Model pooling and changes in the informational content of predictors: An empirical investigation for the euro area

I study the performance of single predictor bridge equation models as well as a wide range of model selection and pooling techniques, including Mallows model averaging and Cross-Validation model averaging, for short-term forecasting euro area GDP growth. I explore to what extend model selection and model pooling techniques are able to outperform a simple autoregressive benchmark model in the periods before, during and after the Great Recession. I find that single predictor bridge equation models suffer a great variation in the forecast performance relative to the benchmark model over the analysed sub-samples. Moreover, model selection techniques turn out to produce quite poor forecasts in some sub-samples. On the contrary, model pooling based on the Cross-Validation and the Mallows criterion provide a very stable and accurate forecast performance.