On testing for structural break of coefficients in factor-augmented regression models

Sanpan Chen, Guowei Cui and Jianhua Zhang

Economics Letters, 2017, vol. 161, issue C, 141-145

Abstract: This paper considers testing for structural break of factor-augmented regression models with unknown change point. In this case, the classical structural break tests proposed by Andrews (1993) and Andrews and Ploberger (1994) are infeasible due to the presence of unobservable factors. This paper develops the feasible two-step tests based on their structural break tests. We prove that the asymptotic null distributions of the proposed two-step tests remain to be the same as those of their infeasible tests. The Monte Carlo simulations confirm the theoretical results and show that the two-step tests perform well in finite sample.

Keywords: Structural break test; Factor-augmented regression model; Asymptotic null distribution (search for similar items in EconPapers)
JEL-codes: C12 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:161:y:2017:i:c:p:141-145

DOI: 10.1016/j.econlet.2017.10.001

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