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Estimation of the treatment effect of higher education on health: Comparison of the multivariate recursive probit model and matching

Author

Listed:
  • Elena Kossova

    (HSE University, Moscow, Russian Federation;)

  • Mariia Kosorukova

    (HSE University, Moscow, Russian Federation;)

Abstract

The paper presents a comparative analysis of the multivariate recursive probit model and matching as the methods for estimating the treatment effect of higher education on binary indicators of individuals’ health. Statistical evidence has been obtained in favor of the presence of a negative treatment effect of higher education on the probability of a woman suffering from hypertension and obesity and a man assessing his health as very good, as well as a positive effect on the probability of a woman having eye diseases and allergy. It is concluded that it is necessary to estimate the treatment effect in applied research simultaneously by different methods to obtain robust estimates

Suggested Citation

  • Elena Kossova & Mariia Kosorukova, 2023. "Estimation of the treatment effect of higher education on health: Comparison of the multivariate recursive probit model and matching," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), vol. 69, pages 65-90.
    • Handle: RePEc:ris:apltrx:0465
    as

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    References listed on IDEAS

    as
    1. Xie, Shiqing & Mo, Taiping, 2014. "The impact of education on health in China," China Economic Review, Elsevier, vol. 29(C), pages 1-18.
    2. Anning Hu, 2014. "The Health Benefits of College Education in Urban China: Selection Bias and Heterogeneity," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(3), pages 1101-1121, February.
    3. Anton Nivorozhkin, 2009. "Regression discontinuity design (in Russian)," Quantile, Quantile, issue 7, pages 1-8, September.
    4. Elena Kossova & Liubov Kupriianova & Bogdan Potanin, 2020. "Parametric and semiparametric multivariate sample selection models estimators’ accuracy: Comparative analysis on simulated data," Applied Econometrics, Russian Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 119-139.
    5. John Antonakis & Samuel Bendahan & Philippe Jacquart & Rafael Lalive, 2010. "On making causal claims : A review and recommendations," Post-Print hal-02313119, HAL.
    6. Donald Kenkel & Dean Lillard & Alan Mathios, 2006. "The Roles of High School Completion and GED Receipt in Smoking and Obesity," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 635-660, July.
    7. Damon Clark & Heather Royer, 2013. "The Effect of Education on Adult Mortality and Health: Evidence from Britain," American Economic Review, American Economic Association, vol. 103(6), pages 2087-2120, October.
    8. Grossman, Michael, 1972. "On the Concept of Health Capital and the Demand for Health," Journal of Political Economy, University of Chicago Press, vol. 80(2), pages 223-255, March-Apr.
    9. Joshua D. Angrist, 2004. "American Education Research Changes Tack," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 20(2), pages 198-212, Summer.
    10. Ruben Enikolopov, 2009. "Estimation of treatment effects (in Russian)," Quantile, Quantile, issue 6, pages 3-14, March.
    11. Giorgio Brunello & Daniele Fabbri & Margherita Fort, 2013. "The Causal Effect of Education on Body Mass: Evidence from Europe," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 195-223.
    12. Jason M. Fletcher & David E. Frisvold, 2009. "Higher Education and Health Investments: Does More Schooling Affect Preventive Health Care Use?," Journal of Human Capital, University of Chicago Press, vol. 3(2), pages 144-176.
    13. Martin Schlotter & Guido Schwerdt & Ludger Woessmann, 2011. "Econometric methods for causal evaluation of education policies and practices: a non-technical guide," Education Economics, Taylor & Francis Journals, vol. 19(2), pages 109-137.
    14. Marion Devaux & Franco Sassi & Jody Church & Michele Cecchini & Francesca Borgonovi, 2011. "Exploring the Relationship Between Education and Obesity," OECD Journal: Economic Studies, OECD Publishing, vol. 2011(1), pages 1-40.
    15. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LLC, vol. 3(3), pages 278-294, September.
    16. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

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