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Combining performance measures to investigate capacity changes in fisheries

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  • Thomas T. Thøgersen
  • Sean Pascoe

Abstract

The Common Fisheries Policy (CFP) aims to achieve a balance between the European fleet capacity and the resources available. This can be realized either by temporarily reducing the fishing effort (i.e. capacity utilization) or quotas in the hope of increasing the resources available or reducing the actual fishing capacity. In both cases, the relationship between effort indicators and capacity needs to be resolved in order for the manager to introduce the right interventions. Previous studies have estimated these relationships in multi-species fisheries using either a multi-output distance function approach (DFA) or with a second stage Data Envelopment Analysis (DEA). Both approaches have advantages and disadvantages. In this article, DEA and DFA are combined to reduce noise in the estimation and to establish more useful interpretations for the manager. The article compares the traditional DFA with the alternative approach for the Danish North Sea demersal trawlers. The alternative approach improves the estimation results and provides better estimates of efficiency scores, compared to the unadjusted DFA. Furthermore, the analyses suggest that the demersal trawlers have a limited ability to substitute catches of cod, plaice and Nephrops and that gross tonnage is a more consistent indicator of fishing capacity than engine power.

Suggested Citation

  • Thomas T. Thøgersen & Sean Pascoe, 2014. "Combining performance measures to investigate capacity changes in fisheries," Applied Economics, Taylor & Francis Journals, vol. 46(1), pages 57-69, January.
  • Handle: RePEc:taf:applec:v:46:y:2014:i:1:p:57-69
    DOI: 10.1080/00036846.2013.829203
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    Cited by:

    1. Yao-yao Song & Xian-tong Ren & Guo-liang Yang, 2023. "Capacity utilization change over time," Journal of Productivity Analysis, Springer, vol. 59(1), pages 61-78, February.
    2. Song Wang & Caizhi Sun & Xin Li & Wei Zou, 2016. "Sustainable Development in China’s Coastal Area: Based on the Driver-Pressure-State-Welfare-Response Framework and the Data Envelopment Analysis Model," Sustainability, MDPI, vol. 8(9), pages 1-19, September.
    3. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    4. Fukuyama, Hirofumi & Song, Yao-yao & Ren, Xian-tong & Yang, Guo-liang, 2022. "Using a novel DEA-based model to investigate capacity utilization of Chinese firms," Omega, Elsevier, vol. 106(C).

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