IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v29y2014i3p715-741.html
   My bibliography  Save this article

Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models

Author

Listed:
  • Giampiero Marra
  • Rosalba Radice
  • Silvia Missiroli

Abstract

Lagrange multiplier and Wald tests for the hypothesis of absence of unobserved confounding are extended to the context of semiparametric recursive and sample selection bivariate probit models. The finite sample size properties of the tests are examined through a Monte Carlo study using several scenarios: correct model specification, distributional and functional misspecification, with and without an exclusion restriction. The simulation results provide some guidelines which may be important for empirical analysis. The tests are illustrated using two datasets in which the issue of unobserved confounding arises. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • 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.
  • Handle: RePEc:spr:compst:v:29:y:2014:i:3:p:715-741
    DOI: 10.1007/s00180-013-0458-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00180-013-0458-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00180-013-0458-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Montmarquette, Claude & Mahseredjian, Sophie & Houle, Rachel, 2001. "The determinants of university dropouts: a bivariate probability model with sample selection," Economics of Education Review, Elsevier, vol. 20(5), pages 475-484, October.
    2. Chiara Monfardini & Rosalba Radice, 2008. "Testing Exogeneity in the Bivariate Probit Model: A Monte Carlo Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(2), pages 271-282, April.
    3. Kamila Cygan-Rehm & Miriam Maeder, 2012. "The Effect of Education on Fertility: Evidence from a Compulsory Schooling Reform," SOEPpapers on Multidisciplinary Panel Data Research 528, DIW Berlin, The German Socio-Economic Panel (SOEP).
    4. Cavanaugh, Joseph E. & Shumway, Robert H., 1996. "On computing the expected Fisher information matrix for state-space model parameters," Statistics & Probability Letters, Elsevier, vol. 26(4), pages 347-355, March.
    5. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    6. Fabian Sobotka & Rosalba Radice & Giampiero Marra & Thomas Kneib, 2013. "Estimating the relationship between women's education and fertility in Botswana by using an instrumental variable approach to semiparametric expectile regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(1), pages 25-45, January.
    7. 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.
    8. Massimiliano Bratti & Alfonso Miranda, 2011. "Endogenous treatment effects for count data models with endogenous participation or sample selection," Health Economics, John Wiley & Sons, Ltd., vol. 20(9), pages 1090-1109, September.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Giampiero Marra & Simon N. Wood, 2012. "Coverage Properties of Confidence Intervals for Generalized Additive Model Components," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(1), pages 53-74, March.
    11. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    12. Ehsan Latif, 2009. "The impact of diabetes on employment in Canada," Health Economics, John Wiley & Sons, Ltd., vol. 18(5), pages 577-589, May.
    13. Rainer Winkelmann, 2012. "Copula Bivariate Probit Models: With An Application To Medical Expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 21(12), pages 1444-1455, December.
    14. Murray D. Smith, 2003. "Modelling sample selection using Archimedean copulas," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 99-123, June.
    15. Banasik, John & Crook, Jonathan, 2007. "Reject inference, augmentation, and sample selection," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1582-1594, December.
    16. Kamila Cygan-Rehm & Miriam Maeder, 2012. "The Effect of Education on Fertility: Evidence from a Compulsory Schooling Reform," Working Papers 121, Bavarian Graduate Program in Economics (BGPE).
    17. Goldman D. P. & Bhattacharya J. & McCaffrey D. F. & Duan N. & Leibowitz A. A. & Joyce G. F. & Morton S. C., 2001. "Effect of Insurance on Mortality in an HIV-Positive Population in Care," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 883-894, September.
    18. Van de Ven, Wynand P. M. M. & Van Praag, Bernard M. S., 1981. "The demand for deductibles in private health insurance : A probit model with sample selection," Journal of Econometrics, Elsevier, vol. 17(2), pages 229-252, November.
    19. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marra Giampiero & Radice Rosalba, 2017. "A joint regression modeling framework for analyzing bivariate binary data in R," Dependence Modeling, De Gruyter, vol. 5(1), pages 268-294, December.
    2. 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.
    3. Lyssenko, Nikita & Martinez-Espineira, Roberto, 2009. "`Been there done that': Disentangling option value effects from user heterogeneity when valuing natural resources with a use component," MPRA Paper 21976, University Library of Munich, Germany, revised 08 Apr 2010.
    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. 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.
    6. Hessami, Zohal & Resnjanskij, Sven, 2019. "Complex ballot propositions, individual voting behavior, and status quo bias," European Journal of Political Economy, Elsevier, vol. 58(C), pages 82-101.
    7. Rainer Winkelmann, 2012. "Copula Bivariate Probit Models: With An Application To Medical Expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 21(12), pages 1444-1455, December.
    8. Luca Zanin & Rosalba Radice & Giampiero Marra, 2013. "Estimating the Effect of Perceived Risk of Crime on Social Trust in the Presence of Endogeneity Bias," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(2), pages 523-547, November.
    9. Alfonso Miranda & Sophia Rabe-Hesketh, 2006. "Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables," Stata Journal, StataCorp LP, vol. 6(3), pages 285-308, September.
    10. Rosalba Radice & Luca Zanin & Giampiero Marra, 2013. "On the effect of obesity on employment in the presence of observed and unobserved confounding," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 436-455, November.
    11. Quinones, Esteban J. & Barham, Bradford L., 2018. "Endogenous Selection, Migration and Occupation Outcomes for Rural Southern Mexicans," Staff Paper Series 587, University of Wisconsin, Agricultural and Applied Economics.
    12. Entorf, Horst, 2013. "Criminal Victims, Victimized Criminals, or Both? A Deeper Look at the Victim-Offender Overlap," IZA Discussion Papers 7686, Institute of Labor Economics (IZA).
    13. Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2017. "A Simultaneous Equation Approach to Estimating HIV Prevalence With Nonignorable Missing Responses," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 484-496, April.
    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. Marra, Giampiero & Radice, Rosalba, 2013. "Estimation of a regression spline sample selection model," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 158-173.
    16. Stephen Finger & Shanti Gamper-Rabindran, 2013. "Testing the effects of self-regulation on industrial accidents," Journal of Regulatory Economics, Springer, vol. 43(2), pages 115-146, April.
    17. Karol Wyszynski & Giampiero Marra, 2018. "Sample selection models for count data in R," Computational Statistics, Springer, vol. 33(3), pages 1385-1412, September.
    18. John S. Heywood & W.S. Siebert & Xiangdong Wei, 2011. "Estimating the Use of Agency Workers: Can Family-Friendly Practices Reduce Their Use?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 50(3), pages 535-564, July.
    19. Riillo, Cesare Fabio Antonio & Peroni, Chiara, 2022. "Immigration and entrepreneurship in Europe: cross-country evidence," MPRA Paper 114580, University Library of Munich, Germany.
    20. Bing Xu & Honglin Wang & Adrian Van Rixtel, 2015. "Do banks extract informational rents through collateral?," BIS Working Papers 522, Bank for International Settlements.

    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:spr:compst:v:29:y:2014:i:3:p:715-741. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.