Regression Discontinuity with Multiple Running Variables Allowing Partial Effects

Jin Young Choi, Myoung Jae Lee

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


In regression discontinuity (RD), a running variable (or score) crossing a cutoff determines a treatment that affects the mean-regression function. This paper generalizes this usual one-score mean RD in three ways: (i) considering multiple scores, (ii) allowing partial effects due to each score crossing its own cutoff, not just the full effect with all scores crossing all cutoffs, and (iii) accommodating quantile/mode regressions. This generalization is motivated by (i) many multiple-score RD cases, (ii) the full-effect identification needing the partial effects to be separated, and (iii) informative quantile/mode regression functions. We establish identification for multiple-score RD (MRD), and propose simple estimators that become local difference in differences in case of double scores. We also provide an empirical illustration where partial effects exist.

Original languageEnglish
Pages (from-to)258-274
Number of pages17
JournalPolitical Analysis
Issue number3
Publication statusPublished - 2018 Jul 1

Bibliographical note

Publisher Copyright:
Copyright © The Author(s) 2018. Published by Cambridge University Press on behalf of the Society for Political Methodology.Â.


  • difference in differences
  • multiple running variables
  • partial effect
  • regression discontinuity

ASJC Scopus subject areas

  • Sociology and Political Science
  • Political Science and International Relations


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