Alternative targeting methods for social assistance programs: Evidence from Tunisia

Abstract

Social assistance programmes are crucial in alleviating poverty, reducing inequality, and addressing social exclusion. The efficacy of these programmes hinges on the precision and efficiency of their targeting methods. Governments, especially in developing countries, can enhance the impact of social assistance programmes and ensure equitable resource distribution by accurately identifying the right individuals or households. This paper proposes two approaches to targeting beneficiaries of social benefits in Tunisia, including cash transfers and healthcare programmes. The first approach, a Mixed Means Test, extends the Proxy Means Test model by integrating individual/household assessments with explicit geographical targeting methods. The second is a multidimensional targeting strategy that explicitly considers the various deprivations faced by the households. Utilising data from the 2015 National Survey on Household Budget, Consumption, and Standard of Living, our results indicate that the targeting performance of the Mixed Means Test surpasses existing programmes both nationally and regionally, notably minimising inclusion and exclusion errors in the poorest regions of Tunisia. However, the multidimensional targeting approach identifies a higher number of potential beneficiaries compared to the current selection process in Tunisia. Including these households in social programmes may be hindered by limited monetary resources and the country's financial constraints. To address this, the multidimensional targeting approach enables the categorisation of potential beneficiaries into three mutually exclusive and collectively exhaustive groups based on their degree of deprivation.