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Impact Evaluation Design×Regression Discontinuity in Policy Evaluation×
ОбластPublic PolicyPublic Policy
СемействоProcess / pipelineRegression model
Година на възникване20161960
СъздателDevelopment and program-evaluation community; codified by Gertler et al. (World Bank)Donald Thistlethwaite & Donald Campbell (design); Imbens, Lemieux, Lee (modern practice)
ТипDesign framework for causal impact evaluationQuasi-experimental causal design for threshold-assigned policies
Основополагащ източникGertler, P. J., Martinez, S., Premand, P., Rawlings, L. B., & Vermeersch, C. M. J. (2016). Impact Evaluation in Practice (2nd ed.). Washington, DC: World Bank. ISBN: 9781464807794Thistlethwaite, 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 ↗
Други названияImpact Evaluation, Causal Impact Evaluation Design, Counterfactual Evaluation DesignPolicy RD Design, Threshold-Based Policy Evaluation, Cutoff Rule Evaluation, Eligibility-Threshold Design
Свързани33
РезюмеImpact evaluation design is the upstream task of structuring an evaluation so that it can credibly attribute changes in outcomes to a policy or program rather than to other factors. Its defining concern is the counterfactual: what would have happened to participants in the absence of the intervention. Codified in resources such as the World Bank's Impact Evaluation in Practice, the design process selects an identification strategy — randomised assignment, or a quasi-experimental method such as difference-in-differences, regression discontinuity, instrumental variables or matching — that constructs a valid comparison and yields an unbiased estimate of the intervention's effect.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.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: Impact Evaluation Design · Regression Discontinuity in Policy Evaluation. Извлечено на 2026-06-25 от https://scholargate.app/bg/compare