A Dynamic Approach to Catch–Effort Data Analysis using a New Concept: the Inertia of the Stock

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Abstract
The steady-state hypothesis assumed in the classical production models, or catch–effort data analysis, is unrealistic in normal fisheries, and dynamic production models have been developed in order to avoid such a hypothesis. In this paper a dynamic approach to production models is presented. This approach does not alter the classical equilibrium curves. It permits us to estimate their parameters from nonequilibrium fisheries data and to describe the trajectories followed by the fishery in the catch–effort plane, so it predicts catches, it has a 1-yr memory and introduces a new meaningful parameter, called inertia, representing the stock's resistance to changes in fishing effort. The approach is applied to two different sets of historical catch–effort data, and compared with the classical one showing an improvement in the fit.

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