09 May 2023

CER's Springford: Are the costs of Brexit big or small?

Critics say my estimate – that the British economy is around 5 per cent smaller due to Brexit – is implausibly large. This insight tests their scepticism against other ways to estimate the cost of Brexit.

In a debate I participated in last month, panellists were asked to say how much Brexit had curbed Britain’s economic output. Graham Gudgin of Policy Exchange and Cambridge University’s Centre for Business Research said he thought the costs had been negligible. Julian Jessop of the Institute of Economic Affairs said GDP was around 1 per cent smaller than it would have been, adding that the short-term impact was always going be negative, before the benefits of bespoke regulation and reduced trade barriers with the rest of the world kicked in. Jonathan Portes of UK in a Changing Europe and King’s College London said the costs amounted to around 2.5 per cent of lost GDP.

All their estimates were lower than mine – my model finds that Brexit had reduced the size of the economy by 5.5 per cent in the second quarter of 2022, and all three panellists expressed doubts about my estimate. Graham rejected it outright, saying I should withdraw it, while Jonathan agreed that the ‘synthetic control method’ (also known as the doppelgänger method) is the one most economists would use, but he thought 5 per cent was on the higher end of plausibility. This piece sets out some checks that I have done in response to their scepticism, and why I continue to think the costs of Brexit are larger than they do.

Why does this matter? After all, both Labour and the Conservatives have said that Britain will not rejoin the single market and customs union, let alone the EU. However, identifying the scale of the impact of Brexit is important, because if the costs are small, there is less urgency to make big changes to Britain’s economic model. The Covid pandemic is under control, energy prices are falling, and once inflation has been tamed living standards will start to improve. If, however, the impact of Brexit is large – as my model estimates – then major reforms will be needed to offset the productivity that has been lost.

As a reminder, my model uses an algorithm to identify a ‘doppelgänger’ UK that never left the EU. From a group of 22 advanced economies, the algorithm selects those whose economic performance was most similar to Britain’s between 2009 and 2016 and puts them together to form the doppelgänger. The countries that the algorithm selects to form this synthesised British economy are the US (30 per cent), Germany (15 per cent), New Zealand (14 per cent), Norway (8 per cent), Australia (5 per cent) with other countries making up smaller shares. We can then use the gap between the doppelgänger and the UK, to estimate the size of the loss to GDP after the referendum. That gap was around 5 per cent by December 2021, before the worst of the energy crisis struck (energy prices started to rise precipitously from July 2022) and before Liz Truss and Kwasi Kwarteng’s ill-fated September budget.

It is healthy for my model to be criticised: we can only estimate how much Brexit has hurt the economy by trying to find the best counterfactual we can. The synthetic control method I (and others) have used is well established in the social science literature as a way to estimate counterfactuals. And, as we will see below, it is the worst way to assess Brexit, apart from all the others. Let us consider the alternatives first.

Model check 1: Extrapolating from Britain’s past

The only way we can estimate ‘what would have been’ is to use some sort of counterfactual. One possible method is to use observations from the past. Economic output tends to grow on average at a certain rate per year, unless that rate is interrupted by a prolonged recession. We can use this average rate – ‘trend growth’ – to see how whether the UK deviated from trend after the referendum in 2016.

Estimating Brexit costs this way is cruder than the doppelgänger method, because the result is very sensitive to the period used to establish trend growth. Chart 1 adopts the method that Josh Martin and Jonathan Haskel of the Bank of England use to estimate the loss of investment, but substitutes GDP for investment. They take the trend from 1999 to 2016, and then add that quarterly trend growth to each quarter after the Covid nadir in the second quarter of 2020...

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