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Balancing goods and bads: A Bayesian analysis of fishery regulatory decisions

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  • This paper examines the regulatory decision problem facing fishery managers tasked with balancing desirable fish catch with undesirable bycatch. I approach the problem using Bayesian decision analysis. I first estimate a model of production, accounting for the fishery’s joint production of desirable and undesirable outputs. I then use the estimated model parameters to evaluate the expected utility maximization problem facing fishery regulators. The primary limitation to evaluating this problem is that bycatch is not priced in society. To address this, I develop an innovative method that uncovers the implicit price of bycatch assuming observed regulations were set optimally. I then apply this method to evaluate full set of possible regulatory decisions, providing a guide for regulators to make optimal decisions conditional on the value of bycatch. I fit the model to panel data from Hawaii's longline fishery collected for 204 vessels operating between 2004 and 2013. Results indicate observed sea turtle regulations from 2004-2009 imply large social values for sea turtle bycatch, in the range of $5.1 million per leatherback, and $4.9 million per loggerhead caught. These implied social values provide critical information to guide decision-makers toward setting optimal fishery regulations that maximize net social value.
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  • Seattle, Washington, USA
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