IDEAS home Printed from https://ideas.repec.org/p/ags/midasp/201163.html
   My bibliography  Save this paper

The Value of Pest Information in a Dynamic Setting: The Case of Weed Control

Author

Listed:
  • Swinton, Scott M.
  • King, Robert P.

Abstract

The value of weed scouting information for soil-applied and post-emergence weed management is estimated using a dynamic, whole-farm, stochastic simulation model. The model simulates outcomes of four expected utility functions from management strategies using three levels of weed information. Results from a representative Minnesota corn and soybean farm indicate high value of weed seedling counts (for post-emergence control) but relatively low value of weed seed counts (for soil-applied control). While herbicide use is often reduced under information based management, this is not always the case.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Swinton, Scott M. & King, Robert P., 1992. "The Value of Pest Information in a Dynamic Setting: The Case of Weed Control," Staff Paper Series 201163, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    • Handle: RePEc:ags:midasp:201163
    DOI: 10.22004/ag.econ.201163
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/201163/files/agecon-msu-92-80.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.201163?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Craig Osteen & Fred Kuchler, 1987. "Pesticide regulatory decisions: Production efficiency, equity, and interdependence," Agribusiness, John Wiley & Sons, Ltd., vol. 3(3), pages 307-322.
    2. Byerlee, Derek R. & Anderson, Jock R., 1982. "Risk, Utility and the Value of Information in Farmer Decision Making," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 50(03), pages 1-16, December.
    3. Thomas R. Harris & Harry P. Mapp, 1986. "A Stochastic Dominance Comparison of Water-Conserving Irrigation Strategies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(2), pages 298-305.
    4. Swinton, Scott M. & King, Robert P., 1994. "A bioeconomic model for weed management in corn and soybean," Agricultural Systems, Elsevier, vol. 44(3), pages 313-335.
    5. Darrell J. Bosch & Vernon R. Eidman, 1987. "Valuing Information When Risk Preferences Are Nonneutral: An Application to Irrigation Scheduling," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 69(3), pages 658-668.
    6. James W. Mjelde & Steven T. Sonka & Bruce L. Dixon & Peter J. Lamb, 1988. "Valuing Forecast Characteristics in a Dynamic Agricultural Production System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 70(3), pages 674-684.
    7. Pannell, David J., 1990. "An Economic Response Model Of Herbicide Application For Weed Control," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 34(3), pages 1-19, December.
    8. Jean-Paul Chavas & Rulon D. Pope, 1984. "Information: Its Measurement and Valuation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(5), pages 705-710.
    9. C. Robert Taylor & Oscar R. Burt, 1984. "Near-Optimal Management Strategies for Controlling Wild Oats in Spring Wheat," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(1), pages 50-60.
    10. Raskin, Rob & Cochran, Mark J., 1986. "Interpretations And Transformations Of Scale For The Pratt-Arrow Absolute Risk Aversion Coefficient: Implications For Generalized Stochastic Dominance," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-7, December.
    11. Lybecker, Donald & Schweizer, Edward & Westra, Philip, 1991. "Computer Aided Decisions for Weed Management in Corn," WAEA/ WFEA Conference Archive (1929-1995) 321442, Western Agricultural Economics Association.
    12. Yen-Shong Chiao & Allan Gillingham, 1989. "The Value of Stabilizing Fertilizer under Carry-Over Conditions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 352-362.
    13. Katherine H. Reichelderfer & Filmore E. Bender, 1979. "Application of a Simulative Approach to Evaluating Alternative Methods for the Control of Agricultural Pests," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 258-267.
    14. Richard A. Schoney & J. Thomas McGuckin, 1983. "Economics of the Wet Fractionation System in Alfalfa Harvesting," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(1), pages 38-44.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dirksmeyer, Walter, 2007. "Ist Eine Reduzierung Des Pflanzenschutzmitteleinsatzes Im Freilandgemüsebau Möglich? Ergebnisse Eines Bioökonomischen Simulationsmodells," 47th Annual Conference, Weihenstephan, Germany, September 26-28, 2007 7592, German Association of Agricultural Economists (GEWISOLA).
    2. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    3. Vaughn, Gerald F. & Breimyer, Harold F. & Paarlberg, Don & Lovell, Sabrina J. & Kuch, Peter J. & Otte, John & Gardner, Bruce L. & Randall, Alan & Cunfer, Barry M., 1999. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 14(3), pages 1-3.
    4. David J. Pannell, 2002. "Prose, Psychopaths and Persistence: Personal Perspectives on Publishing," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 50(2), pages 101-115, July.
    5. Cobourn, Kelly M. & Goodhue, Rachael E. & Williams, Jeffrey C., 2009. "The Role of Harvest Timing in Pest Management: Grower Response to Infestation by the California Olive Fruit Fly," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49475, Agricultural and Applied Economics Association.
    6. Lybbert, Travis J. & Magnan, Nicholas & Gubler, W. Douglas, 2012. "Multi-Dimensional Responses to Risk Information: How do Winegrape Growers Respond to Disease Forecasts and to What Environmental Effect?," Working Papers 162521, Robert Mondavi Institute Center for Wine Economics.
    7. Mitchell, Paul D., 2001. "Additive Versus Proportional Pest Damage Functions: Why Ecology Matters," 2001 Annual meeting, August 5-8, Chicago, IL 20775, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. Jonathan R. McFadden & Alicia Rosburg & Eric Njuki, 2022. "Information inputs and technical efficiency in midwest corn production: evidence from farmers' use of yield and soil maps," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(2), pages 589-612, March.
    9. Wiles, L. J. & King, R. P. & Schweizer, E. E. & Lybecker, D. W. & Swinton, S. M., 1996. "GWM: General weed management model," Agricultural Systems, Elsevier, vol. 50(4), pages 355-376.
    10. Poon, Kenneth & Weersink, Alfons & Deaton, Brady J., Jr., 2011. "Demand and Supply Analysis of Farm, Farmer and Farm Family Data," Working Papers 114094, Structure and Performance of Agriculture and Agri-products Industry (SPAA).
    11. Bennett, Anne L. & Pannell, David J., 1998. "Economic evaluation of a weed-activated sprayer for herbicide application to patchy weed populations," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 42(4), pages 1-20.
    12. Woongchan Jeon & Kwansoo Kim, 2017. "Optimal Weed Control Strategies in Rice Production under Dynamic and Static Decision Rules in South Korea," Sustainability, MDPI, vol. 9(6), pages 1-11, June.
    13. Haight, Robert G. & Polasky, Stephen, 2010. "Optimal control of an invasive species with imperfect information about the level of infestation," Resource and Energy Economics, Elsevier, vol. 32(4), pages 519-533, November.
    14. Dirksmeyer, W., 2008. "Ist eine Reduzierung des Pflanzenschutzmitteleinsatzes im Freilandgemüsebau möglich? Ergebnisse eines bioökonomischen Simulationsmodells," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 43, March.

    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. Swinton, Scott M. & King, Robert P., 1994. "A bioeconomic model for weed management in corn and soybean," Agricultural Systems, Elsevier, vol. 44(3), pages 313-335.
    2. Regmi, Anita, 1990. "The value of information in integrated pest management of corn rootworm and European corn borer in Minnesota," Faculty and Alumni Dissertations 307267, University of Minnesota, Department of Applied Economics.
    3. Oriade, Caleb Adewale, 1995. "A bioeconomic analysis of site-specific management and delayed planting strategies for weed control," Faculty and Alumni Dissertations 307890, University of Minnesota, Department of Applied Economics.
    4. Oriade, Caleb A. & Dillon, Carl R., 1997. "Developments in biophysical and bioeconomic simulation of agricultural systems: a review," Agricultural Economics, Blackwell, vol. 17(1), pages 45-58, October.
    5. Swinton, Scott M. & King, Robert P. & Lybecker, Donald W., 1992. "The Effect of Triazine Restriction Policies on Recommended Weed Management in Corn," Staff Paper Series 201160, Michigan State University, Department of Agricultural, Food, and Resource Economics.
    6. Goh, Siew & Shih, Chao-Chyuan & Cochran, Mark J. & Raskin, Rob, 1989. "A Generalized Stochastic Dominance Program For The Ibm Pc," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 21(2), pages 1-8, December.
    7. D. J. Pannell, 1990. "Responses To Risk In Weed Control Decisions Under Expected Profit Maximisation," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(3), pages 391-401, September.
    8. Archer, David Walter, 1995. "Self-insurance and self-protection in weed control: implications for nonpoint source pollution," ISU General Staff Papers 1995010108000012033, Iowa State University, Department of Economics.
    9. Graham R. Marshall & Kevin A. Parton & G.L. Hammer, 1996. "Risk Attitude, Planting Conditions And The Value Of Seasonal Forecasts To A Dryland Wheat Grower," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 40(3), pages 211-233, December.
    10. Russell J. Gorddard & David J. Pannell & Greg Hertzler, 1995. "An Optimal Control Model For Integrated Weed Management Under Herbicide Resistance," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(1), pages 71-87, April.
    11. Lybbert, Travis J. & Magnan, Nicholas & Gubler, W. Douglas, 2012. "Multi-Dimensional Responses to Risk Information: How do Winegrape Growers Respond to Disease Forecasts and to What Environmental Effect?," Working Papers 162521, Robert Mondavi Institute Center for Wine Economics.
    12. Gorddard, Russell J. & Pannell, David J. & Hertzler, Greg, 1996. "Economic evaluation of strategies for management of herbicide resistance," Agricultural Systems, Elsevier, vol. 51(3), pages 281-298, July.
    13. Wu, JunJie, 2001. "Optimal weed control under static and dynamic decision rules," Agricultural Economics, Blackwell, vol. 25(1), pages 119-130, June.
    14. Böcker, Thomas & Britz, Wolfgang & Finger, Robert, 2017. "Modelling the Effects of a Glyphosate Ban on Weed Management in Maize Production," 57th Annual Conference, Weihenstephan, Germany, September 13-15, 2017 261982, German Association of Agricultural Economists (GEWISOLA).
    15. Dillon, Carl R. & Mjelde, James W. & McCarl, Bruce A., 1989. "Biophysical Simulation In Support Of Crop Production Decisions: A Case Study In The Blacklands Region Of Texas," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 21(1), pages 1-14, July.
    16. Swinton, Scott M. & King, Robert P., 1990. "Weedsim: A Bioeconomic Model Of Weed Management In Corn," Staff Papers 14164, University of Minnesota, Department of Applied Economics.
    17. Liu, Yangxuan & Langemeier, Michael & Small, Ian & Joseph, Laura & Fry, William, 2015. "Risk management strategies using potato precision farming technology," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205417, Agricultural and Applied Economics Association.
    18. Archer, David W. & Shogren, Jason F., 2001. "Risk-indexed herbicide taxes to reduce ground and surface water pollution: an integrated ecological economics evaluation," Ecological Economics, Elsevier, vol. 38(2), pages 227-250, August.
    19. Petersen, E. H. & Fraser, R. W., 2001. "An assessment of the value of seasonal forecasting technology for Western Australian farmers," Agricultural Systems, Elsevier, vol. 70(1), pages 259-274, October.
    20. Yangxuan Liu & Michael R. Langemeier & Ian M. Small & Laura Joseph & William E. Fry & Jean B. Ristaino & Amanda Saville & Benjamin M. Gramig & Paul V. Preckel, 2018. "A Risk Analysis of Precision Agriculture Technology to Manage Tomato Late Blight," Sustainability, MDPI, vol. 10(9), pages 1-19, August.

    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:midasp:201163. 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/damsuus.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.