{"title":"潜在变量框架下处理参数的简单估计及其在学校教育收益估计中的应用","authors":"J. Heckman, J. Tobias, E. Vytlacil","doi":"10.3386/W7950","DOIUrl":null,"url":null,"abstract":"This paper derives simply computed closed-form expressions for the Average Treatment Effect (ATE), the effect of Treatment on the Treated (TT), Local Average Treatment Effect (LATE) and Marginal Treatment Effect (MTE) in a latent variable framework for both normal and non-normal models. The techniques presented in the paper are applied to estimating a variety of treatment parameters capturing the returns to a college education for various populations using data from the National Longitudinal Survey of Youth (NLSY).","PeriodicalId":114523,"journal":{"name":"Labor eJournal","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"83","resultStr":"{\"title\":\"Simple Estimators for Treatment Parameters in a Latent Variable Framework with an Application to Estimating the Returns to Schooling\",\"authors\":\"J. Heckman, J. Tobias, E. Vytlacil\",\"doi\":\"10.3386/W7950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper derives simply computed closed-form expressions for the Average Treatment Effect (ATE), the effect of Treatment on the Treated (TT), Local Average Treatment Effect (LATE) and Marginal Treatment Effect (MTE) in a latent variable framework for both normal and non-normal models. The techniques presented in the paper are applied to estimating a variety of treatment parameters capturing the returns to a college education for various populations using data from the National Longitudinal Survey of Youth (NLSY).\",\"PeriodicalId\":114523,\"journal\":{\"name\":\"Labor eJournal\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"83\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Labor eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3386/W7950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Labor eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3386/W7950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simple Estimators for Treatment Parameters in a Latent Variable Framework with an Application to Estimating the Returns to Schooling
This paper derives simply computed closed-form expressions for the Average Treatment Effect (ATE), the effect of Treatment on the Treated (TT), Local Average Treatment Effect (LATE) and Marginal Treatment Effect (MTE) in a latent variable framework for both normal and non-normal models. The techniques presented in the paper are applied to estimating a variety of treatment parameters capturing the returns to a college education for various populations using data from the National Longitudinal Survey of Youth (NLSY).