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The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management


  • Randall Jones
  • Oscar Cacho
  • Jack Sinden


Seasonal variability is an important source of risk faced by farmers and, regardless of an individual's attitude to risk, there are options to tactically adjust production strategies as the outcomes of risk become known. The objective of this article is to measure the economic benefits of alternative approaches to managing weeds, one of the most serious production problems in Australian cropping systems. A bioeconomic model that combines weed biology, crop growth and economics is developed to value the effects of seasonal variability and the role of tactical responses and sequential decision making in determining an optimal integrated weed management strategy. This shows that there are substantial differences in the measured long‐term benefits from deterministic and stochastic simulations. It is concluded that, for research evaluation of technologies that involve complex biological and dynamic systems, ignoring the impacts of seasonal variability, responses to risk and sequential decision making can lead to an incorrect estimate of the economic benefits of a technology. In this case study of optimal weed management strategies in Australia, the size of the error is high.

Suggested Citation

  • Randall Jones & Oscar Cacho & Jack Sinden, 2006. "The importance of seasonal variability and tactical responses to risk on estimating the economic benefits of integrated weed management," Agricultural Economics, International Association of Agricultural Economists, vol. 35(3), pages 245-256, November.
  • Handle: RePEc:bla:agecon:v:35:y:2006:i:3:p:245-256
    DOI: 10.1111/j.1574-0862.2006.00159.x

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    References listed on IDEAS

    1. Anderson, Jock R. & Dillon, John L. & Hardaker, Brian, 1977. "Agricultural Decision Analysis," Monographs: Applied Economics, AgEcon Search, number 288652, September.
    2. Hardaker, J. Brian, 2000. "Some Issues in Dealing with Risk in Agriculture," Working Papers 12912, University of New England, School of Economics.
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    Cited by:

    1. Tessema, Yohannis & Asafu-Adjaye, John & Rodriguez, Daniel & Mallawaarachchi, Thilak & Shiferaw, Bekele, 2015. "A bio-economic analysis of the benefits of conservation agriculture: The case of smallholder farmers in Adami Tulu district, Ethiopia," Ecological Economics, Elsevier, vol. 120(C), pages 164-174.
    2. Zull, Andrew F. & Cacho, Oscar J. & Lawes, Roger A., 2009. "Optimising woody-weed control," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47620, Australian Agricultural and Resource Economics Society.
    3. David Boussios & Paul V. Preckel & Yigezu A. Yigezu & Prakash N. Dixit & Samia Akroush & Hatem Cheikh M'hamed & Mohamed Annabi & Aden Aw‐Hassan & Yahya Shakatreh & Omar Abdel Hadi & Ayed Al‐Abdallat &, 2019. "Modeling producer responses with dynamic programming: a case for adaptive crop management," Agricultural Economics, International Association of Agricultural Economists, vol. 50(1), pages 101-111, January.
    4. Beltran, Jesusa C. & Pannell, David J. & Doole, Graeme J., 2011. "Economic impacts of high labour cost and herbicide resistance for the management of annual barnyardgrass (Echinochloa crus-galli) in rice production in the Philippines," Working Papers 108770, University of Western Australia, School of Agricultural and Resource Economics.
    5. Crean, Jason & Parton, Kevin & Mullen, John & Hayman, Peter, 2015. "Valuing seasonal climate forecasts in a state-contingent manner," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(1), January.
    6. Jacobs, A. & Kingwell, R., 2016. "The Harrington Seed Destructor: Its role and value in farming systems facing the challenge of herbicide-resistant weeds," Agricultural Systems, Elsevier, vol. 142(C), pages 33-40.
    7. Sneessens, Inès & Sauvée, Loïc & Randrianasolo-Rakotobe, Hanitra & Ingrand, Stéphane, 2019. "A framework to assess the economic vulnerability of farming systems: Application to mixed crop-livestock systems," Agricultural Systems, Elsevier, vol. 176(C).

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