IDEAS home Printed from
   My bibliography  Save this paper

The economic effect of genomic technology on the forestry industry


  • Wang, S.
  • An, H.
  • Chang, W.-Y.
  • Gaston, C.


In response to threats from climate change, such as an increased likelihood of droughts and insect outbreaks, significant investments in forestry genomics research have been made. The main advantage of genomic technology is that it greatly reduces the amount of R&D time to come up with a new product, and it is much more precise than traditional breeding techniques. However, the technology also comes with higher upfront R&D costs. Thus, whether the research effort would result in a worthwhile use of scarce research resources remains unknown. To help quantify the economic effect, we assess the welfare consequences of the forestry genomic research by estimating a timber supply model and a dynamic global forest products trade model. Using the forest industry of Alberta as our empirical setting, we find that the research program can yield an increase in total economic surplus of 400 million CAD in present value and the benefit-cost ratio of the research program is 43.9, indicating that more resources can be allocated advantageously to genomics-assisted tree breeding programs. The findings provide a justification for adopting genomic technology in the forestry sector and are useful in supporting genomics-enhanced reforestation policies and investment decisions. Acknowledgement : We acknowledge cash funding for this research from Genome Canada, Genome Alberta through Alberta Economic Trade and Development, Genome British Columbia, the University of Alberta and the University of Calgary. Further cash funding has been provided by Alberta Innovates BioSolutions, Forest Resource Improvement Association of Alberta, and the Forest Resource Improvement Program through West Fraser Ltd. and Weyerhaeuser Timberlands. In-kind funding has been provided by Alberta Agriculture and Forestry, Blue Ridge Lumber West Fraser, Weyerhaeuser Timberlands Grande Prairie, and the Thomas, Wishart, and Erbilgin labs in support of the Resilient Forests (RES-FOR): Climate, Pests & Policy Genomic Applications project.

Suggested Citation

  • Wang, S. & An, H. & Chang, W.-Y. & Gaston, C., 2018. "The economic effect of genomic technology on the forestry industry," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277443, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae18:277443

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Naseem, Anwar & Singla, Rohit, 2013. "Ex Ante Economic Impact Analysis of Novel Traits in Canola," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(2), pages 1-21, August.
    2. Robert L. Weaber & Jayson L. Lusk, 2010. "The Economic Value of Improvements in Beef Tenderness by Genetic Marker Selection," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1456-1471.
    3. Paris, Quirino & Drogué, Sophie & Anania, Giovanni, 2011. "Calibrating spatial models of trade," Economic Modelling, Elsevier, vol. 28(6), pages 2509-2516.
    4. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    5. Munisamy Gopinath & Terry Roe, 2000. "R&D Spillovers: Evidence from U.S. Food Processing, Farm Machinery and Agricultural Sectors," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 9(3), pages 223-244.
    6. van Kooten, G. Cornelis & Johnston, Craig, 2014. "Global impacts of Russian log export restrictions and the Canada–U.S. lumber dispute: Modeling trade in logs and lumber," Forest Policy and Economics, Elsevier, vol. 39(C), pages 54-66.
    Full references (including those not matched with items on IDEAS)

    More about this item


    Resource/Energy Economics and Policy;

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:iaae18:277443. 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.