A tutorial on evaluating expected returns from research for fishery management using bayes' theorem

Abstract

Traditional methods for evaluating potential or actual returns from research and development include scoring methods, cost-benefit analysis and production-function approaches. The research reported in the present paper complements these traditional methods with the use of statistical decision analysis and Bayesian methods to account explicitly for risk and uncertainty and to capture some of the effects of information evolution. Measurement of the expected returns from research for fishery management is detailed. Both ex post and ex ante evaluation of expected returns are illustrated by deliberately simplified example. © 1997 Wiley Periodicals, Inc.