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Economic weights from profit equations: appraising their accuracy in the long run

Published online by Cambridge University Press:  02 September 2010

P. R. Amer ,
G. C. Fox  and
C. Smith
P. R. Amer
Affiliation:
Department of Animal and Poultry Science, University of Guelph, Ontario N1G2W1, Canada
G. C. Fox
Affiliation:
Department of Agricultural Economics and Business, University of Guelph, Ontario N1G2W1, Canada
C. Smith
Affiliation:
Department of Animal and Poultry Science, University of Guelph, Ontario N1G2W1, Canada
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Abstract

Methods which estimate the effects on farm profit of a change in a genetic trait (economic weight) are compared. A neoclassical economic model based on a Cobb Douglas type production function, is extended to the long run and compared with a conventional profit equation for two types of trait changes. With this model, an optimal production plan can be derived for the farm which depends on input prices and the production function parameters. In the calculation of economic weights by animal breeders, costs are usually linear with respect to farm output, and so input levels and output are determined arbitrarily. Differences between methods for the estimation of both absolute and relative economic weights are shown to be small for proportional trait changes of 0·01 to 0·05. However, for proportional trait changes of 0·3, proportional differences were from 0·01 to 0·75 and from 0 to 0·6 for absolute and relative economic weights respectively, depending on the production function parameters. This dependence on the size of the trait change is attributed to the non-linearity of the production function. The effects of ‘rescaling’, which implicitly discounts economic weights for output increasing traits, are also evaluated. Absolute and relative ‘rescaled’ economic weights for 0·01 proportional trait changes are shown to differ proportionally from those estimated by the neoclassical economic model by from 0·14 and 0·12 to 0·50 respectively. For 0·3 trait changes, proportional differences were from 0·16 to 0·79 and from 0·8 to 0·43 for absolute and relative trait changes respectively. The results have important implications for conventional breeding programmes, and the economic evaluation of breeds and major genes.

Keywords

breeding programmeseconomic weightsprofit equations
Type
Research Article
Information
Animal Production , Volume 58 , Issue 1 , February 1994 , pp. 11 - 18
Copyright
Copyright © British Society of Animal Science 1994

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References

Amer, P. R. and Fox, G. C. 1992. Estimation of economic weights in genetic improvement using neoclassical production theory: an alternative to rescaling. Animal Production 54: 341–350.Google Scholar
Beatie, B. R. and Taylor, C. R. 1985. The economics of production. John Wiley.Google Scholar
Brascamp, E. W., Smith, C. and Guy, D. R. 1985. Derivation of economic weights from profit equations. Animal Production 40: 175–180.Google Scholar
Bright, G. 1991. Economic weights from profit equations: appraising their accuracy. Animal Production 53: 395–398.Google Scholar
Cobb, C. W. and Douglas, P. H. 1928. A theory of production. American Economic Revieio, suppl. 18, pp. 139–156.Google Scholar
Debertin, D. L. 1986. Agricultural production economics. Macmillan, New York.Google Scholar
Dickerson, G. E. 1970. Efficiency of animal production-molding the biological components. journal of Animal Science 30: 849–859.CrossRefGoogle Scholar
Edwards, G. W. and Freebairn, J. W. 1984. The gains from research into tradable commodities. American Journal of Agricultural Economics 66: 41–49.CrossRefGoogle Scholar
Goddard, M. E. 1983. Selection indices for non linear profit functions. Theoretical and Applied Genetics 64: 339–344.CrossRefGoogle ScholarPubMed
Hazel, L. N. 1943. The genetic basis for constructing selection indexes. Genetics, USA 28: 476–490.CrossRefGoogle ScholarPubMed
Heady, E. O. and Dillon, J. L. 1961. Agricultural production functions. Iowa State University Press, Ames, la.Google Scholar
Itoh, Y. and Yamada, Y. 1988. Linear selection indices for non-linear profit functions. Theoretical and Applied Genetics 75: 553–560.CrossRefGoogle Scholar
Ladd, G. W. 1982. A product-characteristics approach to technical change: with application to animal breeding. In Economic analysis and agricultural policy (ed. Day, R. H.). Iowa State University Press.Google Scholar
Lipsey, R. G., Purvis, D. D. and Steiner, P. D. 1985. Economics. 5th ed. Harper and Row, New York.Google Scholar
McArthur, A. T. G. 1987. Weighting breeding objectives —— an economic approach. Proceedings of the sixth annual conference of the Australian Association of Animal Breeders, Perth, pp. 187–197.Google Scholar
Pasternak, H. and Weller, J. I. 1993. Optimum linear indices for non-linear profit functions. Animal Production 55: 43–50.Google Scholar
Smith, C. 1983. Effects of changes in economic weights on the efficiency of index selection. Journal of Animal Sciefice 56: 1057–1064.CrossRefGoogle Scholar
Smith, C. 1984. Rates of genetic change in farm livestock. Research and Development in Agriculture 1: 79–85.Google Scholar
Smith, C, James, J. W. and Brascamp, E. W. 1986. On the derivation of economic weights in livestock improvement. Animal Production 43: 545–551.Google Scholar