How Crop Forecast Similarity, Government Policies, and Macroeconomic Conditions Affect WASDE Forecast Accuracy

ABSTRACT The U.S. Department of Agriculture's (USDA) World Agricultural Supply and Demand Estimates (WASDE) play a central role in how agricultural commodity markets process information about supply, demand, and prices. This study examines how global and domestic shocks, as well as policy interventions, are reflected in the similarity of WASDE forecasts and forecast errors across eight major U.S. crops. Using Dynamic Time Warping (DTW), we measure the distance between forecast series or forecast error series to quantify the degree of similarity across crops. Using WASDE data from marketing years 1999–2000 to 2022–2023, results show that crop forecast series have more distinct forecast patterns, while their forecast errors are more similar across crops, which may be due to the common market shocks affecting all crops. Using regression models controlling for government payments and economic recessions, we find that greater forecast similarity is associated with larger forecast errors, especially for cotton and rice ending stocks. Government payments are associated with lower forecast errors for trade‐related variables (export and import), but higher errors for crop price, whereas recessions are associated with lower area harvested but higher import forecast errors. Additional results suggest that policy and macroeconomic conditions affect forecast similarity only in selected crop‐variable settings rather than producing a uniform pattern across crops. These findings highlight the importance of balancing common cross‐crop information with crop‐specific market fundamentals to improve the accuracy and interpretation of WASDE forecasts.