PSI-CARD Corn Yield Prediction Project

Corn yield prediction provides valuable information about production and prices prior to harvest. Publicly available high-quality corn yield prediction can help address emergent information asymmetry problems and, in doing so, improve price efficiency in futures markets.

Jiang et al. (2018) developed a Long Short-Term Memory (LSTM) model to predict corn yields in ten corn belt states that achieved promising results with the sample data. Overall, the model prediction is only 0.83 bushel per acre (bpa) lower than actual corn yields, a smaller difference than the corresponding prediction from USDA. About 80% of the LSTM county-level corn yield predictions fall within ±20 bpa of actual yields. The model uses ten variables that affect corn yields, which were constructed from data sets provided by the USDA, USDA-NRCS, USDA-NASS, NOAA, and IBM weather underground.