Akanksha Negi, Jeffrey M. Wooldridge
arXiv 5 Oct 2020 · Econometrics · publishedJournal of Business and Economic Statistics (2024) · 4 citations (OpenAlex)
arXiv:2010.01800 · PDF · DOI · OpenAlex · Extracted main text
We study efficiency improvements in randomized experiments for estimating a vector of potential outcome means using regression adjustment (RA) when there are more than two treatment levels. We show that linear RA which estimates separate slopes for each assignment level is never worse, asymptotically, than using the subsample averages. We also show that separate RA improves over pooled RA except in the obvious case where slope parameters in the linear projections are identical across the different assignment levels. We further characterize the class of nonlinear RA methods that preserve consistency of the potential outcome means despite arbitrary misspecification of the conditional mean functions. Finally, we apply these regression adjustment techniques to efficiently estimate the lower bound mean willingness to pay for an oil spill prevention program in California.
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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 | Lin, W (2013) Agnostic notes on regression adjustments to experimental data: Reexamining Freedman's critique | 0.737 | 3 | 2 | 100% |
| 2 | Carson, R. T., M. B. Conaway, W. M. Hanemann, J. A. Krosnick, R. C.… (2004) Valuing Oil Spill Prevention | 0.644 | 2 | 2 | 100% |
| 3 | Freedman, D. A (2008) On regression adjustments to experimental data | 0.644 | 2 | 2 | 100% |
| 4 | Cohen, P. L. and C. B. Fogarty (2024) No-harm calibration for generalized Oaxaca–Blinder estimators | 0.585 | 3 | 1 | 100% |
| 5 | Guo, K. and G. Basse (2023) The generalized oaxaca-blinder estimator | 0.585 | 3 | 1 | 100% |
| 6 | Leon, S., A. A. Tsiatis, and M. Davidian (2003) Semiparametric estimation of treatment effect in a pretest-posttest study | 0.585 | 3 | 1 | 100% |
| 7 | Zhao, A. and P. Ding (2023) Covariate adjustment in multiarmed, possibly factorial experiments | 0.585 | 3 | 1 | 100% |
| 8 | Abadie, A., S. Athey, G. W. Imbens, and J. M. Wooldridge (2020) Sampling-Based versus Design-Based Uncertainty in Regression Analysis self | 0.511 | 2 | 1 | 100% |
| 9 | Cattaneo, M. D (2010) Efficient semiparametric estimation of multi-valued treatment effects under ignorability | 0.511 | 2 | 1 | 100% |
| 10 | Gail, M. H., S. Wieand, and S. Piantadosi (1984) Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 35 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Regression Adjustment for Estimating Distributional Treatment Effects in Randomized Controlled Trials | 0.737 | 3 | 2 |