IDEAS home Printed from https://ideas.repec.org/p/ags/nccc23/379017.html

Does Complexity Pay? Forecasting Corn and Soybean Yields Using Crop Condition Ratings

Author

Listed:
  • Li, Jiarui
  • Irwin, Scott H.
  • Hubbs, Todd

Abstract

No abstract is available for this item.

Suggested Citation

  • Li, Jiarui & Irwin, Scott H. & Hubbs, Todd, 2023. "Does Complexity Pay? Forecasting Corn and Soybean Yields Using Crop Condition Ratings," 2023 Conference, April 24-25, 2023, St. Louis, Missouri 379017, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    • Handle: RePEc:ags:nccc23:379017
    DOI: 10.22004/ag.econ.379017
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/379017/files/Li_Irwin_Hubbs_NCCC-134_2023.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.379017?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
    ---><---

    References listed on IDEAS

    as
    1. Lehecka, Georg V., 2014. "The Value of USDA Crop Progress and Condition Information: Reactions of Corn and Soybean Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(01), pages 1-18, April.
    2. John Kruse & Darnell B. Smith, 1994. "Yield Estimation Throughout the Growing Season," Center for Agricultural and Rural Development (CARD) Publications 94-tr29, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    3. Kruse, John R. & Smith, Darnell, 1994. "Yield Estimation Throughout the Growing Season," 1981-1999 Conference Archive 285619, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    4. Rogier Quaedvlieg, 2021. "Multi-Horizon Forecast Comparison," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 40-53, January.
    5. Kruse, John & Smith, Darnell, 1994. "Yield Estimation Throughout the Growing Season," Staff General Research Papers Archive 768, Iowa State University, Department of Economics.
    6. Colino, Evelyn V. & Irwin, Scott H. & Garcia, Philip & Etienne, Xiaoli, 2012. "Composite and Outlook Forecast Accuracy," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(2), pages 1-19, August.
    7. Bain, Ryan & Fortenbery, T. Randall, 2017. "Impact Of Crop Condition Reports On National And Local Wheat Markets," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(1), pages 97-119, February.
    8. Peter R. Hansen & Asger Lunde & James M. Nason, 2011. "The Model Confidence Set," Econometrica, Econometric Society, vol. 79(2), pages 453-497, March.
    9. Lawrence H. Shaw, 1964. "The Effect of Weather on Agricultural Output: A Look at Methodology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 46(1), pages 218-230.
    10. Fackler, Paul L. & Norwood, Bailey, 1999. "Forecasting Crop Yields and Condition Indices," 1981-1999 Conference Archive 285737, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    11. Irwin, Scott H. & Good, Darrel L. & Tannura, Mike, "undated". "2009 Final Corn and Soybean Yield Forecasts," Marketing and Outlook Briefs 183521, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    13. John Kruse & Darnell B. Smith, 1994. "Yield Estimation Throughout the Growing Season," Food and Agricultural Policy Research Institute (FAPRI) Publications (archive only) 94-tr29, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    14. Irwin, Scott & Hubbs, Todd, . "What to Make of High Early Season Crop Condition Ratings for Corn?," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8.
    15. Irwin, Scott & Hubbs, Todd, . "Measuring the Accuracy of Forecasting Corn and Soybean Yield with Good and Excellent Crop Condition Ratings," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8.
    16. Robert K. Kaufmann & Seth E. Snell, 1997. "A Biophysical Model of Corn Yield: Integrating Climatic and Social Determinants," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(1), pages 178-190.
    17. Irwin, Scott & Good, Darrel, . "How Should We Use Within-Season Crop Condition Ratings for Corn and Soybeans?," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 7.
    18. Irwin, Scott & Hubbs, Todd, . "Does the Bias in Early Season Crop Condition Ratings for Corn and Soybeans Vary with the Magnitude of the Ratings?," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8.
    19. Irwin, Scott & Good, Darrel, . "When Should We Start Paying Attention to Crop Condition Ratings for Corn and Soybeans?," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 7.
    20. Irwin, Scott & Hubbs, Todd, . "What to Make of High Early Season Crop Condition Ratings for Soybeans," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 8.
    Full references (including those not matched with items on IDEAS)

    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. Li, Jiarui & Irwin, Scott H. & Hubbs, Todd, . "Does Complexity Pay? Forecasting Corn and Soybean Yields Using Crop Condition Ratings," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 51(1).
    2. Cao, An N.Q. & Gebrekidan, Bisrat Haile & Heckelei, Thomas & Robe, Michel A., 2022. "County-level USDA Crop Progress and Condition data, machine learning, and commodity market surprises," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322281, Agricultural and Applied Economics Association.
    3. Tannura, Michael A. & Irwin, Scott H. & Good, Darrel L., 2008. "Weather, Technology, and Corn and Soybean Yields in the U.S. Corn Belt," Marketing and Outlook Research Reports 37501, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    4. J. R. Stokes, 2024. "A Markov chain model of crop conditions and intrayear crop yield forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 583-592, April.
    5. Lehecka, Georg V., 2014. "The Value of USDA Crop Progress and Condition Information: Reactions of Corn and Soybean Futures Markets," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(01), pages 1-18, April.
    6. Fackler, Paul L. & Norwood, Bailey, 1999. "Forecasting Crop Yields and Condition Indices," 1981-1999 Conference Archive 285737, NCR-134/ NCCC-134 Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    7. Etienne, Xiaoli L. & Farhangdoost, Sara & Hoffman, Linwood A. & Adam, Brian D., 2023. "Forecasting the U.S. season-average farm price of corn: Derivation of an alternative futures-based forecasting model," Journal of Commodity Markets, Elsevier, vol. 30(C).
    8. Nicholas Jorgensen & Matthew Diersen, 2014. "Forecasting Corn and Sotbean Yields with Crop Conditions," Issue Briefs 2014547, South Dakota State University, Department of Economics.
    9. Lehecka, Georg V., 2013. "The Reaction of Corn and Soybean Futures Markets to USDA Crop Progress and Condition Information," 2013 Annual Meeting, February 2-5, 2013, Orlando, Florida 142491, Southern Agricultural Economics Association.
    10. Verena Monschang & Mark Trede & Bernd Wilfling, 2023. "Multi-horizon uniform superior predictive ability revisited: A size-exploiting and consistent test," CQE Working Papers 10623, Center for Quantitative Economics (CQE), University of Muenster.
    11. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    12. Michael K. Adjemian & Valentina G. Bruno & Michel A. Robe, 2020. "Incorporating Uncertainty into USDA Commodity Price Forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 696-712, March.
    13. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
    14. Fava, Santino Del & Gupta, Rangan & Pierdzioch, Christian & Rognone, Lavinia, 2024. "Forecasting international financial stress: The role of climate risks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
    15. Min Liu & Chien‐Chiang Lee & Wei‐Chong Choo, 2021. "An empirical study on the role of trading volume and data frequency in volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 792-816, August.
    16. Mtiraoui, Amine & Boubaker, Heni & BelKacem, Lotfi, 2023. "A hybrid approach for forecasting bitcoin series," Research in International Business and Finance, Elsevier, vol. 66(C).
    17. Krzysztof Drachal & Michał Pawłowski, 2024. "Forecasting Selected Commodities’ Prices with the Bayesian Symbolic Regression," IJFS, MDPI, vol. 12(2), pages 1-56, March.
    18. Isengildina-Massa, Olga & Sharp, Julia L., 2013. "Interval Forecast Comparison," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150791, Agricultural and Applied Economics Association.
    19. Hossein Hassani & Emmanuel Sirimal Silva, 2015. "A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts," Econometrics, MDPI, vol. 3(3), pages 1-20, August.
    20. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.

    More about this item

    Keywords

    ;
    ;

    Statistics

    Access and download statistics

    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:nccc23:379017. 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: http://www.farmdoc.illinois.edu/nccc134/ .

    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.