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Structural change tests for GEL criteria

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  • Alain Guay
  • Jean-François Lamarche

Abstract

This article examines structural change tests based on generalized empirical likelihood methods in the time series context, allowing for dependent data. Standard structural change tests for the Generalized method of moments (GMM) are adapted to the generalized empirical likelihood (GEL) context. We show that when moment conditions are properly smoothed, these test statistics converge to the same asymptotic distribution as in the GMM, in cases with known and unknown breakpoints. New test statistics specific to GEL methods, and that are robust to weak identification, are also introduced. A simulation study examines the small sample properties of the tests and reveals that GEL-based robust tests performed well, both in terms of the presence and location of a structural change and in terms of the nature of identification.

Suggested Citation

  • Alain Guay & Jean-François Lamarche, 2018. "Structural change tests for GEL criteria," Econometric Reviews, Taylor & Francis Journals, vol. 37(9), pages 1000-1032, October.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:9:p:1000-1032
    DOI: 10.1080/00927872.2016.1178893
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    Cited by:

    1. Alastair R. Hall & Yuyi Li & Chris D. Orme & Arthur Sinko, 2015. "Testing for Structural Instability in Moment Restriction Models: An Info-Metric Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(3), pages 286-327, March.
    2. Alain Guay & Jean-Francois Lamarche, 2005. "The Information Content of Implied Probabilities to Detect Structural Change," Working Papers 0804, Brock University, Department of Economics, revised Oct 2008.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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