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How can dairy farmers become more revenue efficient? Efficiency drivers on dairy farms

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  • Hansen, Bjørn Gunnar
  • Moland, Kathrine
  • Lenning, Monica Ilstad

Abstract

The aim of this article is to identify a set of efficiency drivers which can explain differences in revenue efficiency between dairy farms. To explore farm efficiency, we apply stochastic frontier analysis on a balanced panel of 212 Norwegian dairy farms. The results show that on average the farms can increase the revenue from dairy by 28 percentage points. The article identifies important drivers of revenue efficiency which the farmer can change in the short or medium run to increase efficiency. Automatic milking systems, high beef production per cow, low age at first calving and organic farming are among drivers which can explain differences in revenue efficiency between farms. Our findings have implications for both management scholars, practitioners and policy makers.

Suggested Citation

  • Hansen, Bjørn Gunnar & Moland, Kathrine & Lenning, Monica Ilstad, 2019. "How can dairy farmers become more revenue efficient? Efficiency drivers on dairy farms," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 8(2), August.
    • Handle: RePEc:ags:ijameu:329823
    DOI: 10.22004/ag.econ.329823
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    References listed on IDEAS

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    1. George Battese & Sumiter Broca, 1997. "Functional Forms of Stochastic Frontier Production Functions and Models for Technical Inefficiency Effects: A Comparative Study for Wheat Farmers in Pakistan," Journal of Productivity Analysis, Springer, vol. 8(4), pages 395-414, November.
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    4. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
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    6. Hansen, Bjorn Gunnar & Herje, Hans Olav & Hova, Jonas, 2019. "Profitability on dairy farms with automatic milking systems compared to farms with conventional milking systems," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 22(2).
    7. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    8. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    9. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. Martinson Ankrah Twumasi & Dennis Asante & Jesse Nuamah Brako & Zhao Ding & Yuansheng Jiang, 2023. "The Relationship between Chronic Non-Communicable Diseases of Fish Farm Household Members and Production Efficiency: The Case of Ghana," IJERPH, MDPI, vol. 20(5), pages 1-13, February.
    2. DJOKOTO, Justice G. & BADU-PRAH, Charlotte & GIDIGLO, Ferguson K. & SROFENYOH, Francis Y. & AGYEI-HENAKU, Kofi Aaron A-O. & AFRANE ARTHUR, Akua A., 2022. "Farm Size And Efficiency Nexus: Evidence From A Meta-Regression," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 25(1), March.

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