Social Protection Cash Transfers and Gendered Equality: An Analysis of Gendered Differences in Poverty Reduction and Income Distribution

This research investigates key determinants of poverty reduction and income distribution in eastern Uganda's Teso sub-region. Regression analysis reveals significant negative coefficients for access to healthcare (β = -0.414, p = 0.029) and road infrastructure (β = -0.363, p = 0.014), indicating lower poverty levels in communities with better access. Employment (β = -2.8, p = 0.000) and income (β = 3.3, p = 0.000) also show substantial negative coefficients, underscoring their role in reducing poverty and improving income distribution. While location and education lack statistical significance, the overall regression model exhibits strong explanatory power (R-squared = 0.635), with the F-test confirming significance (F(11, 404) = 53.844, p = 0.000), indicating predictive capability for poverty levels and income distribution. These findings inform actionable strategies for policymakers and practitioners aiming to bolster social protection and gendered equality in the Teso sub-region and similar areas. Prioritizing investments in healthcare, infrastructure, employment, and income-generating initiatives can address poverty and inequality challenges, fostering inclusive development. Employing the Difference-in-Differences (DID) model alongside qualitative insights provides a comprehensive understanding of social protection cash transfers (SPCTs) and socioeconomic influences on poverty vulnerability. While gender emerges as a significant predictor, other factors like dwelling type, access to water, education, health facilities, and income do not notably affect poverty outcomes. Triangulating quantitative and qualitative data enriched the discussions on poverty reduction at the household and community level as well as guided tailored interventions, navigating the complex interplay of socio-economic factors and gendered dynamics.