Sufficient Statistics for Welfare Analysis: A Bridge Between Structural and Reduced-Form Methods
综述了公共经济学中结合简化形式识别优势和结构模型预测能力的方法，通过估计少量充分统计量来评估政策福利效果，适用于税收、社会保险和行为福利经济学等领域。
The debate between structural and reduced-form approaches has generated substantial controversy in applied economics. This article reviews a recent literature in public economics that combines the advantages of reduced-form strategies—transparent and credible identification—with an important advantage of structural models—the ability to make predictions about counterfactual outcomes and welfare. This literature has developed formulas for the welfare consequences of various policies that are functions of reduced-form elasticities rather than structural primitives. I present a general framework that shows how many policy questions can be answered by estimating a small set of sufficient statistics using program-evaluation methods. I use this framework to synthesize the modern literature on taxation, social insurance, and behavioral welfare economics. Finally, I discuss problems in macroeconomics, labor, development, and industrial organization that could be tackled using the sufficient statistic approach.