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Catch Efficiency in the Chilean Pelagic Fishery: Does size matter ?

This paper examines the determinants of technical efficiency for a sample of 204 industrial vessels operating in the Southern-Central pelagic fishery of Chile during the 1985-95 period. Data on vessel's annual landings and fishing effort, vessel's size, age, fishing experience and vessel's controlling firm are analysed considering a Translog stochastic frontier model à-la Battese-Coelli (1995), which includes a vessel-specific inefficiency model. Yearly averages for vessel efficiency vary from 50% to 86%. Close to 90% of the residuals' total variance is accounted by the inefficiency term, suggesting a significant disparity in vessels' catch performance. Vessel age and scale of operation are found to be significant in explaining efficiency. Larger vessels tend to be the most efficient and the ones showing least variance in their efficiency. Smaller vessels, which on average are also the oldest in the fleet, show greater dispersion and lower efficiency scores. We confirm prior results suggesting vessel-level economies of scale at this fishery, related to fishing effort intensity. Explanatory variables aggregated at the ship-owner level, which aim at controlling the firm's operating scale, are also significant as a whole when explaining vessel-level efficiency. We find positive search externalities associated to the number of vessels under control of a given firm, as well as external diseconomies related to each firm's fleet use. Overall, we report significant productive heterogeneity in the fleet under study where control variables associated to 'size effects' do indeed play a significant role.

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Paper provided by Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines in its series ILADES-Georgetown University Working Papers with number inv140.

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Handle: RePEc:ila:ilades:inv140
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  1. Tybout, James, 1998. "Manufacuring firms in developing countries - how well do they do, and why?," Policy Research Working Paper Series 1965, The World Bank.
  2. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
  3. Dale Squires, 1992. "Productivity Measurement in Common Property Resource Industries: An Application to the Pacific Coast Trawl Fishery," RAND Journal of Economics, The RAND Corporation, vol. 23(2), pages 221-236, Summer.
  4. Squires, Dale & Grafton, R. Quentin, 1998. "Where the Land Meets The Sea: Integrated Sustainable Fisheries Development and Artisanal Fishing," University of California at San Diego, Economics Working Paper Series qt93d6156d, Department of Economics, UC San Diego.
  5. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-48, September.
  6. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  7. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
  8. Lall, Somik V. & Rodrigo, G. Chris, 2001. "Perspectives on the Sources of Heterogeneity in Indian Industry," World Development, Elsevier, vol. 29(12), pages 2127-2143, December.
  9. Julio Peña & Michael Basch & Sebastián Vergara, 2003. "Eficiencia Técnica y Escalas de Operación en Pesca Pelágica: Un Análisis de Fronteras Estocásticas," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 40(119), pages 47-87.
  10. Salvatore Comitini & David S. Huang, 1967. "A Study of Production and Factor Shares in the Halibut Fishing Industry," Journal of Political Economy, University of Chicago Press, vol. 75, pages 366.
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