Forecasting economic activity by Bayesian bridge model averaging |
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Authors: | Lorenzo Bencivelli Massimiliano Marcellino Gianluca Moretti |
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Affiliation: | 1.Bank of Italy,Rome,Italy;2.Bocconi University, IGIER and CEPR,Milan,Italy;3.Bank of America Merril Lynch,London,UK |
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Abstract: | This paper proposes the use of Bayesian model averaging (BMA) as an alternative tool to forecast GDP relative to simple bridge models and factor models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA in now-casting by means of a recursive experiment for the euro area and the three largest countries. This method allows flexibility in selecting the information set month by month. We find that BMA-based forecasts produce smaller forecast errors than standard bridge model when forecasting GDP in Germany, France and Italy. At the same time, it also performs as well as medium-scale factor models when forecasting Eurozone GDP. |
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