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Robustness of binary choice models to conditional heteroscedasticity

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  • Ginker, Tim
  • Lieberman, Offer

Abstract

We show that when the true data generating process of a large class of binary choice models contains conditional heteroscedasticity, predictions based on the misspecified MLE in which conditional heteroscedasticity is ignored, are unaffected by the misspecification.

Suggested Citation

  • Ginker, Tim & Lieberman, Offer, 2017. "Robustness of binary choice models to conditional heteroscedasticity," Economics Letters, Elsevier, vol. 150(C), pages 130-134.
    • Handle: RePEc:eee:ecolet:v:150:y:2017:i:c:p:130-134
    DOI: 10.1016/j.econlet.2016.11.024
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    References listed on IDEAS

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    More about this item

    Keywords

    Conditional heteroscedasticity; Misspecified models; Probit;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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