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Estimation of economic weights in genetic improvement using neoclassical production theory: an alternative to rescaling

Published online by Cambridge University Press:  02 September 2010

P. R. Amer  and
G. C. Fox
P. R. Amer
Affiliation:
Department of Animal and Poultry Science, University of Guelph, Ontario N1G 2W1, Canada
G. C. Fox
Affiliation:
Department of Agricultural Economics and Business, University of Guelph, Ontario NIG 2W1, Canada
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Abstract

This paper addresses the rescaling controversy in the estimation of economic weights for livestock improvement programmes. A model of genetic improvement based on the neoclassical theory of the firm and incorporating genetic improvement is proposed for the estimation of economic weights. Disparities between estimates of economic weights calculated per animal as opposed to per unit of product, per breeding female or per enterprise disappear when economic weights are calculated using this model. Equivalences of economic weights at the different bases of evaluation, previously obtained by rescaling the production enterprise to a fixed input, output or profit are compared with this model. The conventional approach to the derivation of economic weights is characterized as implicitly making unreasonable assumptions about the behaviour offarm firms.

Extension of the proposed model to the level of the farm product market allows assessment of the distribution of gains from genetic improvement between producers and consumers using the economic surplus approach. In an illustrative example, the distribution of benefits among producers and consumers from genetic improvement in the Ontario cow-calf sector is shown to depend on the elasticity of demand for beef products in the North American market. When the demand for farm output is elastic, a significant proportion of the benefits from genetic improvement would accrue to producers. Conversely, when demand is inelastic, the majority of benefits would accrue to consumers. Economic weights calculated from the perspective of all producers could thus be different from those calculated from the perspective of an individual farmer or society as a whole. Finally, the market level model is used to compare the effects of genetic improvement which enhance product quality with cost-reducing genetic improvements.

Keywords

economic weightsgenetic improvementneoclassical economics
Type
Research Article
Information
Animal Production , Volume 54 , Issue 3 , June 1992 , pp. 341 - 350
Copyright
Copyright © British Society of Animal Science 1992

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References

Brascamp, E. W., Smith, C. and Guy, D. R. 1985. Derivation of economic weights from profit equations. Animal Production 40: 175–180.Google Scholar
Cochrane, W. W. 1965. The city man's guide to the farm problem. University of Minnesota Press, Minneapolis.Google Scholar
Debertin, D. L. 1986. Agricultural production economics. Macmillan, New York.Google 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
Gibson, J. P. 1989. Economic weights and index selection of milk production traits when multiple production quotas apply. Animal Production 49: 171–181.Google Scholar
Goddard, M. E. 1983. Selection indices for non-linear profit functions. Theoretical and Applied Genetics 64: 339–344.CrossRefGoogle ScholarPubMed
Groen, A. F. 1988. Derivation of economic values in cattle breeding. A model at farm level. Agricultural Systems 27: 195–213.CrossRefGoogle Scholar
Hazel, L. N. 1943. The genetic basis for constructing selection indexes. Genetics, USA 28: 476–490.CrossRefGoogle ScholarPubMed
Hertford, R. and Schmidt, A. 1977. Measuring economic returns to agricultural research. In Resource allocation and productivity in national and international agricultural (ed. Arndt, T. M., Dalrymple, D. G. and Ruttan, J. W.). University of Minnesota Press, Minneapolis.Google Scholar
Kerr, W. A. 1984. Selective breeding, heritable characteristics and genetic based technological change in the Canadian beef cattle industry. Western Journal of Agricultural Economics 9: 14–28.Google 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, Ames, Iowa.Google Scholar
Ladd, G. W. and Gibson, G. 1978. Microeconomics of technical change: what's a better animal worth? American Journal of Agricultural Economics 60: 236–240.Google Scholar
Lemeiux, C. M. and Wohlgenant, M. K. 1989. Ex ante evaluation of the economic impact of agricultural biotechnology: the case of porcine somatotrophin. American Journal of Agricultural Economics 71: 901–914.Google Scholar
Lindner, R. K. and Jarrett, F. G. 1978. Supply shifts and the size of research benefits. American Journal of Agricultural Economics 60: 49–58.CrossRefGoogle 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 Breeding Genetics, Perth, pp. 187–197.Google Scholar
Moav, R. 1973. Economic evaluation of genetic differences. In Agricultural genetics: selected topics, pp. 319–352. Wiley, New York.Google Scholar
Moav, R. and Hill, W. G. 1966. Specialised sire and dam lines. IV. Selection within lines. Animal Production 8: 375–390.Google Scholar
Ontario Ministry of Agriculture and Food. 1988. Ontario farm management analysis project 1988. OMAF publication 69.Google Scholar
Oxley, J., Fox, G. and Moschini, G. 1989. An analysis of the structure and welfare effects of bovine somatotropin on the Ontario dairy industry. Canadian Journal of Agricultural Economics 37: 393–406.CrossRefGoogle Scholar
Ponzoni, R. W. 1988. The derivation of economic values combining income and expense in different ways: an example with Australian Merino sheep. Journal of Animal Breeding and Genetics 105: 143–153.CrossRefGoogle Scholar
Robinson, L. J. and Barry, P. J. 1988. The competitive firm's response to risk. Macmillan, New York.Google Scholar
Rose, R. N. 1980. Supply shifts and research benefits: comment. American Journal of Agricultural Economics 62: 834–840.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
Stokes, K. W., Farris, D. E. and Cartwright, T. C. 1981. Economics of alternative beef cattle genotypes and management/marketing systems. Southern Journal of Agricultural Economics 13: 1–10.Google Scholar
Widmer, L., Fox, G. and Brinkman, G. L. 1988. The rate of return to agricultural research in a small country: the case of beef cattle research in Canada. Canadian Journal of Agricultural Economics 36: 23–35.CrossRefGoogle Scholar
Wise, W. S. and Fell, E. 1980. Supply shifts and the size of research benefits: comment. American Journal of Agricultural Economics 62: 838–840.CrossRefGoogle Scholar