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Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?

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  • De Mol, Christine
  • Giannone, Domenico
  • Reichlin, Lucrezia

Abstract

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range of prior choices. Moreover, we study the asymptotic properties of the Bayesian regression under Gaussian prior under the assumption that data are quasi collinear to establish a criterion for setting parameters in a large cross-section. --

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Bibliographic Info

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2006,32.

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Date of creation: 2006
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Handle: RePEc:zbw:bubdp1:5040

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Keywords: Bayesian VAR; ridge regression; Lasso regression; principal components; large cross-sections;

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  1. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics, Boston College Department of Economics 572, Boston College Department of Economics.
  2. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
  3. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers, C.E.P.R. Discussion Papers 2509, C.E.P.R. Discussion Papers.
  4. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2007. "Opening the black box: structural factor models with large cross-sections," Working Paper Series, European Central Bank 0712, European Central Bank.
  5. Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series, European Central Bank 0633, European Central Bank.
  6. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
  7. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," CEPR Discussion Papers, C.E.P.R. Discussion Papers 3432, C.E.P.R. Discussion Papers.
  8. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report, Federal Reserve Bank of Minneapolis 93, Federal Reserve Bank of Minneapolis.
  9. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers, C.E.P.R. Discussion Papers 2338, C.E.P.R. Discussion Papers.
  10. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, Econometric Society, vol. 74(4), pages 1133-1150, 07.
  11. Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, Elsevier, vol. 146(2), pages 304-317, October.
  12. D''Agostino, Antonello & Giannone, Domenico & Surico, Paolo, 2007. "(Un)Predictability and Macroeconomic Stability," CEPR Discussion Papers, C.E.P.R. Discussion Papers 6594, C.E.P.R. Discussion Papers.
  13. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 4(1), pages 25-38, January.
  14. Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
  15. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, Econometric Society, vol. 71(1), pages 135-171, January.
  16. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(2), pages 147-62, April.
  17. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
  18. Jonathan H. Wright, 2009. "Forecasting US inflation by Bayesian model averaging," Journal of Forecasting, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 28(2), pages 131-144.
  19. D’Agostino, Antonello & Giannone, Domenico, 2006. "Comparing alternative predictors based on large-panel factor models," Working Paper Series, European Central Bank 0680, European Central Bank.
  20. Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics, EconWPA 9804001, EconWPA, revised 31 Jul 1999.
  21. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2004. "The generalised dynamic factor model: consistency and rates," ULB Institutional Repository 2013/10133, ULB -- Universite Libre de Bruxelles.
  22. Gary Koop & Simon Potter, 2003. "Forecasting in large macroeconomic panels using Bayesian Model Averaging," Staff Reports, Federal Reserve Bank of New York 163, Federal Reserve Bank of New York.
  23. 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.
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