FISHERY BULLETIN: VOL. 71, NO. 4 



For any particular fishery, the accuracy of data 

 on aggregate annual landings is fairly reliable. 

 However, the number of fishermen reported by 

 the National Marine Fisheries Service is not 

 adjusted for the extent of utilization during the 

 year. For example, the U.S. Bureau of Labor 

 Statistics collects detailed data on hours worked 

 for most industries in the economy. This makes 

 it possible to compute productivity on the 

 output per man-hour basis. No universally com- 

 parable data are available on the fishing indus- 

 try. Hence, our statistical base is something less 

 than perfect .4 Systematic variations in days and 

 hours worked per year may be a biasing factor, 

 but it is hoped that they are random. In addition, 

 the reader should note that we are comparing 

 rates of growth in productivity among fisheries 

 and other industries and not absolute differ- 

 ences in productivity. 



Table 1 shows the compound annual growth 

 rate of labor productivity for 17 of the nation's 

 major fisheries over the 1950-69 period.^ Notice 

 that the Gulf of Mexico blue crab, Atlantic clam, 

 and Gulf of Mexico menhaden fisheries all had 

 rates of productivity advance over 5% . Unfor- 

 tunately, some of our largest fisheries such as 

 Gulf of Mexico shrimp, Atlantic sea scallop, 

 Atlantic and Gulf of Mexico oysters, and 

 Alaskan salmon exhibited negative trends in 

 productivity. 



One interesting aspect of the growth in labor 

 productivity is its year-to-year fluctuation. This 

 is important for a variety of reasons. Many 

 fishermen are paid according to the "lay" agree- 

 ment where fishermen and vessel owners share 

 the value of the catch on some predetermined 

 basis. Short-run oscillations in labor productiv- 



Table 1. — Ranking of fisheries by the rate of growth in 

 output per fisherman, 1950-69. 



' Linear least squares trends of the logarithms of output 

 pei fisherman. 



- Trend was statistically significant at the 5°o level. 



ity may contribute to an unstable earnings pat- 

 tern .*5 Other industries have fixed wage agree- 

 ments that depend on secular rather than short- 

 run changes in productivity. To get some idea of 

 which fisheries are more subject to oscillations 

 in labor productivity, we constructed an index 

 of instability which measures the percentage 

 fluctuations around the long-run time trend in 

 annual landings per fisherman." Table 2 shows 

 the 17 fisheries discussed earlier ranked accord- 

 ing to cyclical instability in labor productivity. 

 Using the most unstable as a base (i.e.. Gulf of 

 Mexico blue crab pot fishery), we see that 13 of 

 the fisheries have less than one-half the instabil- 

 ity of the base fishery. 



Although the performance of individual fish- 



sure of efficiency, but statisticians have trouble construct- 

 ing the index number that serves as the divisor. They have 

 to combine unHi^e quantities — hours of work and units 

 of capital investment — into a single index. And while 

 statisticians never hesitate to add apples to oranges, the 

 results are questionable. Economists, therefore, usually 

 work with a simpler concept, ""partial productivity." 

 This is the ratio of physical output to a single input, usual- 

 ly labor. In most discussions, "productivity" means "labor 

 productivity" or real output per hour, day, or year of 

 work. It IS a rough measure of the effectiveness with which 

 we use our most important productive resource-labor. 



^ See Appendix to this article on employment figures 

 in the U.S. fishing industry. 



■'' The growth rate in labor productivity was computed 

 by fitting a logarithmic function, i.e. fitting a linear time 

 trend to the logarithm of output per fishermen. The 17 

 fisheries represent 68, 71, and 58% by landings, value, and 

 employment, respectively, for the United States. 



'• Generally, a contraction in landings — due to a de- 

 cline in productivity — will reduce income per fisherman 

 if prices do not change appreciably. Prices may not in- 

 crease if foreign imports are significant and/or price 

 elasticity is large (i.e., a large percentage drop in landings 

 results in a small percentage increase in price). 



^ The formula used to construct the index was: 



N 



CV, 



i= 1 



N 



where CVy = cyclical variation in labor productivity; 

 Yo = observed labor productivity; Yc = computed 

 labor productivity from the time trend; and A' = number 

 of years. 



912 



