DETERMINANTS OF INEFFICIENCY IN NORWEGIAN SALMON AQUACULTURE

Abstract

This article builds on the literature investigating productivity and efficiency in the Norwegian salmon farming industry. The objective of this article is to investigate the determinants of inefficiency. We use a stochastic frontier approach that allows the estimation of a production function and an inefficiency function. The sources of inefficiency can be separated into temporary shocks and factors that lead to permanent efficiency differences. The results indicate an improvement in technical efficiency over time. This improvement can partly be explained by a restructuring of the industry, with firms becoming bigger and more specialized, as well as by improvements in government regulations. The inefficiency that is still present is mainly the result of temporary shocks. Disease outbreaks seem to be the most important of these temporary shocks, as disease problems lead to early harvesting or destruction of the fish and thereby, obviously, increase inefficiency.

Keywords:

• efficiency
• Norway
• Salmon farming
• stochastic frontier approach

ACKNOWLEDGMENTS

Thanks to Ragnar Tveteras and two reviewers for helpful comments, and to the Norwegian Research Council and the Norwegian Seafood Research Fund for financial support. Any errors or views expressed in this article are solely the responsibility of the authors.

Notes

Standard deviation in parentheses.

**Significant at the 1% level.

Salmon trout (Oncorhynchus mykiss) is a large rainbow trout and is also known as steelhead.

Hassanpour et al. (2010, 2011) provide evidence of productivity development in trout farming in Iran.

A non-parametric data envelope analysis approach (DEA) could also have been used to investigate this issue. However, the DEA approach is deterministic, so any deviations from the production frontier are attributed to inefficiency. As salmon farmers are exposed to shocks from biophysical factors, allowing for stochasticity seems appropriate.

It is well documented that there is a global market for salmon (Asche et al., 2002; Asche et al., 2005; Tveteras & Asche, 2008; Asche et al., 2012; Tveteras et al., 2012) and there is no evidence of market power being exploited (Jaffry et al., 2003; Asche et al., 2011). Accordingly, the price can be regarded as exogenous for each individual farmer.

See Asche et al. (1999), Tveterås (2002), Liu and Sumaila (2010) and Torrissen et al. (2013) for discussions of environmental interactions from an economic perspective, and Oglend and Tveteras (2009) for a more risk-oriented perspective.

Since 1973, a license has been required to operate a salmon farm in Norway.

A likelihood-radio test was performed to test if a Cobb–Douglas specification could fit the model. This test is distributed as χ²(20), and with a test statistic of 346.63 and a P-value of less than 0.001, the null hypothesis is clearly rejected.

A production function with a single output is specified, as several studies have shown that the generalized composite commodity theorem holds for different species of salmon (Asche & Guttormsen, 2001; Asche et al., 2005).

There is a long history of diseases in Norwegian and global salmon farming. Asche (1997) relates the main disease outbreaks to production costs in Norway up to 1997, while Asche et al. (2009) and Hansen and Onozaka (2011) discuss the main disease crises after the turn of the century, with particular focus on the major crises in Chile in 2009–2010.

Stata 11 was used for the estimation.

A likelihood-radio test was performed to test if the region-specific variables were superfluous. This test was rejected with a LR χ²(10) statistic of 62.41 and a P-value of less than 0.001.

The category consisting of firms that have farms in several counties is not found to be significantly different from Hordaland. However, comparing this group to the rest of the regions is problematic, as the group consists of firms mainly established after 1992. Until 1992, the government restricted the major ownership to a maximum of one license.

These results also highlight the importance of the concerns raised by Hermansen and Heen (2012) in relation to potential climate effects.

It is of interest to note that this is very much higher than the efficiency score of the Norwegian fishing fleet, at 24.1% (Guttormsen & Roll, 2011). While productivity growth is higher in aquaculture than in traditional fisheries, it is important to note that also there productivity growth and inefficiency is highly important (Squires and Vetstergaard, 2013).

It is of interest to note that the volatility of the salmon price has been increasing over time (Oglend & Sikveland, 2008; Solibakke, 2012). This also has implications for the forecastability of the salmon price (Guttormsen, 1999) and optimal harvesting (Guttormsen, 2008), and is relevant for other species such as tuna (Shamshak, 2011).

It is interesting to note that this also benefited Alaskan wild salmon fishermen, as indicated by Williams et al. (2009) and Valderrama and Anderson (2010).