Knowing what works: the case for rigorous program evaluation
IZA, 1999 - 40 pages
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.
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A Formal Statement
Empirical Approaches to the Evaluation Problem
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093 DATE DUE absence of treatment analysis appropriate assessment Bauer bias choice communities comparable control groups costs D. J. Snower decision decision problem E(Yt econometric Empirical employment Ethnic German evaluation approach evaluation of policy evaluation parameter evaluation problem evaluation strategies evidence exact matching example experiment experimental formal frequency distribution genuine impact Germany group-randomized identification assumption identified from observable implementation instance K. F. Zimmermann Labor Economics labor market outcomes labor market situation lmmigrant low-skilled workers medium-skilled workers modern evaluation research Mx=k Mx=o non-experimental observable confounders observational approaches observed outcome outcome measure participants and non-participants participation decision policy interventions policy maker policy measures population average population of participants population parameter post-treatment period pre-intervention program evaluation program impact program participation R. T. Riphahn randomized assignment receiving the intervention relevant remaining uncertainty Rotte sample size training program treatment and control underlying unemployed University of Heidelberg unobservable factors Wage