Profit and loss dynamics of aquaculture farming

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Aquaculture's contribution has grown substantially in recent years, despite the fact that the price trend of several dominating species has remained constant when compared to input prices. Regardless of the fact that the nature of input usage varies considerably from farm to farm, productivity is improving but not to its maximum potential. Therefore, some farms are unable to make a profit by covering the production cost. For that purpose, this research evaluates the profit-making mechanisms and economic risk of pangasius and tilapia farming. A cross-sectional questionnaire-based survey was performed to collect data from 553 aquaculture farms in seven districts of Bangladesh, of which 275 were pangasius farms and 278 were tilapia farms. The financial performance of farms was evaluated using several descriptive and econometric analyses, while the Monte Carlo simulation method was employed to measure economic risk. Results revealed that the majority of pangasius and tilapia farms were profitable while a portion of farms was non-profitable. However, the lower market price of fish and inadequate inputs management were identified as the reasons for incurring loss at non-profit farms. Within the boundaries of economies of scale, this analysis also identified the optimum level of production for pangasius and tilapia. Meanwhile, sensitivity analysis suggested that lowering feed prices, maintaining feed quality, and raising fish prices would increase profitability on both farms. Besides, the simulation result showed that the risk of gaining profit was higher for pangasius than tilapia farming. Rational inputs use with proper extension support and increasing the output price to a reasonable limit would make pangasius and tilapia farming a more profitable venture.

Original languageEnglish
Article number738619
Number of pages10
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.

    Research areas

  • Coefficient of variation, Monte Carlo simulation, Profit and non-profit farm, Sensitivity analysis, Sustainable aquaculture

ID: 316871827