Multidimensional Poverty and its Determinants in Somalia: A Household Level Analysis
DOI:
https://doi.org/10.47941/ijdcs.2108Keywords:
Multidimensional Poverty, Determinants, Somalia, Alkire & Foster, Ordered Logistic, RegressionAbstract
Purpose: Poverty is widespread and problematic in least developed countries such as Somalia. The main objective of this study is to analyze the extent and determinants of multidimensional poverty in Somalia.
Methodology: To achieve this objective, this study used the Somali Health and Demographic Survey carried out by the Somali National Statistics Bureau in 2020. Alkire and Foster’s methodology was used to measure the extent of multidimensional poverty, and an ordered logistic regression model was employed to identify its determinants at the household level.
Findings: The results of the descriptive analysis show that 84.2 percent of the sampled households are multidimensionally poor, while the intensity of poverty and adjusted headcount ratio were 56.8 percent, and 0.479 respectively. Meanwhile, the study found that the living standard dimension was the major contributor (45 percent) to the overall multidimensional poverty index, followed by education and health dimensions, contributing 28.2 percent, and 26.8 percent, respectively. The ordered logit results indicate that household size significantly increases the likelihood of a household’s status being multidimensionally poor. In contrast, household education, employment of at least one household member, livestock ownership, ownership of agricultural land, and having a bank account significantly reduce the probability of being multidimensionally poor.
Unique Contribution to Theory, Practice and Policy: Based on these findings, the study recommends that the government and international partners target the living standards dimension to reduce multidimensional poverty, improve quality and quantity of education, expand employment opportunities, promote financial inclusion, and foster the livelihoods of households involved in agriculture and livestock.
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