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Valuing Forecast Characteristics in a Dynamic Agricultural Production System

Author

Listed:
  • James W. Mjelde
  • Steven T. Sonka
  • Bruce L. Dixon
  • Peter J. Lamb

Abstract

A dynamic programming model of east-central Illinois corn production is utilized to determine the value of seasonal climate forecasts. Results indicate that the value of climate forecasts is sensitive to economic conditions as well as forecast characteristics. A trade-off between forecast accuracy and lead time exists. A less accurate forecast received earlier in the production process may be more valuable than a more accurate forecast received later. Additional characteristics evaluated include forecast periods of greatest importance, prior knowledge assumptions, and interactions between forecasting adjacent periods.

Suggested Citation

  • 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.
    • Handle: RePEc:oup:ajagec:v:70:y:1988:i:3:p:674-684.
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    Cited by:

    1. Ying Zhang & Liangzhi You & Donghoon Lee & Paul Block, 2020. "Integrating climate prediction and regionalization into an agro-economic model to guide agricultural planning," Climatic Change, Springer, vol. 158(3), pages 435-451, February.
    2. 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.
    3. Hansen, James W., 2002. "Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges," Agricultural Systems, Elsevier, vol. 74(3), pages 309-330, December.
    4. Wallace, Garry E. & Samsul Huda, A.K., 2005. "Using climate information to approximate the value at risk of a forward contracted canola crop," AFBM Journal, Australasian Farm Business Management Network, vol. 2(1), pages 1-9.
    5. 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.
    6. Regnier, Eva, 2008. "Doing something about the weather," Omega, Elsevier, vol. 36(1), pages 22-32, February.
    7. Ingram, K. T. & Roncoli, M. C. & Kirshen, P. H., 2002. "Opportunities and constraints for farmers of west Africa to use seasonal precipitation forecasts with Burkina Faso as a case study," Agricultural Systems, Elsevier, vol. 74(3), pages 331-349, December.
    8. Hammer, G. L. & Hansen, J. W. & Phillips, J. G. & Mjelde, J. W. & Hill, H. & Love, A. & Potgieter, A., 2001. "Advances in application of climate prediction in agriculture," Agricultural Systems, Elsevier, vol. 70(2-3), pages 515-553.
    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. Gitonga, Zachary M. & Visser, Martine & Mulwa, Chalmers, 2020. "Can climate information salvage livelihoods in arid and semiarid lands? An evaluation of access, use and impact in Namibia," World Development Perspectives, Elsevier, vol. 20(C).
    11. Mazzocco, Michael A. & Sherrick, Bruce J. & Sonka, Steven T., 1992. "The Role of Decision Maker Expectations in Valuing Climate Information," WAEA/ WFEA Conference Archive (1929-1995) 321338, Western Agricultural Economics Association.
    12. Scott M. Swinton & Robert P. King, 1994. "The Value of Pest Information in a Dynamic Setting: The Case of Weed Control," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(1), pages 36-46.
    13. Britt, Megan L. & Ramirez, Octavio A. & Carpio, Carlos E., 2002. "Effects Of Quality Considerations And Climate/Weather Information On The Management And Profitability Of Cotton Production In The Texas High Plains," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 34(3), pages 1-23, December.
    14. Mark R. Rosenzweig & Christopher R. Udry, 2019. "Assessing the Benefits of Long-Run Weather Forecasting for the Rural Poor: Farmer Investments and Worker Migration in a Dynamic Equilibrium Model," NBER Working Papers 25894, National Bureau of Economic Research, Inc.
    15. Larson, James A. & Mapp, Harry P. & Verhalen, Laval M. & Banks, J. C., 1996. "Adapting a cotton model for decision analyses: a yield-response evaluation," Agricultural Systems, Elsevier, vol. 50(2), pages 145-167.
    16. Abedullah & Sushil Pandey, 2007. "The Value of Rainfall Forecasts in the Rainfed Rice Areas of the Philippines," Lahore Journal of Economics, Department of Economics, The Lahore School of Economics, vol. 12(2), pages 69-81, Jul-Dec.
    17. Bert, Federico E. & Satorre, Emilio H. & Toranzo, Fernando Ruiz & Podesta, Guillermo P., 2006. "Climatic information and decision-making in maize crop production systems of the Argentinean Pampas," Agricultural Systems, Elsevier, vol. 88(2-3), pages 180-204, June.
    18. Mjelde, J. W. & Hill, H. S. J., 1999. "The effect of the use of improved climate forecasts on variable costs, input usage, and production," Agricultural Systems, Elsevier, vol. 60(3), pages 213-225, June.
    19. Kusunose, Yoko & Mahmood, Rezaul, 2016. "Imperfect forecasts and decision making in agriculture," Agricultural Systems, Elsevier, vol. 146(C), pages 103-110.
    20. Sylvester Mpandeli, 2014. "Managing Climate Risks Using Seasonal Climate Forecast Information in Vhembe District in Limpopo Province, South Africa," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 7(5), pages 1-68, September.
    21. Sylvain Caurla & Antonello Lobianco, 2020. "Estimating climate service value in forestry : The case of climate information on drought for maritime pine in Southwestern France," Post-Print hal-03639335, HAL.
    22. Antle, John M. & Capalbo, Susan Marie & Mooney, Sian, 1999. "Optimal Spatial Scale For Evaluating Economic And Environmental Tradeoffs," 1999 Annual meeting, August 8-11, Nashville, TN 21660, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    23. Maggio, Giuseppe & Sitko, Nicholas, 2019. "Knowing is half the battle: Seasonal forecasts, adaptive cropping systems, and the mediating role of private markets in Zambia," Food Policy, Elsevier, vol. 89(C).
    24. Sylvain Caurla & Antonello Lobianco, 2020. "Estimating climate service value in forestry : The case of climate information on drought for maritime pine in Southwestern France," Post-Print hal-02617889, HAL.
    25. 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.

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