Forecasting with Approximate Dynamic Factor Models: the Role of Non-Pervasive Shocks

Matteo Luciani

Working Papers ECARES from ULB -- Universite Libre de Bruxelles

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.

Keywords: Penalized regressions; Local factors; Bayesian shrinkage; Forecasting (search for similar items in EconPapers)
JEL-codes: C13 C32 C33 C52 C53 (search for similar items in EconPapers)
Pages: 10 p.
Date: 2011-07
New Economics Papers: this item is included in nep-cba, nep-ets and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Published by: Elsevier, International Journal of Forecasting

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Journal Article: Forecasting with approximate dynamic factor models: The role of non-pervasive shocks (2014)
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