{"title":"Assessing external validity in practice","authors":"Sebastian Galiani , Brian Quistorff","doi":"10.1016/j.rie.2024.100964","DOIUrl":null,"url":null,"abstract":"<div><p>We review, from a practical standpoint, the evolving literature on assessing external validity (EV) of estimated treatment effects. We review existing EV measures, and focus on methods that permit multiple datasets (Hotz et al., 2005). We outline criteria for practical usage, evaluate the existing approaches, and identify a gap in potential methods. Our practical considerations motivate a novel method utilizing the Group Lasso (Yuan and Lin, 2006) to estimate a tractable regression-based model of the conditional average treatment effect (CATE). This approach can perform better when settings have differing covariate distributions and allows for easily extrapolating the average treatment effect to new settings. We apply these measures to a set of identical field experiments upgrading slum dwellings in three different countries (Galiani et al., 2017).</p></div>","PeriodicalId":46094,"journal":{"name":"Research in Economics","volume":"78 3","pages":"Article 100964"},"PeriodicalIF":1.2000,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research in Economics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1090944324000280","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
We review, from a practical standpoint, the evolving literature on assessing external validity (EV) of estimated treatment effects. We review existing EV measures, and focus on methods that permit multiple datasets (Hotz et al., 2005). We outline criteria for practical usage, evaluate the existing approaches, and identify a gap in potential methods. Our practical considerations motivate a novel method utilizing the Group Lasso (Yuan and Lin, 2006) to estimate a tractable regression-based model of the conditional average treatment effect (CATE). This approach can perform better when settings have differing covariate distributions and allows for easily extrapolating the average treatment effect to new settings. We apply these measures to a set of identical field experiments upgrading slum dwellings in three different countries (Galiani et al., 2017).
期刊介绍:
Established in 1947, Research in Economics is one of the oldest general-interest economics journals in the world and the main one among those based in Italy. The purpose of the journal is to select original theoretical and empirical articles that will have high impact on the debate in the social sciences; since 1947, it has published important research contributions on a wide range of topics. A summary of our editorial policy is this: the editors make a preliminary assessment of whether the results of a paper, if correct, are worth publishing. If so one of the associate editors reviews the paper: from the reviewer we expect to learn if the paper is understandable and coherent and - within reasonable bounds - the results are correct. We believe that long lags in publication and multiple demands for revision simply slow scientific progress. Our goal is to provide you a definitive answer within one month of submission. We give the editors one week to judge the overall contribution and if acceptable send your paper to an associate editor. We expect the associate editor to provide a more detailed evaluation within three weeks so that the editors can make a final decision before the month expires. In the (rare) case of a revision we allow four months and in the case of conditional acceptance we allow two months to submit the final version. In both cases we expect a cover letter explaining how you met the requirements. For conditional acceptance the editors will verify that the requirements were met. In the case of revision the original associate editor will do so. If the revision cannot be at least conditionally accepted it is rejected: there is no second revision.