Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38399
Title: Identification and estimation of a large factor model with structural instability
Authors: Baltagi, Badi H.
Kao, C.
Wang, F.
First Published: 12-Nov-2016
Publisher: Elsevier
Citation: Journal of Econometrics, 2017, 197(1), pp. 87–100
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.
DOI Link: 10.1016/j.jeconom.2016.10.007
ISSN: 0304-4076
Links: http://www.sciencedirect.com/science/article/pii/S0304407616302032
http://hdl.handle.net/2381/38399
Embargo on file until: 12-Nov-2018
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, Elsevier. Deposited with reference to the publisher’s open access archiving policy.
Description: JEL Classification: C13; C33.
The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Economics

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