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Measuring productivity differentials – An application to milk production in Nordic countries

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  • Sipilainen, Timo
  • Kuosmanen, Timo
  • Kumbhakar, Subal C.

Abstract

The aim of this paper is to analyse the regional productivity differentials on dairy farms in Denmark, Finland and Sweden. Several methods have been suggested for analysing productivity differentials in agriculture between groups of farms or countries. Hayami [5] and Hayami and Ruttan [7] suggested the meta-production function approach. This idea has been further developed by Lau and Yotopoulos [9] and Fulginity and Perrin [13]. Battese and Rao [2] suggested the meta-frontier analysis for these comparisons. One of the advantages of meta-frontiers with respect to metaproduction functions is that they are able to separate technological differences from the differences in technical efficiency. Battese et al. [5] and O’Donnell et al. [16] have extended this idea and developed both parametric and nonparametric approaches. In this paper, we extend the metafrontier analysis to the concave nonparametric least squares estimation of the production function suggested by Kuosmanen [18,19]. In addition, we compare the results with the approach where the estimation of meta-frontier can be avoided. The reference can also be the maximum output providing technology that is the one that yields the maximum estimated output, given inputs [21]. In this case the estimation can be based either on average or frontier production functions. The farm level data is obtained from the EU’s Farm Accountancy Data Network data set for Denmark, Finland and Sweden. They cover 954 dairy farms in 2003. The results suggest that different method provide slightly different results but in all approaches productivity differentials are considerable in favour of Danish farms. In addition, the Danish technology is not only dominating at the mean but also at most of the data points.

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  • Sipilainen, Timo & Kuosmanen, Timo & Kumbhakar, Subal C., 2008. "Measuring productivity differentials – An application to milk production in Nordic countries," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44277, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae08:44277
    DOI: 10.22004/ag.econ.44277
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    References listed on IDEAS

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    1. Fulginiti, Lilyan E & Perrin, Richard K, 1993. "Prices and Productivity in Agriculture," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 471-482, August.
    2. Derek D. Headey & D.S. Prasada Rao & Mohammad Alauddin, 2005. "Explaining Agricultural Productivity Levels and Growth: An International Perspective," CEPA Working Papers Series WP022005, School of Economics, University of Queensland, Australia.
    3. Wiebe, Keith D., 2003. "Linking Land Quality, Agricultural Productivity, And Food Security," Agricultural Economic Reports 34073, United States Department of Agriculture, Economic Research Service.
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    5. Kuosmanen, Timo, 2006. "Stochastic Nonparametric Envelopment of Data: Combining Virtues of SFA and DEA in a Unified Framework," Discussion Papers 11864, MTT Agrifood Research Finland.
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    Cited by:

    1. Mette Asmild & Kurt Nielsen & Peter Bogetoft, 2012. "Are high labour costs destroying the competitiveness of Danish dairy farmers? Evidence from an international benchmarking analysis," MSAP Working Paper Series 01_2012, University of Copenhagen, Department of Food and Resource Economics.
    2. Olusegun, Ajetomobi Joshua, 2012. "Productivity Growth of ECOWAS Common Crops: A Tale of Two Competing Frontier Methods of Analysis," 2012 Eighth AFMA Congress, November 25-29, 2012, Nairobi, Kenya 159404, African Farm Management Association (AFMA).
    3. Sami Ben Naceur & Barbara Casu & Hichem Ben-Khedhiri, 2011. "What Drives the Performance of Selected MENA Banks? A Meta-Frontier Analysis," IMF Working Papers 2011/034, International Monetary Fund.
    4. Latruffe, Laure & Fogarasi, József & Desjeux, Yann, 2012. "Efficiency, productivity and technology comparison for farms in Central and Western Europe: The case of field crop and dairy farming in Hungary and France," Economic Systems, Elsevier, vol. 36(2), pages 264-278.
    5. Manevska-Tasevska, Gordana & Hansson, Helena & Asmild, Mette & Surry, Yves, 2018. "Assessing the regional efficiency of Swedish agriculture under the CAP ‒ a multidirectional efficiency approach," 162nd Seminar, April 26-27, 2018, Budapest, Hungary 271971, European Association of Agricultural Economists.
    6. Heikkila, Anna-Maija & Myyra, Sami & Pietola, Kyosti, 2012. "Effects of Economic Factors on Adoption of Robotics and Consequences of Automation for Productivity Growth of Dairy Farms," Working papers 144002, Factor Markets, Centre for European Policy Studies.
    7. Afsharian, Mohsen, 2017. "Metafrontier efficiency analysis with convex and non-convex metatechnologies by stochastic nonparametric envelopment of data," Economics Letters, Elsevier, vol. 160(C), pages 1-3.
    8. Temitayo A. Adeyemo & Victor O. Okoruwa, 2018. "Value Addition and Productivity Differentials in the Nigerian Cassava System," Sustainability, MDPI, vol. 10(12), pages 1-22, December.

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