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

Filip Premik
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Filip Premik: Group for Research in Applied Economics (GRAPE)

No 54, GRAPE Working Papers from GRAPE Group for Research in Applied Economics

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.

Keywords: child benefits; labor supply; program evaluation; difference-in-difference estimation; covariate balancing propensity score (search for similar items in EconPapers)
JEL-codes: C21 C23 I38 J22 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2021
New Economics Papers: this item is included in nep-big, nep-dcm, nep-isf and nep-lma
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:fme:wpaper:54

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