牙买加针对福利的代理经济状况调查

IF 1.4 3区 经济学 Q2 DEVELOPMENT STUDIES Development Policy Review Pub Date : 2025-01-23 DOI:10.1111/dpr.12828
Garfield O. Blake, Godfrey Gibbison
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引用次数: 0

摘要

在包括牙买加在内的许多低收入和中低收入国家,代理经济状况调查(PMT)已成为社会援助计划的主要目标机制。它有许多强有力的支持者,声称它可以准确地、经济有效地针对穷人。然而,最近,受益群体、政府利益攸关方和民间社会对根据牙买加通过保健和教育促进发展方案选择受益家庭表示关切。对适宜卫生技术方案的评价表明,该方案仅覆盖最贫穷五分之一的约71%的家庭,而23%的方案受益人来自被认为不贫穷的家庭(排在前两个五分之一)。本研究对目前的PMT模式进行了创新,目的是提高穷人获得社会保护福利的针对性。方法和方法我们利用牙买加统计研究所(STATIN)收集的关于适宜卫生技术方案的数据来表明,贫困加权最小二乘回归估计方法的应用提高了最贫困五分之一家庭的覆盖率。贫困加权最小二乘法对贫困家庭的平方误差赋予了更高的权重,从而避免了最小二乘法回归增加贫困家庭预测消费的倾向。利用国家统计局通过年度牙买加生活条件调查汇编的数据,我们发现,使用贫困加权最小二乘估算的国家模型的构建,并将预测消费调整到95%置信区间的下限,将最贫困家庭的覆盖率从71%提高到85%以上。在穷人中实现这种高覆盖率是有代价的,其形式是非穷人的高覆盖率,特别是包括错误的增加。我们认为,这些结果表明,在某些情况下,有可能改进基本的PMT模型,实现PMT旨在实现的目标,有效地向穷人提供社会援助,最大限度地减少对非穷人的泄漏,并保持整个社会援助机制的完整性。
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Proxy means test for targeting welfare benefits in Jamaica

Motivation

The proxy means test (PMT) has become the predominant targeting mechanism for social assistance schemes in many low- and lower-middle income countries, including Jamaica. It has many powerful advocates amid claims that it can accurately and cost-effectively target the poor. However, recently, there have been concerns expressed by beneficiary groups, government stakeholders, and civil society on the selection of households for benefits under Jamaica's Programme of Advancement Through Health and Education (PATH).

Purpose

An evaluation of PATH suggests that it covers only about 71% of households ranked in the poorest quintiles, while 23% of programme beneficiaries are from households considered to be non-poor (ranked in the top two quintiles). This study introduces innovations to the current PMT model with the objective of improving targeting of the poor for social protection benefits.

Approach and methods

We draw on data collected by the Statistical Institute of Jamaica (STATIN) regarding the PATH programme to show that an application of the poverty-weighted least squares regression estimation method improves coverage of households ranked in the poorest quintiles. Poverty-weighted least squares places higher weights on the squared errors of poor households, which avoids the tendency of least squares regression to increase the predicted consumption of the poor.

Findings

Using data compiled by the STATIN through the annual Jamaica Survey of Living Conditions, we showed that the construction of a national model estimated using poverty-weighted least squares, and adjusting predicted consumption to the lower limit of the 95% confidence interval, improves coverage of the poorest households from 71% to over 85%. Achieving this high rate of coverage among the poor came at a cost, in the form of high coverage among the non-poor and, particularly, an increase in inclusion errors.

Policy implications

We believe these results demonstrate that in certain contexts it is possible to improve upon the Basic PMT model and meet the goals the PMT was intended to achieve, efficiently directing social assistance to the poor, minimizing leakage to the non-poor, and maintaining integrity in the overall social assistance mechanism.

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来源期刊
Development Policy Review
Development Policy Review DEVELOPMENT STUDIES-
CiteScore
3.50
自引率
5.90%
发文量
87
期刊介绍: Development Policy Review is the refereed journal that makes the crucial links between research and policy in international development. Edited by staff of the Overseas Development Institute, the London-based think-tank on international development and humanitarian issues, it publishes single articles and theme issues on topics at the forefront of current development policy debate. Coverage includes the latest thinking and research on poverty-reduction strategies, inequality and social exclusion, property rights and sustainable livelihoods, globalisation in trade and finance, and the reform of global governance. Informed, rigorous, multi-disciplinary and up-to-the-minute, DPR is an indispensable tool for development researchers and practitioners alike.
期刊最新文献
Issue Information Impact measurement and management as governance infrastructure in development finance: Catalytic or extractive?
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