.png){kind=icon}
.png){kind=icon}
Return
Targeting with Agents
.png){kind=icon}
PRE
AI
DOI：10.1257/pol.5.1.206.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Targeting assistance to the poor is a central problem in development. We study the problem of designing a proxy means test when the implementing agent is corruptible. Conditioning on more poverty indicators may worsen targeting in this environment because of a novel tradeoff between statistical accuracy and enforceability. We then test necessary conditions for this tradeoff using data on Below Poverty Line card allocation in India. Less eligible households pay larger bribes and are less likely to obtain cards, but widespread rule violations yield a de facto allocation much less progressive than the de jure one. Enforceability appears to matter. (JEL D12, I32, I38, O12, O15)
Keywords:
POVERTY-ALLEVIATION
DECENTRALIZATION
PROGRAM
ACCOUNTABILITY
PERFORMANCE
CORRUPTION
GOVERNANCE
TRANSFERS
DELIVERY
CAPTURE
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
A
IF:
5.7
Papers:
1.4K
Citations:
4.4K
Organization
View more organizations