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Application of Comparative Dynamics in Stochastic Invasive Species Management in Agricultural Production

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  • Lu, Liang
  • Elbakidze, Levan
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    Abstract

    In this study, we formulate a stochastic dynamic framework for pest control over the growing season taking into account forecasts of weather conditions and pest infestation expectations. Using stochastic envelope theorem and stochastic comparative dynamics, we analytically show how the stochastic correlation between the prediction errors should affect optimal pesticide usage path. As a case study, we apply the analytical results of the paper for pesticide use in the Palouse region of Washington where pea aphid is the primary threat for lentil production. By stochastic dynamic programming, our simulation shows the optimal dimethoate usage path, which illustrates our findings in the analytical part.

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    File URL: http://purl.umn.edu/124971
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    Bibliographic Info

    Paper provided by Agricultural and Applied Economics Association in its series 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington with number 124971.

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    Date of creation: 2012
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    Handle: RePEc:ags:aaea12:124971

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    Keywords: Stochastic Optimal Control; Climate Change; Pest Management; Crop Production/Industries; Farm Management; Q10; Q54;

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    1. Lars J. Olson & Santanu Roy, 2002. "The Economics of Controlling a Stochastic Biological Invasion," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(5), pages 1311-1316.
    2. Thomas L. Marsh & Ray G. Huffaker & Garrell E. Long, 2000. "Optimal Control of Vector-Virus-Plant Interactions: The Case of Potato Leafroll Virus Net Necrosis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(3), pages 556-569.
    3. David Sunding & Joshua Zivin, 2000. "Insect Population Dynamics, Pesticide Use, and Farmworker Health," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(3), pages 527-540.
    4. Jean-Daniel M. Saphores, 2000. "The Economic Threshold with a Stochastic Pest Population: A Real Options Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(3), pages 541-555.
    5. Saphores, Jean-Daniel M. & Shogren, Jason F., 2005. "Managing exotic pests under uncertainty: optimal control actions and bioeconomic investigations," Ecological Economics, Elsevier, vol. 52(3), pages 327-339, February.
    6. T.J. Richards & J. Eaves & M. Manfredo & S.E. Naranjo & C.-C. Chu & T.J. Henneberry, 2008. "Spatial-Temporal Model of Insect Growth, Diffusion and Derivative Pricing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 962-978.
    7. Cobourn, Kelly M. & Burrack, Hannah J. & Goodhue, Rachael E. & Williams, Jeffrey C. & Zalom, Frank G., 2011. "Implications of simultaneity in a physical damage function," Journal of Environmental Economics and Management, Elsevier, vol. 62(2), pages 278-289, September.
    8. Zivin, Joshua & Hueth, Brent M. & Zilberman, David, 2000. "Managing a Multiple-Use Resource: The Case of Feral Pig Management in California Rangeland," Journal of Environmental Economics and Management, Elsevier, vol. 39(2), pages 189-204, March.
    9. LaFrance, Jeffrey T. & Barney, L. Dwayne, 1991. "The envelope theorem in dynamic optimization," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 355-385, April.
    10. Chang,Fwu-Ranq, 2004. "Stochastic Optimization in Continuous Time," Cambridge Books, Cambridge University Press, number 9780521834063, April.
    11. Alain Carpentier & Robert D. Weaver, 1997. "Damage Control Productivity: Why Econometrics Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 47-61.
    12. Richard M. Adams & Stephen Polasky, 1998. "The Value of El Ni´┐Żo Forecasts in the Management of Salmon: A Stochastic Dynamic Assessment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(4), pages 765-777.
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