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Basque inshore skippers' long term behaviour: a logit approach

Published online by Cambridge University Press:  09 October 2008

Ikerne del Valle
Affiliation:
Department of Applied Economics V, University of The Basque Country, Avda. Lehendakari Agirre No. 83, 48015 Bilbao, Spain
Kepa Astorkiza
Affiliation:
Department of Applied Economics V, University of The Basque Country, Avda. Lehendakari Agirre No. 83, 48015 Bilbao, Spain
Inmaculada Astorkiza
Affiliation:
Department of Applied Economics V, University of The Basque Country, Avda. Lehendakari Agirre No. 83, 48015 Bilbao, Spain
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Abstract

Based on the discrete optimal choice theory and a random utility model (RUM) framework, this paper focuses on the firm's long-term choices. A behavioural study on the stay and exit decisions of the fishing firms belonging to the inshore fleet of the Basque Country is undertaken by estimating a logistic model from a set of socio-economical sample panel data for the period 2003-04. Specifically, we aim to determine the set of vessels', skippers' and economic variables that may influence the probability of a fishing vessel to exit from the fishing activity. Special attention will be paid to the roll that incentives generated by decommissioning grants play in the fishermen's long-term behaviour. Our results indicate that the owner's age, years of experience being a skipper, the arrangement of continuity in the familiar business, the degree of dependency upon bank loan and lastly but not least decommissioning grants may significantly determine the decision to abandon the activity.

Type
Research Article
Copyright
© EDP Sciences, IFREMER, IRD, 2008

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References

Agresti A., 1996, An Introduction to Categorical Data Analysis. John Wiley and Sons, Inc.
Belsey D., Kuh E., Welsch R., 1980, Regression Diagnostics, John Wiley and Sons, New York.
Berk, P., Perloff, J.M., 1984, An open-access fishery with rational expectations. Econometrica. 52, 489506. CrossRef
Bjorndal, T., Conrad, J.M., 1987, The dynamics of an open access fishery. Can. J. Econ. 20, 7485. CrossRef
Bockstael, N.E., Opaluch, J.J., 1983, Discrete modelling of supply response under uncertainty: The case of the fishery. J. Environ. Econ. Manage. 10, 125137. CrossRef
Bockstael, N.E., Opaluch, J.J., 1984, Behavioural modelling and fisheries management. Ma. Resour. Econ. 1, 105115.
Boyce, J.R., 1995, Optimal Capital accumulation in a fishery: a nonlinear irreversible investment model. J. Environ. Econ. Manage. 28, 324339. CrossRef
Clark, C.W., Clark, F.H., Munro, G.R., 1979, The optimal exploitation of renewable resource stocks: problems of irreversible investment. Econometrica 47, 2547. CrossRef
del Valle, I., Astorkiza, I., Astorkiza, K., 2001, Is the current regulation of the VIII division European anchovy optimal? Environ. Resour. Econ. 19, 5372. CrossRef
del Valle, I., Astorkiza, I., Astorkiza, K., 2003, Fishing effort validation and substitution possibilities among components: The case study of the VIII division European anchovy fishery. Appl. Econ. 35, 6377. CrossRef
del Valle I, Astorkiza I., Astorkiza K., 2008, Prestige's oil spill and its economic effects in the Basque coastal fleet. Communication presented at the XXII ASEPELT Conference, Barcelona.
Hensher D.A., Johnson L.W., 1981, Applied Discrete Choice Modelling. John Wiley.
Hosmer D.W., Lemeshow S., 1989, Applied Logistic Regression. John Wiley & Sons.
Ikiara, M.M., Odink, J.G., 2000, Fishermen resistance to exit fisheries. Mar. Resour. Econ. 14, 199213. CrossRef
Greene W., 2000, Econometric Analysis. 4th ed. Prentice-Hall. New Jersey.
Kirkley, J., Squires, D., Strand, I.E., 1998, Characterizing managerial skill and technical efficiency in a fishery. J. Product. Anal. 9, 14560. CrossRef
McFadden D., 1973, Conditional logit analysis of qualitative choice behaviour. Frontiers in Econometrics.Zarembka (Ed.), New York, Academic Press.
Mackinson, S., Sumaila, U.R., Pitcher, T.J., 1997, Bioeconomics and catchability: fish and fishers behaviour during stock collapse. Fish. Res. 31, 1117. CrossRef
McKelvey, R., 1985, Decentralized regulation of a common property renewable resource industry with irreversible investment. J. Environ. Econ. Manage. 12, 287307. CrossRef
Menard S., 2001, Applied Logistic Regression Analysis. Sage Publications. Ser. Quantitative Applications in the Social Sciences, No. 106.
Pascoe, S., Revill, A., 2004, Costs and benefits of bycatch reduction devices in European brown shrimp trawl fisheries. Environ. Resour. Econ. 27, 4364. CrossRef
Pradhan, N.C. Leung, P., 2004, Modeling entry, stay, and exit decisions of the longline ?shers in Hawaii. Mar. Policy. 28, 311324. CrossRef
Raftery A.E., 1995, Bayesian model selection in social research. In: Marsden P.V. (Ed.), Sociological Methodology. London: Tavistock, pp. 111–163.
Silva L.C., Barroso I.M., 2004, Regresión logística. Cuadernos de Estadística. Editorial La Muralla, Hesperides.
Squires, D., Kirkley, J., 1999, Skipper skill and panel data in fishing industries. Can. J. Fish. Aquat. Sci. 56, 20112018. CrossRef
Ward, J.M., Sutinen, J.G., 1994, Vessel entry-exit behaviour in the Gulf of Mexico shrimp fishery. Am. J. Econ. 76, 916923. CrossRef