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Efficiency data analysis in EU aquaculture production

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This paper analyses the operational efficiency of fish farming across EU Member States using a two-stage Data Envelopment Analysis (DEA) approach. In the first stage, a non-oriented Slacks-Based Measure of efficiency (SBM) DEA model is used to compute efficiency scores in marine and freshwater finfish and shellfish aquaculture subsectors for different EU countries during the period 2014–2016. In a second stage, these scores are processed by standard, censored and fractional regression models to test the effects of some exogenous variables. Between 57% and 74% of the observations, depending on the subsector considered, were efficient. The average technical efficiency was 0.918 for freshwater finfish, 0.885 for marine finfish and 0.802 for shellfish. Extending the best practices to the inefficient countries would involve a reduction of feed costs (2.9% - 4.3%), livestock costs (9.0% - 11.8%), energy costs (2.4% - 25.3%), repairing costs (3.7% - 13.8%) and other operating costs (4.3% - 13.8%) at the same time that an improvement in production value totalling 0.03% for freshwater finfish, 2.13% for marine finfish and 0.37% for shellfish. As regards productivity change in the period under study, there has been a productivity regress in the case of freshwater finfish, productivity increase in the case of marine finfish and an initial productivity increase between 2014 and 2015 followed by a slight decrease between 2015 and 2016 in the case of shellfish. Results also indicate that countries specializing in cultivating freshwater and marine populations are more likely to be on the efficient frontier and that technical efficiency seems to be influenced by the size of the country's gross domestic product and capture fisheries.
2020-01-22
ELSEVIER SCIENCE BV
JRC111668
0044-8486 (online),   
https://www.sciencedirect.com/science/article/pii/S0044848619314097?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC111668,   
10.1016/j.aquaculture.2020.734962 (online),   
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