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

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Wallace, Richard K., William Hosking, and Stephen T. Szedlmayer (1994).<br />

Fisheries Management for Fishermen: A manual for helping fishermen<br />

understand the federal management process. MASGP-94-012, Auburn<br />

University Marine Extension and Research Center, 4170 Commanders Drive,<br />

Mobile, Alabama, 56 pp.<br />

The purpose <strong>of</strong> the manual is to unlock the mysteries <strong>of</strong> <strong>fisheries</strong> jargon<br />

and to explain how regulations are made in the hope that fishermen will get<br />

more involved.<br />

Wallace, Stein W. and Karl Brekke (1986). "Optimal Fleet Size When<br />

National Quotas Can Be Traded." Marine Resource Economics,<br />

2(4):315-329.<br />

Assuming stochastic quotas for a fish stock that is shared between two<br />

nations, we find the optimal fleet size for one <strong>of</strong> them by maximizing expected<br />

pr<strong>of</strong>it under the assumption that national quotas can be traded and that stable<br />

national quotas is a political goal. As an example we use the Norwegian purse<br />

seiner fleet and the summer capelin fishery in the Barents Sea.<br />

Walters, A.A. (1963). "Production and Cost Functions: An Econometric<br />

Survey." Econometrica, 31(1-2):1-66.<br />

A survey article <strong>of</strong> econometric studies <strong>of</strong> cost and production<br />

functions.<br />

Walters, Carl J. (1981). "Optimum Escapements in the Face <strong>of</strong><br />

Alternative Recruitment Hypotheses." Can. J. fish. Aquat. Sci.,<br />

38:678-689.<br />

Available data are <strong>of</strong>ten inadequate to discriminate among alternative<br />

models that make different predictions about the consequences <strong>of</strong> allowing<br />

escapement outside the range <strong>of</strong> recent historical experience. Dynamic<br />

programming is used to show that the optimum policy in such situations can<br />

involve active probing or experimentation with escapements. The optimum<br />

adaptive policy is usually difficult to compute, but generally may be closely<br />

approximated by a "Bayes equivalent" policy that is simpler to estimate but<br />

does not account explicitly for the value <strong>of</strong> information associated with<br />

allowing more extreme escapements. While there are various practical<br />

difficulties in estimating and implementing an optimum policy, it is concluded<br />

that regular probing experiments should be included in every fishery<br />

management plan.<br />

Walters, Carl J. and Ray Hilborn (1976). "Adaptive Control <strong>of</strong> Fishing<br />

Systems." J. Fish. Res. Board Can., 33:145-159.<br />

This paper discusses some formal techniques for deciding how harvesting<br />

policies should be modified in the face <strong>of</strong> uncertainty. Parameter estimation<br />

and dynamic optimization methods are combined for the Ricker stock-recruitment<br />

model to show how exploitation rates should be manipulated to give more<br />

information about the model parameters; in general, harvesting rates should be<br />

lower than would be predicted by the best fitting recruitment curve unless<br />

this curve predicts that the stock is very productive. A decision procedure<br />

is developed for comparing alternative stock-recruitment models; when applied<br />

to the Fraser River sockeye salmon (Oncorhynchus nerka), the procedure<br />

indicates that an experimental increase in escapements would be quite<br />

worthwhile. It appears that there is considerable promise for extending these<br />

methods and procedures to cases where the stock size is unknown and where<br />

fishing effort is poorly controlled.<br />

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