How to Target Households in Adaptive Social Protection Systems?
Proxy Means Test (PMT) and the Household Economy Analysis (HEA) are widely used methods to target chronically poor households and those suffering from food crises respectively. Using panel data from Niger, this study provides the first empirical evidence on the relative efficiency of these methods in identifying households suffering from permanent or seasonal deprivations. Results show limited overlap between households selected by each method. The PMT performs better in targeting chronically poor households, while HEA performs better in targeting seasonal food insecure households. The study also explores the extent to which these methods can be improved, used and potentially combined to target households as part of ASP systems. Results show that the HEA formula could be further improved to target seasonally food insecure households, including through a regression model estimating food insecurity, and a principal component analysis (PCA) model. Combinations of PMT with methods such as HEA, PCA, or a food insecurity formula may be considered to identify households suffering from chronic poverty and seasonal food insecurity as part of an efficient and scalable ASP system. Harmonizing data collection tools of PMT and HEA users would serve as a crucial building block towards a unified registry and play a key role in improving the efficiency of ASP systems.
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Format: | Working Paper biblioteca |
Language: | English en_US |
Published: |
World Bank, Washington, DC
2016-10
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Subjects: | poverty, cash transfers, proxy means testing, targeting, adaptive social protection, |
Online Access: | http://documents.worldbank.org/curated/en/198291477561475360/How-to-target-households-in-adaptive-social-protection-systems-relative-efficiency-of-proxy-means-test-and-household-economy-analysis-in-Niger https://hdl.handle.net/10986/25387 |
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Summary: | Proxy Means Test (PMT) and the Household
Economy Analysis (HEA) are widely used methods to target
chronically poor households and those suffering from food
crises respectively. Using panel data from Niger, this study
provides the first empirical evidence on the relative
efficiency of these methods in identifying households
suffering from permanent or seasonal deprivations. Results
show limited overlap between households selected by each
method. The PMT performs better in targeting chronically
poor households, while HEA performs better in targeting
seasonal food insecure households. The study also explores
the extent to which these methods can be improved, used and
potentially combined to target households as part of ASP
systems. Results show that the HEA formula could be further
improved to target seasonally food insecure households,
including through a regression model estimating food
insecurity, and a principal component analysis (PCA) model.
Combinations of PMT with methods such as HEA, PCA, or a food
insecurity formula may be considered to identify households
suffering from chronic poverty and seasonal food insecurity
as part of an efficient and scalable ASP system. Harmonizing
data collection tools of PMT and HEA users would serve as a
crucial building block towards a unified registry and play a
key role in improving the efficiency of ASP systems. |
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