Is Being Bold Better? Industry Expectations of USDA Corn and Soybean Production Estimates

ABSTRACT Despite the extensive use of industry expectations in measuring forecast accuracy and price reactions to USDA reports, very little is known about their properties beyond the basic statistical characteristics of bias, rationality, efficiency, and relative accuracy. Using unique proprietary data of firm‐level expectations for upcoming USDA corn and soybean production estimates, we demonstrate that these forecasts exhibit cognitive biases such as attribution and anchoring. Prior success leads to overconfidence and bolder forecasts, and firms base their forecasts on a known reference value. We also show that the bolder the forecasts, the lesser the accuracy, indicating that substantially deviating from the herd does not pay off when it comes to crop production forecasts.

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Publication Details

Journal
Agricultural Economics
Published
2025-04-09
DOI
https://doi.org/10.1111/agec.70032
Citations
1
Primary Topic
Agricultural Economics and Policy
Type
article
Field-Weighted Citation Impact
4.83

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article

Is Being Bold Better? Industry Expectations of USDA Corn and Soybean Production Estimates

Olga Isengildina‐Massa, Scott H. Irwin, Berna Karali
1 citations
Agricultural Economics
Agricultural Economics and Policy
4.83
article

Is Being Bold Better? Industry Expectations of USDA Corn and Soybean Production Estimates

Olga Isengildina‐Massa, Scott H. Irwin, Berna Karali
article en
1 citations

Abstract

ABSTRACT Despite the extensive use of industry expectations in measuring forecast accuracy and price reactions to USDA reports, very little is known about their properties beyond the basic statistical characteristics of bias, rationality, efficiency, and relative accuracy. Using unique proprietary data of firm‐level expectations for upcoming USDA corn and soybean production estimates, we demonstrate that these forecasts exhibit cognitive biases such as attribution and anchoring. Prior success leads to overconfidence and bolder forecasts, and firms base their forecasts on a known reference value. We also show that the bolder the forecasts, the lesser the accuracy, indicating that substantially deviating from the herd does not pay off when it comes to crop production forecasts.

Agricultural EconomicsVol. 56(5)
University of Illinois Urbana-Champaign (US), University of Georgia (US), Virginia Tech (US)
U.S. Department of Agriculture
Openalex Percentile: Top 8%
Agricultural Economics and Policy
4.83
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