Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment. (April 2023)

• Record Type: Journal Article
• Authors: Lee, Goeun; Lee, Myoung-jae
• Is Part Of: Evaluation review. Volume 47:Number 2(2023)
• Page Start: 182
• Page End: 208
• Publication Date: 2023-04
• Subjects: regression discontinuity -- binary response -- local maximum likelihood estimator -- extrapolation -- control function; Evaluation research (Social action programs) -- Periodicals; 361.0072
• DOI: 10.1177/0193841X221105968
• Languages: English
• ISSNs: 0193-841X

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.