Li, Jiarui

We compare the accuracy of crop condition models from existing literature in forecasting U.S. corn and soybean yields. The data for the study consists of weekly state and national crop condition ratings from the USDA over 1986 through 2022. A battery of statistical tests is applied to perform out-of-sample forecasts over 2000 through 2022. While there are differences in the accuracy of the models, test results are uniform in suggesting that no model has statistically significant superior forecast accuracy. A key finding is that relatively simple models perform just as well as more complex and computationally demanding models.