Multidimensional Poverty Alleviation: Policy Optimization and Impact Simulation

This paper characterizes several models of state intervention for tackling multidimensional poverty, encompassing alternative scenarios regarding the policymakers’ capacity to allocate resources and tailor those resources for use by households that need them most. The models are applied to pairs of national demographic surveys in five Arab countries (Algeria 2011– 2018, Egypt 2014–2018, Iraq 2011–2018, Mauritania 2011–2015, Tunisia 2011–2018), with the first rounds serving as the baseline and the second rounds serving as the time frame for achieving certain rates of poverty reduction, akin to the challenge presented by the 2030 Agenda. We evaluate the model's policy prescriptions against the observed record of changes in households’ multidimensional deprivations between the two survey rounds, and comment on the prospective policy choices revealed through those achievements. Our optimizations suggest that more cost-effective ways to reduce multidimensional poverty could entail targeting narrower subsets of living conditions. The results suggest that policymakers in Arab middle-income countries should prioritize allocation of more resources to the education sector, while policymakers in low-income countries such as Mauritania should allocate resources to education, housing and access to public services