G2TT
来源类型Working Paper
规范类型报告
DOI10.3386/t0324
来源IDTechnical Working Paper 0324
Nonparametric Tests for Treatment Effect Heterogeneity
Richard K. Crump; V. Joseph Hotz; Guido W. Imbens; Oscar A. Mitnik
发表日期2006-06-26
出版年2006
语种英语
摘要A large part of the recent literature on program evaluation has focused on estimation of the average effect of the treatment under assumptions of unconfoundedness or ignorability following the seminal work by Rubin (1974) and Rosenbaum and Rubin (1983). In many cases however, researchers are interested in the effects of programs beyond estimates of the overall average or the average for the subpopulation of treated individuals. It may be of substantive interest to investigate whether there is any subpopulation for which a program or treatment has a nonzero average effect, or whether there is heterogeneity in the effect of the treatment. The hypothesis that the average effect of the treatment is zero for all subpopulations is also important for researchers interested in assessing assumptions concerning the selection mechanism. In this paper we develop two nonparametric tests. The first test is for the null hypothesis that the treatment has a zero average effect for any subpopulation defined by covariates. The second test is for the null hypothesis that the average effect conditional on the covariates is identical for all subpopulations, in other words, that there is no heterogeneity in average treatment effects by covariates. Sacrificing some generality by focusing on these two specific null hypotheses we derive tests that are straightforward to implement.
主题Econometrics ; Estimation Methods
URLhttps://www.nber.org/papers/t0324
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/569972
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GB/T 7714
Richard K. Crump,V. Joseph Hotz,Guido W. Imbens,et al. Nonparametric Tests for Treatment Effect Heterogeneity. 2006.
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