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Animal Breeding and Productivity Growth of Dairy Farms

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  • Daniel Muluwork Atsbeha
  • Dadi Kristofersson
  • Kyrre Rickertsen

Abstract

We introduce genetic-based technical change into a Malmquist productivity index and measure the growth in productivity caused by bovine breeding. Because breeding is likely to affect milk quality, we adjust milk quantities for quality differences. We use panel data on Icelandic dairy farms from 1997 to 2006 to estimate an input distance function. The Malmquist productivity index shows that the average productivity growth rate is 1.6%. Scale effects are the most important source of this growth, but 19% of the productivity growth rate is due to breeding. If quality differences are ignored, the average productivity growth rate is reduced by 83%. Copyright 2012, Oxford University Press.

Suggested Citation

  • Daniel Muluwork Atsbeha & Dadi Kristofersson & Kyrre Rickertsen, 2012. "Animal Breeding and Productivity Growth of Dairy Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 996-1012.
    • Handle: RePEc:oup:ajagec:v:94:y:2012:i:4:p:996-1012
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    1. Marasas, C. N. & Smale, M. & Singh, R. P., 2003. "The economic impact of productivity maintenance research: breeding for leaf rust resistance in modern wheat," Agricultural Economics, Blackwell, vol. 29(3), pages 253-263, December.
    2. Townsend, Robert & Thirtle, Colin, 2001. "Is livestock research unproductive?: Separating health maintenance from improvement research," Agricultural Economics, Blackwell, vol. 25(2-3), pages 177-189, September.
    3. Giannis Karagiannis & Peter Midmore & Vangelis Tzouvelekas, 2004. "Parametric Decomposition of Output Growth Using A Stochastic Input Distance Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1044-1057.
    4. Loren W. Tauer, 1998. "Productivity of New York Dairy Farms Measured by Nonparametric Malmquist Indices," Journal of Agricultural Economics, Wiley Blackwell, vol. 49(2), pages 234-249.
    5. Bernhard Brümmer & Thomas Glauben & Geert Thijssen, 2002. "Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 628-644.
    6. Godden, David P. & Brennan, John P., 1994. "Technological Change Embodied in Southern NSW and British Wheat Varieties," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 62(02), August.
    7. Lawton L. Nalley & Andrew P. Barkley & Allen M. Featherstone, 2010. "The genetic and economic impact of the CIMMYT wheat breeding program on local producers in the Yaqui Valley, Sonora Mexico," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 453-462, September.
    8. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    10. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    11. Kerr, William A., 1984. "Selective Breeding, Heritable Characteristics And Genetic-Based Technological Change In The Canadian Beef Cattle Industry," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 9(01), July.
    12. Marasas, C.N. & Smale, M. & Singh, R.P., 2003. "The economic impact of productivity maintenance research: breeding for leaf rust resistance in modern wheat," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 29(3), December.
    13. Saito, Yoko & Saito, Hisamitsu & Kondo, Takumi & Osanami, Fumio, 2009. "Quality-oriented technical change in Japanese wheat breeding," Research Policy, Elsevier, vol. 38(8), pages 1365-1375, October.
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    Cited by:

    1. Efthymios G. Tsionas & Subal C. Kumbhakar & Emir Malikov, 2015. "Estimation of Input Distance Functions: A System Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(5), pages 1478-1493.
    2. Daniel Atsbeha & Dadi Kristofersson & Kyrre Rickertsen, 2015. "Broad breeding goals and production costs in dairy farming," Journal of Productivity Analysis, Springer, vol. 43(3), pages 403-415, June.
    3. Markus Lampe & Paul Sharp, 2015. "Just add milk: a productivity analysis of the revolutionary changes in nineteenth-century Danish dairying," Economic History Review, Economic History Society, vol. 68(4), pages 1132-1153, November.
    4. Malikov, Emir, 2016. "Estimating Multi-Product Production Functions and Productivity using Control Functions," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235108, Agricultural and Applied Economics Association.
    5. Richard J. Volpe & Timothy A. Park & Fengxia Dong & Helen H. Jensen, 2016. "Somatic cell counts in dairy marketing: quantile regression for count data," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 43(2), pages 331-358.

    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services

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