IDEAS home Printed from https://ideas.repec.org/p/zur/econwp/029.html
   My bibliography  Save this paper

Copula bivariate probit models: with an application to medical expenditures

Author

Listed:
  • 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.

Suggested Citation

  • Rainer Winkelmann, 2011. "Copula bivariate probit models: with an application to medical expenditures," ECON - Working Papers 029, Department of Economics - University of Zurich.
    • Handle: RePEc:zur:econwp:029
    as

    Download full text from publisher

    File URL: http://www.econ.uzh.ch/static/wp/econwp029.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    2. Ehsan Latif, 2009. "The impact of diabetes on employment in Canada," Health Economics, John Wiley & Sons, Ltd., vol. 18(5), pages 577-589.
    3. Murray D. Smith, 2003. "Modelling sample selection using Archimedean copulas," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 99-123, June.
    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.
    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, August.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Hasanov, Rashad & Bhattacharya, Prasad Sankar, 2019. "Do political factors influence banking crisis?," Economic Modelling, Elsevier, vol. 76(C), pages 305-318.
    5. Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, vol. 121(2), pages 298-301.
    6. repec:eee:transb:v:108:y:2018:i:c:p:84-105 is not listed on IDEAS
    7. McGovern, Mark E. & Canning, David & Bärnighausen, Till, 2018. "Accounting for non-response bias using participation incentives and survey design: An application using gift vouchers," Economics Letters, Elsevier, vol. 171(C), pages 239-244.
    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. 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.
    10. 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.
    11. Ziebarth, Nicolas R., 2017. "Social Insurance and Health," IZA Discussion Papers 10918, Institute of Labor Economics (IZA).
    12. repec:spr:empeco:v:56:y:2019:i:3:d:10.1007_s00181-017-1372-9 is not listed on IDEAS
    13. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    14. Mark McGovern & David Canning & Till Bärnighausen, 2018. "Accounting for Non-Response Bias using Participation Incentives and Survey Design," CHaRMS Working Papers 18-02, Centre for HeAlth Research at the Management School (CHaRMS).
    15. Han, Sukjin & Vytlacil, Edward J., 2017. "Identification in a generalization of bivariate probit models with dummy endogenous regressors," Journal of Econometrics, Elsevier, vol. 199(1), pages 63-73.

    More about this item

    Keywords

    Bivariate probit; binary endogenous regressor; Frank copula; Clayton copula;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zur:econwp:029. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Marita Kieser). General contact details of provider: http://edirc.repec.org/data/seizhch.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.