Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment

Goeun Lee, Myoung Jae Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Regression discontinuity is popular in finding treatment/policy effects when the treatment is determined by a continuous variable crossing a cutoff. Typically, a local linear regression (LLR) estimator is used to find the effects. For binary response, however, LLR is not suitable in extrapolating the treatment, as in doubling/tripling the treatment dose/intensity. The reason is that doubling/tripling the LLR estimate can give a number out of the bound (Formula presented.), despite that the effect should be a change in probability. We propose local maximum likelihood estimators which overcome these shortcomings, while giving almost the same estimates as the LLR estimator does for the original treatment. A simulation study and an empirical analysis for effects of an income subsidy program on religion demonstrate these points.

Original languageEnglish
Pages (from-to)182-208
Number of pages27
JournalEvaluation Review
Issue number2
Publication statusPublished - 2023 Apr

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research of Myoung-jae Lee has been supported by a Korea University research grant.

Publisher Copyright:
© The Author(s) 2022.


  • binary response
  • control function
  • extrapolation
  • local maximum likelihood estimator
  • regression discontinuity

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • General Social Sciences


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