Martingale approximation of eigenvalues for common factor representation
In this paper a martingale approximation is used to derive an asymptotic distribution of simple positive eigenvalues of the sample covariance matrix for a stationary process. The derived distribution can be used to study stability of the common factor representation based on the principal component analysis of the covariance matrix.
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Volume (Year): 83 (2013)
Issue (Month): 1 ()
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References listed on IDEAS
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- Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2008.
"Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change,"
CEPR Discussion Papers
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- Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Working Papers 334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Economics Working Papers ECO2008/17, European University Institute.
- Magnus, J.R., 1985. "On differentiating eigenvalues and eigenvectors," Other publications TiSEM f410e3a5-ba9b-4787-b8cc-4, Tilburg University, School of Economics and Management.
- Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
- Magnus, Jan R., 1985. "On Differentiating Eigenvalues and Eigenvectors," Econometric Theory, Cambridge University Press, vol. 1(02), pages 179-191, August.
- Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, 09.
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