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Renewable resource management with i...

Costello, Christopher James.

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Renewable resource management with information on a random environment.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Renewable resource management with information on a random environment./
Author:	Costello, Christopher James.
Description:	94 p.
Notes:	Chair: Peter Berck.
Contained By:	Dissertation Abstracts International61-07A.
Subject:	Agriculture, Fisheries and Aquaculture. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9979597
ISBN:	059985877X

Renewable resource management with information on a random environment.
Costello, Christopher James.

Renewable resource management with information on a random environment. - 94 p.

Chair: Peter Berck.

Thesis (Ph.D.)--University of California, Berkeley, 2000.

This dissertation is a collection of three closely-related chapters focused on improving management of renewable resources under uncertainty. Chapter 1 theoretically analyzes how forecasts of future environmental variability should be incorporated into management of renewable resources. Variations in environmental conditions affect the growth of renewable resource stocks. The ability to predict such variations is improving, providing scope for improved management. The chapter develops a stochastic stock recruitment model to explore how optimal management changes with environmental prediction. While it might seem that a prediction of adverse future conditions should lead to more conservative management, under reasonable assumptions the opposite is true. This result is demonstrated for both perfect and imperfect forecasts. A case where a nonnegative harvest constraint binds in some periods is also explored and it is shown that a prediction of more adverse conditions may lead to more conservative management.

ISBN: 059985877XSubjects--Topical Terms:

1020913
Agriculture, Fisheries and Aquaculture.

Renewable resource management with information on a random environment.
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020 $a 059985877X
035 $a (UnM)AAI9979597
035 $a AAI9979597
040 $a UnM $c UnM
100 1 $a Costello, Christopher James. $3 1252723
245 1 0 $a Renewable resource management with information on a random environment.
300 $a 94 p.
500 $a Chair: Peter Berck.
500 $a Source: Dissertation Abstracts International, Volume: 61-07, Section: A, page: 2834.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2000.
520 $a This dissertation is a collection of three closely-related chapters focused on improving management of renewable resources under uncertainty. Chapter 1 theoretically analyzes how forecasts of future environmental variability should be incorporated into management of renewable resources. Variations in environmental conditions affect the growth of renewable resource stocks. The ability to predict such variations is improving, providing scope for improved management. The chapter develops a stochastic stock recruitment model to explore how optimal management changes with environmental prediction. While it might seem that a prediction of adverse future conditions should lead to more conservative management, under reasonable assumptions the opposite is true. This result is demonstrated for both perfect and imperfect forecasts. A case where a nonnegative harvest constraint binds in some periods is also explored and it is shown that a prediction of more adverse conditions may lead to more conservative management.
520 $a Chapter 2 demonstrates a potentially valuable empirical application of the theory developed in Chapter 1 by recognizing that many physical environmental processes which affect renewable resource growth are serially correlated through time. El Niño/La Niña cycles, global warming trends, and interannual stream flows are a few examples of such events. Even when the processes that cause variability in resource growth cannot be identified or measured, statistical estimation of resource growth functions often reveals a serially correlated error structure. Bioeconomic models of management under uncertainty in the literature assume independence between inter-periodic shocks. This chapter describes how to optimally harvest a resource where inter-periodic shocks are serially correlated. In this case, optimal escapement is not constant and depends on the magnitude of previously observed shocks. This theory provides potentially useful insights into management under uncertainty in the absence of costly, and often inaccurate exogenous forecasts. Application of this technique is demonstrated with a simplified empirical example of managing a northern British Columbia pink salmon fishery.
520 $a Chapter 3 develops a dynamic game-theoretic model of competition (and cooperation) between two countries who harvest a renewable resource. The empirical example focuses on the 1985 <italic>Treaty with Canada Concerning Pacific Salmon</italic> (United States Congress, 1985), which emphasized equity in harvest of the five transboundary pacific salmon species. Changing environmental conditions, as well as substantial economic incentives to defect from this cooperative arrangement lead to the deterioration of the Pacific Salmon Treaty throughout the 1990's. At significant ecological, monetary, and political expense, high-level negotiations recently lead to a cooperative agreement announced June 3, 1999 regulating such things as harvest interceptions and spawning habitat. The chapter develops a differential game between two nations harvesting two transboundary fish stocks where each country derives utility from harvest as well as stock existence. Each country also has the ability to alter environmental quality, affecting spawning success of salmon. A set of policies which, despite the non-cooperative tendencies of both nations, aims to induce, and maintain a cooperative outcome is derived. These policies consist of harvest taxes coupled with environmental quality subsidies.
590 $a School code: 0028.
650 4 $a Agriculture, Fisheries and Aquaculture. $3 1020913
650 4 $a Economics, Agricultural. $3 626648
690 $a 0503
690 $a 0792
710 2 0 $a University of California, Berkeley. $3 687832
773 0 $t Dissertation Abstracts International $g 61-07A.
790 $a 0028
790 1 0 $a Berck, Peter, $e advisor
791 $a Ph.D.
792 $a 2000
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9979597