Fisheries management with stock growth uncertainty and costly capital adjustment

Abstract

We develop a dynamic model of a fishery which simultaneously incorporates random stock growth and costly capital adjustment. Numerical techniques are used to solve for the resource-rent-maximizing harvest and capital investment policies. Capital rigidities bring diminishing marginal returns to the current period harvest, and introduce an incentive to smooth the catch over time. With density dependent stock growth, however, catch smoothing increases stock variability resulting in reduced average yields. The optimal management policy balances the catch smoothing benefits against yield loss. We calibrate the model to the Alaskan pacific halibut fishery to demonstrate the main insights.

Fleet Restructuring, Rent Generation, and the Design of Individual Fishing Quota Programs: Empirical Evidence from the Pacific Coast Groundfish Fishery

“…For example, it may not be worth investing in additional capital in the event of moderately favorable but nonpermanent stock conditions. It may be preferable to increase the harvest per boat and incur a moderate increase in per-vessel average harvest costs in order to save capital adjustment costs (Singh, Weninger, and Doyle 2006). …”

“…An important focus of our analysis is the implications of the IFQ program design on the composition of the fishing fleet and the resource rents that are generated in the fishery. The conceptual approach follows recent work by Weninger and Waters (2003) and Singh, Weninger, and Doyle (2006). We first estimate cost inefficiency in 2003-04 cost data collected from groundfish vessels under the controlled access program.…”

“…Our model of dynamic fleet adjustment closely follows Singh, Weninger, and Doyle (2006). The dynamic program is summarized by the following Bellman equation:…”

“…and then iterating it to convergence (Judd 1998). The reader can also refer to Singh, Weninger, and Doyle (2006) for technical details.…”

“…The conceptual approach follows recent work by Weninger and Waters (2003) and Singh, Weninger, and Doyle (2006). In a first step, we use data on operating expenses and catch of groundfish vessel operations to estimate the cost inefficiency under the current management program and calibrate vessel level harvesting costs for simulation purposes.…”