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Structural change tests for GEL criteria

Author

Listed:
  • Alain Guay

    () (Department of Economics, Universite du Quebec a Montreal)

  • Jean-Francois Lamarche

    () (Department of Economics, Brock University)

Abstract

This paper examines structural change tests based on generalized empirical likelihood methods in the time series context. Standard structural change tests for GMM with strongly identified parameters are adapted to the GEL context. We show that when moment conditions are properly smoothed, these test statistics converge to the same asymptotic distribution as in GMM, in cases with known and unknown breakpoints. New test statistics specific to GEL methods are also introduced. Finally, we propose stability tests in the GEL framework that are robust to weak identification and dependent data. A simulation study examines the small sample properties of the tests.

Suggested Citation

  • Alain Guay & Jean-Francois Lamarche, 2010. "Structural change tests for GEL criteria," Working Papers 1002, Brock University, Department of Economics.
  • Handle: RePEc:brk:wpaper:1002
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    File URL: https://brocku.ca/repec/pdf/1002.pdf
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    Cited by:

    1. 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.
    2. 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.

    More about this item

    Keywords

    Generalized empirical likelihood; generalized method of moments; parameter instability; structural change; weak identification;

    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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