Abstract
This study examines resource use efficiency in the fish production from different types of fishing vessels operating different types of gears in West Sumatra. Specifically, this study addresses the issues on productivity and technical efficiency of fishing operations of driftnet and payang seine (lampara) fishing in order to determine the economic performance of the small-scale multi-gears fisheries. The translog and Cobb-Douglas production frontier functions were specified as the empirical model of this study. The frontier regression model was estimated using the maximum likelihood estimation (MLE) technique. The Cobb-Douglas stochastic frontier model was found to be unsuitable to represent the data, while the translog model for both driftnet and lampara provide better estimates.The estimates of regression coefficients for the driftnet differed between the OLS and MLE methods. These results could be due to the inefficient estimates by the OLS method. Meanwhile in the case of lampara, the estimated regression coefficients of the two methods were almost similar, indicating that lampara were technically efficient regardless which particular combinations of the selected bundle of inputs used. The return to scale was found to be greater than one for driftnet but less than one for lampara. These results indicated that the level of fishing effort in the lampara fishery has already surpassed the maximum sustainable yield (MSY) level, while the opposite is true for the driftnet. The computed technical efficiencies for individual driftnet fishing units ranged from 0.7272 to 0.9989 with an average of 0.9292, while for lampara it ranged from 0.9035 to 0.9829 with an average of 0.9829. The results also showed that about 70% of driftnet fishing units have achieved technical efficiency of more than 90% while all the lampara fishing units achieved more than 90% technical efficiency. The findings of this study suggests that the room for expansion in the driftnet fishery is greater compared to lampara fishery, through the adoption of the best technology and through optimal resource allocation.
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