Publication Type

Journal Article

Publication Date

5-2017

Abstract

Conventional factor models assume that factor loadings are fixed over a long horizon of time, which appears overly restrictive and unrealistic in applications. In this paper, we introduce a time-varying factor model where factor loadings are allowed to change smoothly over time. We propose a local version of the principal component method to estimate the latent factors and time-varying factor loadings simultaneously. We establish the limiting distributions of the estimated factors and factor loadings in the standard large N and large T framework. We also propose a BIC-type information criterion to determine the number of factors, which can be used in models with either time-varying or time-invariant factor models. Based on the comparison between the estimates of the common components under the null hypothesis of no structural changes and those under the alternative, we propose a consistent test for structural changes in factor loadings. We establish the null distribution, the asymptotic local power property, and the consistency of our test. Simulations are conducted to evaluate both our nonparametric estimates and test statistic. We also apply our test to investigate Stock and Watson’s (2009) U.S. macroeconomic data set and find strong evidence of structural changes in the factor loadings.

Keywords

Factor model, Information criterion, Local principal component, Local smoothing, Structural change, Test, Time-varying parameter

Discipline

Econometrics

Research Areas

Econometrics

Publication

Journal of Econometrics

Volume

198

Issue

1

First Page

84

Last Page

101

ISSN

0304-4076

Identifier

10.1016/j.jeconom.2016.12.004

Publisher

Elsevier

City or Country

Singapore

Embargo Period

2-1-2019

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org/10.1016/j.jeconom.2016.12.004

Available for download on Friday, February 01, 2019

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Econometrics Commons

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