Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper develops a general framework for economic policy evaluation. Using ideas from statistical decision theory, it argues that conventional approaches fail to appropriately integrate econometric analysis into evaluation problems. Further, it is argued that evaluation of alternative policies should explicitly account for uncertainty about the appropriate model of the economy. The paper shows how to develop an explicitly decision-theoretic approach to policy evaluation and how to incorporate model uncertainty into such an analysis. The theoretical implications of model uncertainty are explored in a set of examples, with a specific focus on how to design policies that are robust against such uncertainty. Finally, the framework is applied to the evaluation of monetary policy rules and to the analysis of tariff reductions as a way to increase aggregate economic growth.