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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. The paper develops a proxy means test for Sri Lanka based on the Household Income and Expenditure Survey 2016 and evaluates 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 proxy means test could considerably improve the targeting performance of Samurdhi and would significantly improve the poverty impact of the program. The analysis finds that the performance of the proposed proxy means test model suffers when the coefficients are estimated from samples smaller than 1,000 households. However, the analysis does not find a similar loss of model performance when the model is estimated from seasonal data, provided the sample size is sufficiently large. The proposed model could be applied to targeting a variety of safety net programs after validating and refining the model by conducting a pilot survey.

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.

This paper is an application of multidimensional poverty data to the policy need to improve the effectiveness of the national social protection programme, Samurdhi, in Sri Lanka. This paper argues that any programme aiming to promote people out of poverty, needs to be based on a good understanding of the nature of poverty among the target group. To this end, data from a pilot survey in the Badulla District, Sri Lanka, is used to compare Samurdhi households with non Samurdhi households in relation to deprivation in multiple dimensions. The analysis finds that Samurdhi households are deprived in the dimensions of quality of employment, dignity and psychological and subjective wellbeing, which have practical implications for the design and delivery of Samurdhi.