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Are disaggregate data useful for factor analysis in forecasting French GDP?

  • Karim Barhoumi

    (Banque de France, DGEI-DCPM, Paris, France)

  • Olivier Darné
  • Laurent Ferrara

    (Banque de France, DGEI-DCPM, Paris, France)

This paper compares the GDP forecasting performance of alternative factor models based on monthly time series for the French economy. These models are based on static and dynamic principal components obtained using time and frequency domain methods. We question whether it is more appropriate to use aggregate or disaggregate data to extract the factors used in forecasting equations. The forecasting accuracy is evaluated for various forecast horizons considering both rolling and recursive schemes. We empirically show that static factors, estimated from a small database, lead to competitive results, especially for nowcasting. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1162
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 29 (2010)
Issue (Month): 1-2 ()
Pages: 132-144

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Handle: RePEc:jof:jforec:v:29:y:2010:i:1-2:p:132-144
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  2. Marc Hallin & Mario Forni & Marco Lippi & Lucrezia Reichlin, 2003. "Do financial variables help forecasting inflation and real activity in the Euro area ?," ULB Institutional Repository 2013/2123, ULB -- Universite Libre de Bruxelles.
  3. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Working papers 215, Banque de France.
  4. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May.
  5. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
  6. Reichlin, Lucrezia, 2002. "Factor Models in Large Cross-Sections of Time Series," CEPR Discussion Papers 3285, C.E.P.R. Discussion Papers.
  7. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  8. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  9. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  10. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
  11. George Kapetanios & Gonzalo Camba-Mendez, 2005. "Forecasting euro area inflation using dynamic factor measures of underlying inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(7), pages 491-503.
  12. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  13. 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.
  14. 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.
  15. Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2003. "Leading Indicators for Euro Area Inflation and GDP Growth," CEPR Discussion Papers 3893, C.E.P.R. Discussion Papers.
  16. 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.
  17. Ard H.J. den Reijer, 2005. "Forecasting Dutch GDP using Large Scale Factor Models," DNB Working Papers 028, Netherlands Central Bank, Research Department.
  18. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
  19. Connor, Gregory & Korajczyk, Robert A, 1993. " A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-91, September.
  20. Catherine Doz & Lucrezia Reichlin, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Post-Print peer-00844811, HAL.
  21. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  22. 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.
  23. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
  24. D’Agostino, Antonello & Giannone, Domenico, 2006. "Comparing alternative predictors based on large-panel factor models," Working Paper Series 0680, European Central Bank.
  25. Sandra Eickmeier & Christina Ziegler, 2008. "How successful are dynamic factor models at forecasting output and inflation? A meta-analytic approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 237-265.
  26. Francisco Dias & Maximiano Pinheiro & António Rua, 2010. "Forecasting using targeted diffusion indexes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 341-352.
  27. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
  28. Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, Elsevier.
  29. Danny Quah & Thomas J. Sargent, 1993. "A Dynamic Index Model for Large Cross Sections," NBER Chapters, in: Business Cycles, Indicators and Forecasting, pages 285-310 National Bureau of Economic Research, Inc.
  30. Kapetanios, George, 2004. "A note on modelling core inflation for the UK using a new dynamic factor estimation method and a large disaggregated price index dataset," Economics Letters, Elsevier, vol. 85(1), pages 63-69, October.
  31. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
  32. Breitung, Jörg & Eickmeier, Sandra, 2005. "Dynamic factor models," Discussion Paper Series 1: Economic Studies 2005,38, Deutsche Bundesbank, Research Centre.
  33. Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
  34. repec:dgr:uvatin:2008007 is not listed on IDEAS
  35. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  36. 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.
  37. Calista Cheung & Frédérick Demers, 2007. "Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation," Working Papers 07-8, Bank of Canada.
  38. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
  39. repec:dgr:uvatin:20080007 is not listed on IDEAS
  40. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
  41. 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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