Description/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.
Document Type
Working Paper
Date
Fall 11-2016
Keywords
High Dimensional Factor Model, Structural Change, Rate of Convergence, Number of Factors, Model Selection, Factor Space, Panel Data
Language
English
Series
Working Papers Series
Disciplines
Econometrics | Economics | Macroeconomics
ISSN
1525-3066
Recommended Citation
Baltagi, Badi H.; Kao, Chihwa; and Wang, Fa, "The Identification and Estimation of a Large Factor Model with Structural Instability" (2016). Center for Policy Research. 226.
https://surface.syr.edu/cpr/226
Accessible PDF version
Source
Local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional Information
Working paper no. 194
The authors would like to thank the editor Jianqing Fan, the associate editor and three referees for their valuable comments and suggestions. We would also like to thank Jushan Bai, Xu Cheng, Yoonseok Lee, Lorenzo Trapani, Giovanni Urga and participants of the 2015 NY Camp Econometrics, 2015 International Panel Data Conference and the 2015 World Congress of the Econometric Society for helpful comments and suggestions.