Susan Athey, Guido Imbens, Thai Pham, Stefan Wager
arXiv 4 Feb 2017 · Statistics — Methodology · publishedAmerican Economic Review (2017) · 69 citations (OpenAlex)
arXiv:1702.01250 · PDF · DOI · OpenAlex · Extracted main text
There is a large literature on semiparametric estimation of average treatment effects under unconfounded treatment assignment in settings with a fixed number of covariates. More recently attention has focused on settings with a large number of covariates. In this paper we extend lessons from the earlier literature to this new setting. We propose that in addition to reporting point estimates and standard errors, researchers report results from a number of supplementary analyses to assist in assessing the credibility of their estimates.
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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 | Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo,… (2016) Double machine learning for treatment and causal parameters | 1.000 | 5 | 4 | 100% |
| 2 | Susan Athey, Guido Imbens, and Stefan Wager (2016) Efficient inference of average treatment effects in high dimensions via approximate residual balancing self | 0.843 | 3 | 3 | 100% |
| 3 | Mark J Van Der Laan and Daniel Rubin (2006) Targeted maximum likelihood learning | 0.843 | 3 | 3 | 100% |
| 4 | Alexandre Belloni, Victor Chernozhukov, Ivan Fernández-Val, and Chri… (2013) Program evaluation with high-dimensional data | 0.644 | 2 | 2 | 100% |
| 5 | Keisuke Hirano, Guido Imbens, Geert Ridder, and Donald Rubin (2001) Combining panels with attrition and refreshment samples self | 0.644 | 2 | 2 | 100% |
| 6 | James Robins and Andrea Rotnitzky (1995) Semiparametric efficiency in multivariate regression models with missing data | 0.644 | 2 | 2 | 100% |
| 7 | James Robins, Andrea Rotnitzky, and L.P. Zhao (1995) Analysis of semiparametric regression models for repeated outcomes in the presence of missing data | 0.644 | 2 | 2 | 100% |
| 8 | Daniel O Scharfstein, Andrea Rotnitzky, and James M Robins (1999) Adjusting for nonignorable drop-out using semiparametric nonresponse models | 0.644 | 2 | 2 | 100% |
| 9 | Aad W. van der Vaart (2000) Asymptotic Statistics | 0.644 | 2 | 2 | 100% |
| 10 | Stefan Wager, Wenfei Du, Jonathan Taylor, and Robert J Tibshirani (2016) High-dimensional regression adjustments in randomized experiments self | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 34 scored citations.
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 | Deep Neural Networks for Estimation and Inference | 0.405 | 1 | 1 |
| 2 | Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org | 0.405 | 1 | 1 |