Aditya Ghosh, Guido Imbens, Stefan Wager
arXiv 12 Mar 2025 · Econometrics
arXiv:2503.09907 · PDF · DOI · OpenAlex · Extracted main text
Regression discontinuity designs have become one of the most popular research designs in empirical economics. We argue, however, that widely used approaches to building confidence intervals in regression discontinuity designs exhibit suboptimal behavior in practice: In a simulation study calibrated to high-profile applications of regression discontinuity designs, existing methods either have systematic under-coverage or have wider-than-necessary intervals. We propose a new approach, partially linear regression discontinuity inference (PLRD), and find it to address shortcomings of existing methods: Throughout our experiments, confidence intervals built using PLRD are both valid and short. We also provide large-sample guarantees for PLRD under smoothness assumptions.
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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, J., P. Todd, and W. V. der Klaauw (2001) Identification and estimation of treatment effects with a regression-discontinuity design | 1.000 | 5 | 3 | 100% |
| 2 | Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust nonparametric confidence intervals for regression-discontinuity designs | 0.916 | 26 | 6 | 77% |
| 3 | Imbens, G. and K. Kalyanaraman (2012) Optimal bandwidth choice for the regression discontinuity estimator self | 0.899 | 11 | 5 | 73% |
| 4 | Armstrong, T. B. and M. Kolesár (2018) Optimal inference in a class of regression models | 0.866 | 20 | 5 | 65% |
| 5 | Athey, S., G. W. Imbens, J. Metzger, and E. Munro (2024) Using wasserstein generative adversarial networks for the design of monte carlo simulations self | 0.811 | 4 | 2 | 100% |
| 6 | Imbens, G. and S. Wager (2019) Optimized regression discontinuity designs self | 0.794 | 20 | 5 | 50% |
| 7 | Kolesár, M. and C. Rothe (2018) Inference in regression discontinuity designs with a discrete running variable | 0.794 | 8 | 4 | 50% |
| 8 | Jacob, B. A. and L. Lefgren (2004) Remedial education and student achievement: A regression-discontinuity analysis | 0.763 | 9 | 4 | 44% |
| 9 | Matsudaira, J. D (2008) Mandatory summer school and student achievement | 0.763 | 9 | 4 | 44% |
| 10 | Ludwig, J. and D. L. Miller (2007) Does head start improve children's life chances? evidence from a regression discontinuity design | 0.737 | 5 | 4 | 40% |
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