Practical issues in conducting distributional weighting in benefit‐cost analysis
本文通过多个真实案例进行分配加权，探讨了过程中的方法论问题，并提供了简化步骤，发现分配加权并不比未加权分析更易受假设影响，反驳了其不可行的担忧。
Abstract A commonly expressed concern about distributional weighting in benefit‐cost analysis is that the informational burden is too high and the practical challenges insurmountable. In this paper, we address this concern by conducting distributional weighting on a number of real‐world examples, covering a range of different types of policy impacts. We uncover and explore a number of methodological issues that arise in the process of distributional weighting and provide a simplified set of steps that we believe can be implemented by practitioners with a wide range of expertise. We conduct sensitivity analysis and Monte Carlo simulation to test the robustness of our estimates of weighted net benefits to the various assumptions we make, and find that, in general, distributional weighting is no more vulnerable to modeling assumptions and parameter selection than unweighted benefit‐cost analysis itself. We conclude that the concern about the practicability of distributional weighting is, at least in a range of important cases, unfounded.