Economic Analysis Of Recommended Technologies On Coffee Performance Among Smallholder Farmers In Embu County, Kenya

ABSTRACT

The coffee subsector in Kenya has been characterized by low and declining productivity at farm levels. Over the years, coffee research in Kenya has developed technologies that are aimed at increasing the productivity and improving the quality of coffee produced. Despite many agronomic recommendations, coffee productivity has not increased with increase in acreage. This may be attributed to the interaction between the recommendations and prevailing socioeconomic factors experienced by the farmers at the farm environment. There is limited research based information on the combined impact of the recommended coffee production technologies and prevailing socioeconomic environment on productivity, returns and quality of coffee at farm level. The purpose of this study was to analyze the combined effect of the recommended technologies and farmer socioeconomic characteristics on coffee productivity, profitability and quality among smallholder farmers in Embu County. Data was collected from a sample comprising of 376 farmers who were randomly selected from six cooperative societies using multistage stratified and probability proportional to size sampling techniques. Data was collected using semi-structured questionnaires, focus group discussion and oral interviews, and included farm demographic data, coffee management, production and quality data. The collected data on farm and farmer characteristics was analyzed using descriptive statistics such as means and frequencies. The combined effect of the recommended technologies and socioeconomic factors on productivity, profitability and quality was determined using Stochastic Cobb-Douglas Production Function, Profit Function and Binary Logit Models respectively. The regression results of estimated Stochastic Cobb-Douglas production function revealed that the recommended foliar feed, manure, herbicide and pesticide rates were significant and positive in affecting coffee productivity at 5% level. The results of the estimated Profit function revealed that recommended varieties, manure rate and capping were positive and significant in influencing coffee profitability at 5% level. Binary Logistic Regression results revealed that the recommended foliar feed rate, manure rate and pruning were significant in affecting the coffee quality. The results of the study also revealed that education, household size and off-farm income have significant impact on productivity and cherry quality. This indicates that there is possibility to increase productivity by using the recommended rate for foliar feed, manure, pesticide and herbicide and increase coffee returns by adoption of the improved coffee variety. Therefore, to increase coffee productivity, profitability and quality, more focus should be put on on-farm research, accompanied by farmer education, specifically on usage of manure, foliar feed, herbicide and pesticide and adoption of the improved coffee varieties. Policy makers need to develop a land use policy and also offer coffee farmers more incentives to access and use these inputs.