Economics of indigenous vegetable marketing: a case study in Arumeru District

Abstract

Study objective was to analyze the marketing efficiency of indigenous vegetables in Arumeru district. Specifically to (i) identify the present marketing channels of Amaranthus, African nightshade and African eggplant and the role played by various market participants’ objectives were (ii) To examine the relative competitiveness of Amaranthus, African eggplant and African nightshade with the selected exotic vegetables grown in the study area. (iii) Determine price differences and market margin among various market participants and selected IVs. Structural Conduct Performance model showed Indigenous Vegetables (IV) have similar marketing channel with other selected crops except the occurrence of seasonal collectors. There was no producers or traders organization to influence market price. IV sellers concentration index showed there is possibility of oligopolistic behavior in African eggplant farmer’s sellers (CI=82.03%) since most of their revenues were obtained from selling to traders/transporters from other regions especially Dar-es-Salaam rather than Arusha city markets. Amaranthus and Africa nightshade sellers were found to have weak oligopolistic behavior since the concentration index was 38.92% and 36.7% respectively. From Gross Margin (GM) analysis the performances of IVs were competitive. African nightshade (Solanum aethiopicum) GM was higher (190 079.59 TSh) than selected exotic vegetables (Chinadese cabbage and spinach). Their GM was 39 796.67 TSh and 20 840.47 TSh for Chinese cabbage and spinach respectively. Also Market Margin (MM) among market participants were excessive at retailer-consumer level for all studied vegetables. MM for amaranthus was regressed against buying prices as a representative of indigenous vegetables to find correlation between MM and selling prices. It was found that 72.1% of the variation in selling prices is explained by buying prices and the remaining percent (27.9%) might be explained by other factors such as marketing costs. Also correlation analysis shows that there is positive correlation coefficient (r>0.765; p=0.01) between MM and selling price. Indicating there is subsequent price movement to the next market level. There was positive correlation between MM, selling and buying prices.