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Identification and Estimation of a Large Factor Model with Structural Instability

Listed author(s):
  • Badi H. Baltagi

    (Syracuse University)

  • Chihwa Kao

    (University of Connecticut)

  • Fa Wang

    (Shanghai University of Finance and Economics)

This paper tackles the identi cation and estimation of a high dimensional factor model with unknown number of latent factors and a single break in the number of factors and/or factor loadings occurring at unknown common date. First, we propose a least squares estimator of the change point based on the second moments of estimated pseudo factors and show that the estimation error of the proposed estimator is Op(1). We also show that the proposed estimator has some degree of robustness to misspeci cation of the number of pseudo fac-tors. With the estimated change point plugged in, consistency of the estimated number of pre and post-break factors and convergence rate of the estimated pre and post-break factor space are then established under fairly general assump-tions. The nite sample performance of our estimators is investigated using Monte Carlo experiments. JEL Classification: C13; C33 Key words: high dimensional factor model, structural change, rate of con-vergence, number of factors, model selection, factor space, panel data

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File URL: http://web2.uconn.edu/economics/working/2016-34.pdf
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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2016-34.

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Length: 75 pages
Date of creation: Oct 2016
Handle: RePEc:uct:uconnp:2016-34
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University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063

Phone: (860) 486-4889
Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/

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