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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.

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Sources

  1. 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
  2. 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
  3. 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

How to cite this page

ScholarGate. (2026, June 22). Regression Discontinuity Design for Policy Evaluation. ScholarGate. https://scholargate.app/en/public-policy/regression-discontinuity-policy

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ScholarGateRegression Discontinuity in Policy Evaluation (Regression Discontinuity Design for Policy Evaluation). Retrieved 2026-06-24 from https://scholargate.app/en/public-policy/regression-discontinuity-policy · Dataset: https://doi.org/10.5281/zenodo.20539026