Forecasting with approximate dynamic factor models: The role of non-pervasive shocks |
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Authors: | Matteo Luciani |
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Institution: | F.R.S.-FNRS, 5 Rue d’Egmont, 1000, Brussels, Belgium; European Center for Advanced Research in Economics and Statistics (ECARES), Solvay Business School of Economics and Management, Université libre de Bruxelles, 50 av. F.D. Roosevelt, CP 114, B1050 Brussels, Belgium |
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Abstract: | This paper studies the role of non-pervasive shocks when forecasting with factor models. To this end, we first introduce a new model that incorporates the effects of non-pervasive shocks, an Approximate Dynamic Factor Model with a sparse model for the idiosyncratic component. Then, we test the forecasting performance of this model both in simulations, and on a large panel of US quarterly data. We find that, when the goal is to forecast a disaggregated variable, which is usually affected by regional or sectorial shocks, it is useful to capture the dynamics generated by non-pervasive shocks; however, when the goal is to forecast an aggregate variable, which responds primarily to macroeconomic, i.e. pervasive, shocks, accounting for non-pervasive shocks is not useful. |
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Keywords: | Dynamic factor models Penalized regressions Local factors Bayesian shrinkage Forecasting |
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