Quota Trading and Technical Efficiency

Suggested Bibliographic Reference: Challenging New Frontiers in the Global Seafood Sector: Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, July 11-15, 2016. Compiled by Stefani J. Evers and Ann L. Shriver. International Institute of Fisheries Economics and Trade (IIFET), Corvallis, 2016.Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, held July 11-15, 2016 at Aberdeen Exhibition and Conference Center (AECC), Aberdeen, Scotland, UK.Catch share management programs are designed to reduce overcapacity in fisheries through trading as efficient harvesters buy out their less efficient counterparts. Numerous studies have looked at either the ex-ante potential of catch shares management to reduce overcapacity in a fishery or the ex-post effects of implementing such a program, but no research has evaluated how catch share trading networks impact fleet level efficiency gains. Many commercial fisheries cover large areas and are geographically segmented into distinct regional groups with little interaction between groups; given this reality catch share trading is often localized with limited trading between regions due to high transaction costs. This research uses social network analysis of quota trading markets to determine how trading network structure impacts fleet consolidation in a catch share managed fishery. Using a combination of IFQ trading and fishing effort data from the Gulf of Mexico red snapper fishery this research evaluates how trading network structure impacted capacity reduction and fleet efficiency gains after IFQ implementation. This analysis will evaluate and compare realized technical efficiency gains and fleet consolidation to what would be expected if quota trading were frictionless (a non-segmented market with no search costs). Simulated trading networks will be generated based on network metrics of the realized trading network; these simulations will then be used to generate a range of possible fleet consolidation and technical efficiency gains to compare with the realized and frictionless market outcomes