Adapting Multidimensional Poverty and Inequality Measures to National and Regional Contexts: Evidence from Ethiopia



This study has designed a national MPI framework adapted to the Ethiopian context. Unlike the global MPI, the national MPI framework includes four dimensions (education, health, income, and living condition) with 10 indicators validated for their relevance in explaining the welfare situation in Ethiopia. A sample of 4954 households and 22296 individuals from the LSMS dataset was utilized. The Alkire-Foster methodology was employed to estimate and decompose the welfare measures. To estimate the multidimensional inequality index (MII), and the relative contribution of dimensions, the Araar (2009) method was employed. The results show that, on average, 81.3% of the Ethiopia population are multidimensionally poor and deprived in 46.6% of the total potential deprivations they could experience overall. The incidence of monetary poverty (22.1%) and nonmonetary poverty (70.5%) were significantly different across regions and areas of residence. The relative contributions of welfare dimensions to total MPI were considerable, income being the first (44%), followed by health, education, and living condition. The MII was 22.9% with significant variation across areas of residence. Monetary inequality was 34.4%, which is twofold higher than the nonmonetary inequality. Decomposition of the total MII shows that income is the first source of inequality (with 46.9% contribution); followed by education (23.8%), health (17.4%), and living condition (11.9%). The findings suggest the need to design and implement relevant welfare interventions based on the welfare measures and the relative role of dimensions adapted to the national context. Moreover, this study shows LSMS as one source of dataset with different indicators to estimate national MPIs for 100 countries having LSMS-based surveys.


decomposition, dimensions and indicators, distributive analysis, Ethiopia, MPI, poverty and inequality.

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