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Changes in Informational Value and the Market Reaction to USDA Reports in the Big Data Era

Author

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  • Karali, Berna
  • Isengildina-Massa, Olga
  • Irwin, Scott H.
  • Adjemian, Michael K.

Abstract

This study investigates whether major USDA reports still provide important news to changing crop markets. The news component of each report, or market “surprise,” is measured as a difference between the USDA estimate and its private expectation in corn, soybeans, and wheat markets. Changes in the relevance of USDA information are assessed by examining changes in the magnitude of market surprises and shifts in the futures price reaction to these surprises, which isolates the impact of each report. The stable size of market surprises over time suggests that competition from alternative data sources has not reduced the news component of USDA crop reports. Increasing price reaction to most reports, including those facing competition from alternative information sources, suggests that value of public information may be enhanced in uncertain markets affected by structural changes.
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Suggested Citation

  • Karali, Berna & Isengildina-Massa, Olga & Irwin, Scott H. & Adjemian, Michael K., 2016. "Changes in Informational Value and the Market Reaction to USDA Reports in the Big Data Era," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235580, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea16:235580
    DOI: 10.22004/ag.econ.235580
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    2. Arnade, Carlos Anthony & Hoffman, Linwood A., 2020. "The Impact of Public Information on Commodity Market Performance : The Response of Corn Futures to USDA Corn Production Forecasts," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304181, Agricultural and Applied Economics Association.
    3. Ying, Jiahui & Shonkwiler, J. Scott, 2017. "A Temporal Impact Assessment Method for the Informational Content of USDA Reports in Corn and Soybean Futures Markets," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258201, Agricultural and Applied Economics Association.
    4. Berna Karali & Scott H. Irwin & Olga Isengildina‐Massa, 2020. "Supply Fundamentals and Grain Futures Price Movements," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 548-568, March.
    5. Siddhartha S. Bora & Ani L. Katchova & Todd H. Kuethe, 2021. "The Rationality of USDA Forecasts under Multivariate Asymmetric Loss," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1006-1033, May.
    6. Cao, An N.Q. & Heckelei, Thomas & Ionici, Octavian & Robe, Michel A., 2024. "USDA reports affect the stock market, too," Journal of Commodity Markets, Elsevier, vol. 34(C).
    7. Joshua Huang & Teresa Serra & Philip Garcia, 2021. "The Value of USDA Announcements in the Electronically Traded Corn Futures Market: A Modified Sufficient Test with Risk Adjustments," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 712-734, September.
    8. Goyal, Raghav & Adjemian, Michael K., 2021. "The 2019 government shutdown increased uncertainty in major agricultural commodity markets," Food Policy, Elsevier, vol. 102(C).
    9. Adjemian, Michael K. & Irwin, Scott H., 2020. "The market response to government crop news under different release regimes," Journal of Commodity Markets, Elsevier, vol. 19(C).
    10. Isengildina-Massa, Olga & Cao, Xiang & Karali, Berna & Irwin, Scott H. & Adjemian, Michael & Johansson, Robert C., 2021. "When does USDA information have the most impact on crop and livestock markets?," Journal of Commodity Markets, Elsevier, vol. 22(C).
    11. An N. Q. Cao & Michel A. Robe, 2022. "Market uncertainty and sentiment around USDA announcements," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(2), pages 250-275, February.
    12. Pierrick Piette, 2019. "Can Satellite Data Forecast Valuable Information from USDA Reports ? Evidences on Corn Yield Estimates," Working Papers hal-02149355, HAL.
    13. Jesse Tack & Keith H. Coble & Robert Johansson & Ardian Harri & Barry J. Barnett, 2019. "The Potential Implications of “Big Ag Data” for USDA Forecasts," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 41(4), pages 668-683, December.
    14. Kexin Ding & Ani L. Katchova, 2024. "Testing the optimality of USDA's WASDE forecasts under unknown loss," Agribusiness, John Wiley & Sons, Ltd., vol. 40(4), pages 846-865, October.
    15. Capitani, Daniel H D & Mattos, Fabio L. & Cruz, Jose Cesar & Silva, Renato Moraes & Franco Da Silveira, Rodrigo Lanna, 2024. "The Reaction Of Corn Futures Prices To U.S. And Brazilian Crop Reports," 2024 Annual Meeting, July 28-30, New Orleans, LA 343571, Agricultural and Applied Economics Association.

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    More about this item

    Keywords

    Demand and Price Analysis;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness

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