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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.
  14. Karen Smith Conway & Andrea Kutinova, 2006. "Maternal health: does prenatal care make a difference?," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 461-488.
  15. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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  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. Ziebarth, Nicolas R., 2017. "Social Insurance and Health," IZA Discussion Papers 10918, Institute for the Study of Labor (IZA).
  3. 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.
  4. 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.
  5. 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.
  6. Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, vol. 121(2), pages 298-301.
  7. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
  8. 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.
  9. repec:eee:econom:v:199:y:2017:i:1:p:63-73 is not listed on IDEAS
  10. 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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