European Commission's Forecasts Accuracy Revisited: Statistical Properties and Possible Causes of Forecast Errors

This paper updates a previous assessment of the European Commission's track record for forecasting key economic variables (González Cabanillas and Terzi 2012) by extending the observation period to 2014. It also examines the accuracy of the Commission's forecasts over a shorter and more recent period (2000-2014) so that a comparison can be made between the performance of forecasts made before and after the Great Recession of 2008-2009. Going beyond the 2012 approach, this paper also examines the extent to which forecast errors can be explained by external or technical assumptions that prove incorrect ex post. It also updates the comparison of the Commission’s performance vis à vis the OECD, the IMF, a consensus forecast of market economists, and the ECB. Inclusion of the 2012-2014 period lowers the forecasting error for some key variables or leads to no change in others. Focussing on the years since the turn of the century, current-year and year-ahead forecasting errors for the three main variables examined (GDP growth, inflation and general government balances) have been larger in the crisis and post-crisis period (2008-2014) than in the precrisis period (2000-2007) for a large majority of Member States. This appears mainly to be the result of an anomalously large error in 2009, a year which confounded many forecasters. The country-bycountry analysis confirms the finding of earlier studies which show that the Commission's forecasts are largely unbiased. The newly-introduced panel data approach also confirms the absence of bias in current-year GDP forecasts across EU Member States but shows that year-ahead forecasts for GDP growth tend to be slightly over optimistic across the whole sample. The analysis also shows that autocorrelation of forecast errors is not a major issue in the Commission's forecasts. Other advanced tests shed more light on the performance of the Commission’s forecasts, demonstrating that they are directionally accurate and generally beat a naïve forecast but that they are not always efficient in terms of their use of all available data. The decomposition of forecast errors shows that unexpected changes in external assumptions seem to have only a limited impact on current-year GDP growth forecasts. However, more than half of the variance in year-ahead forecast errors appears to come from external assumptions that prove to be incorrect ex post. Finally, the Commission’s economic forecasts come out as being more accurate than those of the market and comparable to those of the other international institutions considered.