Publication: Belarus - Social Assistance Policy Note : Improving Targeting Accuracy of Social Assistance Programs
Belarus has a large and extensive social protection system (SP) covering a significant share of the population. Belarus has adopted a single methodology for calculating income to target Public Targeted Social Assistance (GASP). This methodology also is used when testing an applicant's income/means for some of the child benefits. To reduce the leakage of benefits to the non-poor while expanding GASP, this note assesses the usefulness of applying a Hybrid-Means-Test method (HMT), a variation of the means-testing method that combines means testing and proxy-means testing. All outcomes in this note have been estimated on the basis of the 2008 Belarusian Household Budget Survey (2008 HBS). The HMT model improves estimates of 'means' by generating a predicted value for hard-to-verify incomes, which are then added to the observed (reported) values of easy-to-verify incomes. In this way, the HMT model can improve predictions of per capita households (HH) income. The note is divided in six sections. In section one, the authors present an overview of the current social safety net (SSN) programs in Belarus, their design features, number of beneficiaries, and eligibility criteria to draw the overall picture of the types of programs delivered in Belarus and the magnitude of their public spending. Section two reviews the targeting accuracy of existent SP programs in Belarus. Section three analyzes whether HMT can be an option for targeting in Belarus. Section four presents the HMT formulae. In section five the authors describe how HMT also can be used for client profiling of beneficiaries. In section six, the authors conclude by discussing the results of some simulations about the targeting accuracy of the HMT method.
“World Bank. 2011. Belarus - Social Assistance Policy Note : Improving Targeting Accuracy of Social Assistance Programs. © Washington, DC. http://openknowledge.worldbank.org/entities/publication/95207a31-db1a-5734-9ee3-c7665f95aabd License: CC BY 3.0 IGO.”