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Binary Choice Model with Endogeneity: Identification via Heteroskedasticity

Author

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  • Minxian Yang

    (School of Economics, Australian School of Business, the University of New South Wales)

Abstract

The idea of identifying structural parameters via heteroskedasticity is explored in the context of binary choice models with an endogenous regressor. Sufficient conditions for parameter identification are derived for probit models without relying on instruments or additional restrictions. The results are extendable to other parametric binary choice models. The semi- parametric model of Manski (1975, 1985), with endogeneity, is also shown to be identifiable in the presence of heteroskedasticity. The role of heteroskedasticity in identifying and estimating structural parameters is demonstrated by Monte Carlo experiments.

Suggested Citation

  • Minxian Yang, 2014. "Binary Choice Model with Endogeneity: Identification via Heteroskedasticity," Discussion Papers 2014-34, School of Economics, The University of New South Wales.
    • Handle: RePEc:swe:wpaper:2014-34
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2014-34.pdf
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    More about this item

    Keywords

    Qualitative response; Probit; Logit; Linear median regression; Endogeneity; Identification; Heteroskedasticity;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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