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

Author

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  • Kossova, Elena

    (HSE University, Moscow, Russian Federation;)

  • Kosorukova, Mariia

    (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

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

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    More about this item

    Keywords

    treatment effect; matching; propensity score; multivariate probit model; education; self-assessment of health; chronic diseases.;
    All these keywords.

    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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