A Proxy Means Test for Sri Lanka
This paper intends to inform the effort of the Sri Lankan government to reform the targeting efficacy of its social protection programs, in particular, Samurdhi, which currently distributes benefits based on self-reported income. We develop a Proxy Means Test (PMT) for Sri Lanka based on the Household Income and Expenditure Survey 2016 and evaluate its performance for targeting benefits of Samurdhi. The paper considers a range of models and policy parameters that could be applied depending on data availability and country preferences. The results indicate that switching to a PMT could considerably improve the targeting performance of Samurdhi and would significantly improve the poverty impact of the program. We find that the performance of the proposed PMT model suffers when the coefficients are estimated from samples smaller than 1,000 households. However, we do not find a similar loss of model performance when the model is estimated from seasonal data, provided the sample size is sufficiently large. The model we propose could be applied to the targeting of a variety of safety net programs after validating and refining our model by conducting a pilot survey.
| Main Authors: | , , , , , |
|---|---|
| Format: | Working Paper biblioteca |
| Language: | English |
| Published: |
World Bank, Washington, DC
2018-06
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| Subjects: | PROXY-MEANS TESTING, POVERTY, WELFARE, TARGETING, SURVEY, SAFETY NETS, |
| Online Access: | http://documents.worldbank.org/curated/en/465611529698573713/A-Proxy-Means-Test-for-Sri-Lanka https://hdl.handle.net/10986/30125 |
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| Summary: | This paper intends to inform the effort
of the Sri Lankan government to reform the targeting
efficacy of its social protection programs, in particular,
Samurdhi, which currently distributes benefits based on
self-reported income. We develop a Proxy Means Test (PMT)
for Sri Lanka based on the Household Income and Expenditure
Survey 2016 and evaluate its performance for targeting
benefits of Samurdhi. The paper considers a range of models
and policy parameters that could be applied depending on
data availability and country preferences. The results
indicate that switching to a PMT could considerably improve
the targeting performance of Samurdhi and would
significantly improve the poverty impact of the program. We
find that the performance of the proposed PMT model suffers
when the coefficients are estimated from samples smaller
than 1,000 households. However, we do not find a similar
loss of model performance when the model is estimated from
seasonal data, provided the sample size is sufficiently
large. The model we propose could be applied to the
targeting of a variety of safety net programs after
validating and refining our model by conducting a pilot survey. |
|---|