Statistical Modeling of Fishing Activities in the North Atlantic

Carmen Fernandez, Eduardo Ley and Mark Steel ()
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Carmen Fernandez: CentER and Dept of Econometrics/Tilburg University/The Netherlands

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Abstract: This paper deals with the issue of modeling daily catches of fishing boats in the Grand Bank fishing grounds. We have data on catches per species for a number of vessels collected by the European Union in the context of the North Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics ---such as the size of the ship, the fishing technique used, the mesh size of the nets, etc.---, are obvious candidates, but one can also consider the season or the actual location of the catch. In all, our database leads to 23 possible regressors, resulting in a set of $8.4\times 10^6$ possible linear regression models. Prediction of future catches and posterior inference will be based on Bayesian model averaging, using a Markov Chain Monte Carlo Model Composition (MC$^3$) approach. Particular attention is paid to the elicitation of the prior and the prediction of catch for single and aggregated observations.

Keywords: Bayesian model averaging; Grand Bank fisheries; Predictive inference; Prior elicitation (search for similar items in EconPapers)
JEL-codes: C11 C15 (search for similar items in EconPapers)
Date: 1997-12-04
Note: Type of Document - Acrobat PDF 3.0; prepared on Textures 1.7, MacOS 8, Acrobat Distiller 3.0; to print on any printer; pages: 22; figures: included. (Data and code will be posted shortly.)
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Related works:
Working Paper: Statistical modeling of fishing activities in the North Atlantic
Working Paper: Statistical modeling of fishing activities in the North Atlantic (1997)
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Persistent link: http://EconPapers.repec.org/RePEc:wpa:wuwpem:9712001

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