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

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  • Matteo Luciani

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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Bibliographic Info

Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2013/97308.

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Length: 10 p.
Date of creation: Jan 2014
Date of revision:
Publication status: Published by: Elsevier, International Journal of Forecasting
Handle: RePEc:eca:wpaper:2013/97308

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Keywords: Penalized regressions; Local factors; Bayesian shrinkage; Forecasting;

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  1. Jan J.J. Groen & George Kapetanios, 2008. "Revisiting Useful Approaches to Data-Rich Macroeconomic Forecasting," Working Papers, Queen Mary, University of London, School of Economics and Finance 624, Queen Mary, University of London, School of Economics and Finance.
  2. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series, European Central Bank 0966, European Central Bank.
  3. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, Elsevier, vol. 146(2), pages 304-317, October.
  4. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, Econometric Society, vol. 71(1), pages 135-171, January.
  5. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
  6. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "Do Financial Variables Help Forecasting Inflation and Real Activity in the Euro Area?," CEPR Discussion Papers 3146, C.E.P.R. Discussion Papers.
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Cited by:
  1. A. Girardi & R. Golinelli & C. Pappalardo, 2014. "The Role of Indicator Selection in Nowcasting Euro Area GDP in Pseudo Real Time," Working Papers wp919, Dipartimento Scienze Economiche, Universita' di Bologna.

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