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Comparing alternative predictors based on large-panel factor models

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  • D’Agostino, Antonello
  • Giannone, Domenico

Abstract

This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a "large" panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar exercises in the literature. As in Stock and Watson (2002), we find that effciency improvements due to the weighting of the idiosyncratic components do not lead to significant more accurate forecasts. In contrast to Boivin and Ng (2005), we show that the dynamic restrictions imposed by the procedure of Forni, Hallin, Lippi, and Reichlin (2005) are not harmful for predictability. Our main conclusion is that for the dataset at hand the two methods have a similar performance and produce highly collinear forecasts. JEL Classification: C31, C52, C53

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0680.

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Date of creation: Oct 2006
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Handle: RePEc:ecb:ecbwps:20060680

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Keywords: Factor models; forecasting; Large Cross-Section;

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  1. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
  2. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
  3. Antonello D'Agostino & Domenico Giannone & Paolo Surico, 2005. "(Un)Predictability and Macroeconomic Stability," Macroeconomics 0510024, EconWPA.
  4. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2007. "Opening the black box: structural factor models with large cross-sections," Working Paper Series 0712, European Central Bank.
  5. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-304, September.
  6. 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.
  7. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
  8. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre.
  9. Mario Forni & Lucrezia Reichlin, 1998. "Let's get real: a factor analytical approach to disaggregated business cycle dynamics," ULB Institutional Repository 2013/10147, ULB -- Universite Libre de Bruxelles.
  10. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
  11. 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, vol. 97, pages 1167-1179, December.
  12. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
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