瞄准移动目标：收入波动时社会项目瞄准工具的评估

中文摘要

低收入和中等收入国家的政策制定者面临的一项关键挑战是，在收入不可观测且波动的情况下，设计一种筛选社会项目受益人的方法。我们使用一个独特的面板数据集，其中包含从哥伦比亚社会登记系统中随机抽取的家庭在2020年经济危机之前、期间和之后的信息，以评估传统的静态代理家计调查（PMT）以及三种具有政策相关性的替代方案。我们考察了在政府社会福利函数具有不同曲率、宏观经济环境不同以及预算和政治约束不同的情况下，瞄准指标和社会福利的表现。相对于静态PMT，更新PMT数据并未改善社会福利。放宽资格门槛减少了排除误差，增加了纳入误差，并提高了社会福利。一种利用冲击数据估计收入可变部分的动态方法减少了排除误差，并限制了覆盖范围的扩大，在经济危机期间提高了社会福利。

Abstract

A key challenge for policymakers in low- and middle-income countries is to design a method to select beneficiaries of social programs when income is unobservable and volatile. We use a unique panel dataset of a random sample of households in Colombia’s social registry that contains information before, during, and after the 2020 economic crisis to evaluate a traditional static proxy-means test (PMT) and three policy-relevant alternatives. We consider targeting metrics and social welfare under different curvatures of governments’ social welfare function, aggregate economic environments, and budgetary and political constraints. Updating the PMT data does not improve social welfare relative to the static PMT. Relaxing the eligibility threshold reduces the exclusion error, increases the inclusion error, and increases social welfare. A dynamic method that uses data on shocks to estimate a variable component of income reduces exclusion errors and limits the expansion in coverage, increasing social welfare during the economic crisis.