Sebastian Calonico, Matias D. Cattaneo, Max H. Farrell, Filippo Palomba, Rocio Titiunik
arXiv 17 Mar 2025 · Econometrics
arXiv:2503.13696 · PDF · DOI · OpenAlex · Extracted main text
Empirical studies using Regression Discontinuity (RD) designs often explore heterogeneous treatment effects based on pretreatment covariates, even though no formal statistical methods exist for such analyses. This has led to the widespread use of ad hoc approaches in applications. Motivated by common empirical practice, we develop a unified, theoretically grounded framework for RD heterogeneity analysis. We show that a fully interacted local linear (in functional parameters) model effectively captures heterogeneity while still being tractable and interpretable in applications. The model structure holds without loss of generality for discrete covariates. Although our proposed model is potentially restrictive for continuous covariates, it naturally aligns with standard empirical practice and offers a causal interpretation for RD applications. We establish principled bandwidth selection and robust bias-corrected inference methods to analyze heterogeneous treatment effects and test group differences. We provide companion software to facilitate implementation of our results. An empirical application illustrates the practical relevance of our methods.
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| 10 | Lindo, J. M., Sanders, N. J., and Oreopoulos, P (2010) Ability, Gender, and Performance Standards: Evidence from Academic Probation | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 18 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | rdhte: Conditional Average Treatment Effects in RD Designs | 1.000 | 13 | 4 |
| 2 | Leveraging Covariates in Regression Discontinuity Designs | 0.511 | 2 | 1 |
| 3 | Boundary Discontinuity Designs: Theory and Practice | 0.405 | 1 | 1 |