Impact of social protection on multidimensional poverty in Togo

Abstract

Abstract This article first estimates the multidimensional poverty index using data from the Harmonized Survey of Household Living Conditions, conducted in 2018–2019 in Togo. Then, the paper examines the impact of social protection on multidimensional poverty. To account for selection biases, this paper employs the conditional mixed process, built from the seemingly unrelated regression framework. The findings show significant inequalities in the multidimensional poverty rate depending on the geographical zone, the education of the head of household, age, and the region. In particular, the level of multidimensional poverty is more than five times higher in rural areas than in urban areas. Using a variety of social protection indicators, the results clearly show that social protection significantly and statistically reduces the likelihood of being multi-dimensionally poor. The results also suggest that rural residents and economically disadvantaged regions are statistically and significantly more likely to be poor. There is no statistically significant impact of gender on multidimensional poverty.