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annotated bibliography of fisheries economics literature - Office of ...

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Dissertation, Department <strong>of</strong> Resource Economics, University <strong>of</strong><br />

Rhode Island.<br />

The primary objectives <strong>of</strong> this research are (1) a global analysis <strong>of</strong> the<br />

codevelopment <strong>of</strong> the net-pen salmon aquaculture industry and related public<br />

institutions, (2) development <strong>of</strong> a conceptual, intertemporal, multilevel<br />

economic poly model, and (3) formulation and application <strong>of</strong> a numerical model<br />

capable <strong>of</strong> generating economic policy information for salmon aquaculture<br />

policy development.<br />

Sylvia, Gilbert (1990). "Market Information and Fisheries Management: A<br />

Multiobjective Analysis." Draft report, Oregon State University,<br />

Coastal Oregon Marine Experiment Station, Hatfield Marine Science<br />

Center, Newport, Oregon.<br />

Market related issues are <strong>of</strong>ten implicitly or explicitly treated as<br />

exogenous to the <strong>fisheries</strong> policy problem. Examples illustrate the<br />

relationship <strong>of</strong> market demand, variation in intrinsic and extrinsic seafood<br />

qualities, and regulatory policy. A dynamic multiobjective model is used to<br />

demonstrate how policy factors including market information, regulatory<br />

instruments, and fishery stock dynamics can impact the levels and distribution<br />

<strong>of</strong> social benefits. Socioeconomic policy information is summarized in the<br />

form <strong>of</strong> dynamic and capitalized policy frontiers.<br />

Sylvia, Gilbert and Deqin Cai (1995). "Generating Policy Information<br />

for Fisheries Management: A Comparison <strong>of</strong> Alternative Approaches."<br />

Marine Resource Economics, 10(1):77-91.<br />

The potential for economic policy modeling approaches under alternative<br />

theories <strong>of</strong> <strong>fisheries</strong> management are reviewed. Conceptual dynamic models are<br />

developed to illustrate the discussion. Results suggest that the class <strong>of</strong><br />

multi objective models known as multi attribute utility theory are consistent<br />

with a <strong>fisheries</strong> policy process characterized primarily by principles <strong>of</strong><br />

scientific management. Conversely, multi objective policy models based on<br />

generating techniques may be more appropriate when the policy process is<br />

driven by a pluralistic process. Conceptual and numerical models are used to<br />

demonstrate the potential for these approaches in incorporating environmental<br />

externalities. Dynamic and capitalized policy frontiers are generated for<br />

purposes <strong>of</strong> comparative analysis. The paper concludes by emphasizing the role<br />

that multi objective methods can play in improving the efficiency <strong>of</strong> the<br />

<strong>fisheries</strong> policy process.<br />

Sylvia, Gilbert and Roberto R. Enriquez (1994). "Multiobjective<br />

Bioeconomic Analysis: An Application to the Pacific Whiting<br />

Fishery." Marine Resource Economics, 9(4):311-328.<br />

A multiobjective bioeconomic policy model was developed for the United<br />

States Pacific whiting fishery. Pareto optimal solutions for three policy<br />

objectives-rents, production, and female spawning biomass-were developed and<br />

analyzed using "hybrid" generating technique. Three policy instruments were<br />

considered: harvest quotas, fleet capacity limits, and allocation between<br />

shore based and <strong>of</strong>fshore <strong>fisheries</strong>. Results indicate that Pareto optimal<br />

allocations to shore based and at sea industries will depend on the spatial<br />

and temporal characteristics <strong>of</strong> the stock and the assumptions regarding the<br />

harvesting and processing characteristics <strong>of</strong> each fleet. The analysis also<br />

suggests approaches for measuring opportunity costs associated with<br />

misidentifying "biological risk" and operationalizing the concept known as<br />

"optimum yield".<br />

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