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

Goeun Lee () and Myoung-jae Lee

Evaluation Review, 2023, vol. 47, issue 2, 182-208

Abstract: 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 [ − 1 ,  1 ] , 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.

Keywords: regression discontinuity; binary response; local maximum likelihood estimator; extrapolation; control function (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:evarev:v:47:y:2023:i:2:p:182-208

DOI: 10.1177/0193841X221105968

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