#### Event Title

Forecasting the Price of Corn Received by Farmers Using a Vector Autoregressive Model

#### Faculty Sponsor

Jeffrey A. Summers

#### Location

Jereld R. Nicholson Library

#### Date

5-17-2013 3:00 PM

#### End Date

5-17-2013 4:30 PM

#### Subject Area

Economics (applied)

#### Description

We forecast the price for domestic grain corn using a vector autoregressive model and a time-series dataset with quarterly observations spanning the period 1986 to 2011. Endogenous variables in our model include the amount of corn used, price of corn, price of ethanol and share of corn to ethanol production, price of corn syrup, price of feed, and the price of soybeans. Exogenous variables in our model include amount of precipitation in the Corn Belt agricultural region and the implementation of government agricultural policies. Our vector autoregressive model is constructed by taking the reduced form of the six simultaneous equations generated by the endogenous variables, and specified with a lag length of four quarters. A relatively close relationship between this model’s generated baseline mean and actual historical trends suggests it has the ability to produce realistic projections. This model’s forecast is that the price of corn will rise to $12.98 per bushel by the fourth quarter of 2013.

#### Recommended Citation

Cedergreen, Jay R., "Forecasting the Price of Corn Received by Farmers Using a Vector Autoregressive Model" (2013). *Science and Social Sciences.* Event. Submission 5.

https://digitalcommons.linfield.edu/studsymp_sci/2013/all/5

Forecasting the Price of Corn Received by Farmers Using a Vector Autoregressive Model

Jereld R. Nicholson Library

We forecast the price for domestic grain corn using a vector autoregressive model and a time-series dataset with quarterly observations spanning the period 1986 to 2011. Endogenous variables in our model include the amount of corn used, price of corn, price of ethanol and share of corn to ethanol production, price of corn syrup, price of feed, and the price of soybeans. Exogenous variables in our model include amount of precipitation in the Corn Belt agricultural region and the implementation of government agricultural policies. Our vector autoregressive model is constructed by taking the reduced form of the six simultaneous equations generated by the endogenous variables, and specified with a lag length of four quarters. A relatively close relationship between this model’s generated baseline mean and actual historical trends suggests it has the ability to produce realistic projections. This model’s forecast is that the price of corn will rise to $12.98 per bushel by the fourth quarter of 2013.