IDEAS home Printed from https://ideas.repec.org/p/ags/eaae11/114763.html
   My bibliography  Save this paper

Comparing productivity growth in conventional and grassland dairy farms

Author

Listed:
  • Kellermann, Magnus
  • Salhofer, Klaus

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.

Suggested Citation

  • Kellermann, Magnus & Salhofer, Klaus, 2011. "Comparing productivity growth in conventional and grassland dairy farms," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114763, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae11:114763
    DOI: 10.22004/ag.econ.114763
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/114763/files/Kellermann_Magnus_293.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.114763?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Catherine J. Morrison Paul & Warren E. Johnston & Gerald A. G. Frengley, 2000. "Efficiency in New Zealand Sheep and Beef Farming: The Impacts of Regulatory Reform," The Review of Economics and Statistics, MIT Press, vol. 82(2), pages 325-337, May.
    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. 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.
    4. 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.
    5. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, June.
    6. 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.
    7. 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.
    8. 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.
    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. Antonio Alvarez & Julio del Corral, 2010. "Identifying different technologies using a latent class model: extensive versus intensive dairy farms," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 37(2), pages 231-250, June.
    11. Luis Orea, 2002. "Parametric Decomposition of a Generalized Malmquist Productivity Index," Journal of Productivity Analysis, Springer, vol. 18(1), pages 5-22, July.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dragan Milić & Tihomir Novaković & Dragana Tekić & Bojan Matkovski & Danilo Đokić & Stanislav Zekić, 2023. "Economic Sustainability of the Milk and Dairy Supply Chain: Evidence from Serbia," Sustainability, MDPI, vol. 15(21), pages 1-21, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alvarez, Antonio & del Corral, Julio & Tauer, Loren W., 2012. "Modeling Unobserved Heterogeneity in New York Dairy Farms: One-Stage versus Two-Stage Models," Agricultural and Resource Economics Review, Cambridge University Press, vol. 41(3), pages 275-285, December.
    2. Areal, Francisco J. & Tiffin, Richard & Balcombe, Kelvin G., 2012. "Provision of environmental output within a multi-output distance function approach," Ecological Economics, Elsevier, vol. 78(C), pages 47-54.
    3. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    4. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    5. Johannes Sauer & Catherine J. Morrison Paul, 2013. "The empirical identification of heterogeneous technologies and technical change," Applied Economics, Taylor & Francis Journals, vol. 45(11), pages 1461-1479, April.
    6. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    7. Johannes Sauer, 2011. "The Empirical Identification of Heterogenous Technologies and Technical Change," Post-Print hal-00768585, HAL.
    8. Sauer, J. & Morrison-Paul, C., 2011. "Technologies and Localized Technical Change," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 46, March.
    9. Xie, Bai-Chen & Ni, Kang-Kang & O'Neill, Eoghan & Li, Hong-Zhou, 2021. "The scale effect in China's power grid sector from the perspective of malmquist total factor productivity analysis," Utilities Policy, Elsevier, vol. 69(C).
    10. Heike Wetzel, 2008. "Productivity Growth in European Railways: Technological Progress,Efficiency Change and Scale Effects," Working Paper Series in Economics 101, University of Lüneburg, Institute of Economics.
    11. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    12. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    13. Sauer, Johannes & Davidova, Sophia & Gorton, Matthew, 2012. "Land fragmentation, market integration and farm efficiency: empirical evidence from Kosovo," 86th Annual Conference, April 16-18, 2012, Warwick University, Coventry, UK 134968, Agricultural Economics Society.
    14. Mike Tsionas & Marwan Izzeldin & Arne Henningsen & Evaggelos Paravalos, 2022. "Addressing endogeneity when estimating stochastic ray production frontiers: a Bayesian approach," Empirical Economics, Springer, vol. 62(3), pages 1345-1363, March.
    15. Ahimbisibwe, Vianny & Zhunusova, Eliza & Kassa, Habtemariam & Günter, Sven, 2024. "Technical efficiency drivers of farmer-led restoration strategies, and how substantial is the unrealised potential for farm output?," Agricultural Systems, Elsevier, vol. 213(C).
    16. Lajos Baráth & Imre Fertő & Heinrich Hockmann, 2020. "Technological Differences, Theoretical Consistency, and Technical Efficiency: The Case of Hungarian Crop-Producing Farms," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    17. Stefano Mainardi, 2021. "Parametric and Semiparametric Efficiency Frontiers in Fishery Analysis: Overview and Case Study on the Falkland Islands," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 169-210, June.
    18. Latruffe, Laure & Bravo-Ureta, Boris E. & Moreira, Victor H. & Desjeux, Yann & Dupraz, Pierre, 2011. "Productivity and Subsidies in European Union Countries: An Analysis for Dairy Farms Using Input Distance Frontiers," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114396, European Association of Agricultural Economists.
    19. Cullmann, Astrid & Zloczysti, Petra, 2013. "Towards an Efficient Use of R&D ? Accounting for Heterogeneity in the OECD," CEPR Discussion Papers 9345, C.E.P.R. Discussion Papers.
    20. K Hervé Dakpo & Laure Latruffe & Yann Desjeux & Philippe Jeanneaux, 2021. "Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 760-781, September.

    More about this item

    Keywords

    Livestock Production/Industries; Productivity Analysis;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:eaae11:114763. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.