脆弱环境下的社会救助瞄准:一项基于社区瞄准的实验
Targeting social assistance in fragile settings: An experiment in community-based targeting
Journal of Development Economics · 2026 · [{"name": "Kibrom A. Abay", "affiliation": ["International Food Policy Research Institute"]}, {"name": "Guush Berhane", "affiliation": ["International Food Policy Research Institute"]}, {"name": "Daniel O. Gilligan", "affiliation": ["International Food Policy Research Institute"]}, {"name": "Kibrom Tafere", "affiliation": ["World Bank"]}, {"name": "Alemayehu Seyoum Taffesse", "affiliation": ["International Food Policy Research Institute"]}]
中文摘要
瞄准是社会与人道主义援助项目设计与实施中一个重要却颇具挑战的过程。以社区领导者作为瞄准代理人的社区型瞄准(CBT)因其本地信息优势而通常更受青睐, 尤其是在数据驱动方法不可行时。然而, 不同的 CBT 方法在不同约束与情境下表现如何仍不清楚。具体而言, 在不同资源约束与自由裁量权下, 社区领导者如何瞄准并分配资源? 我们在埃塞俄比亚 180 个村庄的社区领导者中实施了一项整群随机对照试验, 以评估社区领导者在不同预算约束与自由裁量权下如何瞄准并分配资源。我们发现, 当资源有限时, 社区领导者倾向于通过降低平均转移支付金额来增加受益人数。社区领导者似乎会尽量减少排除错误, 即便代价是纳入错误增加。与此一致, 我们发现, 给予社区领导者一定程度的自由裁量权, 能使他们减少排除错误, 并纳入那些物质匮乏或生活在受冲突影响地区的家庭。最后, 当预算较大且缺乏自由裁量权时, 社区领导者更容易出现偏袒行为。这些发现提供了重要启示, 可为预算压力与削减不断加剧背景下的瞄准工作提供借鉴。
Abstract
Targeting is an important but challenging process in the design and delivery of social and humanitarian assistance programs. Community-based targeting (CBT) that uses community leaders as targeting agents is often preferred for their local information advantages, especially when data-driven methods are not feasible. However, it remains unclear how different CBT approaches fare under different constraints and contexts. Specifically, how do community leaders target and allocate resources under different resource constraints and discretion? We implemented a cluster-randomized controlled trial among community leaders in 180 villages in Ethiopia to evaluate how community leaders target and allocate resources under different budget constraints and discretion. We find that, when resources are limited, community leaders prefer to increase the number of beneficiaries by reducing the average transfer amounts. Community leaders appear to minimize exclusion errors even at the expense of increased inclusion errors. Consistent with this, we find that granting community leaders some level of discretion allows them to reduce exclusion errors and include households that are materially deprived or living in conflict-affected settings. Finally, community leaders are more vulnerable to favoritism when the budget is larger and they lack discretion. These findings offer important lessons that can inform targeting in the context of increasing budget pressures and cuts.
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