Matthew A. Masten, Alexandre Poirier, Linqi Zhang
arXiv 31 Dec 2020 · Econometrics · publishedJournal of Business and Economic Statistics (2023) · 20 citations (OpenAlex)
arXiv:2012.15716 · PDF · DOI · OpenAlex · Extracted main text
This paper provides a set of methods for quantifying the robustness of treatment effects estimated using the unconfoundedness assumption (also known as selection on observables or conditional independence). Specifically, we estimate and do inference on bounds on various treatment effect parameters, like the average treatment effect (ATE) and the average effect of treatment on the treated (ATT), under nonparametric relaxations of the unconfoundedness assumption indexed by a scalar sensitivity parameter c. These relaxations allow for limited selection on unobservables, depending on the value of c. For large enough c, these bounds equal the no assumptions bounds. Using a non-standard bootstrap method, we show how to construct confidence bands for these bound functions which are uniform over all values of c. We illustrate these methods with an empirical application to effects of the National Supported Work Demonstration program. We implement these methods in a companion Stata module for easy use in practice.
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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 | Masten, M. A. and A. Poirier (2018) Identification of treatment effects under conditional partial independence self | 1.000 | 13 | 3 | 100% |
| 2 | Masten, M. A. and A. Poirier (2020) Inference on breakdown frontiers self | 1.000 | 8 | 5 | 100% |
| 3 | Imbens, G. W (2003) Sensitivity to exogeneity assumptions in program evaluation | 0.874 | 6 | 2 | 100% |
| 4 | Fang, Z. and A. Santos (2019) Inference on directionally differentiable functions | 0.830 | 14 | 6 | 57% |
| 5 | Imbens, G. W. and D. B. Rubin (2015) Causal Inference for Statistics, Social, and Biomedical Sciences | 0.811 | 4 | 2 | 100% |
| 6 | Manpower Demonstration Research Corporation (MDRC (1983) Summary and Findings of the National Supported Work Demonstration | 0.737 | 3 | 2 | 100% |
| 7 | Hong, H. and J. Li (2018) The numerical delta method | 0.644 | 2 | 2 | 100% |
| 8 | van der Vaart, A. and J. Wellner (1996) Weak Convergence and Empirical Processes: With Applications to Statistics | 0.630 | 8 | 5 | 25% |
| 9 | Rosenbaum, P. R (1995) Observational Studies | 0.585 | 3 | 1 | 100% |
| 10 | Rosenbaum, P. R (2002) Observational Studies | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 38 scored citations.
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