Determinants of Rural-Out Migration in Makete District, Njombe Region, Tanzania: A Logit Regression Model Approach

Abstract; Purpose: This study investigates the determinants of rural-out migration in Makete District, Njombe Region, Tanzania, using a binary logit regression model. The objective was to identify socio-economic, environmental, and institutional factors influencing household migration decisions. Makete was selected due to its high migration rates and agro-ecological vulnerability. Methodology: A total of 450 households were surveyed across 15 villages, selected through multi-stage sampling stratified by agro-ecological zones (highland, midland, lowland), with households chosen randomly and systematically. Complementary qualitative data were collected via 25 key informant interviews and six gender-segregated focus group discussions. The dependent variable was household migration status (1 = migrant, 0 = non-migrant), while independent variables included education, landholding size, income, infrastructure access, and exposure to climate shocks. Results from STATA 18 indicate that education (OR = 1.289, p < 0.001), land size (OR = 0.430, p < 0.05), infrastructure access (OR = 0.537, p < 0.001), and climate shocks (OR = 4.067, p < 0.001) significantly affect migration likelihood. Income and age were marginally significant, while household size and gender were not. Findings: The findings suggest that rural-out migration in Makete is largely driven by structural factors, especially land scarcity and environmental stress, rather than purely demographic characteristics. Migration emerges as a proactive household adaptation strategy to economic and climatic uncertainties. Policy Implications: Policy recommendations include integrating migration dynamics into Tanzania’s rural development frameworks, such as the Five-Year Development Plan III and SAGCOT. Practical Implications: Strengthening rural infrastructure, land tenure, and climate resilience, while leveraging remittances and skills transfer, is essential for sustainable rural transformation.