Prediction and the politics of uncertainty

Immigration will be one of the main topics of debate during the forthcoming general election in the UK.

One of the origins of recent mass immigration into the UK was the accession of the mostly ex-Communist countries into the EU in 2004.

The Guardian has published an account of the politics and policy making around immigration and in particular in advance of the eastwards expansion of the EU.

A report was commissioned by the Home Office in 2003 to predict the likely impact on immigration of opening up the UK’s borders to the accession countries. They came up with a number of between 5,000 – 13,000 net immigrants per year from the new countries. So between 50,000 – 130,000 over 10 years. ONS estimated the actual number between 2004 and 2012 as being 423,000.

This illustrates two problems.

Firstly the difficulty of predicting the behaviour of social systems, especially when there is little precedent.

Secondly, and perhaps more significantly, it shows the weakness in the way the prediction was interpreted by policy makers and reported by the media.

It seems it was seen at the time as a prediction of the form “this is what will happen”. Now it is generally reported as an incompetent piece of analysis and that clearly anyone could see that the number was going to be much higher.

However what is interesting is that the original report does not make such a definitive prediction. The prediction was effectively of the form “This is what will happen IF [list assumptions here]”.

The critical assumption in this report was that all EU countries would open up their borders. In the end only three did – all the others put in place transitional controls.

The reality is that many other assumptions went into the analysis that generated the prediction – in particular the relative states of different economies and their job markets.

Perhaps a better predictive model could have been developed which could have more effectively captured the many factors driving immigration. The question is whether that is irrelevant and that the fault was not actually in the original prediction but more in the way it was presented, interpreted and then used to inform and evaluate policy.

A straightforward, precise prediction is more attractive because it provides the illusion of certainty. It allows you to develop a strategy around that certainty. However that strategy might collapse if the prediction turns out to be wrong.

We are going to hear a lot of predictions from politicians over the next few weeks and there is value in communications terms for those predictions to be clear and definitive – “you will (not might) be better off with our policy on immigration (or whatever)”.
This is comforting but not realistic where many of the key variables are not under their control. It is unlikely that any of our politicians will start couching their policies in terms of “what it might deliver if Greece does / does not leave the Eurozone”.

This is understandable but a shame as good strategies or policies are robust in different scenarios. Exploring those scenarios is central to understanding which on balance would be most effective in an uncertain future.

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