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Sustainable management of natural resources such as fish is important as millions of people rely on such resources for food, source of income, and well-being. It is increasingly challenging, however, for institutions and stakeholders to induce a sustainable exploitation of such resources due to factors arising from environmental, biological, and economic conditions (e.g., uncertainty, strategic behavior, and resource displacement). This thesis develops three articles to formally address such issues. The paragraphs below provide a summary of such articles. Stability of international fisheries agreements under stock growth uncertainty: Scientific evidence reveals that renewable resource stock dynamics are subject to uncertainty due to changes in environmental conditions. Despite its critical impacts on management, little is known about the effects of such uncertainty on the formation of regional fisheries management organizations (RFMOs). In this paper, we design a dynamic stock recruitment framework to examine this issue in a common pool setting. We find that stock growth uncertainty critically affects equilibrium behaviors under both open loop membership and dynamic membership. For instance, we delineate conditions under which uncertainty induces full non-cooperation in equilibrium. Strategic behaviors may also shift equilibrium outcomes from full non-cooperation under deterministic conditions to full cooperation under uncertainty when countries anticipate a small environmental variability. Moreover, strategic interactions to extract the resource stock may lead to higher individual payoffs under uncertainty. We also outline the differences in equilibrium responses of membership, harvest, and payoff to variations in environmental conditions under both open loop membership and dynamic membership. Learning and uncertainty in spatial resource management: Natural resources such as fish, and wildlife have the ability to move across different areas within an ecosystem. Such movements are subject to random changes in environmental conditions (e.g., nutrients, temperature, oxygen). Although empirical evidence suggests that learning about such movements helps improve management, the related economic literature concentrates on scenarios in which the resource population lives in a closed area and cannot migrate. In this paper, we develop a spatial bioeconomic model to examine a renewable resource harvester's responses to learning about fish movements. Our baseline is the scenario in which the harvester is fully informed about the distribution of fish movements. We find that introducing uncertainty and learning about fish movements critically affects extraction incentives. For instance, we show that uncertainty and learning may increase harvest in a patch and reduce harvest in another patch when the marginal harvesting cost function is constant. In the stock dependent marginal harvesting cost case, we delineate conditions under which uncertainty and learning increase harvest in all patches. We also show how harvest responses to learning change with the distribution of uncertainty. Effectiveness of regional fisheries management organizations: Evidence from the general fisheries commission for the mediterranean: The 1995 United Nations Fish Stocks Agreement urges countries to exploit straddling and highly migratory fish stocks cooperatively through regional fisheries management organizations (RFMOs). Although this recommendation is being implemented across jurisdictions, little is known about the effectiveness of RFMOs to carry out their mandate of conservation. Using panel data on fish stock overuse in national exlusive economic zones (EEZs), we compare overfishing within EEZs of member countries of the General Fisheries Commission for the Mediterranean (GFCM) to that of a synthetic counterfactual. Our results indicate that the GFCM's management policies has been ineffective in reducing overfishing among member countries. Further, analysis of the share of collapsed stocks and rebuilding stocks supports our conclusion. Robustness checks conducted using different sub-samples of our control group support these results. We elaborate on policy implications of our results, most significantly, the importance of identifying and addressing the issues that undermine the performance of RFMOs. |
