ADOPTION AND INCOME IMPACT OF IMPROVED FOOD LEGUME TECHNOLOGIES IN BALE HIGHLANDS OF ETHIOPIA

Abstract

The study designed particularly on the identification of factors determining adoption of improved food legume technologies, evaluation of impacts of adoption status and intensity of improved food legume varieties, identifying intra-household impact dynamics due to adoption of improved legume varieties and spotting out the major challenges and opportunities faced by smallholders in their adoption of improved food legume technologies. This study used cross sectional data acquired from a total of 600 households, which were randomly and proportionately sampled from 12 major legume producer kebeles in 3 districts of Bale highlands by using three-stage sampling technique. Probit and Clog-log binary model were estimated to identify the underlying factors that determined adoption of improved food legume technologies. PSM model was estimated to evaluate the impacts of adoption status of improved food legume varieties. In addition, continuous treatment effects model (GPS) was also employed to estimate the impact of intensity of adoption on farm households by discarding non-adopters from the analysis. The results from probit and clog-log indicate that age, livestock holding, farm size, membership in farmers cooperatives, contact with agricultural research center, household head participation in off-farm activity, distance from agricultural extension office and main market; and district dummy were factors that significantly determined farmers decision to adopt improved food legume technologies. The outputs from PSM indicated that adoption of improved food legume varieties has positive and significant impact on the income and the adopters receive 25% higher income than nonadopters. The intra household analysis indicated that households with productive labor force receive better income while households with economically dependents female members receive considerably lower income from adoption of improved food legume varieties, suggesting the prevalent intra-household differences. The result of GPS also confirms the positive effect of intensity of adoption on income, consumption expenditure and calorie intake. The study also indicates that adoption of improved food legume technologies can motivate farmers to shift from the mono-cropping system to diversified one, improve household’s income and they are the major source of protein. However, adoption of improved food legume technologies is highly constrained by labor-intensive nature of production, lack of improved food legume technologies especially water logging tolerant varieties and market irregularities. The results suggests the need to design interventions enhancing adoption of food legume technologies focusing on improving adoption rates and minimizing intra household differences in income.