Regression Discontinuity in Policy Evaluation
Regression discontinuity (RD) is a quasi-experimental design for estimating the causal effect of a policy that is assigned by a sharp threshold on some continuous eligibility score — an income line for a benefit, a test score for a scholarship, a vote share for winning office, a population cutoff that triggers a regulation. Units falling just below and just above the cutoff are nearly identical except for their treatment status, so comparing their outcomes isolates the policy's effect at the threshold. First used by Thistlethwaite and Campbell in 1960 and revived as a workhorse of policy evaluation by economists in the 2000s, RD is widely regarded as the quasi-experimental design with the strongest claim to internal validity.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Thistlethwaite, D. L., & Campbell, D. T. (1960). Regression-discontinuity analysis: An alternative to the ex post facto experiment. Journal of Educational Psychology, 51(6), 309–317. · DOI 10.1037/h0044319
- Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615–635. · DOI 10.1016/j.jeconom.2007.05.001
- Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281–355. · DOI 10.1257/jel.48.2.281
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.