Abstract:
Agro-forestry has continued to receive increasing attention from researchers and policy makers’ especially in coffee farming systems but there is lack of sufficient evidence on its role in productivity and profitability of coffee farming in Kenya. There is also lack of empirical evidence on whether factors that influence adoption of shade technology have the same effect on productivity and profitability of coffee. The general objective of the study was to examine the adoption of agroforestry-based coffee management systems and the role of these systems in increasing the productivity, and profitability of smallholder coffee enterprise in Imenti South District. The study also extends the application of the Tobit model in the realm of analysis of farm productivity and profitability. Specific objectives included categorization of smallholder farmers into adopters and non-adopters of shade technology, productive and non-productive farmers, profitable versus non-profitable coffee farms using the local means as cutoff points. A structured questionnaire was administered to a representative sample, chosen through multistage sampling, of 346 smallholder farmers in Imenti South District of Kenya. First, descriptive statistics, t-tests and chi-square analyses were used to explore socioeconomic characteristics of adopters and non-adopters of shade coffee technology, productive versus non-productive farmers, as well as profitable versus non-profitable coffee farms. Using the sample mean for binary categorization of coffee farming households, 40 percent of the sample farm households were effectively classified as adopter of shade coffee, 44 percent was classified as productive coffee farmers, while about 43 percent of the farm households were classified as profitable coffee farming households. Socioeconomic characteristics of the productive and non-productive farmers, as well as profitable versus non-profitable farming households, were different and hence requiring different sets of stimuli to increase productivity and profitability. Second, separate Tobit models were then used to examine factors that determine the rate and intensity of adoption of shade technology, as well as determinants of productivity and profitability of coffee/agroforestry system. The Tobit results show that different sets of socioeconomic factors determine the rate and intensity of adoption of coffee shade technology, productivity and profitability requiring proper understanding of the interplay of these factors in order to promote appropriate policy incentives. Policy implications are drawn.
