IDEAS home Printed from https://ideas.repec.org/p/ags/iaae18/277443.html
   My bibliography  Save this paper

The economic effect of genomic technology on the forestry industry

Author

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

Abstract

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
    DOI: 10.22004/ag.econ.277443
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/277443/files/579.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.277443?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Clancy, Matthew & Fuglie, Keith & Heisey, Paul, 2016. "U.S. Agricultural R&D in an Era of Falling Public Funding," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, issue 10, pages 1-1, November.
    3. 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.
    4. Paris, Quirino & Drogué, Sophie & Anania, Giovanni, 2011. "Calibrating spatial models of trade," Economic Modelling, Elsevier, vol. 28(6), pages 2509-2516.
    5. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    6. 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.
    7. 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.
    8. Barkley, Andrew P., 1997. "Kansas Wheat Breeding: An Economic Analysis," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35929, Western Agricultural Economics Association.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Johnston, Craig M.T. & Parajuli, Rajan, 2017. "What's next in the U.S.-Canada softwood lumber dispute? An economic analysis of restrictive trade policy measures," Forest Policy and Economics, Elsevier, vol. 85(P1), pages 135-146.
    2. Kooten, G. Cornelis van, 2013. "Modeling Forest Trade in Logs and Lumber: Qualitative and Quantitative Analysis," Working Papers 149182, University of Victoria, Resource Economics and Policy.
    3. Liu, Xuan & van Kooten, Gerrit Cornelis & Duan, Jun, 2020. "Calibration of agricultural risk programming models using positive mathematical programming," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(3), July.
    4. 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.
    5. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2016. "Global trade impacts of increasing Europe's bioenergy demand," Journal of Forest Economics, Elsevier, vol. 23(C), pages 27-44.
    6. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2017. "Impact of inefficient quota allocation under the Canada-U.S. softwood lumber dispute: A calibrated mixed complementarity approach," Forest Policy and Economics, Elsevier, vol. 74(C), pages 71-80.
    7. Umed Temurshoev & Marian Mraz & Luis Delgado Sancho & Peter Eder, 2015. "EU Petroleum Refining Fitness Check: OURSE Modelling and Results," JRC Research Reports JRC96207, Joint Research Centre.
    8. Johnston, Craig M.T. & van Kooten, G. Cornelis, 2014. "Modelling Bi-lateral Forest Product Trade Flows: Experiencing Vertical and Horizontal Chain Optimization," Working Papers 197898, University of Victoria, Resource Economics and Policy.
    9. Louhichi, Kamel & Gomez y Paloma, Sergio, 2014. "A farm household model for agri-food policy analysis in developing countries: Application to smallholder farmers in Sierra Leone," Food Policy, Elsevier, vol. 45(C), pages 1-13.
    10. Cao, Zhaodan & Zhu, Tingju & Cai, Ximing, 2023. "Hydro-agro-economic optimization for irrigated farming in an arid region: The Hetao Irrigation District, Inner Mongolia," Agricultural Water Management, Elsevier, vol. 277(C).
    11. Britz, Wolfgang & Linda, Arata, "undated". "How Important Are Crop Shares In Managing Risk For Specialized Arable Farms? A Panel Estimation Of A Programming Model For Three European Regions," 56th Annual Conference, Bonn, Germany, September 28-30, 2016 244801, German Association of Agricultural Economists (GEWISOLA).
    12. Kaplan, Jonathan D. & Johansson, Robert C., 2003. "When The !%$? Hits The Land: Implications For Us Agriculture And Environment When Land Application Of Manure Is Constrained," 2003 Annual meeting, July 27-30, Montreal, Canada 22002, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Franz Sinabell & Martin Schönhart & Erwin Schmid, 2015. "Austrian Agriculture 2010-2050. Quantitative Effects of Climate Change Mitigation Measures – An Analysis of the Scenarios WEM, WAM and a Sensitivity Analysis of the Scenario WEM," WIFO Studies, WIFO, number 58400, January.
    14. Scheierling, Susanne M. & Treguer, David O. & Booker, James F. & Decker, Elisabeth, 2014. "How to assess agricultural water productivity ? looking for water in the agricultural productivity and efficiency literature," Policy Research Working Paper Series 6982, The World Bank.
    15. Britz, Wolfgang & Kuhn, Arnim, 2011. "Can Hydro-economic River Basis Models Simulate Water Shadow Prices Under Asymmetric Access?," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114272, European Association of Agricultural Economists.
    16. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(1), March.
    17. Masahiko Gemma & Yacov Tsur, 2007. "The Stabilization Value of Groundwater and Conjunctive Water Management under Uncertainty ," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 29(3), pages 540-548.
    18. Schuck, Eric C. & Green, Gareth P., 2002. "Supply-based water pricing in a conjunctive use system: implications for resource and energy use," Resource and Energy Economics, Elsevier, vol. 24(3), pages 175-192, June.
    19. Key, Nigel D. & Kaplan, Jonathan D., 2007. "Multiple Environmental Externalities and Manure Management Policy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 32(1), pages 1-20, April.
    20. Kamel Louhichi & Aymeric Ricome & Sergio Gomez y Paloma, 2022. "Impacts of agricultural taxation in Sub‐Saharan Africa: Insights from agricultural produce cess in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 671-686, September.

    More about this item

    Keywords

    Resource/Energy Economics and Policy;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.