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Weak identification in probit models with endogenous covariates

Author

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  • Jean-Marie Dufour

    (McGill University)

  • Joachim Wilde

    (Fachbereich Wirtschaftswissenschaften)

Abstract

Weak identification is a well-known issue in the context of linear structural models. However, for probit models with endogenous explanatory variables, this problem has been little explored. In this paper, we study by simulating the behavior of the usual z-test and the LR test in the presence of weak identification. We find that the usual asymptotic z-test exhibits large level distortions (over-rejections under the null hypothesis). The magnitude of the level distortions depends heavily on the parameter value tested. In contrast, asymptotic LR tests do not over-reject and appear to be robust to weak identification.

Suggested Citation

  • Jean-Marie Dufour & Joachim Wilde, 2018. "Weak identification in probit models with endogenous covariates," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(4), pages 611-631, October.
    • Handle: RePEc:spr:alstar:v:102:y:2018:i:4:d:10.1007_s10182-018-0325-8
    DOI: 10.1007/s10182-018-0325-8
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    1. Last Week's Reading
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2013-06-04 00:35:00

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    Cited by:

    1. David T. Frazier & Eric Renault & Lina Zhang & Xueyan Zhao, 2020. "Weak Identification in Discrete Choice Models," Papers 2011.06753, arXiv.org, revised Jan 2021.
    2. Dakyung Seong, 2022. "Binary response model with many weak instruments," Papers 2201.04811, arXiv.org, revised May 2023.

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    More about this item

    Keywords

    Probit model; Weak identification; z-test;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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