Economic performance indicators for coastal fisheries : the case of purse-seining in Khanh Hoa, Vietnam.

Abstract

A field study on the economic performance indicators for coastal fisheries are needed in order to implement fisheries policy in Khanh Hoa as well as in Vietnam. The research project “Economic performance indicators for coastal fisheries - the case of pure-seining in Khanh Hoa” established to fulfill these demands. A questionnaire about technical characteristics and economic data is used for data collection through interviews with vessel owners. This paper presents preliminary findings for 100 purse seiners, representing 10% of the total population, in Nha Trang and Cam Ranh (Khanh Hoa province) in the group of vessels with engine power of less than 90 HP. The following indicators are presented: gross revenue, gross value added, gross cash flow, net profit and crew share. The results show that the coastal purse seine fishery in Cam Ranh is more profitable than in Nha Trang for each engine power group. The owner of an average purse seiner of all groups of horse power in both locations of Nha Trang and Cam Ranh is not only capable paying for all expenses, but also has a reward for the operating year. The boat owner of an average vessel in the group of horse power of 75 -< 90 Hp has the highest values of annual gross cash flow and net profit following location. Thus, the annual average of crew shares for this group of horse power was quite high. It was almost 2.0 times more than the average earnings of labor in the whole country. The boat owners of the engine power group of < 20Hp and 20-<45Hp have lowest values of annual vessel gross cash flow and net profit following location. Thus, the annual average of crew shares for those groups of horse power is quite low. They are almost 1.2 times more than the average earnings of labor in the whole country. Regression analysis of gross revenue using technical characteristics as independent variables is performed, and the results are demonstrated. The technical factors that impact on the gross revenue are the length of net, fishing experience of skipper and location. These are significant factors impacting on the gross revenue. Further work will include collection of more data, which will be analyzed with stronger techniques for in depth analysis such as Data Envelopment Analysis (DEA) or Stochastic Production Frontier (SPF).