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Estimation of Binary Choice Models with Linear Index and Dummy Endogenous Variables

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  • Nese Yildiz

    (University of Rochester, Department of Economics)

Abstract

This paper presents computationally simple estimators for the index coefficients in a binary choice model with a binary endogenous regressor without relying on distributional assumptions or on large support conditions and yields root-n consistent and asymptotically normal estimators. We develop a multi-step method for estimating the parameters in a triangular, linear index, threshold-crossing model with two equations. Such an econometric model might be used in testing for moral hazard while allowing for asymmetric information in insurance markets. In outlining this new estimation method two contributions are made. The first one is proposing a novel ”matching” estimator for the coefficient on the binary endogenous variable in the outcome equation. Second, in order to establish the asymptotic properties of the proposed estimators for the coefficients of the exogenous regressors in the outcome equation, the results of Powell, Stock and Stoker (1989) are extended to cover the case where the average derivative estimation requires a first step semi-parametric procedure.

Suggested Citation

  • Nese Yildiz, 2012. "Estimation of Binary Choice Models with Linear Index and Dummy Endogenous Variables," Koç University-TUSIAD Economic Research Forum Working Papers 1202, Koc University-TUSIAD Economic Research Forum.
    • Handle: RePEc:koc:wpaper:1202
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    File URL: http://eaf.ku.edu.tr/sites/eaf.ku.edu.tr/files/erf_wp_1202.pdf
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    References listed on IDEAS

    as
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    7. Amemiya, Takeshi, 1978. "The Estimation of a Simultaneous Equation Generalized Probit Model," Econometrica, Econometric Society, vol. 46(5), pages 1193-1205, September.
    8. Richard W. Blundell & James L. Powell, 2004. "Endogeneity in Semiparametric Binary Response Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 655-679.
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    12. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
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