Regression Discontinuity design is a quasi-experimental impact evaluation design which attempts to find the causal effects of interventions by assigning a threshold(cut off point) above and below which the treatment is assigned. Observations closely on either side of the threshold are compared to estimate the average treatment effect.
Types of RD
Sharp regression discontinuity designs are designs where the cut off point perfect predicts whether the subject(individual, groups, etc) becomes treatment or control.
Examples from DIME portfolio of sharp RD
A fuzzy RD design is a design where the cutoff point does not completely separate the controls and treatments. Some people who should be in the treatment might not be in treatment and some people who should be in the control group could be in the treatment group.
Examples from DIME portfolio of fuzzy RD
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This article is part of the topic Impact Evaluation Design
- An introduction and user guide to Regression discontinuity. Lee, David S., and Thomas Lemieuxa. "Regression discontinuity designs in economics." Journal of economic literature 48, no. 2 (2010): 281-355.