Table 3 Statistical summary of the main vessel variables VARIABLE 1997 1998

# Table 3 statistical summary of the main vessel

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Table 3. Statistical summary of the main vessel variables VARIABLE 1997 1998 1999 Mean S.D. Mean S.D. Mean S.D. No. of fishing days 50.76 33.45 41.02 29.79 17.13 12.28 Capacity in GRT 7.48 8.02 6.31 4.27 6.18 3.94 Capacity in GT 7.10 7.12 6.21 5.25 6.22 5.20 Length 8.31 2.22 8.04 1.77 8.09 1.65 Power in HP 72.94 49.99 67.48 38.31 66.84 37.29 Age in years 29.63 16.32 30.59 16.61 32.53 16.99 No. of crew members 3.76 1.72 3.49 1..30 3.52 1.37 No. of vessels 143 127 107 Source: Own elaboration based on the fleet census of the SGPM 7 and the crew members statistics from the ISM 8 . The number of fishing days will be considered a variable productive input in each year. In addition to the above variables, there were other variables which were taken into account such as usual port of the vessel, the fishing gear and the invested amount of money in the last ten years. The usual port of the vessel and the fishing gear were incorporated in the model by means of dummy variables and the invested amount of money was included in the model through a monetary variable. In the latter variable, we have differentiated between new-built and modernized vessels. All this information has been got from the investement aid applications handed to DGP. None of the last three variables (usual port, fising gear and investment in the last ten years) were significant from a statistical point of view. Table 3 shows a statistical summary of the main vessel variables. Theoretical background 7 SGPM: Secretaría General de Pesca Marítima, which depends on the Ministry of Agriculture, Food and Fisheries, Spain. 8 ISM: Instituto Social de la Marina. 4
As the production theory states, the production function is defined as the relationship between the quantity of inputs which are used for each vessel and the catch per unit of time. It is obvious that each vessel can modify its output changing the quantities of the inputs. Each vessel will try to apply the most efficient production technique so that it does not incur any unnecesary expenses. However, in the fishing activity there is an input which is not under control of the fishermen: the exploited stock. In current literature about bioeconomic models of fisheries, only two productive inputs are considered in the fishing activity, that is, fishing effort and stock. While the latter variable has a clear interpretation (the higher the stock density is, the larger the catch is), the former has a more difficult interpretation and determination. From a biological point of view, the fishing effort is strongly linked to the fishing mortality. The fishing mortality is usually defined for each vessel as the multiplication of the fishing time by the individual fishing power [Beverton & Holt (1957)]. Nonetheless, the fishing power is not clearly defined because it depends on the technology and the exploited stock features. Intuitively, it is understood that the individual fishing power must be a function of capital and labour force inputs used by each vessel.

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