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Climate impact on the USDA ending stocks forecast errors

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  • Li, Ziran
  • Li, Ding
  • Zhang, Tengfei
  • Zhang, Tianyang

Abstract

Analysts and investors that make financial forecasts are prone to climate-induced biases. Would public institutions reporting market-moving forecasts also be influenced by climate? This article analyzes the role of climate in explaining the USDA ending stocks forecast errors. We show that during the period from 1980/81 to 2018/19, the USDA forecasts of corn ending stocks did not take precipitation during the summer growing season fully into account. Increasing precipitation is likely to lead the USDA to underestimate the ending stocks level. The proposed model increases the USDA ending stock forecasts by 12.4%, and the results are robust in different subsamples.

Suggested Citation

  • Li, Ziran & Li, Ding & Zhang, Tengfei & Zhang, Tianyang, 2022. "Climate impact on the USDA ending stocks forecast errors," Finance Research Letters, Elsevier, vol. 48(C).
    • Handle: RePEc:eee:finlet:v:48:y:2022:i:c:s1544612322001799
    DOI: 10.1016/j.frl.2022.102930
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    References listed on IDEAS

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    1. William N. Goetzmann & Dasol Kim & Alok Kumar & Qin Wang, 2015. "Weather-Induced Mood, Institutional Investors, and Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 73-111.
    2. David Hirshleifer & Tyler Shumway, 2003. "Good Day Sunshine: Stock Returns and the Weather," Journal of Finance, American Finance Association, vol. 58(3), pages 1009-1032, June.
    3. Westcott, Paul C. & Jewison, Michael, 2013. "Weather Effects on Expected Corn and Soybean Yields," Agricultural Outlook Forum 2013 146846, United States Department of Agriculture, Agricultural Outlook Forum.
    4. Jiang, Danling & Norris, Dylan & Sun, Lin, 2021. "Weather, institutional investors and earnings news," Journal of Corporate Finance, Elsevier, vol. 69(C).
    5. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    6. Good, Darrel & Irwin, Scott, 2014. "Accuracy of USDA Forecasts of Corn Ending Stocks," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 4, May.
    7. Jinzhi Xiao & Chad E. Hart & Sergio H. Lence, 2017. "USDA Forecasts Of Crop Ending Stocks: How Well Have They Performed?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 39(2), pages 220-241.
    8. Olga Isengildina-Massa & Berna Karali & Scott H. Irwin, 2013. "When do the USDA forecasters make mistakes?," Applied Economics, Taylor & Francis Journals, vol. 45(36), pages 5086-5103, December.
    9. Michael K Adjemian & Scott H Irwin, 2018. "USDA Announcement Effects in Real-Time," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(4), pages 1151-1171.
    10. Tianyang Zhang & Ziran Li, 2022. "Can a rational expectation storage model explain the USDA ending grain stocks forecast errors?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 313-337, March.
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