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Estimating the effects of universal transfers: new ML approach and application to labor supply reaction to child benefits

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  • Filip Premik

    (Group for Research in Applied Economics (GRAPE))

Abstract

This paper evaluates effects of introduction of a universal child benefit program on female labor supply. Large scale government interventions affect economic outcomes through different channels of various magnitude and direction of the effects. In order to account for this feature, I develop a model in which a woman decides whether to participate in the labor market in a given period. I show how to use the resulting decision rules to explain flows in aggregate labor supply and simulate counterfactual paths of labor force. My framework combines flexibility of reduced form approaches with an appealing structure of dynamic discrete choice models. The model is estimated nonparametrically using recent advances in machine learning methods. The results indicate a 2-4 percentage points drop in labor force among the eligible females, mainly driven by changes in women's perceived trade-offs and beliefs that discouraged inflows.

Suggested Citation

  • Filip Premik, 2021. "Estimating the effects of universal transfers: new ML approach and application to labor supply reaction to child benefits," GRAPE Working Papers 54, GRAPE Group for Research in Applied Economics.
    • Handle: RePEc:fme:wpaper:54
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    References listed on IDEAS

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    9. Michael Baker & Derek Messacar & Mark Stabile, 2023. "Effects of Child Tax Benefits on Poverty and Labor Supply: Evidence from the Canada Child Benefit and Universal Child Care Benefit," Journal of Labor Economics, University of Chicago Press, vol. 41(4), pages 1129-1182.
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    Cited by:

    1. Filip Premik, 2022. "Evaluating Poland’s Family 500+ Child Support Programme," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 1-19.

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    More about this item

    Keywords

    child benefits; labor supply; program evaluation; difference-in-difference estimation; covariate balancing propensity score;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply

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