Determinants of livelihood diversification among rural forest-dependent households in Mt. Elgon region, Western Kenya

Purpose Rural people seek diverse opportunities to increase and stabilize their welfare. Understanding the factors influencing livelihood strategies can help improve policies that promote rural households’ well-being. This study identifies livelihood strategies adopted by rural households and the factors influencing their choices in the Mt. Elgon region of Western Kenya. Design/methodology/approach Data were obtained from a survey of 924 randomly selected households in the Mt. Elgon area in Western Kenya. The study adopted a two-step activity-based cluster analysis to identify the various livelihood strategies undertaken by rural households. Further, the study applied multinomial logistic (MNL) regression to assess the factors influencing the choice of livelihood strategies. Findings The three livelihood clusters identified are forest extraction and farming (75.7%), business livelihoods (19.7%), and wage employment and remittance (4.7%). Using forest extraction and farming as the reference category, the MNL regression results show that household size, years of schooling, distance to markets, distance to all-weather roads, access to extension services and expenditure levels positively influence a household’s decision to adopt business livelihoods relative to the other options (e.g. forest extraction, farming and employment). Further, shock value and membership in farmer groups had a negative influence on business livelihoods. On the other hand, the number of years of schooling, expenditure levels, access to credit, and asset value positively influenced wage employment and remittance strategies compared to forest extraction and farming, while age had a negative influence. Originality/value Despite the diverse livelihood strategies that rural households adopt, a gap exists regarding how livelihood diversification is often measured. Many studies use a simple count of income sources as a measure of livelihood diversification. However, aggregate household income data may vary across years, leading to failure to capture the qualitative aspects of revenue sources and the complex dynamics of livelihood diversification across time. To address this research gap, we employed an asset and activity-based livelihood analysis to measure livelihood diversification among households in Mt. Elgon, Western Kenya. The findings indicate that strengthening institutional support services such as improving access to extension services, access to credit facilities and improving the road infrastructure could help households diversify their livelihoods, hence improving their welfare. The findings highlight the importance of policies and interventions to facilitate transitions from extractive practices to business and employment-based livelihood options.