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PLRD: Partially Linear Regression Discontinuity Inference

Aditya Ghosh, Guido Imbens, Stefan Wager

arXiv 12 Mar 2025 · Econometrics

arXiv:2503.09907 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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.

Citation extraction

40
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Hahn, J., P. Todd, and W. V. der Klaauw (2001) Identification and estimation of treatment effects with a regression-discontinuity design1.00053100%
2Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust nonparametric confidence intervals for regression-discontinuity designs0.91626677%
3Imbens, G. and K. Kalyanaraman (2012) Optimal bandwidth choice for the regression discontinuity estimator self0.89911573%
4Armstrong, T. B. and M. Kolesár (2018) Optimal inference in a class of regression models0.86620565%
5Athey, S., G. W. Imbens, J. Metzger, and E. Munro (2024) Using wasserstein generative adversarial networks for the design of monte carlo simulations self0.81142100%
6Imbens, G. and S. Wager (2019) Optimized regression discontinuity designs self0.79420550%
7Kolesár, M. and C. Rothe (2018) Inference in regression discontinuity designs with a discrete running variable0.7948450%
8Jacob, B. A. and L. Lefgren (2004) Remedial education and student achievement: A regression-discontinuity analysis0.7639444%
9Matsudaira, J. D (2008) Mandatory summer school and student achievement0.7639444%
10Ludwig, J. and D. L. Miller (2007) Does head start improve children's life chances? evidence from a regression discontinuity design0.7375440%

Showing the top 10 of 40 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Joint Inference for the Regression Discontinuity Effect and Its External Validity0.40511
2Inference in Regression Discontinuity Designs with Clustered Data This version: . We thank Debopam Bhattacharya, Morten Nielsen, Zhuan Pai and numerous seminar and conference participants for helpful comments and suggestions. The second author gratefully acknowledges financial support from the European Research Council ERC through grant SH-1852332. Author contact information: Claudia Noack, Department of Economics, University of Bonn0.40511