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Effect of yield and price risk on conversion from conventional to organic farming

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  • Acs, Szvetlana
  • Berentsen, Paul
  • Huirne, Ruud
  • van Asseldonk, Marcel
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    Abstract

    Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility-efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk-neutral farmer it is optimal to convert to organic farming. However, for a more risk-averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.

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    Bibliographic Info

    Article provided by Australian Agricultural and Resource Economics Society in its journal Australian Journal of Agricultural and Resource Economics.

    Volume (Year): 53 (2009)
    Issue (Month): 3 (September)
    Pages:

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    Handle: RePEc:ags:aareaj:161974

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    Related research

    Keywords: arable farming; conversion process; dynamic utility-efficient programming model; organic farming; risk aversion; Agribusiness; Crop Production/Industries; Farm Management;

    References

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    1. Richardson, James W. & Klose, Steven L. & Gray, Allan W., 2000. "An Applied Procedure For Estimating And Simulating Multivariate Empirical (Mve) Probability Distributions In Farm-Level Risk Assessment And Policy Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 32(02), August.
    2. Harwood, Joy L. & Heifner, Richard G. & Coble, Keith H. & Perry, Janet E. & Somwaru, Agapi, 1999. "Managing Risk in Farming: Concepts, Research, and Analysis," Agricultural Economics Reports 34081, United States Department of Agriculture, Economic Research Service.
    3. Lien, Gudbrand & Hardaker, J. Brian & Asseldonk, Marcel A.P.M. van & Richardson, James W., 2009. "Risk programming and sparse data: how to get more reliable results," Agricultural Systems, Elsevier, vol. 101(1-2), pages 42-48, June.
    4. James A. Langley & Earl O. Heady & Kent D. Olson, 1982. "Macro Implications of a Complete Transformation of U.S. Agricultural Production to Organic Farming Practices," Center for Agricultural and Rural Development (CARD) Publications 82-wp9, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    5. G Lien & JB Hardaker, 2001. "Whole-farm planning under uncertainty: impacts of subsidy scheme and utility function on portfolio choice in Norwegian agriculture," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 28(1), pages 17-36, March.
    6. Pannell, David J. & Malcolm, Bill & Kingwell, Ross S., 2000. "Are we risking too much? Perspectives on risk in farm modelling," Agricultural Economics: The Journal of the International Association of Agricultural Economists, International Association of Agricultural Economists, vol. 23(1), June.
    7. Pannell, David J. & Malcolm, Bill & Kingwell, Ross S., 2000. "Are we risking too much? Perspectives on risk in farm modelling," Agricultural Economics, Blackwell, vol. 23(1), pages 69-78, June.
    8. Martin, Sandra, 1996. "Risk Management Strategies in New Zealand Agriculture and Horticulture," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 64(01), April.
    9. K. D. Cocks, 1968. "Discrete Stochastic Programming," Management Science, INFORMS, vol. 15(1), pages 72-79, September.
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    Cited by:
    1. van Winsen, Frankwin & Wauters, Erwin & Lauwers, Ludwig H. & de Mey, Yann & Van Passel, Steven & Vancauteren, Mark, 2011. "Combining risk perception and risk attitude: A comprehensive individual risk behavior model," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115749, European Association of Agricultural Economists.
    2. Aude Ridier & Karim Chaib & Caroline Roussy, 2012. "The adoption of innovative cropping systems under price and production risks: a dynamic model of crop rotation choice," Working Papers SMART - LERECO 12-07, INRA UMR SMART.
    3. Chavez, M.D. & Berentsen, P.B.M. & Oude Lansink, A.G.J.M., 2014. "Analyzing diversification possibilities on specialized tobacco farms in Argentina using a bio-economic farm model," Agricultural Systems, Elsevier, vol. 128(C), pages 35-43.
    4. Wauters, Erwin & De Cock, Lieve & Wit, Jan de & Lauwers, Ludwig H., 2011. "The foregone risk premium: a communicative and practical method for the evaluation of risk-return profiles in agriculture," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115737, European Association of Agricultural Economists.
    5. Mzoughi, Naoufel, 2011. "Farmers adoption of integrated crop protection and organic farming: Do moral and social concerns matter?," Ecological Economics, Elsevier, vol. 70(8), pages 1536-1545, June.
    6. Gandorfer, Markus & Pannell, David & Meyer-Aurich, Andreas, 2011. "Analyzing the effects of risk and uncertainty on optimal tillage and nitrogen fertilizer intensity for field crops in Germany," Agricultural Systems, Elsevier, vol. 104(8), pages 615-622, October.
    7. Naoufel Mzoughi, 2011. "Farmers adoption of integrated crop protection and organic farming: Do moral and social concerns matter?," Working Papers 40181, Institut National de la Recherche Agronomique, France.

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