Hierarchical Analysis of Production Efficiency in a Coastal Trawl Fishery

Abstract

We present, pedagogically, the Bayesian approach to composed error models under alternative, hierarchical characterizations; demonstrate, briefly, the Bayesian approach to model comparison using recent advances in Markov Chain Monte Carlo (MCMC) methods; and illustrate, empirically, the value of these techniques to natural resource economics and coastal fisheries management, in particular. The Bayesian approach to fisheries efficiency analysis is interesting for at least three reasons. First, it is a robust and highly flexible alternative to commonly applied, frequentist procedures, which dominate the literature. Second, the Bayesian approach is extremely simple to implement, requiring only a modest addition to most natural-resource economist tool-kits. Third, despite its attractions, applications of Bayesian methodology in coastal fisheries management are few.

Copies of computer code used to process the data in this study are available from David Tomberlin at: David.Tomberlin@noaa.gov. We are grateful to several colleagues with whom we enjoyed discussions. Siddhartha Chib, Gary Koop and Bill Greene, in particular, deserve special thanks. We are also highly indebted toWilliam Daspit and Brad Stenberg of the Pacific States Marine Fisheries Commission who were extremely helpful with data access and interpretation. Responsibility for error remains ours.