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Bayesian modelling of catch in a Northwest Atlantic Fishery

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  • Carmen Fernandez
  • E. Ley
  • M. F. J. Steel

Abstract

This paper deals with the issue of modelling 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 (EU) in the context of the Northwest Atlantic Fisheries Organization (NAPO). 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 26 possible regressors, resulting in a set of 44 million possible linear regression models for the log of catch. Zero observations are treated separately through a probit model. Prediction of future cathes and poster/or inference will be based on Bayesian model averaging, using a Markov chain Monte Carlo approach. Particular attention is paid to prediction of catch for single and aggregated observations.

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Bibliographic Info

Paper provided by Edinburgh School of Economics, University of Edinburgh in its series ESE Discussion Papers with number 67.

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Date of creation: Apr 2004
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Handle: RePEc:edn:esedps:67

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References

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  1. Carmen Fernández & Eduardo Ley & Mark F. J. Steel, . "Benchmark priors for Bayesian Model averaging," Working Papers 98-06, FEDEA.
  2. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
  3. Min, C.K. & Zellner, A., 1992. ""Bayesian and Non-Bayesian Methods for Combining Models and Forecasts with Applications to Forecasting International Growth Rates"," Papers 90-92-23, California Irvine - School of Social Sciences.
  4. Eva Ferreira & Fernando Tusell, 1996. "Un modelo aditivo semiparamétrico para estimación de capturas: el caso de las pesquerías de Terranova," Investigaciones Economicas, Fundación SEPI, vol. 20(1), pages 143-157, January.
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Cited by:
  1. Babatunde Abidoye & Joseph Herriges, 2012. "Model Uncertainty in Characterizing Recreation Demand," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 53(2), pages 251-277, October.
  2. Irwin Guttman & Daniel Peña & M Dolores Redondas, 2003. "A Bayesian Approach for Predicting with Polynomial Regresión of Unknown Degree," Statistics and Econometrics Working Papers ws032104, Universidad Carlos III, Departamento de Estadística y Econometría.
  3. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
  4. Theo Eicher & Jeff Begun, 2008. "In Search of a Sulphur Dioxide Environmental Kuznets Curve: A Bayesian Model Averaging Approach," Working Papers UWEC-2007-19-P, University of Washington, Department of Economics.

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