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

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  • Goeun Lee
  • Myoung-jae Lee

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.

Suggested Citation

  • Goeun Lee & Myoung-jae Lee, 2023. "Regression Discontinuity for Binary Response and Local Maximum Likelihood Estimator to Extrapolate Treatment," Evaluation Review, , vol. 47(2), pages 182-208, April.
    • Handle: RePEc:sae:evarev:v:47:y:2023:i:2:p:182-208
    DOI: 10.1177/0193841X221105968
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    References listed on IDEAS

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