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Variable Selection, Estimation and Inference for Multi-period Forecasting Problems

  • M. Hashem Pesaran
  • Andreas Pick
  • Allan Timmermann

This paper conducts a broad-based comparison of iterated and direct multi-period forecasting approaches applied to both univariate and multivariate models in the form of parsimonious factor-augmented vector autoregressions. To account for serial correlation in the residuals of the multi-period direct forecasting models we propose a new SUREbased estimation method and modified Akaike information criteria for model selection. Empirical analysis of the 170 variables studied by Marcellino, Stock and Watson (2006) shows that information in factors helps improve forecasting performance for most types of economic variables although it can also lead to larger biases. It also shows that finitesample modifications to the Akaike information criterion can modestly improve the performance of the direct multi-period forecasts.

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File URL: http://www.dnb.nl/binaries/Working%20paper%20250_tcm46-235991.pdf
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Paper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 250.

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Date of creation: Jun 2010
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Handle: RePEc:dnb:dnbwpp:250
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Web page: http://www.dnb.nl/en/

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  1. Schorfheide, Frank, 2005. "VAR forecasting under misspecification," Journal of Econometrics, Elsevier, vol. 128(1), pages 99-136, September.
  2. Athanasopoulos, George & Vahid, Farshid, 2008. "VARMA versus VAR for Macroeconomic Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 237-252, April.
  3. Jushan Bai & Serena Ng, 2009. "Boosting diffusion indices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 607-629.
  4. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
  5. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," CEPR Discussion Papers 3432, C.E.P.R. Discussion Papers.
  6. Guillaume Chevillon, 2007. "Direct Multi-Step Estimation And Forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 746-785, 09.
  7. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  8. Pesaran, M Hashem & Timmermann, Allan G, 2004. "Small Sample Properties of Forecasts From Autoregressive Models Under Structural Breaks," CEPR Discussion Papers 4401, C.E.P.R. Discussion Papers.
  9. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  10. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
  11. Carlo A. Favero & Andrea Tamoni, 2010. "Demographics and the Econometrics of the Term Structure of Stock Market Risk," Working Papers 367, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  12. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
  13. Ullah, Aman, 2004. "Finite Sample Econometrics," OUP Catalogue, Oxford University Press, edition 1, number 9780198774488, March.
  14. Ing, Ching-Kang, 2003. "Multistep Prediction In Autoregressive Processes," Econometric Theory, Cambridge University Press, vol. 19(02), pages 254-279, April.
  15. repec:cup:cbooks:9780521634809 is not listed on IDEAS
  16. Bao, Yong, 2007. "Finite-Sample Properties Of Forecasts From The Stationary First-Order Autoregressive Model Under A General Error Distribution," Econometric Theory, Cambridge University Press, vol. 23(04), pages 767-773, August.
  17. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
  18. repec:cup:cbooks:9780521632423 is not listed on IDEAS
  19. Brown, Bryan W & Mariano, Roberto S, 1989. "Measures of Deterministic Prediction Bias in Nonlinear Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(3), pages 667-84, August.
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