| Summary: | This thesis consists of three chapters on the economics of international fisheries management. The first chapter explores the economic and biological effects of exploiter and species interactions in a multinational and multispecies fishery. The Northeast Atlantic pelagic complex fishery (Norwegian spring-spawning herring, mackerel, and blue whiting) is harvested by several countries, and the species are ecologically interdependent through, for example, predation and competition for food. I develop a stylized bioeconomic model of the pelagic complex fishery, and estimate the outcomes of different types of fishery management. Specifically, I consider (1) whether exploiters ignore or take into account species interactions, and (2) whether countries cooperate or compete in the fishery. I consider three major exploiters: Norway, the European Union, and Iceland, which differ in terms of harvesting costs and ex-vessel prices. In the cooperative case, applying multispecies management increases the net present value of the fishery by over 20 percent compared to single-species management. The global optimum (i.e., cooperation and multispecies management) increases net present value by over 91 percent compared to the situation where both the common property and biological externality are uninternalized. Non-cooperative management leads to poor biological outcomes, such as depletion of the mackerel stock, irrespective of the type of biological management adopted. The second chapter examines empirically the effectiveness of Regional Fisheries Management Organizations (RFMOs). The fraction of overexploited and collapsed international fish stocks has grown over the past decades, but has international management improved sustainability of managed stocks? The purpose of RFMOs is to promote sustainable use and conservation of international fisheries within their purview. To elicit whether RFMOs have a conservation effect, I examine if RFMO management has reduced the probability of stock collapse. I exploit global fisheries data ...
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