Abstract
In recent years, European producers of cultured sea bass and sea bream have experienced a highly competitive market with low prices that have caused profitability challenges. An important factor of economic competitiveness for firms is to produce efficiently. In this paper, technical efficiency of European producers of cultured sea bass and sea bream is evaluated for the period 2008–2017 using the stochastic production frontier (SPF) approach. In addition, the effect of a set of specific-firm factors on firms’ efficiency is investigated. The majority of firms in the sample were found to have a technical efficiency over 90% with Cypriot and Greek firms being, on average, the most efficient. We also found evidence that the technical efficiency of these firms is positively related to their size. Moreover, the high degree of average efficiency means that further production growth requires innovations that move up the production frontier.
Notes
1 Some authors who have applied the SPF approach in the aquaculture industry are Ara et al. (Citation2004), Asche and Roll (Citation2013), Dey et al. (Citation2000), Dey et al. (Citation2005), Iinuma et al. (Citation1999), Islam et al. (Citation2016), or Tveteras and Battese (Citation2006). On the other hand, authors who have employed the DEA approach are Alam (Citation2011), Alam and Murshed-e-Jahan (Citation2008), Bozoglu et al. (Citation2006), Cinemre et al. (Citation2006), Kaliba and Engle (Citation2006), Ngoc et al. (Citation2018), or Sharma et al. (Citation1999).
3 This variable can be a proxy for possible differences in general biophysical and environmental conditions (Tzouvlekas et al., Citation2001). For example, the average temperature of the sea, which is higher in the East Mediterranean Sea, is a recognized factor that influences positively on fish growth (Llorente & Luna, Citation2013).
4 The inverse of income was used instead of income directly, or other transformations (logarithmic or power), because it has been the only option to obtain the parameter estimates of our model since the estimation method required a convergence of the different solutions (iterative process).
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Funding
This work was supported by Horizon 2020 Framework Programme [GA727315].
http://orcid.org/0000-0002-1042-7572
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