The Impact of Improved Coffee Technology Adoption and Determinants of Coffee Productivity: A Quantile Regression Approach

Abstract

Non-morphological and non-physiological factors that affect the productivity of coffee were not critically examined in different coffee-related studies. The objective of this study was to explore such factors that affect the productivity of coffee and estimate the impact of the adoption of improved coffee varieties on yield. It was conducted in major coffee-producing zones of Ethiopia.  A total of 694 households made up the sample for the study. The data were analyzed using descriptive statistics and an econometric approach. Socio-demographic and economic factors determining the productivity of coffee were investigated using quantile regression. The propensity score matching (PSM) was used to empirically determine the impact of the adoption of improved coffee varieties on farmers' yield. The result exhibited a positive and significant effect of improved coffee variety on productivity. Adopters can get 25-34% additional yield over non-adopters.  An inverse relationship was observed between the size of the area allocated to improved coffee varieties and productivity in the lower quantiles. There was also a local difference both in technology adoption and coffee productivity. The magnitude of the effect of some of the variables in the quantile regression was found significantly different from the OLS estimates suggesting that the latter doesn't reflect the variable effect at different productivity levels. The finding suggests the need to reach out to less addressed areas such as Benishangul Gumuz through aggressive technology promotion efforts, enhance farmers' resource management skills and make training more tailored to farmers falling in different productivity ranges.