Sammenlign metoder

	Impact Evaluation Design	Regression Discontinuity in Policy Evaluation
Fagområde	Public Policy	Public Policy
Familie	Process / pipeline	Regression model
Oprindelsesår	2016	1960
Ophavsperson	Development and program-evaluation community; codified by Gertler et al. (World Bank)	Donald Thistlethwaite & Donald Campbell (design); Imbens, Lemieux, Lee (modern practice)
Type	Design framework for causal impact evaluation	Quasi-experimental causal design for threshold-assigned policies
Oprindelig kilde	Gertler, 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: 9781464807794	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.
Aliasser	Impact Evaluation, Causal Impact Evaluation Design, Counterfactual Evaluation Design	Policy RD Design, Threshold-Based Policy Evaluation, Cutoff Rule Evaluation, Eligibility-Threshold Design
Relaterede	3	3
Resumé	Impact 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.