PSI-CARD Corn Yield Prediction Project

Difference from Corn Trend Yield in 2019

Prediction Date:

below more than 20bpa below less than 20bpa above less than 20bpa above more than 20bpa no data
Corn Belt Region Prediction

predicted at

bpa help

Implied National Prediction

bpa help

Data sources: corn yield prediction model and USDA data

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About the Corn Belt 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—Illinois, Indiana, Iowa, Kansas, Michigan, Missouri, Minnesota, Nebraska, Ohio, and South Dakota—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.

Daily Prediction Visualization

The daily yield prediction and maps are based on the November corn yield prediction model from Jiang et al. (2018), which relies on realized weather variables from the corn growing season (April 1 to October 31). Pre-November corn yield prediction relies on non-realized weather variables and uses historical daily average to complete the input data set.

Maps are prepared with the daily corn yield prediction data and historical data queried from USDA Quick Stats.

Difference from 2019 Trend Yield Map

Yield difference in this map is defined as the predicted corn yield minus the corn trend yield in 2019. The corn trend yield is calculated from historical county yields queried from USDA Quick Stats. A logarithm of yields on the year variable are regressed along with a set of county dummies and 2019 trend yields are predicted with estimates from that regression.

Difference from 2018 Harvested Acreage Map

The harvested acreage difference is defined as the imputed county harvested acreage minus the harvested acreage in 2018 queried from USDA Quick Stats. Acreage information is from the annual acreage report. The 2019 acreage report was released June 28, 2019 [link]. The 2019 county harvested acreage is imputed based on the correlation of county planted/harvested acreage and state planted/harvested acreage statistics in 2018.

2019 Production Map

Corn production in 2019 is computed as the predicted corn yield times the imputed harvested acreage.

Corn Belt and National Yield and Production Prediction

Jiang et al. (2018) explicitly models 925 out of 930 counties in the ten Corn Belt states and our daily prediction model produces yield predictions for these counties. Our predictions are weighted by imputed harvested acreage to get the yield for the Corn Belt counties with individually reported acreage numbers in 2018 (USDA Quick Stats). In 2018, more than 600 counties reported acreage numbers—86.6% of the total harvested acreage in the ten Corn Belt states and 68.4% of the national total. The production of these 600+ counties represents 88.6% of the total production in the ten Corn Belt states and 72.5% of the national total production. In 2018, the average yield for these 600+ counties was 187.21 bpa and the national yield was 176.71 bpa.

Once we obtain the Corn Belt yield, we impute the daily national yield as follows: 176.71*(1+(Corn Belt prediction-187.21)/187.21). The implicit assumption is that all the yields are adjusted by the same percentage change as the Corn Belt yields. For the national production, we simply multiply the imputed national yield with an estimate of harvested acreage imputed from the 2019 annual acreage report.

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