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A Comprehensive Evaluation of USDA Cotton Forecasts

Author

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  • Isengildina-Massa, Olga
  • MacDonald, Stephen
  • Xie, Ran

Abstract

This study evaluates all USDA cotton supply and demand estimates for the United States and China (including unpublished price forecasts) from 1985/86 through 2009/10 for accuracy and efficiency. Results reveal that at every stage of the forecasting cycle forecast smoothing was the most widespread and persistent type of inefficiency observed in most U.S. variables. Correlation with past errors indicated the tendency to repeat past errors in most cases. Tendency to overestimate growth was also found. Bias was uncommon and limited to several cases of overestimation of China’s exports and U.S. price and underestimation of China’s domestic use. While forecasts of China’s imports and endings stocks improved, U.S. price and ending stock forecast errors became larger toward the end of the study period.

Suggested Citation

  • Isengildina-Massa, Olga & MacDonald, Stephen & Xie, Ran, 2012. "A Comprehensive Evaluation of USDA Cotton Forecasts," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 37(01), pages 1-16, April.
    • Handle: RePEc:ags:jlaare:122314
    DOI: 10.22004/ag.econ.122314
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    File URL: https://ageconsearch.umn.edu/record/122314/files/Isengildina_%20pg.%2098-113.pdf
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    References listed on IDEAS

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    Cited by:

    1. Bahram Sanginabadi, 2018. "USDA Forecasts: A meta-analysis study," Papers 1801.06575, arXiv.org.
    2. Qingjie Zhou & Panpan Zhu & You Wu & Yinpeng Zhang, 2022. "Research on the Volatility of the Cotton Market under Different Term Structures: Perspective from Investor Attention," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    3. MacDonald, Stephen & Isengildina-Massa, Olga, 2012. "Information Rigidity and Correcting Inefficiency in USDA’s Commodity Forecasts," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124890, Agricultural and Applied Economics Association.
    4. McWilliams, William N. & Isengildina Massa, Olga & Stewart, Shamar L., 2024. "Annual Food Price Inflation Forecasting: A Macroeconomic Random Forest Approach," 2024 Annual Meeting, July 28-30, New Orleans, LA 343923, Agricultural and Applied Economics Association.
    5. 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.

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