Application of Ordered Logit Model to Analyze Determinants of Rural Households Multidimensional Poverty in Western Ethiopia (Published)
Rural households’ multidimensional poverty is still widespread and severe everywhere. For instance, worldwide a total of 1.45 billion people from 103 countries are multidimensional poor, most MPI poor people (72%) of them live-in middle-income countries. In East Africa, 559 million (42%) people are multidimensional poor. In Ethiopia, the new global 2018 multidimensional poverty index revealed that 49% of the Ethiopian population is multidimensional poor. A thorough analysis of the nature and determinants of multidimensional poverty is a key input for interventions to curb this horrific enemy of mankind. Thus, the general objective of the current study is an analysis of the status and determinants of rural households’ multidimensional poverty in Jimma Geneti woreda (Ethiopia). A mixed-methods approach is used to achieve the research objective. Primary data are collected from 387 randomly selected rural households using survey questionnaires. In the analysis of the data, both descriptive and inferential statistics are used. The ordered logistic regression model is employed to investigate the determinants of being multidimensional poor. Results of the descriptive analysis show that 80.1% of the sample respondents are multidimensional poor. The intensity of poverty is 66.3% and the adjusted headcount ratio is found 53.1%. Dimensionally, the living standard dimension is the highest contributor to the overall multidimensional poor of the sample households (42.5%) followed by the education dimension (36.7%) and health dimension (20.9%. Among eleven multidimensional poverty index indicators, school attendance indicators (19.9%) and years of schooling indicators (16.8%) have the highest relative contribution to the overall multidimensional poverty index of the study area. The coastal area has contributed a total of 28.1% to the overall 80.1% of the incidence of poverty. Furthermore, results of the regression analysis indicated that kebele dummy, marital status, literacy status, farm size, and membership to cooperatives of households are found significant determinants of households being multidimensional poor. Policy implications that give top priority to living standard, education, and health dimensions respectively, that benefit sample households from the coastal area and that give due consideration to significant variables in poverty reduction efforts required.