Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
A long‐standing puzzle in commodity markets is the low explanatory power of supply and demand fundamentals for explaining the variability of prices in these markets. We apply an instrumental variable correction for measurement errors to investigate how noise in the surprise component of USDA Crop Production reports affects estimated price responses in corn, soybeans, and wheat futures markets from 1970 to 2016. Our findings demonstrate that after correcting for measurement error in market surprises, the explanatory power of our models increases about threefold and often exceeds 70%. This is compelling evidence that fundamental supply news play an important role in explaining grain futures price movements.