsby Wonka or

Who’s the Wealthiest?

Anna Howell, Economics, 2019 It is often of popular opinion that economists know nothing of art, and artists know nothing of economics. Yet, from Charlotte Brontë’s portrayal of England’s 19th century social system, to the First World War evoking the work of poets such as Owen and Sassoon, economics continuously permeates fictional literature to leave subsequent generations with a vast library of implicit socio-economic information. After acknowledging this association, how can we appreciate the worth of incomes and wealth referenced in history’s literature when the value of money itself and its purchasing power has changed so? Jane Austen’s character Mr Darcy is famously worth £10,000 a year – a staggering sum in Georgian era England, but equates to an income of under the National Minimum Wage for a full-time worker in present-day figures. Analysis of novels themselves and the economic climates that they were written in, may give rise to a deeper appreciation of monetary references made and their equivalents in today’s financial markets.

The narrative voice in Pride and Prejudice states that ‘it is a truth universally acknowledged that a single man in possession of a good fortune may be in want of a wife’ (1), representing the importance of wealth in the British 19th century marriage market and the ideals of moving through social hierarchies using advantageous marriages. First published in 1813, society was characterised by limited independent legal rights for women and inheritance operating via descent and entailment – laws fundamental to determining one’s wealth, which was accumulated primarily through land ownership.

The witty Austen lavishes Mr Darcy in affluence before the plot even begins by associating him with the ruling class of medieval England, as ‘D’Arcy’ is a traditional Anglo-Norman name (2). So, we know Darcy’s rich, but just how extensive is his £10,000 fortune?

We can first observe the purchasing power of money in the Regency era through the cost of basic indicators of social status. An income of £100 per year represents the bare minimum income on which a small household could be sustained with one maid – a servant being a necessary expense to maintain a respectable status. On a greater income of £700 a year, a family could support two servants and a carriage (3). Therefore Darcy’s £10,000 suggests he obtains the real purchasing means to afford the most luxurious lifestyle. Steven Broadbury, professor of economic history at Oxford University, provides data to further this analysis by adjusting for inflation over the past two centuries (4). He finds that an income of £10,000 a year in the 19th century is the equivalent of £838,100 in 2017 – an income exceeding that of a VP-level credit trader on Wall Street. He extends this analysis by accounting for the increase in labour earnings by the 21st century, and therefore the sense that working a day today will enable one to purchase many more

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goods than working a day in the early 1800s, even adjusted for inflation. This adjustment raises Darcy’s earnings to a staggering £9.995 million per year making him a comfortable multimillionaire. Broadbury also acknowledges that the British economy was smaller in the 19th century than today with UK population expanding from 10 million in 1800 to around 66 million in 2017 If we consider Darcy’s £10,000 as a share of national income then this equates to just under £61.6 million per year today – a higher salary than the sum Cristiano Ronaldo receives from his contract extension with Real Madrid (5).

Where a Georgian society could appreciate the immensity of Mr Darcy’s wealth, present day readers of Austen’s work can only recognise his riches through altering finances for macroeconomic data – an instance where art can only be truly grasped with simultaneous economic comprehension.

As the name suggests, The Great Gatsby by F. Scott Fitzgerald gave rise to another of the wealthiest men in celebrated literature – Gatsby. The fictional novel set in Long Island, 1922, encompasses many features of the Roaring Twenties in America. This period of economic prosperity across the US and Western Europe saw the birth of the American Dream and substantial expansion in technological progress – particularly the mass production of vehicles in the US leading to the wealthiest of the population owning ostentatious automobiles. Post World War One, the US and Wall Street gained dominance in international financial markets which only ceased following the Wall Street Crash of 1929. In the summer of 1922 the sale, production, and transportation of alcohol was made illegal succeeding the National Prohibition Act of 1920 (6).

Starting life as a ‘penniless young man’ Fitzgerald alludes to the fact that Gatsby makes his fortune through ‘bootlegging’ – a form of organised crime shipping alcohol illegally (7). Gatsby lives a garish lifestyle complete with a mansion, Rolls-Royce, and an excessive party at least once a fortnight. In 2010, a property similar to that of Gatsby’s in Long Island, was listed for $29.5 million – around $2.7 million in 1920 according to the Bureau of Labor Statistics CPI inflation calculator, suggesting Gatsby was another literary multimillionaire. This also implies Gatsby may have utilised other criminal activities to establish his wealth pre-prohibition in order to pay at least a down payment on the mansion before 1920, as loans were typically written not exceeding 50% of the property value in the 1920s and therefore this payment could be over a million dollars (8).

Though creating his riches from potentially less virtuous techniques than Mr Darcy, Gatsby can still be considered to be one of the most notoriously wealthy characters in literature.

prize for the richest of the three yet is unfortunately surpassed by the likes of Bruce Wayne and Mr Grey (10). More importantly, the availability of various price indexes and purchasing power estimations have enabled us to approximate the extent of the income of three fictional characters from various time periods and countries – demonstrating the importance of storing economic data, not only to the practise economics, but literary and historic exploration too.

References Austen, Jane. ‘Pride and Prejudice’. Oxford University Press. (1988) Doody, Margaret. Jane Austen’s Names: Riddles, Persons, Places. University of Chicago Press. P 72. (2015) Copeland, Edward. ‘“Money.” The Cambridge Companion to Jane Austen’. Cambridge University Press. (1997) Producer: McDonald, Charlotte. ‘More or Less podcasts, “How Rich was Jane Austen’s Mr Darcy?”’. BBC World Service. (Aired: November 2017) Badenhausen, Kurt. ‘The World’s Highest Paying Athletes 2017: Behind the Numbers’. Forbes Media. (2017) Accessed: https://www.forbes.com/profile/cristiano-ronaldo/?list=athletes Bruccoli, Matthew Joseph. ‘F. Scott Fitzgerald’s The Great Gatsy: A Literary Reference’. Carroll & Graf Publishers. (2000) Fitzgerald, F. Scott. ‘The Great Gatsby’. Cambridge University Press. (1991) Snowden, Kenneth A.’The Anatomy of a Resedential Mortgage Crisis: A Look Back to the 1930s’. Bryan School of Business and Economics, UNC Greensboro. (2009) Advanced Technology Services, inc. ‘What Willy Wonkas Chocolate Factory Would Cost Today’. Accessed: https://www.advancedtech.com/resource/willy-wonkas-chocolate-factory-cost-today/ (2017) Noer, Michael and Ewalt, David M. ‘The Forbes Fictional 15’. Forbes Media. (2013) Accessed: https://www.forbes.com/special-report/2013/fictional-15/jay-gatsby.html

A fictional character arguably even more outlandish than Gatsby is Roald Dahl’s Willy Wonka in Charlie and the Chocolate Factory. Although potentially not one of the leading exemplars of literature with notable economic teachings, the novel was inspired by strong competition and espionage between Cadbury and Rowntree’s – England’s largest rival firms in the chocolate market in 1920. Though the source of Wonka’s wealth is ambiguous, an expense list created by Advanced Tech Services estimates the cost of his chocolate factory would be approximately £160 million today – including Oompa Loompa healthcare and labour expenses, the cost of edible wallpaper and a chocolate river (9). This equates to around £3.8 million in 1920 according to the Office for National Statistics composite price index, meaning Wonka is equally as worthy to be considered a prosperous character.

Charlie and the Chocolate Factory is a well-known children’s book which Dahl may not have intended to contain economic issues, however this proves that even the most fictional of tales can be influenced by social and monetary conditions.

Gatsby’s 2013 feature in Forbes’ The Fictional 15, a list of the top 15 wealthiest fictional characters, may mean he takes the

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Time’s up Trident on

Daniel Light, Economics, 2018 We live in a country of conventional wisdoms. Political norms which cease to be challenged, as if you are foolish enough to challenge them, you will have your morality, humanity and sanity interrogated by ‘the establishment’. The NHS is a prime example of this. We have a health system that is in perpetual crisis. To me, it is quite clear that we need to change our approach to public health provision. The completely boring outcry for more money, while it may be a credible short-term fix, is only to detract from the central issue. We are clouded by an emotional mist which doesn’t allow us to see fault in what has been the beating heart of this country for the last 80 years. Despite the enormity of the problem I have just outlined, one that I see to be even more blatant is the stupidity of our ‘nuclear deterrent’.

Britain’s relationship with these weapons of mass destruction began in the summer of 1945 when the, then Labour, government, headed by Clement Attlee, created a cabinet committee tasked with exploring the possibility of acquiring an atomic bomb. Seven years later, in October of 1952, Britain becomes the third nation, after the United States and the Soviet Union, to successfully detonate a nuclear weapon.

Britain ceased in their maintenance of an independent nuclear deterrent when Harold Macmillan took the decision, in 1962, to procure Polaris missiles from the United States under the US-UK Mutual Defence Agreement. Our procurement from the US was updated in 1980 when Margaret Thatcher’s government agreed to acquire Trident, replacing the Polaris system.

The independence of a nuclear deterrent is paramount.

If our foreign policy was to diverge significantly from that of the United States (which looks progressively likely under the Presidency of Mr. Trump), what would stop them from rendering Trident operationally useless. In essence, we have to conform or our deterrent becomes pointless.

It begins to look like the special relationship is marginally more one-sided than we, on this side of the Atlantic, would like to admit. In the 2014 Concluding Report of the independent, all-party Trident Commission, it admitted that our nuclear deterrent was ‘hostage to American goodwill’.

In short, our Nuclear Weapons system has three parts; the submarines, the missiles and the warheads. The submarines are manufactured in Cumbria, in the North-West of England. However, they are developed using US designs with a substantial proportion of the components imported from the US. We lease the missiles from the US and regularly have to return them to Kings Bay, Georgia for maintenance and replacement. The warheads are produced

The relationship that led to Britain forgoing their independent nuclear deterrent. President John F. Kennedy and Prime Minister Harold MacMillan in April 1961 by the Atomic Weapons Establishment who operate out of Berkshire, England but the components essential to the development of these warheads (gas reservoirs and body shells) are, again, imported from the US. The UK also rely on the US for weather and navigational data which is provided by the US GPS system. In a scenario where the US decided to withdraw this technical support, hitting targets accurately would be far harder (Select Committee on Defense, 2006). Highlighting our dependence even further, the only location we can test our nuclear deterrent is off the Florida coast in Cape Canaveral. Testing our program so far away from our own shores has had fallbacks. In 2016, Trident misfired and we heard precious little about it in the UK media (rumored to be under Barak Obama’s orders) which may not have been the case if we were testing closer to home The British government maintain that Trident is fully independent and could be used without prior NATO and White House approval. A senior fellow with the International Security Program, Thomas Karako, tried to contextualize this when he said ‘just because my car is made in Japan or Germany, doesn’t mean it’s not my car to drive. Do I need to make my own filing cabinet to have an independent office?’ But of course, the reality of this situation is different. Ted Seay, a senior consultant at the British American Security Information Council (BASIC), who spent three years at NATO, put it perfectly. when he said ‘As a policy statement, it’s ludicrous to say

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that the US can effectively donate a nuclear program to the UK but have no influence on how it is used. It would also be unthinkable for the UK to launch a strike outside of NATO. There is an incredible pressure on every member to conform.

I know that as an insider. If you’re thinking about launching nuclear weapons at Russia or perhaps Iran, it has to be fought out around the NATO table. To say that you (Britain) could launch a unilateral attack over the heads of NATO and Washington might be theoretically true, but practically speaking, it’s rubbish.’ It is worth pointing one can argue Trident has been beneficial in the context of the United Nations. The United Kingdom is a one of the permanent five members on the United Nations Security Council. All five of these nations (US, UK, France, Russia and China) have nuclear capability and many attribute our presence on the top diplomatic table down to Trident. It is unclear as to whether we would lose our seat in the scenario in which we terminated our nuclear program.

Despite my feelings towards Britain’s nuclear program, I am not a proponent of complete nuclear disarmament. Nuclear deterrence has worked. The concept of Mutually Assured Destruction has reduced the conflict between nuclear nations. Even at the height of the Cold War with immense worldwide ideological polarisation, we avoided the scale of death experienced prior to nuclear weapons. The issue I take is not with the weapons in general, but the state of our program in the United Kingdom, as I have outlined.

Another question we need to be asking ourselves, as a country, is who is our nuclear deterrent actually deterring?

Every single person you ask this question will say something along the lines of ‘no one now but the future is uncertain’.

Despite tensions with Russia increasing since the Salisbury attack, can anyone really argue that the threat is nuclear?

The world has moved on and the dangers we face today are different to those faced throughout the 20th Century.

For example, the current threat level in the United Kingdom is up to Severe and has fluctuated up to Critical in the wake of terror attacks during 2017. We need extra funding to aid terror prevention. Police recorded crime is on the rise with many attributing this to reductions in police budgets in this time of austerity. We need extra funding to help the police fight crime. It is estimated that over 300,000 people are either homeless or living in inadequate housing; an increase of 13,000 over the past year. We need extra funding to ensure all citizens are able to sleep in safe shelter.

potential economic benefits is that decommissioning would be expensive. The Ministry of Defence has estimated it would cost £9.6bn. This includes disposing of the 200 warheads, decommissioning the Vanguard submarines, paying off expensive contracts and the list goes on. On top of this, our nuclear defence industry is a large-scale employer with some estimating that 15,000 jobs could be lost if Trident wasn’t renewed (BBC, 2017). However, many of these jobs could be transferred to other sectors. For instance, Paul Ingram, executive director at BASIC, makes the point that ‘the nuclear engineers could be redeployed on green energy projects’.

The continuation of our Trident Nuclear Program is nothing more than pandering to US interests and attempting to maintain our international prestige. Is our population safer than the populations of Germany and Mexico because of our nuclear capability? If anything, it makes us more of a target. It time that those in power put their egos behind them and make a decision that would free up billions for our public services.

References The Secretary of State for Defence and The Secretary of State for Foreign and Commonwealth Affairs, The Future of the United Kingdom’s Nuclear Deterrent. December, 2006.

The Guardian. 2017. One in every 200 people in UK are homeless, according to Shelter. [ONLINE] Available at: https://www.theguardian.com/society/2017/nov/08/onein-every-200-people-in-uk-are-homeless-according-to-shelter. [Accessed 13 March 2018].

UK Defence Journal. 2017. No, America doesn’t control Britain’s nuclear weapons.

[ONLINE] Available at: https://ukdefencejournal.org.uk/no-america-doesnt-control-britains-nuclear-weapons/. [Accessed 13 March 2018].

BBC. 2017. A guide to Trident and the debate about replacement. [ONLINE] Available at: http://www.bbc.co.uk/news/uk-politics-13442735. [Accessed 13 March 2018]. he Trident Commission. 2014. The Concluding Report. [ONLINE] Available at: http:// www.basicint.org/sites/default/files/trident_commission_finalreport.pdf. [Accessed 13 March 2018].

Select Committee on Defence. 2006. Written Evidence. [ONLINE] Available at: https:// publications.parliament.uk/pa/cm200506/cmselect/cmdfence/986/986we13.htm.

[Accessed 13 March 2018]

The annual spend on Trident is £2bn, around five or six percent of the Ministry of Defence’s budget. However, the Vanguard submarines need to be replaced and this is expected to cost £31bn with an extra £10bn to cover any additional costs incurred. In July 2016, MPs voted 472 to 117 in favour of renewing the program. We need to be realistic about our position globally and understand that, quite frankly, the money could be spent better elsewhere. The counter argument to the

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Is a Graduate Tax the Answer to Our Prayers?

Rosie Mahoney, Industrial Economics, 2019 Tuition fees; two words that cause images of empty bank accounts and anxiety stricken students to flood to mind. Last year there were a total of 2,250,500 students attending university in the UK (HESA, 2017) paying one of the world’s highest education fees, contrasting to those living the high-life in European countries such as Germany and France which merely charge administration fees of a few hundred Euros (baguette anyone?) (Kentish, 2017). Short of packing my bags and adopting a pitiful accent, the question I’ve been left asking is, what’s the alternative?

The history of tuition fees is a rather long and complex one, unsurprisingly linked to the traditional Tory Vs Labour fisticuffs we’ve grown accustomed to and find somewhat entertaining. Although it may be difficult for you or I to remember a time when the words “student finance” didn’t send a shiver down our spine, prior to 1997 tuition fees were a thing of the future and grants were given to young people pursuing higher education. In 1998 the university finance system changed drastically, and the first tuition fees were introduced and capped at £1,000 (must have been nice…). Since then tuition fees have represented the country’s political divide. Even recently, Labour’s promise to scrap tuition fees rallied students across the country during the general election, whilst bringing into question the plausibility of this (Coughlan, 2017).

A graduate tax differs to tuition fees in that it would be levied throughout an individual’s working life once higher education is completed, with greater earnings after graduation requiring more to be paid back. Currently, tuition fees are capped at £9,250 in the form of a loan paid to the university directly. Graduates start paying this back once they earn £21,000 and repay 9% of the amount they earn above this figure for 30 years, after which any remaining debt is written off (McQuillan, 2017).

So, what are the arguments for replacing tuition fees with a graduate tax?

Supporters of a graduate tax system advocate its progressive nature, as those who benefit most from university and land themselves a swanky job repay the most. This would remove the deterrence that those from lower-income backgrounds may feel when thinking of applying to university due

to fear of collecting large amounts of debt (Institute for Fiscal Studies, 2014). Whilst some speculate a tax would not raise enough money to fund universities at the same standard, a study conducted by the consultancy firm London Economics found that a tax levied at around 2% would raise as much money as the fees currently in place (London Economics, 2017).

An added benefit of introducing a tax is that the bureaucracy of the student loans company would be diminished and the higher education financial system could become more efficient as it would instead be handled by HM Revenue and Customs (BBC, 2010).

However, a graduate tax may not be all sunshine and rainbows. Some argue that a tax would be a logistical nightmare. If it were introduced this year students would not pay until 2022, forcing the government to fund universities alone during this period, adding to national debt (Coughlan, 2017). Similarly, what would the government do about those jetting off abroad to work in the sun after graduation? Student loans are legal contacts that can be enforced if students move abroad but collecting tax from those outside the UK system would present yet more difficulties.

Opponents also argue a tax may be unfair as those who are most successful end up paying the most, subsidising their peers and paying more than their share (McQuillan, 2017).

Please hold your grumbles, for there are actually several benefits to our current payment system. Tuition fees have allowed English universities to separate themselves from the central government, meaning they are not limited in the number of places they can offer to students, facilitating a boom in demand. When tuition fees were implemented it was mandated that institutions spend at least 1/3 on disadvantaged students, contradicting the common notion that fees have created a barrier for those from a poorer background in accessing higher education (Balls, 2017).

Despite this, the tried and…somewhat trusted system clearly does have its faults. The Institute for Fiscal Studies (2014) has suggested that 73% of future graduates will never earn enough to pay off the debt accumulated by the fees, leading the government to write off around 45% of all loans, which brings into question the sustainability of this system in

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the long run. It is also believed that fees create an unfair system as those who earn more after university can end up paying less into the system over time than lower earners as the 9% repayment rate reduces their debt owed at a faster rate (Blake, 2010).

There you have it, graduate tax Vs tuition fees. Clear things up?

Didn’t think so…

Even some critics of tuition fees have gone as far as to claim that the current system is practically already in the form of a tax. Believing that in practice, tuition fees are a form of income tax as they are paid through PAYE or after self-assessment so are hardly different from an increased income tax. Increases in the income tax threshold under the coalition government mean that the graduates of 1997 (the last year not to pay tuition fees) paid roughly the exact same amount in taxation as the graduating class of 2012 (the first to pay the £9,000 fee) (Intergenerational Foundation, 2015). So really, I may have just wasted my time in so eloquently presenting this debate for you.

These two seemingly very similar systems do have alternatives. Researchers at the UCL Institute of Education have set out proposals for a new “all-age graduate tax” that could be used to bring down tuition fees, whereby graduates aged 40 and above who benefited from a free university education would pay a retrospective tax to help fund the current generation of students (Green, 2017).

So maybe think twice before asking your parents for a new car…

So, is introducing a graduate tax the answer to students’ prayers?

I would have to say...no. Well...maybe.

How about we all just move to Germany?

References Kentish, Benjamin. “University tuition fees in England now the highest in the world, new analysis suggests.” The Independent , March 28, 2017. Accessed March 7, 2018. http://www.independent. co.uk/news/education/university-tuition-fees-england-highest-world-compare-students-student-loan-calculator-a7654276.html.

HESA. “Who’s Studying in HE?” HESA. 2017. Accessed March 1, 2018. https://www.hesa.ac.uk/ data-and-analysis/students/whos-in-he.

Blake, Heidi. “Grants, loans and tuition fees: a timeline of how university funding has evolved.”

The Telegraph, November 10, 2010. Accessed February 28, 2018. https://www.telegraph.co.uk/ education/educationnews/8057871/Grants-loans-and-tuition-fees-a-timeline-of-how-university-funding-has-evolved.html.

Coughlan, Sean. “10 charts that show the effect of tuition fees.” BBC News, July 8, 2017. Accessed February 26, 2018. http://www.bbc.co.uk/news/education-40511184.

McQuillan, Martin. “Graduate tax: a short history of a long-lasting bad idea.” The Guardian, September 7, 2017. Accessed March 7, 2018. https://www.theguardian.com/higher-education-network/2016/sep/07/graduate-tax-history-bad-idea.

London Economics. “The Impact of Student Loan Repayments on Graduate Taxes.” Final Report for the University and College Union, July 20, 2017, 16-37. Accessed March 7, 2018. https:// londoneconomics.co.uk/wp-content/uploads/2017/07/LE-Impact-of-student-loan-repayments-on-graduate-taxation-FINAL.pdf.

BBC. “Tuition fees and graduate tax: What’s the difference?” BBC News, December 8, 2010. Accessed February 27, 2018. http://www.bbc.co.uk/news/uk-politics-11946585.

Institute for Fiscal Studies. “A graduate tax for the UK? .” 2014. Accessed March 7, 2018. https:// www.ifs.org.uk/budgets/gb2002/chap8.pdf.

Balls, Katie. “There’s a progressive argument to be made for tuition fees – why won’t the government make it?” The Spectator . October 16, 2017. Accessed March 7, 2018. https://blogs.spectator.co.uk/2017/10/theres-a-progressive-argument-to-be-made-for-tuition-fees-why-wont-thegovernment-make-it/.

Green , Andy. The Crisis for Young People: Generational Inequalities in Education, Work, Housing and Welfare. London: Palgrave, 2017.

Intergenerational Foundation. “Higher education: would a graduate tax be fairer than income-contingent loans?” Intergenerational Foundation. April 17, 2015. Accessed February 28, 2018. http://www.if.org.uk/2015/04/17/higher-education-would-a-graduate-tax-be-fairer-thanincome-contingent-loans/.

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