A poor means test? Econometric targeting in Africa
A poor means test? Econometric targeting in Africa
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DOI：
10.1016/j.jdeveco.2018.05.004
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发表时间：
2018-09-01
影响因子：
5
通讯作者：
van de Walle, Dominique
中科院分区：
文献类型：
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作者：
Brown, Caitlin;Ravallion, Martin;van de Walle, Dominique
代理均值测试（PMT）在信息不完善的贫困目标定位中很流行。在广泛使用的版本中，对数消耗回归根据协变量校准 PMT 分数，然后将其用于针对样本外。使用九个非洲国家的数据评估了各种 PMT 方法的性能。标准的PMT有助于过滤掉非贫困人口，但排除了许多贫困人口，从而减少了对贫困的影响。以贫困为重点的计量经济学方法（例如使用分位数回归）通常效果更好。我们还描述了贫困目标的最佳信息可行解决方案，并将其与计量经济学方法进行比较。即使有足够的预算来消除贫困并提供充分的信息，所研究的目标确定方法都没有使贫困率低于其初始值的四分之三左右。现行方法在惠及最贫困人口方面尤其不足。使用简单的人口计分卡的基本收入计划或转移支付通常在减少贫困方面也能起到同样的作用，甚至更好。
Proxy-means tests (PMTs) are popular for poverty-targeting with imperfect information. In a widely-used version, a regression for log consumption calibrates a PMT score based on covariates, which is then implemented for targeting out-of-sample. The performance of various PMT methods is assessed using data for nine African countries. Standard PMTs help filter out the non-poor, but exclude many poor people, thus diminishing the impact on poverty. Poverty-focused econometric methods such as using quantile regression generally do better. We also characterize the optimal informationally-feasible solution for poverty targeting and compare it to econometric methods. Even with a budget sufficient to eliminate poverty with full information, none of the targeting methods studied bring the poverty rate below about three-quarters of its initial value. The prevailing methods are particularly deficient in reaching the poorest. A basic-income scheme or transfers using a simple demographic scorecard often do as well, or even better, in reducing poverty.