Art and Economics

Art and economics probably aren’t the most natural of bedfellows. In my latest attempt at pretending to be sophisticated, and as part of a summer trip gallivanting around Barcelona, I ended up visiting (among all the other wonderful culinary and cultural delights) the city’s Museum of Contemporary Arts (MACBA).

The ground floor of MACBA is taken up with an exhibit by Andrea Fraser, called “L’1%, c’est moi”, which tries to present information and musings about the art world, with particular focus on individuals that have obtained and developed large personal collections of art. Unsurprisingly, Fraser’s angle is one of how those individuals with their own art collections are, for want of a better word, dubious (both in terms of their ethics and in terms of how they have been able to afford to obtain their art collections).

Indeed, one of the more wide-reaching points that Fraser tries to make is that an increase in inequality (it is unclear is Fraser is referring to wealth or income inequality) has enabled those individuals to build their collections. To that end, one of the “artworks” included in the exhibit was a short report, presumably put together by Fraser herself, that purports to demonstrate that rising inequality has benefited art collectors. In other words, Fraser is claiming that increasing inequality has enabled art collectors to benefit from increases in the value of their art collections.

However, Fraser’s “analysis” is pitiful at best. For a start, it is widely acknowledged that (income) inequality now is at roughly the same level as it was about 200 years ago (see, for example, here), yet Fraser chooses to focus solely on the past 50 years to try to bolster her claim that inequality is exceptionally high. Fraser does not extend her analysis back far enough in time to enable the conclusions she makes to be supported by the evidence. In fact, this is borne out by the graph on page 3 of Fraser’s report (reproduced below) showing that income inequality has been pretty much constant 50 years – hardly a marked increase in inequality at all.


Moreover, the graphs Fraser included in the MACBA exhibit indicate that her understanding of statistical analysis does not extend even as far as the well-known maxim that “correlation does not imply causation”. To be fair to Fraser, a few economic researchers also don’t understand this concept particularly well. Nonetheless, in using the graph shown below, Fraser tries to support her claim that increases in inequality are leading to increases in the value of art.


She does not, it seems, realise that there are plenty of other alternative reasons for the observed relationship – for example, it could be that the increase in the value of art is itself causing, or that both an increase in the value of art and the share of income obtained by the top 0.01% is driven by a common third factor (such as, for example, the rate of return on other investments).

The potentially absurd inferences that can be obtained by relying just on correlations can be seen even better in the graph below. The black dashed lines show the growth in the number of prisons and museums in the US over time, while the solid red line shows the US prison population. If one were to rely on correlations to make inferences, one would draw the conclusion that one way to reduce the US’ prison population would be to decrease the number of museums in the US. This shows the sheer ridiculousness of drawing conclusions from simple correlations alone.


Hence, it’s clear that Andrea Fraser really should have put a bit more thought/work into the “analyses” she included as part of this exhibition.

PS. As a bonus piece of artsy mumo-jumbo economics, here is a description of an artwork by Adrian Melis. Enjoy





George Osborne: A solid, but not spectacular Chancellor

As announced last night, George Osborne is no longer Chancellor of the Exchequer. Plenty of articles have already been written regarding how he’ll be remembered and whatnot (see, for example, here), but what really matters in an evaluation of his performance as Chancellor is focusing on the long-term impact of his main policies.

Of course, the main focus of Osborne’s term as Chancellor was “austerity” (or, as it is described in technical terms, a “fiscal consolidation”). There is lots of debate as to whether austerity is harmful or is beneficial to growth in the short-run – for example, Alesina & Ardagna, and some parts of the IMF, find that fiscal consolidations actually increase short-term growth, whereas the likes of Guajardo et al. and other parts of the IMF believe that fiscal consolidations harm short-term growth.

However, what really matters in evaluating the impact of austerity is its likely affect on long-term growth. Here, none of the aforementioned studies have anything to say, but there are good reasons to believe that austerity is beneficial for long-term growth. For example, it seems plausible that the amount of time required for a country to re-establish any lost credibility (either with taxpayers or the central bank) that arises from running continually large fiscal deficits could be relatively high – convincing people that a country is now fiscally responsible is unlikely to be the matter of a few years’ work.

In other words, it is plausible that it could take longer than just a few years for people to change their opinion regarding a country’s fiscal responsibility, such that the full impact of fiscal consolidations are only likely to be felt far into the future. Moreover, even though a recent working paper (by Fata & Summers) suggest that fiscal consolidations hamper long-run growth, those papers are based on a methodology that is fundamentally flawed.) Hence, austerity per se could have been a good policy of Osborne’s.

However, Osborne erred when he cut government spending on investments and infrastructure. At a time of incredibly low interest rates, it would have made sense to borrow to invest in projects that would have reaped a return in the future – the costs of borrowing are low, while the expected future benefits of such investments are likely to be high (in terms of their impact on future growth and on future tax revenues). Therefore, Osborne’s focus on cutting all, rather than just day-to-day, spending was misguided. Just as misguided (for the same reasons, since it prevented Osborne from borrowing to invest in infrastructure) was his Fiscal Charter.

Similarly, protecting spending on the NHS and on international development meant that there was little incentive for those departments to find savings despite the fact that they, and the NHS in particular, is bloated and full of inefficiencies (witness the large NHS deficits). If those departments had not had their budgets protected, a more efficient and equitable distribution of the cuts to day-to-day spending could have been achieved (since if the NHS or development budgets had been cut slightly, then other departments’ budgets would not need decreasing as much). Likewise, the triple lock on pensions. So, another negative point for Osborne there.

On the other hand, Osborne did set up the Office of Budget Responsibility (OBR), which was undoubtedly a very good thing. Although not quite as dramatic as Labour granting the Bank of England (instrument) independence in 1997, this step was important since it enabled and promoted independent oversight of government forecasts and spending plans. Moreover, it added much-needed rigour to Treasury analysis, evaluation of government performance against fiscal targets etc. since those working in the Treasury know that people at the OBR will review and evaluate any plans and forecasts.

Getting on to some of the smaller issues, the pasty-tax debacle was also a negative point. Specifically, the introduction of the tax was actually a decent idea – it removed some of the myriad of exemptions that apply to VAT, thereby simplifying the tax system – but the subsequent reversal of the policy in the face of (relatively small) public backlash was weak and disappointing to see. Likewise, the introduction of the National Living Wage policy was a good idea, but restricting it to over 25s seems rather a cop-out, and instead the minimum wage should (and could easily) have been increased to the level of the NLW, thereby benefiting more people without substantially increasing businesses’ costs.

There are also things that Osborne couldn’t really do much about, but for which some might blame him anyway. The lack of productivity growth might be one, but that’s more the responsibility of other departments than it is the Treasury. Failing to meet, or continually adjusting, his fiscal targets could be another – but Osborne was hampered in meeting those because of sluggish growth in the global economy.

Overall, then, it seems as though there are plenty of things over which Osborne can be criticised (e.g. refusing to borrow to invest, protecting certain departments’ budgets), but equally there are plenty of policies he introduced that are worthy of praise (e.g. the OBR, consolidating day-to-day fiscal spending). As such, Osborne will most likely go down in history as fairly middle of the road – some good bits, some bad bits, but generally not outstanding in either category.

Pesky immigrants, coming over here, making our lives better

Further to a previous post about how immigration can benefit the global economy, it’s also important to examine how immigration can affect the people in areas to where people have migrated. One of the main arguments used by those that try to claim that immigration is harmful is that immigration hurts the wages / employment of the low-skilled because supposedly cheaper immigrants take those jobs away from domestic workers. The fact that this argument is based on the false “lump of labour” theory has been covered well elsewhere (see, for example, here), but it can also be tested empirically.

To that end, a recent paper by Foged & Peri investigates the impact of immigration on domestic workers of various different skill types. To do so, it makes use of a quirk in the system that Denmark used to re-locate successful asylum-seekers and the fact that in subsequent years, relatives of those asylum seekers came to join them. Specifically, between 1986 and 1998, Denmark distributed refugees across the country taking into account only the refugee’s family size, the nationality of the refugee (so as to try to achieve “clusters” of refugees that would help each other out), and the availability of housing in each area.

In this way, the location of refugees was almost entirely independent of local labour market conditions. (Note that it is not entirely independent because there is likely to be some relationship between an area’s labour market and the availability of housing.) Nonetheless, this distribution of refugees was followed by a period between 1995 and 2003 in which immigrants from various regions moved to Denmark (most of these were from the likes of the Former Yugoslavia, Somalia etc. and were trying to escape local conflicts).

The people in this “new wave” of immigrants tended to settle in areas where earlier refugees/immigrants with the same nationality had settled – in this way, the initial distribution of refugees (that was mostly independent of labour market conditions) also drove future immigrants’ decisions of where to settle. Hence, the increase in immigration to Denmark from 1995 on can be used to assess the impact of immigration on the labour market in Denmark since the locational decisions of those immigrants was mostly independent of the labour market conditions themselves. (This is important because otherwise the results of an analysis of the impact of immigration on the labour market would be biased if the amount of immigration to a particular area itself was affected by the labour market in that area).

Therefore, in order to assess the impact of immigration on Danish workers, the paper uses a “longitudinal cohort study” – i.e. a frequent survey of a large group of people over a prolonged period of time (in this case, the Danish Integrated Database for Labour Market Research). This survey contains information related to someone’s age, municipal location, whether or not they are employed, their occupation, the number of hours they work, their salary etc. Coupled with information on where immigrants settled as per the previous paragraph, this dataset thus enables the researchers to investigate the impact of immigration on domestic workers.

The results of the study are extremely interesting. Contrary to the fallacious argument that low-skilled workers are harmed by immigration, the results of this study indicate that immigration actually benefits low-skilled workers in multiple ways.

First, immigration motivates and enables low-skilled workers to progress into more complex occupations. Second, these more complex jobs are associated with higher wages, such that immigration actually increases the hourly wage of low-skilled workers. Third, immigration does not result in (some number) of low-skilled workers becoming unemployed. In other words, immigration doesn’t force low-skilled workers out of a job, but instead enables them to obtain better jobs.

In addition, the study also looks to see if the impact of immigration falls different across different sets of low-skilled workers. It finds that the positive impact of immigration is felt most strongly by those low-skilled workers that are either young (less than 46 years old) or have not been in their jobs very long (less than four years), but also that there are no statistically significant negative effects for older workers or those that have been in their jobs a long time.

Overall, therefore, this study is pretty conclusive that immigration is beneficial to low-skilled workers and that those that claim that immigration harms those on low wages really don’t know what they’re talking about.

The cost of Brexit (part 2 of who knows how many)

In response to the Treasury’s report on the costs of Brexit (and, obviously, to my blog post covering that report) a group calling themselves “Economists for Brexit” published a pamphlet which they claim contains a more reasonable estimate of the impact of Brexit on the UK economy.

Unsurprisingly, they find that, contrary to the Treasury’s report (and, indeed, the vast majority of economic reports published on this issue), that Brexit would benefit the UK economy by increasing GDP growth by about 0.5% points per year on average (with the majority of this increase coming in 2020, the final year of their forecast).

Equally unsurprisingly, their estimate is fundamentally flawed. In an impressive attempt to hide these flaws, the report contains only a two page summary of the model they have used to obtain their results, but even then the numerous flaws are apparent.

First, the report assumes that leaving the EU would mean that the UK would be able to remove EU-set trade barriers to non-EU countries, but would still keep the same terms-of-trade it currently has with EU countries. Moreover, it assumes that all trade barriers will reduce by half over the next five years. These assumptions drive the report’s “finding” that Brexit would increase UK living standards by 3.2% by 2020. However, the report does not provide any evidence to support the validity of either of these assumptions. Indeed, there is plenty of evidence to suggest that they are not valid – for example, they assume a rate of decrease in trade barriers not seen since the 1960s.

Second, the report assumes that the 0.8% GDP net saving from the UK not having to contribute to the EU budget would be passed-on entirely to taxpayers in the form of an income tax cut. This is extremely unlikely to happen – due to the current government’s austerity policies, any savings from Brexit are likely to be used to reduce the government deficit rather than hand out a (potentially politically damaging) tax cut.

Third, not only does the report assume that there would be a reduction in regulation if the UK were to leave the UK (which is an unproven assumption), the report then assumes that this reduction in regulation would have exactly the same effect as a 2% point decrease in the employer rate of NI. One hopes that those writing the point must have released how barmy such an assumption is – the report doesn’t contain even a passing attempt to justify how a decrease in regulation would have exactly the same impact as reduction in employer NI. Indeed, it is barely possible to conceive how anyone could think this was a reasonable assumption.

Anyway, moving on. Finally, the report assumes that the government deficit is unchanged due to the aforementioned assumptions resulting in the government’s revenues not changed. However, this fails to recognise the possibility that some of the money that was spent on EU goods and services previously could now be spent on UK goods and services, thereby potentially increasing tax receipts. Conversely, the report also assumes that non-UK people and businesses won’t decide to move away from the UK, which would result in a decrease in tax revenues.

And all of this is to say nothing of the fact that the report has excluded countless other factors that could be detrimental to the UK. For example, the report does not even mention the potential impact Brexit could have on immigration (note that the vast majority of studies find that immigration is beneficial for the country to which immigrants relocate and this is even true for low-skilled workers in that country). Nor does it cover the costs associated with the uncertainty that would be created and persist for a number of years regarding exactly what form of agreement between the UK and the EU would be put in place post-Brexit.

In essence, the study published by the “Economists for Brexit” group is so full of holes it is no surprise that they were only able to find eight professional economists to support it. Contrast this to the almost 200 economists (including yours truly) that are signatories to a letter in the Times stating that “[l]eaving would entail significant long-term costs.” That in itself should be damning enough.

Why the difference between correlation and causation matters

A blog post by a member of the Economic Policy Institute (a US think-tank) has claimed that the decline in Trade Union membership is the cause of the increase in (a single measure) of inequality in the USA.

The blog post looks at how membership of Trade Unions and the share of income that goes to the top 10% change during the period 1917-2012, notices that they appear to be negatively correlated, and therefore concludes that decline in trade union membership is responsible for the increase in inequality.

First, it is important to note that inequality has actually decreased over time, rather than increased as the article claims (see, for example, here and here). Moreover, the blog’s use of a very specific measure of inequality, focusing solely on the income share of the top 10%. It does not take into account any other factor that determines the level of inequality within a country – for example, whether the majority of income in the top 10% is distributed evenly across that 10%, or is concentrated in the top 1% or even the top 0.1%.

Indeed, a more comprehensive measure of inequality (such as the Gini coefficient) takes into account the distribution of income across the entire spectrum rather than merely focusing on a subset of that distribution. When looking at such measures over time, it becomes apparent that inequality across the entire distribution of incomes has barely increased since the 1960s, despite the measure used in the blog post having increased since that time.

(And that is not withstanding other ways in which inequality might arise, such as via the distribution of wealth, access to healthcare, and/or access to education.)

Second, the author’s evidence to support their argument that a decline in trade union membership is responsible for the increase in inequality  consists solely of the fact that the measure of US inequality they choose is negatively correlated with US Trade Union membership.

There are plenty of examples of two series being correlated over time, despite there not being any way in which a causal relationship can exist between them. For example, Tyler Vigen presents such examples as Arcade revenues being correlated with number of Computer Science PhDs being awarded, and there being a strong correlation between Maine’s divorce rate and per capita consumption of margarine.

Moreover, the article’s “analysis” fails to account for the countless other factors that could have affected inequality over the course of the almost 100 years covered. For example, demographic changes, changes in the industries, technological developments, new infrastructure, changing societal attitudes individually and together are likely to have contributed to the changes in inequality. Indeed, the correlation between the US Trade Union membership and the chosen measure of inequality appears to be the large increase in TU membership and the large decrease in inequality between 1936 and 1945. And it’s not as though there were other things going on during that period of time at all!  Despite this, the article attributes the changes in inequality solely to changes in Trade Union membership.

Finally, the article does not even try to come up with a mechanism by which Trade Union membership can affect inequality beyond a vague description of how trade unions increase bargaining power. There are no doubt plenty of other things that are negatively correlated with the measure of inequality used in the report and that the report’s author presumably also thinks is just as likely a reason for changes in inequality as is Trade Union membership (US military strength might well be one, as could the number of black and white television sets in use).

I look forward to the Economic Policy Institute writing about those in due course.



Gravity, Gobbledygook, and Government Reports

Mark Reckless is an idiot. Now, if I stopped there, it wouldn’t make much of a blog post (although it would, as usual, be factually accurate). So, you might be asking, “Why is Mark Reckless an idiot?” But that is the wrong question. Instead, what you should be asking is “How has Mark Reckless demonstrated his idiocy this time?” And that would be a very good question indeed.

The answer to that question rests in the tweet below. This was Reckless’ comment regarding a description of one part of the methodology that the Treasury used to estimate the costs of Brexit – the equation in question was contained in a technical annex (i.e. where one would expect to find a detailed explanation of the approach used).

Reckless appears to be claiming that the equation in the picture he posted is equivalent to the fraudulent claims of a fortune teller. That could not be further from the truth.

Instead, the equation posted by Reckless is an algebraic representation of the “Gravity Equation” as applied to international trade. Emanating from Newtonian physics, this equation relates trade between two countries to the relative sizes of those countries (in terms of output and population) and the distance between them, plus some other controls for whether or not the countries in question share a common border / language / colonial history.

This is not a controversial method to estimate the impact of those factors on trade between two countries. In fact, the use of gravity equations is widespread in the assessment of international trade. A priori, one would expect larger countries to trade more with each other, but countries that are further away to trade less with each other and this is indeed reflected in the Treasury’s results.

The main point of this exercise, however, was to estimate the impact of being in the EU on the UK’s trade, and the Treasury does this by including a variable to capture that. The main result is that being in the EU increases trade in goods by about 100% (i.e. leaving the EU would result in a decrease in trade in goods of 53%) and increases trade in services by about 22%. Hence, being in the EU increases trade in goods and services overall by about 75%.

However, although the main approach used by the Treasury is reasonable, there are some areas in which it could be refined further. First, the Treasury’s analysis uses data covering the period 1948-2013, yet does not really try to control for factors that change over time (other than GDP and population). For example, there have been substantial changes to exchange rates and barriers to trade during the period covered by the Treasury’s data, both of which would have had substantial impacts on trade between two countries. The Treasury’s attempt to control for these changes over time consists solely of using dummy variables for each year (that do not vary across countries), which cannot even begin to capture the changes in exchange rates, trade barriers etc that would have occurred over the time period. This means that the estimated impact of being in the EU could well be incorrect.

Second, the Treasury’s approach assumes that the impact of being in the EU is the same for all countries. However, it is possible that the EU has an heterogeneous impact across countries – for some countries the impact of being in the EU might be larger than it is for other countries. By assuming away this possibility, the Treasury is likely to have under or over-estimated the impact of Brexit on trade.

Third, and on a more technical note, the Treasury does not specify what standard errors it has used. If the Treasury has used incorrect standard errors (for example, ones that do not correct for serial correlation or heteroscedasticity), that means that the statistical significance of its estimates is incorrect and, more importantly, that the error bounds (i.e. the upper and lower ends of their estimate) are likely to be incorrect.

Nonetheless, these minor potential refinements of the Treasury’s approach do not detract from the fact that Mark Reckless has been remarkably foolhardy in his response to the Treasury’s assessment of the impact of Brexit.


The cost of Brexit

How much does the UK’s membership of the EU actually cost? And, in fact, does being in the EU represent a net economic benefit, rather than a net cost?

If you were to believe the information provided by Vote Leave, you might think you’d know that the answer. Vote Leave has claimed that membership of the EU costs the UK about £18 billion per year, the equivalent of about £280 per person per year. However, this figure does not include the substantial rebates and public/private sector receipts that the UK receives from the EU – once these are taken into account the actual direct budgetary cost of the UK’s membership of the EU is about £8.4 billion, or £131 per person, per year (i.e. less than half of the original Vote Leave claim).

Moreover, the Vote Leave figure only includes the direct budgetary costs of being part of the EU. Importantly, it does not include, nor does the Vote Leave campaign attempt to include, any “indirect” benefits that result from EU membership. Such indirect benefits include, for example, any jobs or exports resulting from trade with EU countries that would not otherwise occur absent EU membership. If membership of the EU increases UK output above what it would have been if the UK was not part of the EU (which is likely to be the case), then leaving the EU would result in a decrease in UK output.

This could happen for such wide-ranging reasons as EU consumers have more diverse tastes than just those in the UK allowing a larger number of different firms to flourish in the UK and export their output to the EU than would otherwise prevail if the UK left the EU and UK firms would have reduced demand from EU countries; or collaboration between EU and UK firms enables a wider spread of technology that would not be possible after Brexit such that UK productivity is higher than it would be outside the EU; or membership of the EU encourages investment not just from EU firms but from firms located in the Rest of the World that would not occur if the UK were to leave the EU. There are plenty of other potential mechanisms through which EU membership increases UK output.

Importantly, although Vote Leave has not attempted to include such factors, the Centre for Economic Performance (CEP) has done so and finds that leaving the EU would reduce the UK’s output by at least £850 per household per year. That is the best case scenario for the Vote Leave supporters. Note, too, that this only includes “static trade consequences” – i.e. the impact that can be attributed just to losing the ability to trade freely with EU countries; it does not include any of the costs associated with reduced migration, technology transfer, investment etc that would also result from leaving the EU. In fact, once these factors are taken into account, the cost of leaving the EU could be as high as £6,400 per household per year.

As such, the £850 figure likely underestimates the true cost of leaving the EU.

Nonetheless, that is not to say that every part of the CEP analysis is beyond criticism. For example, the study assumes that intra-EU trade costs will continue to fall as they have done in the past, but does not provide any evidence to suggest that such an assumption is reasonable. If, in fact, intra-EU trade costs were to fall less quickly than assumed by the study, then the costs to leaving the EU would be reduced.

Moreover, little information is provided regarding how the estimates of the cost of leaving the EU that account for the aforementioned “dynamic” factors (such as migration and investment) are obtained. Given that those estimates are likely to be based (at least in part) on complex (albeit commonly used) statistical methods, a higher level of transparency regarding the approach used would be welcome so as to enable a higher degree of confidence that the estimates have been obtained via a reasonable approach.

Overall, therefore, although the Vote Leave figure regarding the benefits of leaving the EU is an egregious over-estimation, and it is actually highly likely that there would be a large net cost to leaving the EU, it is unclear what exactly the cost per household per year is. However, this uncertainty regarding the exact cost should not detract from the fact that the cost to leaving the EU is large.