EconBase
← All papers

A unified test for regression discontinuity designs

Koki Fusejima, Takuya Ishihara, Masayuki Sawada

arXiv 9 May 2022 · Econometrics · publishedJournal of Econometrics (2025) · 1 citations (OpenAlex)

arXiv:2205.04345 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Diagnostic tests for regression discontinuity design face a size-control problem. We document a massive over-rejection of the diagnostic restriction among empirical studies in the top five economics journals. At least one diagnostic test was rejected for 19 out of 59 studies, whereas less than 5% of the collected 787 tests rejected the null hypotheses. In other words, one-third of the studies rejected at least one of their diagnostic tests, whereas their underlying identifying restrictions appear plausible. Multiple testing causes this problem because the median number of tests per study was as high as 12. Therefore, we offer unified tests to overcome the size-control problem. Our procedure is based on the new joint asymptotic normality of local polynomial mean and density estimates. In simulation studies, our unified tests outperformed the Bonferroni correction. We implement the procedure as an R package rdtest with two empirical examples in its vignettes.

Citation extraction

47
references
117
in-text mentions
47
distinct cited
1
self-citations
24,882
main-text words

appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.

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
1Cattaneo, M. D., M. Jansson, and X. Ma (2020) Simple local polynomial density estimators1.000215100%
2Calonico, S., M. D. Cattaneo, and R. Titiunik (2014) Robust Nonparametric Confidence Intervals for Regression-Discontinuity Designs1.000204100%
3Roth, J (2022) Pretest with caution: Event-study estimates after testing for parallel trends1.00063100%
4McCrary, J (2008) Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test1.00053100%
5Lee, D. S (2008) Randomized Experiments from Non-Random Selection in U.S0.92844100%
6Cattaneo, M. D., N. Idrobo, and R. Titiunik (2019) A Practical Introduction to Regression Discontinuity Designs: Foundations0.87482100%
7Fort, M., A. Ichino, and G. Zanella (2020) Cognitive and Noncognitive Costs of Day Care at Age 0–2 for Children in Advantaged Families0.73732100%
8Calonico, S., M. D. Cattaneo, and M. H. Farrell (2022) Coverage Error Optimal Confidence Intervals for Local Polynomial Regression0.64422100%
9Canay, I. A. and V. Kamat (2018) Approximate Permutation Tests and Induced Order Statistics in the Regression Discontinuity Design0.64422100%
10Lee, D. S. and T. Lemieux (2010) Regression Discontinuity Designs in Economics0.64422100%

Showing the top 10 of 47 scored citations.