College of Business and Economics

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    DETERMINANT OF INCOME SOURCE DIVERSIFICATION AND ITS CONTRIBUTION TO LIVELIHOOD IN THE CASE OF ABIY-ADDI TOWN.
    (Mekelle University, 2025-11-25) Berihu Knfe Mekenen
    This study, titled “Determinants of Income Source Diversification and Its Contribution to the Livelihoods of Urban Households: The Case of Abiy-Addi Town,” examines the socioeconomic and institutional factors influencing income diversification among urban households and evaluates its contribution to livelihood enhancement. Conducted in Abiy-Addi Town, Central Zone of Tigray, Ethiopia, the research employed a cross-sectional design integrating quantitative and qualitative approaches. Data were collected from 376 randomly selected households through structured questionnaires and direct observations, supplemented by secondary information from reports and literature. Descriptive results indicated that the average household head was 46.9 years old, with a mean family size of 5.47 and an average education level of 2.7 years of schooling, reflecting low human capital. Approximately 72.6% of households participated in non-farm or off-farm income-generating activities, mainly in trade, construction, and services. However, only 48.7% had access to credit, with high interest rates and lack of collateral serving as major obstacles to diversification. The Poisson regression model identified key determinants of income diversification, revealing that education level, family size, access to credit, extension services, and training significantly and positively affected the degree of diversification. A one-year increase in education raised the likelihood of engaging in additional income-generating activities by 0.31, while access to credit increased diversification probability by 0.42. Conversely, older and female-headed households were less likely to diversify due to limited resources and cultural constraints. The model diagnostics confirmed the absence of overdispersion, validating the model’s specification. To estimate the welfare impact of diversification, Propensity Score Matching (PSM) was applied using covariates such as age, education, credit access, and training. The estimated Average Treatment Effect on the Treated (ATT) showed that diversified households earned significantly higher incomes (54,046 Birr) compared to non-diversified ones (23,649 Birr), implying that diversification nearly doubled annual income levels. Diversified households were also more food secure and less vulnerable to income shocks. These findings are consistent with Ellis (2000), Woldehanna (2000), and Fikru (2008), who underscored non-farm diversification as a key strategy for reducing poverty and improving household welfare in Ethiopia and Sub-Saharan Africa. Institutional and infrastructural challenges— including high loan interest rates, limited working premises, inadequate training centers, and poor market linkages—were found to constrain diversification. Strengthening microfinance systems, improving urban infrastructure, and expanding vocational training are therefore essential policy measures. In conclusion, the study confirms that income source diversification substantially contributes to improving urban household livelihoods in AbiyAddi Town. Promoting non-farm sectors such as small-scale manufacturing, agro-processing, and construction enhance income stability, economic resilience, and urban employment opportunities. Integrating these strategies into local development policies is crucial for achieving sustainable urban growth and poverty reduction.