using FSA Data to Improve the Prices Received for Grain Program
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The United States Department of Agriculture’s National Agricultural Statistics Service (NASS)
conducts a prices received for grain survey each month. This survey is used to assess monthly
prices received by farms for a given commodity at grain elevators. Prediction modeling was
performed that compared NASS mid-month prices to Farm Service Agency (FSA) prices in
order to determine which did the best job of forecasting the NASS whole-month price,
potentially reducing respondent burden if the NASS mid-month price was not surveyed. This
was performed on nine commodities, comparing three models on each.
The prediction modeling and validation testing resulted in models for several commodities that
accurately predict the mid-month price over time with low model variance and little or no bias.
However, it was determined that the FSA prices did a relatively poor job at predicting the NASS
whole-month price and should not be used.