arXiv 15 May 2023 · Econometrics · 4 citations (OpenAlex)
arXiv:2305.08340 · PDF · DOI · OpenAlex · Extracted main text
Experiments that use covariate adaptive randomization (CAR) are commonplace in applied economics and other fields. In such experiments, the experimenter first stratifies the sample according to observed baseline covariates and then assigns treatment randomly within these strata so as to achieve balance according to pre-specified stratum-specific target assignment proportions. In this paper, we compute the semiparametric efficiency bound for estimating the average treatment effect (ATE) in such experiments with binary treatments allowing for the class of CAR procedures considered in Bugni, Canay, and Shaikh (2018, 2019). This is a broad class of procedures and is motivated by those used in practice. The stratum-specific target proportions play the role of the propensity score conditional on all baseline covariates (and not just the strata) in these experiments. Thus, the efficiency bound is a special case of the bound in Hahn (1998), but conditional on all baseline covariates. Additionally, this efficiency bound is shown to be achievable under the same conditions as those used to derive the bound by using a cross-fitted Nadaraya-Watson kernel estimator to form nonparametric regression adjustments.
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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 | Hahn, Jinyong (1998) On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects | 1.000 | 20 | 5 | 100% |
| 2 | Bugni, Federico A., Canay, Ivan A., Shaikh, Azeem M (2019) Inference under Covariate-Adaptive Randomization with Multiple Treatments | 1.000 | 13 | 4 | 100% |
| 3 | Bugni, Federico A., Canay, Ivan A., Shaikh, Azeem M (2018) Inference Under Covariate-Adaptive Randomization | 1.000 | 12 | 4 | 100% |
| 4 | LeCam, Lucien (1960) Locally Asymptotically Normal Families of Distributions: Certain Approximations to Families of Distributions and Their Use in th… | 0.928 | 5 | 3 | 80% |
| 5 | Chernozhukov, Victor, Chetverikov, Denis, Demirer, Mert, Duflo, Esth… (2018) Double/debiased machine learning for treatment and structural parameters | 0.811 | 4 | 2 | 100% |
| 6 | Devroye, Luc P., Wagner, T. J (1980) Distribution-Free Consistency Results in Nonparametric Discrimination and Regression Function Estimation | 0.737 | 3 | 2 | 100% |
| 7 | Spiegelman, C., Sacks, J (1980) Consistent Window Estimation in Nonparametric Regression | 0.737 | 3 | 2 | 100% |
| 8 | Armstrong, Timothy B (2022) Asymptotic Efficiency Bounds for a Class of Experimental Designs | 0.693 | 5 | 1 | 100% |
| 9 | Hájek, Jaroslav (1970) A characterization of limiting distributions of regular estimates | 0.644 | 3 | 2 | 67% |
| 10 | Hájek, Jaroslav (1972) Local asymptotic minimax and admissibility in estimation | 0.644 | 3 | 2 | 67% |
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