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Information rigidities in USDA crop production forecasts

Author

Listed:
  • Raghav Goyal
  • Michael K. Adjemian
Abstract
USDA invests significant public resources into developing its crop projection reports. These publications inform decisions across the supply chain. Several previous studies find that revisions to the department's production and yield forecasts for major agricultural commodities are positively correlated and conclude that they deviate from what would be observed under rational expectations, possibly due to smoothing on the part of forecasters. Yet correlated revisions may also be explained by information rigidities that cause forecasts to be infrequently or only partially updated. We apply a recently developed test to these USDA revisions for corn, soybeans, and wheat, and find no significant evidence that the forecasts are smoothed strategically. Rather, we show that information rigidities are the more likely culprit, due to production and yield information that is either too costly to obtain or too noisy. Our results demonstrate that data challenges are the main source of inefficiency in USDA projections, and that the department can improve the efficiency of its forecasts by making investments that improve its access to crop data, perhaps through crop‐monitoring satellite and remote sensing technology.

Suggested Citation

  • Raghav Goyal & Michael K. Adjemian, 2023. "Information rigidities in USDA crop production forecasts," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(5), pages 1405-1425, October.
    • Handle: RePEc:wly:ajagec:v:105:y:2023:i:5:p:1405-1425
    DOI: 10.1111/ajae.12373
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    References listed on IDEAS

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    1. 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).
    2. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
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    7. Isengildina, Olga & Irwin, Scott H. & Good, Darrel L., 2013. "Do Big Crops Get Bigger and Small Crops Get Smaller? Further Evidence on Smoothing in U.S. Department of Agriculture Forecasts," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(01), pages 1-13, February.
    8. Scott H. Irwin & Mary E. Gerlow & Te‐Ru Liu, 1994. "The forecasting performance of livestock futures prices: A comparison to USDA expert predictions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(7), pages 861-875, October.
    9. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    10. Vogel, Fred A. & Bange, Gerald A., 1999. "Understanding USDA Crop Forecasts," USDA Miscellaneous 320799, United States Department of Agriculture.
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    12. Goyal, Raghav & Adjemian, Michael K., 2021. "The 2019 government shutdown increased uncertainty in major agricultural commodity markets," Food Policy, Elsevier, vol. 102(C).
    13. Olga Isengildina-Massa & Scott H. Irwin & Darrel L. Good & Jennifer K. Gomez, 2008. "Impact of WASDE reports on implied volatility in corn and soybean markets," Agribusiness, John Wiley & Sons, Ltd., vol. 24(4), pages 473-490.
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    15. Beckmann, Joscha & Reitz, Stefan, 2020. "Information rigidities and exchange rate expectations," Journal of International Money and Finance, Elsevier, vol. 105(C).
    16. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2021. "A new method to assess the degree of information rigidity using fixed-event forecasts," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1576-1589.
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    Cited by:

    1. Fernando Dupin da Cunha Mello & Prashant Kumar & Erick G. Sperandio Nascimento, 2024. "Advancements in Soybean Price Forecasting: Impact of AI and Critical Research Gaps in Global Markets," Economies, MDPI, vol. 12(11), pages 1-24, November.
    2. Fang, Xiaoyi & Katchova, Ani, 2024. "An Evaluation of the Revisions in the OECD-FAO Baseline Projections in the European Union," 2024 Annual Meeting, July 28-30, New Orleans, LA 344007, Agricultural and Applied Economics Association.

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