{"title":"Evaluating Poland’s Family 500+ Child Support Programme","authors":"Filip Premik","doi":"10.33119/gn/149193","DOIUrl":null,"url":null,"abstract":"I investigate the immediate effects of the introduction of a large-scale child benefit programme on the labour supply of household members in Poland. Due to non-ran-dom eligibility and the universal character of the programme, standard evaluation estimators may be inconsistent. In order to address this issue, I propose an approach that combines difference-in-difference (DID) propensity score based methods with the covariate balancing propensity score (CBPS) approach developed by Imai and Ratkovic [ 2014 ]. The DID estimators exploit the time dimension to uncover the causal effect of interest. The CBPS method is expected to significantly reduce the bias resulting from systematic differences between treated and untreated subpopulations. I also account for potential heterogeneity among households by focus-ing on comparisons between locally defined subpopulations","PeriodicalId":40977,"journal":{"name":"Gospodarka Narodowa-The Polish Journal of Economics","volume":" ","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gospodarka Narodowa-The Polish Journal of Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33119/gn/149193","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1
Abstract
I investigate the immediate effects of the introduction of a large-scale child benefit programme on the labour supply of household members in Poland. Due to non-ran-dom eligibility and the universal character of the programme, standard evaluation estimators may be inconsistent. In order to address this issue, I propose an approach that combines difference-in-difference (DID) propensity score based methods with the covariate balancing propensity score (CBPS) approach developed by Imai and Ratkovic [ 2014 ]. The DID estimators exploit the time dimension to uncover the causal effect of interest. The CBPS method is expected to significantly reduce the bias resulting from systematic differences between treated and untreated subpopulations. I also account for potential heterogeneity among households by focus-ing on comparisons between locally defined subpopulations