BrexitCentral: Even the new Civil Service approach seems to show the benefit of Free Trade outside the EU Customs Union

The Civil Service reportedly has redone the Treasury’s Brexit long-term forecasts with a new approach, so say numerous leaks via Buzzfeed and elsewhere. ‘Officials believe the methodology for the new assessment is better than that used for similar analyses before the referendum,’ reports Buzzfeed. This new approach has, it seems, dumped the old Treasury calculations and methodology published in the original Treasury Project Fear report during the referendum. Plainly, the criticisms of this old approach – persistently so from us at Economists for Free Trade – have hit home; if so, that is real progress.

Under its old approach, the Treasury used something they called the ‘gravity approach’. This approach consisted of four steps:

  1. A set of trade correlations amongst a variety of countries between trade and GDP that noted their membership of different trade blocs. To get the trade effects of Brexit, they put into these correlations estimates of the estimated EU-membership and WTO-option effects, which are assumed to correspond to the different policy possibilities.
  2. These effects on trade were then fed into a set of correlations between trade and Foreign Direct Investment (FDI), from data on many countries and time periods. This produced the FDI effects.
  3. These FDI effects were then fed into a set of correlations between FDI and productivity, from data on many UK industries over many time periods. This produced the productivity effects.
  4. These productivity effects were then fed into a standard macro model of the UK economy; a popular one is the National Institute Global Econometric Model (NIGEM), operated by the National Institute of Economic and Social Research (NIESR). These productivity effects feed into GDP ‘potential’ and trigger the final macroeconomic forecasts that are publicised.

As the Treasury or Civil Service seems now to have conceded, this procedure makes no sense because all these relationships are ‘correlations’ – correlations do not reveal causation. We have a correlation between unemployment and crime; but it would be dangerous to use it to predict unemployment from data on crime. This is because both these data series are impacted by a complex causal system involving a lot of other factors.

To read Patrick’s piece for BrexitCentral in full, click here.

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