Jun Ma, Yuya Sasaki, Zhengfei Yu
arXiv 24 Sep 2026 · Econometrics
arXiv:2609.29249 · PDF · Extracted main text
It is standard practice to include covariates in regression discontinuity designs (RDDs) and regression kink designs (RKDs), but the theoretical justification for doing so does not generally extend beyond linear estimands. This paper proposes a novel entropy balancing reweighting approach for covariate adjustment within a general framework of RDDs and RKDs. While conventional regression-based covariate adjustment methods generally fail to deliver consistent estimation for nonlinear estimands such as quantile treatment effects, our reweighting approach achieves consistency while improving efficiency. Moreover, even in settings where the regression-based covariate adjustment method already improves efficiency, our approach can deliver additional efficiency gains. Simulation studies corroborate these theoretical findings. We present an empirical application in which our covariate adjustment yields statistically significant results that would not be obtained without covariate adjustment.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
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 | van der Vaart, A. W (1998) Asymptotic Statistics | 1.000 | 10 | 5 | 100% |
| 2 | Qu, Zhongjun and Yoon, Jungmo (2019) Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs | 1.000 | 10 | 3 | 100% |
| 3 | Dong, Yingying and Lewbel, Arthur (2015) Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models | 0.928 | 4 | 3 | 100% |
| 4 | Chen, Xiaohui and Kato, Kengo (2020) Jackknife Multiplier Bootstrap: Finite Sample Approximations to the U-Process Supremum with Applications | 0.874 | 9 | 2 | 100% |
| 5 | Chernozhukov, Victor and Chetverikov, Denis and Kato, Kengo (2014) Gaussian Approximation of Suprema of Empirical Processes | 0.874 | 9 | 2 | 100% |
| 6 | Card, David and Lee, David S. and Pei, Zhuan and Weber, Andrea (2015) Inference on Causal Effects in a Generalized Regression Kink Design | 0.874 | 5 | 2 | 100% |
| 7 | Hainmueller, Jens (2012) Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies | 0.874 | 5 | 2 | 100% |
| 8 | Hahn, Jinyong and Todd, Petra and Van der Klaauw, Wilbert (2001) Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design | 0.843 | 3 | 3 | 100% |
| 9 | van der Vaart, A. W. and Wellner, Jon A (1996) Weak Convergence and Empirical Processes: With Applications to Statistics | 0.811 | 4 | 2 | 100% |
| 10 | Cattaneo, Matias D. and Idrobo, Nicolás and Titiunik, Rocío (2019) A Practical Introduction to Regression Discontinuity Designs: Foundations | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 41 scored citations.