Abstract
This study was conducted to assess the linkages and roles of various actors in the fish value chain, post harvest losses of fish, the determinants of value addition decision, market choice and price transmission asymmetry of four fishes namely; Rui (Labeo rohita), Catla (Catla catla), Tilapia (Oreochromis mossambicus /O.niloticus) and Pangas (Pangasius hypophthalmus). The primary data were collected from 200 fish farmers and 212 market actors from Mymensingh, Jashore and Dhaka districts through face to face interview during October, 2017 to March, 2018 and secondary data were collected from Department of Agricultural Marketing for the period of 2010-2016. Taylor's value chain analysis approach was used to identify actors, their linkages and roles. Ordinary Least Square (OLS) model was used to identify the factors causing post harvest fish losses and Poisson Regression model was used to identify factors affecting farmers decision on value addition while Multinomial logistic model was employed to identify factors influencing farmers choice of fish market. Causal relationships among farm, wholesale and retail prices were tested using the Granger causality test while asymmetries in price transmission were examined using the Houck and Ward approach and von Cramon-Taubadel and Loy approach as well as the error-correction approach. The major actors of fish in the study areas were fish farmers, Bepari, rural Paikar, Aratdar, urban Paikar and retailer. The marketing channels of fish in the study areas show five major marketing channels and major share of farmers goes to channels- I and III. The most desirable and efficient marketing channel was channel-III: Farmer Rural Paikar Aratdar Retailer-Consumer for fish value chain in the study areas. In fish value chain retailer added highest values. The estimated average fish losses for fish farmers were 8.10 kg/quintal of which physical quality and market losses were 26.41%, 15.18% and 60.37% respectively. The major factors causing losses were unforeseen demand and supply, inefficiencies at the collection points, poor packaging and handling practices. The results of the OLS model reveal that higher education (p<0.10), better transportation facilities (p<0.01), infrastructure facilities (p<0.01) and labour facilities (p<0.01) negatively influenced post-harvest fish losses. The Poisson regression analysis indicates that four variables such as education (p<0.05), experience in fish farming (p<0.01), access to extension services (p<0.05) positively and age of the farmers (p<0.01) negatively influenced the value addition decisions. The results of the MNL model reveal that the probability to choose the Upazila and district markets was positively and significantly affected by training, extension service, distance from the market, income level, access to market information, access to financial assistance and membership in cooperatives while age of the farmers and education level negatively influenced the farmers market choice. The findings of asymmetric price transmission of retail prices of fishes indicate that increases in the retail price of the fishes are likely to pass through to the primary markets more fully than decreases in retail prices. In general, the price transmission was found to be symmetric in the short-run while a mix of symmetric and asymmetric in the long-run. Out of 15 pairs of farmgate, wholesale and retail price series, 14 pairs were found to be co-integrated at (P<0.01 and P<0.05) level of significance. Improving access to services, market information, providing training, education and infrastructural development are some of the actions to be taken to strengthen the development of fisheries sector. The major benefit of the price spread goes to retailers. Therefore, market monitoring and visit should be encouraged. Accurate market information should be disseminated quickly so that value chain actors can response and adjust with supply and demand.