{"title":"A bootstrap procedure to estimate the causal effect of a public policy, considering overlap and imperfect compliance.","authors":"Stefano Cabras","doi":"10.1080/02664763.2024.2428994","DOIUrl":null,"url":null,"abstract":"<p><p>This paper introduces a nonparametric bootstrap method for estimating the causal effects of public policy under the circumstances of imperfect compliance and overlap. It focuses on business investment subsidies in Sardinia by comparing firms eligible for the 1999 subsidies to those not, amid issues of imperfect compliance and overlapping programs. Bootstrap confidence intervals (CI) are proposed for the average effect of treatment on the sub-population of compliers. The obtained CIs are consistent across nominal levels and robust against data nonnormality; they show coverages of credible intervals close to nominal, suggesting effectiveness for assessing causal effects. Compared to other methods, the results of the new combination of a specific estimator for incompliance and the bootstrap align with those of more modern approaches such as Bayesian Additive Regression Trees and Causal forest.</p>","PeriodicalId":15239,"journal":{"name":"Journal of Applied Statistics","volume":"52 7","pages":"1470-1484"},"PeriodicalIF":1.1000,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117864/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/02664763.2024.2428994","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a nonparametric bootstrap method for estimating the causal effects of public policy under the circumstances of imperfect compliance and overlap. It focuses on business investment subsidies in Sardinia by comparing firms eligible for the 1999 subsidies to those not, amid issues of imperfect compliance and overlapping programs. Bootstrap confidence intervals (CI) are proposed for the average effect of treatment on the sub-population of compliers. The obtained CIs are consistent across nominal levels and robust against data nonnormality; they show coverages of credible intervals close to nominal, suggesting effectiveness for assessing causal effects. Compared to other methods, the results of the new combination of a specific estimator for incompliance and the bootstrap align with those of more modern approaches such as Bayesian Additive Regression Trees and Causal forest.
期刊介绍：
Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.
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