Community Research and Development Information Service - CORDIS

Multi-output technical efficiency measure analysis and results

When the scores of single output SPF analysis and multiple-output DEA analysis are compared, the effect of random error is reduced and the TE scores are closer in magnitude than when single output SPF and DEA results are compared. This is due to the fact that the multiple-output measures provide several pieces of output information against which each vessels' activity can be ranked to determine where the efficient frontier lies and how each vessel compares to it, given its input level. In comparison, the single-output measures contain information on only one output. For example, in an analysis involving single-output measures, if one vessel caught very large amounts of one species whilst other vessels fishing the same gear in the same month caught 'normal' amounts of this species (and all vessels caught normal amounts of other species), the other vessels would be ranked much less efficient if a single-output measure is used as compared to a multi-output measure. In this situation, a multi-output measure would determine that the other vessels caught normal amounts of the other species, but were just not as lucky to catch so much of the high value species. Thus their DEA scores would be higher and more accurate under the multi-output measure analysis, as compared to the single-output measure. Consequently, the greater level of information available in the multi-output analyses enables a more accurate estimation of efficiency scores.

Another possible explanation for the higher estimates with multi-outputs may be related to the estimation process. With a single output measure, the boat's performance is compared to the boat that has the highest overall level of output (catch) irrespective of the composition of the catch. When the multiple outputs are considered, boats are compared with other boats that have a similar catch composition. As a result, the boats appear to be more efficient when compared with other boats with similar catch compositions (which are undertaking similar activities) than when compared to the boat with the greatest overall catch irrespective of catch composition (and may be undertaking quite different activities). The number of observations available largely limits the number of outputs that could potentially be included in the analyses, as too few degrees of freedom in the data results in inflated TE scores.

A number of new techniques were also applied. These included an analysis of mix efficiency using DEA, a methodology for deriving output specific measures of technical change in multi-output industries such as fishing, and the use of multi-output stochastic frontier models. As well as providing information on the distribution of efficiency in the fisheries, the results of the analyses provided interesting insights into the operation of the fisheries examined, including distortions in input use as a result of input controls, and the potential for output substitution in multi-species fisheries (i.e. the degree to which fishers can alter their output mix).

Multi-output analyses were undertaken by all project partners. The multi-output DEA results were compared with the single output efficiency estimates from SPF and DEA and the results are described in Pascoe, S., Tingley, D. and Mardle, S. (Eds) 2003 'Single output measures of technical efficiency in EU fisheries', CEMARE Report 61, CEMARE, University of Portsmouth, UK.

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University of Portsmouth
Locksway Road
PO4 8JF Southsea
United Kingdom
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