Matias D. Cattaneo, Fang Han, Zhexiao Lin
arXiv 12 Dec 2023 · Mathematics — Statistics Theory · publishedBiometrika (2024) · 1 citations (OpenAlex)
arXiv:2312.07683 · PDF · DOI · OpenAlex · Extracted main text
In two influential contributions, Rosenbaum (2005, 2020) advocated for using the distances between component-wise ranks, instead of the original data values, to measure covariate similarity when constructing matching estimators of average treatment effects. While the intuitive benefits of using covariate ranks for matching estimation are apparent, there is no theoretical understanding of such procedures in the literature. We fill this gap by demonstrating that Rosenbaum's rank-based matching estimator, when coupled with a regression adjustment, enjoys the properties of double robustness and semiparametric efficiency without the need to enforce restrictive covariate moment assumptions. Our theoretical findings further emphasize the statistical virtues of employing ranks for estimation and inference, more broadly aligning with the insights put forth by Peter Bickel in his 2004 Rietz lecture (Bickel, 2004).
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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 | Rosenbaum, P. R (2020) Design of Observational Studies | 1.000 | 6 | 3 | 100% |
| 2 | Belloni, A., Chernozhukov, V., Chetverikov, D., and Kato, K (2015) Some new asymptotic theory for least squares series: Pointwise and uniform results | 0.928 | 4 | 3 | 100% |
| 3 | Cattaneo, M. D. and Farrell, M. H (2013) Optimal convergence rates, bahadur representation, and asymptotic normality of partitioning estimators self | 0.928 | 4 | 3 | 100% |
| 4 | Cattaneo, M. D., Farrell, M. H., and Feng, Y (2020) Large sample properties of partitioning-based series estimators self | 0.928 | 4 | 3 | 100% |
| 5 | Lin, Z., Ding, P., and Han, F (2023) Estimation based on nearest neighbor matching: from density ratio to average treatment effect self | 0.874 | 6 | 4 | 67% |
| 6 | Lin, Z. and Han, F (2022) On regression-adjusted imputation estimators of the average treatment effect self | 0.843 | 4 | 4 | 75% |
| 7 | Huang, J (2003) Local asymptotics for polynomial spline regression | 0.843 | 3 | 3 | 100% |
| 8 | Newey, W. K (1997) Convergence rates and asymptotic normality for series estimators | 0.843 | 3 | 3 | 100% |
| 9 | Cattaneo, M. D., Crump, R. K., Farrell, M. H., and Feng, Y (2023) On binscatter self | 0.737 | 3 | 2 | 100% |
| 10 | Abadie, A. and Imbens, G. W (2006) Large sample properties of matching estimators for average treatment effects | 0.644 | 2 | 2 | 100% |
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