ANALYSIS OF COFFEE MARKET CHAIN: THE CASE OF GIMBO DISTRICT, KAFFA ZONE, SOUTHWEST, ETHIOPIA

Abstract

Coffee is Ethiopia's most important export crop, accounting for a significant portion of the country's GDP. However, its potential is inhibited by inadequate production and market development along the market chains. Thus, the study was proposed to analyze the market chain. Using a multi-stage sampling procedure, 200 coffee producers, 22 traders, and 22 consumers were selected to collect primary data through structured questionnaires. For data analysis, descriptive statistics and econometrics analysis were used. Two-stage least square model for the determinants of coffee market supply and a multivariate probit model for the determinants of producers’ market outlets choice decision was used for data analysis. The identified coffee market chain actors in the study area include producers, local collectors, retailers, private traders, cooperatives, Ethiopian commodity exchange (ECX), and consumers. Six market channels were identified for coffee in the study area. The result from the analysis of market concentration indicates that the structure of the coffee market in Gimbo District is a weak oligopoly with the four coffee largest traders’ concentration ratios of 36%. The coffee market in the district shows some deviations from competitive market norms. The result of market conduct shows that coffee producers have less power to decide on the price of coffee. The result of market performance indicates that no actors were generating negative gross profit. The total gross marketing margin is largest in channel II which was 17.67% and lowest in channel III which was 10.69%. In addition to this, the maximum producers' share from total consumer price is highest in channel III (89.31%) and lowest in channel II (82.4%). The two-stage least squares regression results reveal that the quantity of coffee produced, access to market information, access to credit, education level, and sex of the household head positively and significantly affected the coffee market supply while the distance from the nearest market negatively and significantly affected it. The multivariate probit model results indicate that the probabilities that producers chose consumers, retailers, private traders, cooperatives, and local collectors market outlets were 31.5%, 78.5%, 73.5%, and 51.5%, respectively. Moreover, the probability of jointly choosing the four outlets simultaneously is 6.78%. Besides, the quantity of coffee supplied to the market, xvi distance to the nearest market, number of extension contact, and access to market information significantly affected coffee producers’ market outlets' choice. Therefore, based on the findings of the study policy interventions need to be made to increase the capacity through training, enhance the yield of coffee, road infrastructure development, and provide agricultural and marketing-based information access.