Optimally Managing a Stochastic Renewable Resource under General Economic Conditions

Bruce McGough 1 , 1 , Andrew J. Plantinga 2 , 2  and Christopher Costello 3 , 3
  • 1 Oregon State University, bruce.mcgough@oregonstate.edu
  • 2 Oregon State University, plantinga@oregonstate.edu
  • 3 University of California, Santa Barbara, costello@bren.ucsb.edu

Abstract

Empirical evidence indicates that environmental fluctuations have important effects on fisheries production. However, existing analytical solutions of stochastic fisheries models have been produced only under highly simplified economic and biological conditions. The main contribution of this paper is to derive under general conditions a policy function for the management of a stochastic fishery. Our model includes general specifications of demand and cost relationships and a stochastic biological growth function with serially-correlated shocks. Applying methods from the theory of dynamic stochastic general equilibrium modeling and multivariate linear expectational difference equations, we derive a linear approximation of the solution to the model. Our main result is a reduced-form expression for an approximation to optimal escapement, which is shown to be a function of the current stock, past environmental shocks, and model parameters. This theoretically-grounded policy function has intuitive appeal, yields insights into comparative statics, and provides a theoretically-grounded, practical starting point for fisheries management.

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The B.E. Journal of Economic Analysis & Policy (BEJEAP) is an international forum for scholarship that employs microeconomics to analyze issues in business, consumer behavior and public policy. Topics include the interaction of firms, the functioning of markets, the effects of domestic and international policy and the design of organizations and institutions.

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