Knowing What Works: The Case for Rigorous Program Evaluation

41 Pages Posted: 16 Aug 2000

See all articles by Christoph M. Schmidt

Christoph M. Schmidt

RWI - Leibniz-Insitut für Wirtschaftsforschung (RWI Essen); Ruhr-Universität Bochum (RUB); Institute for the Study of Labor (IZA); Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: December 1999


Since interventions by the public sector generally commit substantial societal resources, the evaluation of effects and costs of policy interventions is imperative. This paper outlines why program evaluation should follow well-respected scientific standards and why it should be performed by independent researchers. Moreover, it outlines the three fundamental elements of evaluation research, the choice of the appropriate outcome measure, the assessment of the direct and indirect cost associated with the intervention, and the attribution of effects to underlying causes. The paper proceeds to outline in intuitive terms that the construction of a credible counterfactual situation is at the heart of the formal statistical evaluation problem. It introduces several approaches, based on both experiments and on non-experimental data, that have been proposed in the literature to solve the evaluation problem, and illustrates them numerically.

JEL Classification: H43, C40, C90

Suggested Citation

Schmidt, Christoph M., Knowing What Works: The Case for Rigorous Program Evaluation (December 1999). Available at SSRN: or

Christoph M. Schmidt (Contact Author)

RWI - Leibniz-Insitut für Wirtschaftsforschung (RWI Essen) ( email )

Hohenzollernstraße 1-3
Essen, 45128
++49 201 8149-227 (Phone)
++49 201 8149-236 (Fax)

Ruhr-Universität Bochum (RUB)

GC 2/150
Universitätsstr. 150
D-44780 Bochum

Institute for the Study of Labor (IZA)

P.O. Box 7240
Bonn, D-53072

Centre for Economic Policy Research (CEPR)

United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
PlumX Metrics