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Copula Bivariate Probit Models: With An Application To Medical Expenditures

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  • Rainer Winkelmann

Abstract

The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the "treatment") on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing non-normal dependence using copulas. In an application of the copula bivariate probit model to the effect of insurance status on the absence of ambulatory health care expen- diture, a model based on the Frank copula outperforms the standard bivariate probit model.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 21 (2012)
Issue (Month): 12 (December)
Pages: 1444-1455

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Handle: RePEc:wly:hlthec:v:21:y:2012:i:12:p:1444-1455

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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Cited by:
  1. Giampiero Marra & Rosalba Radice & Silvia Missiroli, 2014. "Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models," Computational Statistics, Springer, Springer, vol. 29(3), pages 715-741, June.
  2. Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, Elsevier, vol. 121(2), pages 298-301.
  3. Katarzyna BieĊ„-Barkowska, 2012. "A Bivariate Copula-based Model for a Mixed Binary-Continuous Distribution: A Time Series Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, CEJEME, vol. 4(2), pages 117-142, June.

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