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.