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

Author

Listed:
  • Szvetlana Acs
  • Paul Berentsen
  • Ruud Huirne
  • Marcel van Asseldonk
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. Copyright 2009 The Authors. Journal compilation 2009 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd.

Suggested Citation

  • Szvetlana Acs & Paul Berentsen & Ruud Huirne & Marcel van Asseldonk, 2009. "Effect of yield and price risk on conversion from conventional to organic farming ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(3), pages 393-411, July.
  • Handle: RePEc:bla:ajarec:v:53:y:2009:i:3:p:393-411
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    References listed on IDEAS

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    1. 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," Food and Agricultural Policy Research Institute (FAPRI) Publications (archive only) 82-wp9, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    2. 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.
    3. Harwood, Joy L. & Heifner, Richard G. & Coble, Keith H. & Perry, Janet E. & Somwaru, Agapi, 1999. "Managing Risk in Farming: Concepts, Research, and Analysis," Agricultural Economic Reports 34081, United States Department of Agriculture, Economic Research Service.
    4. Allan N. Rae, 1971. "Stochastic Programming, Utility, and Sequential Decision Problems in Farm Management," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 53(3), pages 448-460.
    5. 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(2), pages 1-17, August.
    6. J. Brian Hardaker & Louise H. Patten & David J. Pannell, 1988. "Utility‐Efficient Programming For Whole‐Farm Planning," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 32(2-3), pages 88-97, 08-12.
    7. David K. Lambert & Bruce A. McCarl, 1985. "Risk Modeling Using Direct Solution of Nonlinear Approximations of the Utility Function," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(4), pages 846-852.
    8. Flaten, O. & Lien, G., 2007. "Stochastic utility-efficient programming of organic dairy farms," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1574-1583, September.
    9. K. D. Cocks, 1968. "Discrete Stochastic Programming," Management Science, INFORMS, vol. 15(1), pages 72-79, September.
    10. 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.
    11. 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), pages 1-14, April.
    12. 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, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 28(1), pages 17-36, March.
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