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

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  • Chen, Sanpan
  • Cui, Guowei
  • Zhang, Jianhua

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.

Suggested Citation

  • Chen, Sanpan & Cui, Guowei & Zhang, Jianhua, 2017. "On testing for structural break of coefficients in factor-augmented regression models," Economics Letters, Elsevier, vol. 161(C), pages 141-145.
    • Handle: RePEc:eee:ecolet:v:161:y:2017:i:c:p:141-145
    DOI: 10.1016/j.econlet.2017.10.001
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    References listed on IDEAS

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    More about this item

    Keywords

    Structural break test; Factor-augmented regression model; Asymptotic null distribution;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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