Policy Evaluation in Uncertain Economic Environments
提出基于决策理论的政策分析方法，强调政策评估应依据决策者偏好和给定政策下结果的条件分布，并主张用模型平均法处理模型不确定性，以货币政策和增长政策为例说明。
This paper develops a decision-theoretic approach to policy analysis. We argue that policy evaluation should be conducted on the basis of two factors: the policymaker's preferences, and the conditional distribution of the outcomes of interest given a policy and available information. From this perspective, the common practice of conditioning on a particular model is often inappropriate, since model uncertainty is an important element of policy evaluation. We advocate the use of model averaging to account for model uncertainty and show how it may be applied to policy evaluation exercises. We illustrate our approach with applications to monetary policy and to growth policy.