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Technical, Allocative, and Economic Efficiency in Swedish Dairy Farms: The Data Envelopment Analysis Versus the Stochastic Frontier Approach

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  • Johansson, Helena
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    Abstract

    Technical, allocative, and economic input efficiency scores were estimated for an unbalanced panel of Swedish dairy farms, using data envelopment analysis (DEA) and the stochastic frontier approach (SFA). By comparing the results it was concluded that when the entire dairy farm is studied the DEA is more appropriate to use since it does not require any particular parametric form to be chosen. The average DEA technical, allocative and economic efficiency indices were eventually found to be 0.77, 0.57, and 0.43 respectively. The influence of size on the efficiency scores was analyzed and significant evidence indicating a positive relationship between size and efficiency was found. Finally it was concluded that the main challenge facing the Swedish dairy farms is to enhance their cost minimizing skills.

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    Bibliographic Info

    Paper provided by European Association of Agricultural Economists in its series 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark with number 24478.

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    Date of creation: 2005
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    Handle: RePEc:ags:eaae05:24478

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    Keywords: technical efficiency; allocative efficiency; economic efficiency; data envelopment analysis; stochastic frontier approach; Livestock Production/Industries; C14; C23; C24;

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    1. 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.
    2. Kopp, Raymond J. & Diewert, W. Erwin, 1982. "The decomposition of frontier cost function deviations into measures of technical and allocative efficiency," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 319-331, August.
    3. Iraizoz, Belen & Rapun, Manuel & Zabaleta, Idoia, 2003. "Assessing the technical efficiency of horticultural production in Navarra, Spain," Agricultural Systems, Elsevier, vol. 78(3), pages 387-403, December.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Tim J. Coelli, 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 219-245, December.
    6. Alvarez, Antonio & Arias, Carlos, 2004. "Technical efficiency and farm size: a conditional analysis," Agricultural Economics, Blackwell, vol. 30(3), pages 241-250, May.
    7. Coelli, Tim & Perelman, Sergio, 1999. "A comparison of parametric and non-parametric distance functions: With application to European railways," European Journal of Operational Research, Elsevier, vol. 117(2), pages 326-339, September.
    8. Blank, Steven C., 2005. "The Business of an Agricultural “Way of Life”," Choices, Agricultural and Applied Economics Association, vol. 20(2).
    9. Bailey, DeeVon & Biswas, Basudeb & Kumbhakar, Subal C. & Schulthies, B. Kris, 1989. "An Analysis Of Technical, Allocative, And Scale Inefficiency: The Case Of Ecuadorian Dairy Farms," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 14(01), July.
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    Cited by:
    1. Kelly, E & Shalloo, L & Geary, U & Kinsella, A & Thorne, F & Wallace, M, 2013. "An analysis of the factors associated with technical and scale efficiency of Irish dairy farms," International Journal of Agricultural Management, Institute of Agricultural Management & International Farm Management Association, vol. 2(3), April.
    2. Pardo Martínez, Clara Inés, 2013. "An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries," Socio-Economic Planning Sciences, Elsevier, vol. 47(2), pages 120-130.

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