Optimally Managing a Stochastic Renewable Resource under General Economic Conditions

Bruce McGough (), Plantinga Andrew J. () and Christopher Costello
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Plantinga Andrew J.: Oregon State University

The B.E. Journal of Economic Analysis & Policy, 2009, vol. 9, issue 1, 31

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.

Keywords: dynamic stochastic general equilibrium; fisheries management; renewable resources; stochasticity (search for similar items in EconPapers)
Date: 2009
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DOI: 10.2202/1935-1682.2313

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