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Powdery Mildew Risk And Forecasting In Wine Grapes: Do Growers Change Risk Management Strategies In Response To Disease Forecasts?

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  • Lybbert, Travis J.
  • Magnan, Nicholas
  • Gubler, W. Douglas

Abstract

How and how well growers manage the risks inherent in agriculture has direct welfare implications for producers and consumers at both local and societal levels. While better weather, pest and disease forecast information are rapidly disseminating among producers and are often touted as promising inputs to production and risk management, little is known about how this new information actually shapes producer behavior in practice. We argue that better forecast information can benefit growers and improve their capacity to manage disease and pests effectively, but that we must jointly consider the various margins of adjustment available to growers in order to properly understand their response to this improved information. Using the case of California wine grape growers and high resolution panel data that includes plot-level powdery mildew treatments, we characterize growers’ response to a popular powdery mildew risk model that generates forecast in the form of a daily risk index (PMI). Our analysis suggests that growers using the PMI primarily adjust their choice of product in response to the PMI by switching to higher potency synthetic fungicides when the risk is high. Since these products have longer minimum intervals, this implies that – if anything – PMI users have longer intervals as the PMI increases. Our preliminary results also suggest that the net environmental impact of this documented multi-dimensional response to the PMI may actually be negative, although we emphasize that these are preliminary results. Futhermore, it is important to note that the magnitude of this effect is small compared to the general improvements in wine grape growers’ environmental impact over the past several years.

Suggested Citation

  • Lybbert, Travis J. & Magnan, Nicholas & Gubler, W. Douglas, 2010. "Powdery Mildew Risk And Forecasting In Wine Grapes: Do Growers Change Risk Management Strategies In Response To Disease Forecasts?," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61745, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea10:61745
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    File URL: http://purl.umn.edu/61745
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    References listed on IDEAS

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    1. Cowan, Robin & Gunby, Philip, 1996. "Sprayed to Death: Path Dependence, Lock-In and Pest Control Strategies," Economic Journal, Royal Economic Society, vol. 106(436), pages 521-542, May.
    2. Eli Feinerman & Joseph A. Herriges & Derald Holtkamp, 1992. "Crop Insurance as a Mechanism for Reducing Pesticide Usage: A Representative Farm Analysis," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 14(2), pages 169-186.
    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. Khanna, Madhu & Zilberman, David, 1997. "Incentives, precision technology and environmental protection," Ecological Economics, Elsevier, vol. 23(1), pages 25-43, October.
    5. Maria Travisi, Chiara & Nijkamp, Peter & Vindigni, Gabriella, 2006. "Pesticide risk valuation in empirical economics: a comparative approach," Ecological Economics, Elsevier, vol. 56(4), pages 455-474, April.
    6. Christopher B. Barrett, 1998. "The Value of Imperfect ENSO Forecast Information: Discussion," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1109-1112.
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    Cited by:

    1. Atallah, Shady S. & Gómez, Miguel I. & Conrad, Jon M., 2013. "A Bioeconomic Model of Plant Disease Management under Spatial-Dynamic Externalities: Grapevine Leafroll Disease," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151144, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Crop Production/Industries; Farm Management; D8; Q1; Q5;

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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