(10) C = 0.4977 £■ - 0.1539 £"2 /?2 = o.98 

 (4.3) (-4.0) D-W = 3.0 



+ 690.9 T + 6.43 B SEE = 322 



(5.7) (1.8) 



(11) C 



= 0.6584 E - 0.2129 E- R- = 0.98 



(13.5) (-10.3) D-W = 2.5 



+ 582.2 7 + 0.215 "C SEE = 360 



(5.9) (1.6) 



Where: 



C 

 E 

 T 



L 

 B 

 V 



= Total landings 



= Fishing effort 



= Technological change, labor 

 skills (1961, T = 1; 1962, 

 T = 2; 1963, T = 3; etc.) 



= Labor employed in the fishery 



= Adult bird population 



= Dummy variable: closed sea- 

 son 1' = ; open season V' = 1 



= Temperature of water in 

 Trujillo, Peru 



Due to the fact that the theoretical Schaefer 

 model does not include a constant term, the 

 estimations of the f-values of the coefficients 

 presented above are biased upwards. However, 

 in regressions having the constant term in it, 

 it happens that this constant term is not 

 significant in any regression (f-value around 

 0.2). The difference between coefficients of 

 regressions with and without the constant term 

 is not significant, since in all cases this dif- 

 ference is less than 0.4 standard deviations of 

 the coefficients. 



In all regressions having the constant term, 

 the variable technological change (T) is sta- 

 tistically significant at the 1% level of signifi- 

 cance. In the equations presented above, even 

 though the f-values are biased upwards, the 

 variables labor size (L), veda seasons {V), bird 

 population (B), and temperature (°C) are not 

 statistically significant. However, the impor- 

 tance of technological change ( T) alone is such 

 that its introduction into equation (7) is suf- 

 ficient to improve substantially the coefficient 

 of determination of the equation from 0.84 in 

 equation (6) to 0.97 in equation (7). Also the 

 Durbin-Watson statistics (1.8) are now in the 

 acceptable range (1.6-2.4). 



Using expression (5) on page 61 we can 

 obtain the optimal level of fishing effort in terms 

 of the efficiency of 1969 vessels. Equation (7) 



gives 16.2 million ton-trips as the optimal level 

 of fishing effort. Equations (8) to (11) give the 

 following values for optimal effort in terms of 

 million ton-trips: 15.2, 16.0, 16.0. and 15.0, 

 respectively. All these estimates are in close 

 agreement, but differ markedly from the value 

 of 23 million ton-trips obtained by Schaefer 

 (1970). and from equation (6). However, because 

 of the statistical significance of the variable "T" 

 in equation (7). the high autocorrelation in 

 equation (6). and the theoretical appeal of the 

 procedure, it seems that the value of 16.2 

 million ton-trips is closest to the true optimal 

 level of fishing effort. Also, this value makes 

 more sense in terms of the data presented in 

 Table 1. In this table we can see that in 1962- 

 1963, with vessels of less efficiency than those 

 existing today, 11.8 million ton-trips produced 

 6.9 million metric tons of landings. A simple 

 extrapolation would indicate that 8.8 million 

 tons offish could be landed by 18.3 million ton- 

 trips of vessels with 1963 efficiency levels. 



CONCLUSIONS 



The method presented here appears useful 

 in obtaining an unbiased estimation of the 

 optimal level of fishing effort in a fishery. It 

 adequately considers the effect of several signifi- 

 cant inputs that cannot be directly introduced 

 into the traditional measure of fishing effort. 

 Using this procedure, the optimal level of fishing 

 effort in the Peruvian fishery is 16.2 million 

 ton-trips, or only 68% of the level of effort used 

 in Peru in 1968-1969. This result has clear 

 implications for the management of the Peruvian 

 fishing industry. 



LITERATURE CITED 



BOEREMA. L. K., et al, 1961. Report on the Effects of 

 Fishing on the Peruvian Stock of Anchovy. F.'^O 

 Fisheries Technical Paper Number 55. Rome. 



GULLAND, J. A., 1961. Fishing and the .Stock of Fish 

 in Iceland. Ministry of Agriculture, Fisheries and Food. 

 United Kingdom. 



GULLAND, J. A., 1968. Report on the Population 

 Dynamics of the Peruvian Anchoveta. FAO Fisheries 

 Technical Paper Number 72. Rome. 



Institute del Mar del Peru, Lima. 1970. Resumen General 

 de la Pesqueria, 1970. 



63 



