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The Identification and Estimation of a Large Factor Model with Structural Instability

Badi Baltagi (), Chihwa Kao () and Fa Wang
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Fa Wang: School of Economics, Shanghai University of Finance and Economics

No 194, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: This paper tackles the identification 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 misspecification of the number of pseudo factors. 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 assumptions. The finite sample performance of our estimators is investigated using Monte Carlo experiments.

Keywords: High Dimensional Factor Model; Structural Change; Rate of Convergence; Number of Factors; Model Selection; Factor Space; Panel Data (search for similar items in EconPapers)
JEL-codes: C13 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ore
Date: 2016-11
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Related works:
Journal Article: Identification and estimation of a large factor model with structural instability (2017) Downloads
Working Paper: Identification and Estimation of a Large Factor Model with Structural Instability (2016) Downloads
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