arXiv 18 May 2021 · Econometrics
arXiv:2105.08766 · PDF · DOI · OpenAlex · Extracted main text
I consider estimation of the average treatment effect (ATE), in a population composed of $S$ groups or units, when one has unbiased estimators of each group's conditional average treatment effect (CATE). These conditions are met in stratified experiments and in matching studies. I assume that each CATE is bounded in absolute value by $B$ standard deviations of the outcome, for some known $B$. This restriction may be appealing: outcomes are often standardized in applied work, so researchers can use available literature to determine a plausible value for $B$. I derive, across all linear combinations of the CATEs' estimators, the minimax estimator of the ATE. In two stratified experiments, my estimator has twice lower worst-case mean-squared-error than the commonly-used strata-fixed effects estimator. In a matching study with limited overlap, my estimator achieves 56% of the precision gains of a commonly-used trimming estimator, and has an 11 times smaller worst-case mean-squared-error.
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| Reference | Intensity | Mentions | Sections | Main text | |
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| 1 | Behaghel, De Chaisemartin \ Gurgand (2017) `Ready for boarding? the effects of a boarding school for disadvantaged students', American Economic Journal: Applied Economics… | 0.693 | 12 | 1 | 100% |
| 2 | Connors, Speroff, Dawson, Thomas, Harrell, Wagner, Desbiens, Goldman… (1996) `The effectiveness of right heart catheterization in the initial care of critically iii patients', Jama 276(11), 889–897 | 0.693 | 7 | 1 | 100% |
| 3 | Armstrong \ Kolesár (2021) `Sensitivity analysis using approximate moment condition models', Quantitative Economics 12(1), 77–108 | 0.693 | 6 | 1 | 100% |
| 4 | Crump, Hotz, Imbens \ Mitnik (2009) `Dealing with limited overlap in estimation of average treatment effects', Biometrika 96(1), 187–199 | 0.693 | 6 | 1 | 100% |
| 5 | Armstrong \ Kolesár (2018) `Optimal inference in a class of regression models', Econometrica 86(2), 655–683 | 0.644 | 4 | 1 | 100% |
| blattman2016can | unmatched citation key blattman2016can | 0.644 | 4 | 1 | 100% |
| de2020estimating | unmatched citation key de2020estimating | 0.644 | 4 | 1 | 100% |
| 8 | Donoho (1994) `Statistical estimation and optimal recovery', The Annals of Statistics pp. 238–270 | 0.644 | 4 | 1 | 100% |
| 9 | Armstrong \ Kolesár (2018) `Optimal inference in a class of regression models', Econometrica 86(2), 655–683 | 0.585 | 3 | 1 | 100% |
| 10 | Armstrong \ Kolesár (2021) `Finite-sample optimal estimation and inference on average treatment effects under unconfoundedness', Econometrica 89(3), 1141–1… | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 26 scored citations. 2 of these could not be matched to a bibliography entry, so only the citation key is shown.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
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| 1 | Robust Inference for Weighted Estimands | 0.405 | 1 | 1 |