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Uncertainty and technical efficiency in Finnish agriculture: a state-contingent approach

Author

Listed:
  • Celine Nauges

    () (School of Economics, University of Queensland)

  • Chris O'Donnell

    () (School of Economics, University of Queensland)

  • John Quiggin

    () (School of Economics, University of Queensland)

Abstract

In this article, we present one of the first real-world empirical applications of state-contingent production theory. Our state-contingent behavioral model allows us to analyze production under both inefficiency and uncertainty without regard to the nature of producer risk preferences. Using farm data for Finland, we estimate a flexible production model that permits substitutability between state-contingent outputs. We test empirically, and reject, an assumption that has been implicit in almost all efficiency studies conducted in the last three decades, namely that the production technology is output-cubical, i.e., that outputs are not substitutable between states of nature.

Suggested Citation

  • Celine Nauges & Chris O'Donnell & John Quiggin, 2010. "Uncertainty and technical efficiency in Finnish agriculture: a state-contingent approach," Risk & Uncertainty Working Papers WPR10_2, Risk and Sustainable Management Group, University of Queensland.
  • Handle: RePEc:rsm:riskun:r10_2
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    File URL: http://www.uq.edu.au/rsmg/WP/WPR10_02.pdf
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    References listed on IDEAS

    as
    1. C. J. O'Donnell & W. E. Griffiths, 2006. "Estimating State-Contingent Production Frontiers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 249-266.
    2. Jean-Paul Chavas, 2008. "A Cost Approach to Economic Analysis Under State-Contingent Production Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 435-466.
    3. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
    4. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521785235, December.
    5. Xing, Liu & Pietola, Kyosti, 2005. "Forward Hedging Under Price and Production Risk of Wheat," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24467, European Association of Agricultural Economists.
    6. Christopher O’Donnell & Robert Chambers & John Quiggin, 2010. "Efficiency analysis in the presence of uncertainty," Journal of Productivity Analysis, Springer, vol. 33(1), pages 1-17, February.
    7. Phoebe Koundouri & Marita Laukkanen & Sami Myyrä & Céline Nauges, 2009. "The effects of EU agricultural policy changes on farmers' risk attitudes," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(1), pages 53-77, March.
    8. G. Karagiannis & V. Tzouvelekas & A. Xepapadeas, 2003. "Measuring Irrigation Water Efficiency with a Stochastic Production Frontier," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(1), pages 57-72, September.
    9. G. Battese & A. Rambaldi & G. Wan, 1997. "A Stochastic Frontier Production Function with Flexible Risk Properties," Journal of Productivity Analysis, Springer, vol. 8(3), pages 269-280, August.
    10. Teresa Serra & Spiro Stefanou & Alfons Oude Lansink, 2010. "A dynamic dual model under state-contingent production uncertainty," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 37(3), pages 293-312, September.
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    Citations

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    Cited by:

    1. Theodoros Skevas & Teresa Serra, 2016. "The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 139-153, December.
    2. Macedo, Pedro & Scotto, Manuel, 2014. "Cross-entropy estimation in technical efficiency analysis," Journal of Mathematical Economics, Elsevier, vol. 54(C), pages 124-130.
    3. Carpentier, Alain & Gohin, Alexandre & Sckokai, Paolo & Thomas, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Revue d'Etudes en Agriculture et Environnement, Editions NecPlus, vol. 96(01), pages 131-165, March.
    4. Yang, Sansi & Shumway, C. Richard, 2015. "Asset Fixity under State-Contingent Production Uncertainty," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205256, Agricultural and Applied Economics Association.
    5. Tomas Baležentis, 2015. "The Sources of the Total Factor Productivity Growth in Lithuanian Family Farms: A Färe-Primont Index Approach," Prague Economic Papers, University of Economics, Prague, vol. 2015(2), pages 225-241.

    More about this item

    Keywords

    state-contingent; production; uncertainty;

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water

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