Guessing immigration is a mug's game

Before writing this article I decided to look up how the various online slang dictionaries defined the term “a mug’s game.” The first two definitions that popped up on Google were: “a futile or unprofitable endeavor” and “an activity that will not make you happy or successful,” both of which describe efforts to predict the number of Romanian and Bulgarian migrants to the UK rather well.

This is because it is impossible for the government—or anyone else—to develop an effective method to predict accurately the number of migrants who will come to the UK from Romania and Bulgaria when workers from these countries gain full access to the EU labour market in 2014.

It would be valuable to have this information, but generating it is an impossible task. There are organisations and individuals out there who have undertaken various calculations looking at different variables – the wage differentials between the UK and A2 countries (as Romania and Bulgaria are known); the relative sizes of the populations of Poland and Romania; and a host of other considerations.

But while this does help us to consider a range of scenarios, it is little different to looking at the form of various racehorses and saying which one will win. Someone’s bound to be right, but one can’t know who until after the race, which is one of the reasons why betting on horse racing is also seen as a mug’s game.

So any predictions about the levels of A2 migration—whether based on surveys undertaken in Romania and Bulgaria, assessments of various economic factors or any other method—will be, at best, informed guesses and therefore not reliable enough to develop policy responses.

Much of the evidence that underpins the UK’s migration debate more generally is flawed in one way or another—as today’s meeting of the Public Administration Select Committee will hear. Understanding the limits and problems associated with different data sources is extremely important for policy makers.

Recently, for example, the Office for National Statistics introduced a measurement of the margin of error to its Long Term International Migration (LTIM) net migration estimates. This error measure shows that the government could hit its “tens of thousands” net migration target but appear to have missed it by more than 30,000—or miss the target but still appear to have hit it. Essentially, the key data source—a survey—is not very well suited to providing clear data for specific numerical targets.

The 2011 census highlighted that the LTIM data had also been underestimated for a decade and that net migration between 2001 and 2011 was actually around half a million higher than had been anticipated. While this highlights the challenge of using a ten-year census supported with a survey as the key data source, there are problems with any means of trying to understand the make-up of the population. One frequently proposed alternative—a population register—would provide much better data but would also be costly and face substantial opposition.

E-Borders, the programme being implemented to track all entries and exits across Britain’s borders, has the potential to improve some elements of migration data collection too, but it can only tell us so much. The impacts of immigration are felt at a local level, while E-Borders provides information from points of entry and exit.

Which brings us back to A2 migration: quite aside from the impossibility of knowing how many migrants will come to Britain from Romania and Bulgaria, most impacts of a change in the population are likely to be regionally and neighbourhood specific—and there is no way of knowing where migrants will choose to live.

So rather than making preparations for 2014 based on guesses, government departments, local authorities and other relevant bodies may do better to develop a plan which allows them to respond rapidly to a range of potential demands and pressures.