A Comparative Analysis of Poverty and Income Inequality Between Bole and Kirkos Sub-Cities in Addis Ababa, Ethiopia
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Date
2024-10
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Addis Ababa University
Abstract
Poverty and income inequality are significant global challenges with wide-ranging implications. These challenges are particularly prevalent in urban areas of Ethiopia. While Ethiopia has made progress in reducing national poverty rates, urban poverty and inequality remain persistent issues in the country, especially in Addis Ababa. These urban challenges are exacerbated by factors like rapid urbanization, limited job opportunities, and the recent conflict. So, making a comparative analysis of poverty and income inequality between sub-cities helps to identify the nature and extent of these issues. This study therefore investigates the comparative analysis of poverty and income inequality between Bole and Kirkos sub-cities. The study’s objectives include measure and compare the poverty status and income inequality levels in these two sub-cities, as well as identify the key factors driving these economic disparities and poverty. The study employed a structured questionnaire to gather primary data. A multistage random sampling strategy was used to select the research sites, with the Bole and Kirkos sub-cities of Addis Ababa being chosen. Within these two sub-cities, 280 household heads were randomly sampled to participate in the survey. This study used both descriptive and econometric analyses. The descriptive analysis revealed stark contrasts in multidimensional poverty and income inequality between the Bole and Kirkos sub-cities. Kirkos exhibited significantly higher poverty, with 66.5% of individuals classified as poor compared to 32.8% in Bole. The poverty incidence (H) was 0.66 in Kirkos versus 0.32 in Bole, and the Multidimensional Poverty Index (MPI) was more than double in Kirkos at 0.39 versus 0.15 in Bole. Income inequality was also more pronounced in Kirkos, with a Gini coefficient of 0.371 compared to 0.345 in Bole. The ordered logistic regression model identifies several key determinants of multidimensional poverty. The education level of the household head is a significant factor, where a 1-year increase in education reduces the probability of higher multidimensional poverty by 65%. Other variables, such as marial status, dependency, saving, and equb edir membership also significantly affect poverty. The quantile regression analysis also identifies key drivers of household income inequality, including education, occupation, family size, and savings behavior. Higher education and private sector jobs are linked to greater incomes, especially at lower and middle quantiles. Larger families and dependency are significantly negatively related to income levels, particularly at the upper end of the distribution. Based on the results, it is recommended the government should target interventions to alleviate the significantly higher multidimensional poverty in Kirkos sub-city. Expanding access to inclusive financial services, like savings and credit, could help build household resilience, as lack of savings is linked to higher poverty. Addressing key drivers of income inequality, such as home ownership, through affordable housing and financing programs, could also reduce inequality.
Keywords: multidimensional poverty, income inequality, ordered logistic regression model, quantile regression model, Bole sub city, Kirkos sub citiy, Addis Ababa.