Article ID: | iaor201256 |
Volume: | 31 |
Issue: | 1 |
Start Page Number: | 15 |
End Page Number: | 46 |
Publication Date: | Jan 2012 |
Journal: | Journal of Forecasting |
Authors: | Espinoza Raphael, Fornari Fabio, Lombardi Marco J |
Keywords: | time series: forecasting methods, statistics: regression, economics |
Previous research found that the US business cycle leads the European one by a few quarters, and can therefore be useful in predicting euro area gross domestic product (GDP). In this paper we investigate whether additional predictive power can be gained by adding selected financial variables belonging to either the USA or the euro area. We use vector autoregressions (VARs) that include the US and euro area GDPs as well as growth in the Rest of the World and selected combinations of financial variables. Out-of-sample root mean square forecast errors (RMSEs) evidence that adding financial variables produces a slightly smaller error in forecasting US economic activity. This weak macro-financial linkage is even weaker in the euro area, where financial indicators do not improve short- and medium-term GDP forecasts even when their timely availability relative to GDP is exploited. It can be conjectured that neither US nor European financial variables help predict euro area GDP as the US GDP has already embodied this information. However, we show that the finding that financial variables have no predictive power for future activity in the euro area relates to the unconditional nature of the RMSE metric. When forecasting ability is assessed as if in real time (i.e. conditionally on the information available at the time when forecasts are made), we find that models using financial variables would have been preferred in several episodes and in particular between 1999 and 2002.