How do fishery policies affect Hawaii's longline fishing industry? Calibrating a positive mathematical programming model
Jonathan R. Sweeney, Richard E. Howitt, Hing Ling Chan, Minling Pan,, PingSun Leung

TL;DR
This paper develops and calibrates a vessel-specific positive mathematical programming model for Hawaii's longline fishery, enabling assessment of policy impacts on vessel behavior and catch, with implications for fishery management and policy support.
Contribution
It introduces a novel PMP modeling approach to fisheries, specifically tailored for Hawaii's longline fleet, demonstrating its predictive accuracy and policy simulation capabilities.
Findings
Model predicts vessel-specific bigeye catch with 12-35% accuracy.
Policy changes in catch limits have moderate to large impacts on vessels.
The model reveals heterogeneous vessel responses to policy adjustments.
Abstract
We present a vessel and target-specific positive mathematical programming model (PMP) for Hawaii's longline fishing fleet. Although common in agricultural economics, PMP modeling is rarely attempted in fisheries. To demonstrate the flexibility of the PMP framework, we separate tuna and swordfish production technologies into three policy relevant fishing targets. We find the model most accurately predicts vessel-specific annual bigeye catch in the WCPO, with an accuracy of 12% to 35%, and a correlation between 0.30 and 0.53. To demonstrate the model's usefulness to policy makers, we simulate the economic impact to individual vessels from increasing and decreasing the bigeye catch limit in the WCPO by 10%. Our results suggest that such policy changes will have moderate impacts on most vessels, but large impacts on a few generating a fat tailed distribution. These results offer insights…
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