Regression discontinuity is a research design used in causal inference to evaluate the impact of an intervention or treatment by comparing outcomes for units just above and just below a cutoff point. This method takes advantage of the natural experiment created by a discontinuity in the assignment of treatment at a predetermined threshold. By comparing outcomes on both sides of the threshold, researchers can estimate the causal effect of the treatment or intervention. Regression discontinuity is commonly used in economics, political science, education, and public policy research.