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The Costs and Benefits of Pierce’s Disease Research in the California Winegrape Industry

Author

Listed:
  • Alston, Julian M.
  • Fuller, Kate
  • Kaplan, Jonathan D.
  • Tumber, Kabir

Abstract

Pierce’s Disease (PD) of grapevines costs more than $100 million per year, even with public control programs in place that cost $50 million per year (Tumber et al., 2012). If the PD Control Program ended, and the GWSS was distributed freely throughout California, the annual cost to the winegrape industry would increase by more than $185 million (Alston et al., 2012). Using a simulation model of the market for California winegrapes, we estimate the benefits from research, development and adoption of PD-resistant vines as ranging from $4 million to $125 million annually over a 50 year horizon, depending on the length of the R&D lag and the rate of adoption. In addition to these quantitative results the paper offers insight into the broader question of economic evaluation of damage-mitigation technology for perennial crops.

Suggested Citation

  • Alston, Julian M. & Fuller, Kate & Kaplan, Jonathan D. & Tumber, Kabir, 2013. "The Costs and Benefits of Pierce’s Disease Research in the California Winegrape Industry," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149994, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea13:149994
    DOI: 10.22004/ag.econ.149994
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    References listed on IDEAS

    as
    1. Alston, Julian M. & Fuller, Kate B. & Kaplan, Jonathan D. & Tumber, Kabir P., 2013. "Economic Consequences of Pierce’s Disease and Related Policy in the California Winegrape Industry," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(2), pages 1-29, August.
    2. Bruce A. Babcock & Erik Lichtenberg & David Zilberman, 1992. "Impact of Damage Control and Quality of Output: Estimating Pest Control Effectiveness," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 74(1), pages 163-172.
    3. Cheryl Brown & Lori Lynch & David Zilberman, 2002. "The Economics of Controlling Insect-Transmitted Plant Diseases," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 279-291.
    4. Atanu Saha & C. Richard Shumway & Arthur Havenner, 1997. "The Economics and Econometrics of Damage Control," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(3), pages 773-785.
    5. Alston, Julian M. & Chan-Kang, Connie & Marra, Michele C. & Pardey, Philip G. & Wyatt, T. J., 2000. "A meta-analysis of rates of return to agricultural R & D: ex pede Herculem?," Research reports 113, International Food Policy Research Institute (IFPRI).
    6. Robert G. Chambers & Erik Lichtenberg, 1994. "Simple Econometrics of Pesticide Productivity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(3), pages 407-417.
    7. Fuller, Kate B. & Alston, Julian M. & Sanchirico, James N., 2011. "Spatial Externalities and Vector-Borne Plant Diseases: Pierce’s Disease and the Blue-Green Sharpshooter in the Napa Valley," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103865, Agricultural and Applied Economics Association.
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    More about this item

    Keywords

    Agricultural and Food Policy; Crop Production/Industries; Production Economics;
    All these keywords.

    JEL classification:

    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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