Yu-Chin Hsu, Ta-Cheng Huang, Haiqing Xu
arXiv 20 Mar 2018 · Econometrics · publishedEconometric Theory (2022)
arXiv:1803.07514 · PDF · DOI · OpenAlex · Extracted main text
Unobserved heterogeneous treatment effects have been emphasized in the recent policy evaluation literature (see e.g., Heckman and Vytlacil, 2005). This paper proposes a nonparametric test for unobserved heterogeneous treatment effects in a treatment effect model with a binary treatment assignment, allowing for individuals' self-selection to the treatment. Under the standard local average treatment effects assumptions, i.e., the no defiers condition, we derive testable model restrictions for the hypothesis of unobserved heterogeneous treatment effects. Also, we show that if the treatment outcomes satisfy a monotonicity assumption, these model restrictions are also sufficient. Then, we propose a modified Kolmogorov-Smirnov-type test which is consistent and simple to implement. Monte Carlo simulations show that our test performs well in finite samples. For illustration, we apply our test to study heterogeneous treatment effects of the Job Training Partnership Act on earnings and the impacts of fertility on family income, where the null hypothesis of homogeneous treatment effects gets rejected in the second case but fails to be rejected in the first application.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Heckman, Smith, and Clements (1997) Making the most out of programme evaluations and social experiments: Accounting for heterogeneity in programme impacts | 1.000 | 5 | 3 | 100% |
| 2 | Imbens and Angrist (1994) Identification and estimation of local average treatment effects | 0.874 | 7 | 2 | 100% |
| 3 | Lu and White (2014) Testing for separability in structural equations | 0.874 | 7 | 2 | 100% |
| 4 | Chernozhukov and Hansen (2005) An IV model of quantile treatment effects | 0.874 | 5 | 2 | 100% |
| 5 | Abadie, Angrist, and Imbens (2002) Instrumental variables estimates of the effect of subsidized training on the quantiles of trainee earnings | 0.811 | 4 | 2 | 100% |
| 6 | Frölich and Melly (2013) Unconditional quantile treatment effects under endogeneity | 0.811 | 4 | 2 | 100% |
| 7 | Heckman and Vytlacil (2005) Structural equations, treatment effects, and econometric policy evaluation | 0.737 | 3 | 2 | 100% |
| 8 | Matzkin (2003) Nonparametric estimation of nonadditive random functions | 0.737 | 3 | 2 | 100% |
| 9 | Hsu (2017) Consistent tests for conditional treatment effects self | 0.644 | 3 | 2 | 67% |
| 10 | Chesher (2003) Identification in nonseparable models | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 65 scored citations.