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Efficient Estimation of Factor Models

  • In Choi

    ()

    (Department of Economics, Sogang University, Seoul)

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This paper considers the factor model Xt = Ft + et. Assuming a nor- mal distribution for the idiosyncratic error et conditional on the factors fFtg, conditional maximum likelihood estimators of the factor and factor- loading spaces are derived. These estimators are called generalized prin- cipal component estimators (GPCEs) without the normality assumption. This paper derives the asymptotic distributions of the GPCEs of the fac- tor and factor-loading space. It is shown that variances of the GPCEs of the common components are smaller than those of the principal com- ponent estimators studied in Bai (2003). The approximate variance of the forecasting error using the GPCE-based factor estimates is derived and shown to be smaller than that based on the principal component es- timators. The feasible GPCE (FGPCE) of factor space is shown to be asymptotically equivalent to the GPCE. The GPCEs and FGPCEs are shown to be more efficient than the principal component estimators in finite samples.

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File URL: ftp://163.239.165.41/RePEc/sgo/wpaper/CI_RIME_2007-01.pdf
File Function: Second version, 2010
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Paper provided by Research Institute for Market Economy, Sogang University in its series Working Papers with number 0701.

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Length: 43 pages
Date of creation: Mar 2007
Date of revision: Dec 2010
Handle: RePEc:sgo:wpaper:0701
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  1. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  2. Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
  3. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
  4. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  5. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  6. Jones, Christopher S., 2001. "Extracting factors from heteroskedastic asset returns," Journal of Financial Economics, Elsevier, vol. 62(2), pages 293-325, November.
  7. Hyungsik Roger MOON & Benoit PERRON, 2002. "Testing For A Unit Root In Panels With Dynamic Factors," Cahiers de recherche 18-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  8. Sydney Ludvigson & Serena Ng, 2006. "The Empirical Risk-Return Relation: a factor analysis approach," 2006 Meeting Papers 236, Society for Economic Dynamics.
  9. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  10. 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.
  11. Massimiliano Marcellino & Carlo A. Favero & Francesca Neglia, 2005. "Principal components at work: the empirical analysis of monetary policy with large data sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 603-620.
  12. Peter C. B. Phillips & Donggyu Sul, 2003. "Dynamic panel estimation and homogeneity testing under cross section dependence *," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 217-259, 06.
  13. 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.
  14. Jushan Bai & Serena Ng, 2001. "A Panic Attack on Unit Roots and Cointegration," Economics Working Paper Archive 469, The Johns Hopkins University,Department of Economics.
  15. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
  16. Bai, Jushan & Ng, Serena, 2010. "Instrumental Variable Estimation In A Data Rich Environment," Econometric Theory, Cambridge University Press, vol. 26(06), pages 1577-1606, December.
  17. Kapetanios, George & Marcellino, Massimiliano, 2006. "A Parametric Estimation Method for Dynamic Factor Models of Large Dimensions," CEPR Discussion Papers 5620, C.E.P.R. Discussion Papers.
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