Yuta Okamoto, Yuuki Ozaki
arXiv 5 Dec 2024 · Econometrics
arXiv:2412.04265 · PDF · DOI · OpenAlex · Extracted main text
We investigate how to learn treatment effects away from the cutoff in multiple-cutoff regression discontinuity designs. Using a microeconomic model, we demonstrate that the parallel-trend type assumption proposed in the literature is justified when cutoff positions are assigned as if randomly and the running variable is non-manipulable (e.g., parental income). However, when the running variable is partially manipulable (e.g., test scores), extrapolations based on that assumption can be biased. As a complementary strategy, we propose a novel partial identification approach based on empirically motivated assumptions. We also develop a uniform inference procedure and provide two empirical illustrations.
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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 | Cattaneo, M. D., Keele, L., Titiunik, R., and Vazquez-Bare, G (2021) Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs | 0.954 | 23 | 6 | 87% |
| 2 | Melguizo, T., Sanchez, F., and Velasco, T (2016) Credit for Low-Income Students and Access to and Academic Performance in Higher Education in Colombia: A Regression Discontinuit… | 0.928 | 4 | 3 | 100% |
| 3 | Calonico, S., Cattaneo, M. D., and Farrell, M. H (2018) On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference | 0.874 | 6 | 3 | 67% |
| 4 | McCrary, J (2008) Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test | 0.874 | 5 | 2 | 100% |
| 5 | Londoño-Vélez, J., Rodríguez, C., and Sánchez, F (2020) Upstream and Downstream Impacts of College Merit-Based Financial Aid for Low-Income Students: Ser Pilo Paga in Colombia | 0.843 | 4 | 3 | 75% |
| 6 | Calonico, S., Cattaneo, M. D., and Titiunik, R (2014) Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs | 0.843 | 5 | 3 | 60% |
| 7 | Dong, Y. and Lewbel, A (2015) Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models | 0.811 | 4 | 2 | 100% |
| 8 | Fudenberg, D. and Levine, D. K (2022) Learning in Games and the Interpretation of Natural Experiments | 0.811 | 4 | 2 | 100% |
| 9 | Hahn, J., Todd, P., and Van der Klaauw, W (2001) Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design | 0.737 | 3 | 2 | 100% |
| 10 | Mammen, E (1993) Bootstrap and Wild Bootstrap for High Dimensional Linear Models | 0.725 | 7 | 2 | 57% |
Showing the top 10 of 55 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Joint Inference for the Regression Discontinuity Effect and Its External Validity | 1.000 | 7 | 3 |