VALUE CHAIN ANALYSIS OF MAIZE: THE CASE OF NEDJO WOREDA, OROMIA NATIONAL REGIONAL STATE

Value chain analysis of maize in Nedjo woreda has been conducted to identify value chain actors, and their roles and linkages, to analyze maize marketing costs and margins of different actors along the value chain, and to identify factors affecting marketed surplus of maize at producers’ level. To accomplish these tasks, both primary and secondary sources of data were used. Data have been collected from randomly selected 119 maize producer households in Nedjo woreda using a semi-structured questionnaire and from thirty consumers, five farmer traders, three wholesalers, three cooperatives, one union and ten retailers. Descriptive statistical analysis indicates that maize diseases, lack of pesticides, shortage of farm land, increasing fertilizer and seed prices, improved seed shortage and oxen problem were the major hindrance of maize production. The result of marketing costs and margins shows that farmer traders incurred the smallest marketing costs followed by retailers. Of all maize traders, retailers get the highest gross marketing margin. The Heckman two-stage regression analysis was used in order to capture the selectivity bias and to identify factors affecting the decision enter in the market and maize sale volume of the household. Based on the Heckman two-stage model, the study has identified the main determinants of maize market participation decision and that of the quantity sold. The probit model analysis revealed that livestock holding, number of oxen owned, farm size, extension service, recommended technology package and non/off-farming activities were found to have significant impact on the probability of household’s maize market participation. Similarly, the second stage Heckman model indicated that recommended technology package, access to irrigation, number of oxen owned, livestock holding, and education level of the household head are the significant factors affecting volume of maize sold. Therefore, the findings of the study underscore focusing on these significant variables for policy interventions.