Capacity and Economic Efficiency of Coastal and Offshore Longline Fisheries of Northern Taiwan
研究生: 徐鉦忠 Jeng-Jung Shiu
臺灣沿近海漁船筏約2萬2千餘艘，近十年漁船數與馬力數增加了5.6%及19%，而漁獲產量卻減少27%。其中延繩釣船數占沿近海總船數45%，臺北縣與基隆市延繩釣漁船占9%，屬於重要漁業種類之一，本研究欲了解延繩釣漁戶的經營效率、漁船產能狀況，以提供管理建議。調查時間自2009年7月至2010年1月，在臺北縣與基隆市主要漁港以問卷蒐集漁船資料。結果總計調查39艘延繩釣漁船，87%為專營漁業，船長平均年資30年，全年平均作業天數157天，單船漁獲量約12.9公噸，主要魚種為紅目鰱及赤鯮，占總漁獲量約47%。經濟指標方面，平均毛利約2,920千元，平均淨利約1515千元，投入成本主要為油料費及工資，兩者各占27%，漁獲處理費用18%，平均每船財務盈餘為676千元，較多20~50噸級漁船有虧損情形。資料包絡法 (Data Envelopment Analysis, DEA)分析結果顯示，79%漁船處於規模報酬遞減，產能利用率平均在0.8以上，10噸以下漁船最具技術效率。效率分群比較發現，油料費及漁獲量為造成效率差異的主因，造成漁獲量差異月份為2月、11月及12月，作業時段從晚上至白天的漁船有較好的漁獲量。最後以Tobit迴歸判斷影響效率及產能利用率因子發現，技術效率主要受作業地點及作業時段影響，在彭佳嶼附近作業對於技術效率具正面影響，產能利用率與船長的年資有顯著正相關。作業漁船成本調整，10~20噸效率低漁船，平均每船應減少餌料成本7%，20~50噸效率低漁船，平均每船應減少油料費20%及餌料費11%。政府減船收購對象可針對經營虧損、規模報酬遞減、技術效率低及產能利用率高的漁船。
The number of total coastal and offshore fishing vessels was around 22000. The number and horsepower increased 5.6% and 19% in the recent ten years, respectively. However, the catches decreased around 27%. Among those fisheries, longline vessels was around 45% in number, which Taipei county and Keelung city were 9% of total longline vessels. The object of this research is to study the operational efficiency of those longline fishing vessels and provide management suggestions. The data was collected from July 2009 to January 2010 by questionnaire. The study collected data from 39 longline fishing vessels, which 87% fisherman were full-time fishermen. The average experience was 30 years. The total fishing days was 157 days and the catch per vessels was 12.9. The target species were Priacanthus macracanthus and Dentex tumifrons, were 47% of total catch in weight. Regarding the economic perforence, gross revenue and net revenue were around NT$ 2.9 million and NT$1.5 million. Fuel and crews were the main costs stand for 27% respectively. Bait was 18% among total costs. Financial profit was about NT$676 thousand in average. More fishing vessels between 20 to 50 have loss. Through data envelopment analysis, 79% vessels were decreased return to scale (DRS), average Capacity Utilization were larger than 0.8. Vessels less than 10 Gross tonnages had better efficiency. Fuel and catches were the main factors. In addition, catches in February, November and December were significant different between high efficiency and low efficiency groups. Vessel which working shift from night to day with more catches than at other working times. According to tobit regression, fishing ground and fishing time were the main factor to TE, a positive correlation between CU and captain’s experience. However, for those low efficiency vessels, which the tonnage between 10 to 20 should reduce 7% bait costs in average. Those vessels tonnage between 20 to 50 should reduce 20%fuel and 11% bait costs. In vessel buyback program, government could consider to buyback those fishing vessels which operate loss, DRS, with low TE and high CU ones.
