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Comparing productivity growth in conventional and grassland dairy farms

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  • Kellermann, Magnus
  • Salhofer, Klaus
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    Abstract

    This paper analyzes technical efficiency and productivity growth of dairy farms in southern Germany. We compare the performance of farms operating on permanent grassland and conventional farms using fodder crops from arable land. Using a latent class stochastic frontier model, intensive and extensive production systems are identified for both types of farms. We estimate stochastic output distance functions to represent the production technology. TFP change is calculated and decomposed using a generalized Malmquist productivity index. Our results show that grassland farms can in general keep up with conventional farms. The productivity on intensive (extensive) grassland dairy farms grew by 1.15% (0.93%) per year, compared to 1.19% (intensive) and 1.0% (extensive) on conventional farms.

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    Bibliographic Info

    Paper provided by European Association of Agricultural Economists in its series 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland with number 114763.

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    Date of creation: 02 Sep 2011
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    Handle: RePEc:ags:eaae11:114763

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    Keywords: productivity; dairy farming; stochastic frontier analysis; Livestock Production/Industries; Productivity Analysis;

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    1. Bernhard Br�mmer & 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.
    2. Carol Newman & Alan Matthews, 2006. "The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach," Journal of Productivity Analysis, Springer, vol. 26(2), pages 191-205, October.
    3. Tim Coelli & Sergio Perelman, 2000. "Technical efficiency of European railways: a distance function approach," Applied Economics, Taylor & Francis Journals, vol. 32(15), pages 1967-1976.
    4. Luis Orea & Subal C. Kumbhakar, 2004. "Efficiency measurement using a latent class stochastic frontier model," Empirical Economics, Springer, vol. 29(1), pages 169-183, January.
    5. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    6. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(2), pages 231-250, June.
    7. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528, October.
    8. 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.
    9. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
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