Assessing the Frontiers of Ultrapoverty Reduction: Evidence from Challenging the Frontiers of Poverty Reduction/Targeting the Ultra-poor, an Innovative Program in Bangladesh
Assessing the Frontiers of Ultrapoverty Reduction: Evidence from Challenging the Frontiers of Poverty Reduction/Targeting the Ultra-poor, an Innovative Program in Bangladesh
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评估消除极端贫困的前沿：挑战消除贫困前沿/瞄准极端贫困人口的证据，这是孟加拉国的一项创新计划
DOI：
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发表时间：
2014
影响因子：
2
通讯作者：
Arif Al Mamun
中科院分区：
文献类型：
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作者：
A. M. Mobarak;Arif Al Mamun
本文使用家庭面板数据提供了强有力的证据，对孟加拉国的BRAC（建设资源跨越国家）针对极端贫困（TUP）计划的影响。我们使用替代治疗比较对;除了BRAC自己的分类，我们利用BRAC选择过程中分配的1型错误来创建第二个治疗比较对。这使我们能够估计计划对目标群体的影响，而不是受到错误的影响。为了解决不可观测的选择，我们实现了基于异方差的识别和两个最近的估计匹配和倾向得分重新加权的基础上。结果表明，参与对粮食安全、衣服、鞋子、牲畜和现金储蓄产生了显著的积极影响，但对家庭耐用品和资产数量以及健康和妇女赋权指标的影响很弱或没有证据。对穷人中最穷的人（目标群体）的影响可能不同于对TUP方案的普通参与者的影响。当考虑到初始条件的差异时，TUP方案对穷人中最穷的人的影响要大得多（以结果的初始平均值标准化的方案效果来衡量），这表明TUP方案如果有更好的针对性，会产生更大的影响。
This article uses household panel data to provide robust evidence on the effects of BRAC’s (Building Resources across Countries) Targeting the Ultra-poor (TUP) program in Bangladesh. We use alternative treatment-comparison pairs; in addition to BRAC’s own classification, we exploit type 1 errors in assignment in BRAC’s selection process to create a second treatment-comparison pair. This allows us to estimate the program effects on the target group, not contaminated by mistargeting. To address selection on unobservables, we implement heteroskedasticity-based identification and two recent estimators based on matching and propensity score reweighting. The results show that participation had significant positive effects on food security, clothing, shoes, livestock, and cash savings, but there is weak or no evidence of an impact on the number of household durables and assets and indicators of health and women’s empowerment. The effects on the poorest of the poor (the target group) may be different from the effects on an average participant in the TUP program. When one takes into account the differences in initial conditions, the effects of the TUP program on the poorest of the poor are much larger (as measured by the program effect normalized by the initial mean value of an outcome), which suggests that the TUP program would have had a larger impact with better targeting.