Conference Agenda

This paper studies the optimal allocation of fishery resources under uncertainty by developing a stochastic differential game framework that integrates ecological dynamics, strategic fishing behavior, and policy interventions. We first establish a benchmark deterministic model based on logistic fish population growth and compare outcomes under a social planner, symmetric open-loop equilibrium, and Markov perfect equilibrium. The analysis shows that open-loop strategies lead to overexploitation and the lowest sustainable biomass, while the social planner achieves the highest stock level at the cost of reduced fishing effort and income. In contrast, Markov strategies generate a set of equilibria that balance ecological sustainability and economic returns, yielding higher long-run income and more abundant fish stocks than open-loop outcomes.

We further extends the benchmark model and employs a power-law diffusion term to depict persistent stochastic environmental disturbances, categorizing fluctuation patterns into linear, sublinear and superlinear types. Analysis conducted within the golden-rule harvesting strategy framework reveals that linear fluctuations leave the overall structure of optimal harvesting strategies intact, while nonlinear fluctuations shift the interval of population stock levels. Under sublinear fluctuations, fishermen retain fewer precautionary resource stocks; superlinear fluctuations, by contrast, amplify downside risks and drive market participants to adopt far more conservative harvesting decisions, whereby adequate fish stocks are preserved to buffer severe environmental shocks.

Finally, the paper examines taxation and subsidy policies, showing that cost-based interventions primarily alter the slope of marginal cost curves and thus influence fishing incentives without fundamentally altering equilibrium structures.