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Weak Identification in Probit Models with Endogenous Covariates

Author

Listed:
  • Jean-Marie Dufour
  • Joachim Wilde

    (Universitaet Osnabrueck)

Abstract

Weak identification is a well known topic for linear multiple equation models. However, little is known whether this problem also matters for probit models with endogenous covariates. Therefore, the behaviour of the usual z-statistic in case of weak identification is analysed in a simulation study. It shows large size distortions. However, a new puzzle is found: The magnitude of the size distortion depends heavily on the parameter value that is tested. Alternatively the LR-statistic was calculated which is known to be more robust against weak identification in case of linear multiple equation models. The same seems to be true for probit equations. No size distortions are found. However, medium undersizing is observed.

Suggested Citation

  • Jean-Marie Dufour & Joachim Wilde, 2013. "Weak Identification in Probit Models with Endogenous Covariates," IEER Working Papers 95, Institute of Empirical Economic Research, Osnabrueck University, revised 28 Feb 2013.
    • Handle: RePEc:iee:wpaper:wp0095
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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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    Keywords

    probit model; weak identification;

    JEL classification:

    • C - Mathematical and Quantitative Methods

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