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A Bayesian Generalized Factor Model with Comparative Analysis (Genellestirilmis Faktor Modellerinin Bayesyen Yaklasimi ve Karsilastirmali Analizi)

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  • Necati Tekatli

Abstract

This paper has two major objectives. First, we develop and implement a Bayesian generalized factor model that allows for non-orthogonality of the idiosyncratic factors and the flexibility of cross-sectional and time series dimensions. Second, we evaluate the significance of the orthogonality assumption in factor models, a controversial assumption discussed in the recent literature. To this end, we propose a simple methodology to choose the generalized factor model that best determines the idiosyncratic correlations and provide a comparative analysis between the classical and generalized factor models. The proposed methodology is applied to both the simulated data and the foreign exchange rate data.

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Bibliographic Info

Paper provided by Research and Monetary Policy Department, Central Bank of the Republic of Turkey in its series Working Papers with number 1018.

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Date of creation: 2010
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Handle: RePEc:tcb:wpaper:1018

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Keywords: Factor model; Bayesian time series; MCMC simulation; Model selection.;

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  1. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, Elsevier, vol. 132(1), pages 169-194, May.
  2. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 17(06), pages 1113-1141, December.
  3. James H. Stock & Mark W. Watson, 1998. "Diffusion Indexes," NBER Working Papers 6702, National Bureau of Economic Research, Inc.
  4. John Geweke, 2004. "Getting It Right: Joint Distribution Tests of Posterior Simulators," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 99, pages 799-804, January.
  5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, Econometric Society, vol. 70(1), pages 191-221, January.
  6. Poirier, Dale J., 1998. "Revising Beliefs In Nonidentified Models," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 14(04), pages 483-509, August.
  7. James H. Stock & Mark W. Watson, 1990. "Business Cycle Properties of Selected U.S. Economic Time Series, 1959-1988," NBER Working Papers 3376, National Bureau of Economic Research, Inc.
  8. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, American Economic Association, vol. 93(4), pages 1216-1239, September.
  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. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2004. "The generalised dynamic factor model: consistency and rates," ULB Institutional Repository, ULB -- Universite Libre de Bruxelles 2013/10133, ULB -- Universite Libre de Bruxelles.
  11. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, Econometric Society, vol. 71(1), pages 135-171, January.
  12. Geweke, John & Zhou, Guofu, 1996. "Measuring the Pricing Error of the Arbitrage Pricing Theory," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 9(2), pages 557-87.
  13. 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.
  14. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers, Federal Reserve Bank of Minneapolis 55, Federal Reserve Bank of Minneapolis.
  15. Aguilar, Omar & West, Mike, 2000. "Bayesian Dynamic Factor Models and Portfolio Allocation," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 18(3), pages 338-57, July.
  16. Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, Elsevier, vol. 13(3), pages 341-360, December.
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