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Marginal effects of a bivariate binary choice model

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  • Hasebe, Takuya

Abstract

This paper discusses the copula-based approach of a bivariate binary choice model. We derive the marginal effects of explanatory variables on an outcome of interest (both direct and indirect) in the model. We also show that the signs of the marginal effects are determined by the signs of the coefficient parameters. A real-data application is provided.

Suggested Citation

  • Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, vol. 121(2), pages 298-301.
    • Handle: RePEc:eee:ecolet:v:121:y:2013:i:2:p:298-301
    DOI: 10.1016/j.econlet.2013.08.028
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    References listed on IDEAS

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    1. 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.
    2. William H. Greene, 1998. "Gender Economics Courses in Liberal Arts Colleges: Further Results," The Journal of Economic Education, Taylor & Francis Journals, vol. 29(4), pages 291-300, January.
    3. Partha Deb & Murat K. Munkin & 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, November.
    4. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
    5. Christofides, Louis N. & Stengos, Thanasis & Swidinsky, Robert, 1997. "On the calculation of marginal effects in the bivariate probit model," Economics Letters, Elsevier, vol. 54(3), pages 203-208, July.
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    Citations

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    Cited by:

    1. Mustafa Coban, 2021. "rbprobit: Recursive bivariate probit estimation and decomposition of marginal effects," London Stata Conference 2021 20, Stata Users Group.
    2. Hasebe, Takuya, 2021. "On the treatment effects of a binary choice outcome model," Economics Letters, Elsevier, vol. 200(C).
    3. Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2019. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Journal of Human Capital, University of Chicago Press, vol. 13(2), pages 260-292.
    4. Abayomi Samuel Oyekale, 2023. "Effect of Health Insurance Uptake on Hesitancy toward COVID-19 Vaccines in Nigeria: A Recursive Bivariate Probit and Decomposition Estimation," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
    5. Mustafa Coban, 2022. "rbicopula: Recursive bivariate copula estimation and decomposition of marginal effects," 2022 Stata Conference 04, Stata Users Group.
    6. Pérez-Urdiales, María & García-Valiñas, María Ángeles, 2016. "Efficient water-using technologies and habits: A disaggregated analysis in the water sector," Ecological Economics, Elsevier, vol. 128(C), pages 117-129.
    7. Minghui Yin & Balekouzou Augustin & Chang Shu & Tingting Qin & Ping Yin, 2016. "Probit Models to Investigate Prevalence of Total Diagnosed and Undiagnosed Diabetes among Aged 45 Years or Older Adults in China," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-13, October.

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    More about this item

    Keywords

    Copula; Binary choice; Marginal effect;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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