No abstract

To enrich agriculture reform and reap its benefits, policy makers need to localise policy issues within and across their domestic zones. Using a stochastic meta-frontier function, this study analysed the production efficiency of the cassava subsector of cassava growers from Bomi and Nimba counties in Liberia. The paper contributes to the domestication of agriculture policy issues within a country. The study found different scales of production returns for cassava growers in Bomi and Nimba counties. Farmer age, gender, household size and access to credit were key determinants of the technical gap ratio of the cassava subsector. The study recommends that relevant stakeholders (in a multistakeholder partnership) design a holistic approach of innovative finance (including microfinance, agriculture insurance and a grouped loan scheme) and social enterprise development that will encourage more women and young people to grow cassava efficiently for the higher productivity of the cassava subsector

The productivity of the few established cash crops in Makueni County is affected by low rainfall reliability, which in turn leads to drought and crop failure. Thus, the dairy sector is a crucial source of livelihood for the residents in Makueni County. The dairy sector, however, is constrained by the lack of adequate processing capacity which has the potential to enhance the shelf life and retail price of milk. It’s for this reason that the Kikima dairy plant was established to provide a ready market for farmers’ milk and enhance the processing capacity within Makueni County. However, there is scanty empirical evidence on the impact this dairy plant has had on farmers’ welfare. The current study assessed the impact of participation in milk processing on farmers’ welfare in Makueni County using farm income as the welfare indicator. The study used primary data with a sample size of 200 respondents drawn from Mbooni and Kilome sub-counties in Makueni County. The respondents were stratified by participation and farmers were randomly selected from the two sampling frames to give a sub-sample of 100 project participants and 100 non-participants. Data were then analyzed using descriptive and inferential statistics. The endogenous switching regression model was used to analyze the impact. The results indicated a negative impact of participating in milk processing on farmers’ income.

We employ stochastic meta-frontier and region-specific frontiers based on the “true” random effect framework to examine technical efficiencies, technology gaps and meta-frontier technical efficiency of Kenyan smallholder dairy farmers in different agro-ecological zones. The empirical analysis is based on comprehensive three-wave household level panel data from across three agro-ecological zones in Kenya. Results show variations in efficiency measures and that smallholder milk production is characterized by increasing returns scale across all agro-ecological zones. The results indicate that the milk output of smallholder dairy farmers from all the agro-ecological zones lags behind their potential with the technology available and the prevailing enviromnetal conditions in their agro-ecological zones. We also, find that there exists a significant technology gap in dairy production across the agro-ecological zones in Kenya. These findings generate important policy implication for achieving increased technical efficiency and reduce the technology gap in smallholder dairy production.