MARKET CHAIN ANALYSIS OF WHEAT (Triticum Aestivum L.): THE CASE OF MISHA WOREDA, HADIYA ZONE, SOUTHERN ETHIOPIA

Abstract

In this study, market chain of wheat in Misha woreda was analyzed. The area is known for its potential production of wheat. However, the market chain of wheat was not well understood. The objectives of this study were to analyze the structure, conduct, and performance of wheat markets; to identify factors affecting the market supply of wheat and producers’ market outlet's choice in Misha woreda. Qualitative and quantitative data from primary and secondary sources were used. Primary data from 194 wheat producers from five randomly selected kebeles, 30 traders, and 22 consumers were collected. Descriptive statistics and econometric models were used for analyzing data. Structure-Conduct-Performance model for market performance analysis, two-stage least square model for the determinants of wheat market supply, and multivariate probit model for the determinants of producers’ market outlets choice decision were used for data analysis. The identified wheat market chain actors in the study area include producers, local collectors, retailers, wholesalers, processors, and consumers. Seven market channels were identified for wheat in the study area with the major share of a volume of wheat marketed goes to marketing through channel VII (producers-wholesalers-processors-consumers) which was 1158.9qt (23.5%). The result from the analysis of market concentration indicates that the structure of the wheat market in Misha woreda is a weak oligopoly with the four largest wheat traders’ concentration ratios of 34.63%. The wheat market in the woreda shows some deviations from competitive market norms. The result of market conduct shows that wheat producers have less power to decide on the price of wheat. The result of market performance indicates that no actors were generating negative gross profit. The total gross marketing margin is largest in channel VI (producer’s-local collectors-wholesalers-processors-consumers) which was 52.367% and lowest in channel II (producers-retailers-consumers) which was 14.28%. In addition to this, the maximum producers share from total consumer price is highest in channel II (85.72%) and lowest in channel VI (47.64%). The two-stage least squares regression results reveal that the quantity of wheat produced, access to market information, frequency of extension contact, and landholding size positively and significantly affected the wheat market supply while family size and distance from the nearest market negatively and significantly affected it. The multivariate probit model results indicate that the probabilities that producers chose consumers, retailers, wholesalers, and local collectors market outlets were 44.9%, 63.4%, 72.6%, and 56.6%, respectively. Moreover, the probability of jointly choosing the four outlets simultaneously is 16.6%. Besides, the quantity of wheat supplied to the market, distance to the nearest market, frequency of extension contact, education level and access to market information significantly affected wheat producers’ market outlets choice. Therefore, based on the findings of the study policy interventions need to be made to increase the capacity through training, frequency of extension contact, intensive use of the existing land, providing adult education opportunity program, enhance the yield of wheat, road infrastructure development, and providing agricultural and marketing based information access.