IDEAS home Printed from
   My bibliography  Save this article

A Dynamic Decision Model of Technology Adoption under Uncertainty: Case of Herbicide-Resistant Rice


  • Annou, Mamane Malam
  • Wailes, Eric J.
  • Thomsen, Michael R.


Herbicide-resistant (HR) rice technology is a potential tool for control of red rice in commercial rice production. Using an ex ante mathematical programming framework, this research presents an empirical analysis of HR rice technology adoption under uncertainty. The analysis accounts for stochastic germination of red rice and sheath blight to model a profit maximization problem of crop rotation among HR rice, regular rice, and soybeans. The results demonstrate that risk attitudes and technology efficiency determine adoption rates and optimal rotation patterns.

Suggested Citation

  • Annou, Mamane Malam & Wailes, Eric J. & Thomsen, Michael R., 2005. "A Dynamic Decision Model of Technology Adoption under Uncertainty: Case of Herbicide-Resistant Rice," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 37(1), pages 1-12, April.
  • Handle: RePEc:ags:joaaec:43724
    DOI: 10.22004/ag.econ.43724

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Robert N. Collender & David Zilberman, 1985. "Land Allocation under Uncertainty for Alternative Specifications of Return Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(4), pages 779-786.
    2. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    3. Jose B. Falck-Zepeda & Greg Traxler & Robert G. Nelson, 2000. "Rent creation and distribution from biotechnology innovations: The case of bt cotton and Herbicide-Tolerant soybeans in 1997," Agribusiness, John Wiley & Sons, Ltd., vol. 16(1), pages 21-32.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Lyman, Nathaniel & Nalley, Lawton Lanier, 2013. "Stochastic Valuation of Hybrid Rice Technology in Arkansas," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142505, Southern Agricultural Economics Association.
    2. Busdieker-Jesse, Nichole L. & Nogueira, Lia & Onal, Hayri & Bullock, David S., 2016. "The Economic Impact of New Technology Adoption on the U.S. Apple Industry," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(3), pages 1-21, September.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:joaaec:43724. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.