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  • Christophe Boucher
  • Bertrand Maillet

Abstract

The forecasting literature has identified three important and broad issues: the predictive content is unstable over time, in-sample and out-of-sample discordant results and the problematic statistical inference with highly persistent predictors. In this paper, we simultaneously address these three issues, proposing to directly treat the persistence of forecasting variables before use. We thus cut-out the low frequency components and show, in simulations and on financial data, that this pre-treatment improves the predictive power of the studied economic variables. Classification JEL : C14, C53, G17.

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Article provided by Presses de Sciences-Po in its journal Revue économique.

Volume (Year): 63 (2012)
Issue (Month): 3 ()
Pages: 581-590

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Handle: RePEc:cai:recosp:reco_633_0581

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  2. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1131-1147, October.
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  8. Christophe Boucher & Bertrand Maillet, 2011. "Une analyse temps-fréquences des cycles financiers," Documents de travail du Centre d'Economie de la Sorbonne 11003, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  9. Pesaran, M. Hashem & Timmermann, Allan, 2007. "Selection of estimation window in the presence of breaks," Journal of Econometrics, Elsevier, vol. 137(1), pages 134-161, March.
  10. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  11. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
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