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Copula bivariate probit models: with an application to medical expenditures

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Listed author(s):
  • 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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Paper provided by Department of Economics - University of Zurich in its series ECON - Working Papers with number 029.

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Date of creation: Sep 2011
Handle: RePEc:zur:econwp:029
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Keywords: Bivariate probit; binary endogenous regressor; Frank copula; Clayton copula;

Other versions of this item:

Find related papers by JEL classification:
  • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
  • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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  1. Michael T. French & Johanna C. Maclean, 2006. "Underage alcohol use, delinquency, and criminal activity," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1261-1281.
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  3. Murray D. Smith, 2003. "Modelling sample selection using Archimedean copulas," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 99-123, 06.
  4. Trivedi, Pravin K. & Zimmer, David M., 2007. "Copula Modeling: An Introduction for Practitioners," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(1), pages 1-111, April.
  5. Munkin, Murat K. & Trivedi, Pravin K., 2008. "Bayesian analysis of the ordered probit model with endogenous selection," Journal of Econometrics, Elsevier, vol. 143(2), pages 334-348, April.
  6. Nikolay Nenovsky & S. Statev, 2006. "Introduction," Post-Print halshs-00260898, HAL.
  7. Lara Gitto & Domenico Santoro & Giuseppe Sobbrio, 2006. "Choice of dialysis treatment and type of medical unit (private vs public): application of a recursive bivariate probit," Health Economics, John Wiley & Sons, Ltd., vol. 15(11), pages 1251-1256.
  8. repec:dau:papers:123456789/1623 is not listed on IDEAS
  9. Koenker, Roger & Yoon, Jungmo, 2009. "Parametric links for binary choice models: A Fisherian-Bayesian colloquy," Journal of Econometrics, Elsevier, vol. 152(2), pages 120-130, October.
  10. Brigitte Dormont & Pierre-Yves Geoffard & Karine Lamiraud, 2009. "The influence of supplementary health insurance on switching behaviour: evidence from Swiss data," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1339-1356.
  11. Prokhorov, Artem & Schmidt, Peter, 2009. "Likelihood-based estimation in a panel setting: Robustness, redundancy and validity of copulas," Journal of Econometrics, Elsevier, vol. 153(1), pages 93-104, November.
  12. Ziggy MacDonald & Michael A. Shields, 2004. "Does problem drinking affect employment? Evidence from England," Health Economics, John Wiley & Sons, Ltd., vol. 13(2), pages 139-155.
  13. Murphy, Anthony, 2007. "Score tests of normality in bivariate probit models," Economics Letters, Elsevier, vol. 95(3), pages 374-379, June.
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  16. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
  17. Murat K. Munkin & Partha Deb & Pravin K. Trivedi, 2006. "Bayesian analysis of the two-part model with endogeneity: application to health care expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1081-1099.
  18. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
  19. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
  20. Murray D. Smith, 2005. "Using Copulas to Model Switching Regimes with an Application to Child Labour," The Economic Record, The Economic Society of Australia, vol. 81(s1), pages 47-57, 08.
  21. Zimmer, David M. & Trivedi, Pravin K., 2006. "Using Trivariate Copulas to Model Sample Selection and Treatment Effects: Application to Family Health Care Demand," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 63-76, January.
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Cited by:

  1. Keay, Myoung-Jin, 2016. "Partial copula methods for models with multiple discrete endogenous explanatory variables and sample selection," Economics Letters, Elsevier, vol. 144(C), pages 85-87.
  2. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
  3. Katarzyna Bień-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, vol. 4(2), pages 117-142, June.
  4. Jörg Schwiebert, 2016. "Multinomial choice models based on Archimedean copulas," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(3), pages 333-354, July.
  5. Pravin Trivedi & David Zimmer, 2017. "A Note on Identification of Bivariate Copulas for Discrete Count Data," Econometrics, MDPI, Open Access Journal, vol. 5(1), pages 1-11, February.
  6. Magdalena Six & Franz Wirl & Jaqueline Wolf, 2017. "Information as potential key determinant in switching electricity suppliers," Journal of Business Economics, Springer, vol. 87(2), pages 263-290, February.
  7. Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, vol. 121(2), pages 298-301.
  8. repec:eee:econom:v:199:y:2017:i:1:p:63-73 is not listed on IDEAS
  9. Giampiero Marra & Rosalba Radice & Silvia Missiroli, 2014. "Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models," Computational Statistics, Springer, vol. 29(3), pages 715-741, June.

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