The Environmental Protection Agency (EPA) used a computer model developed by researchers at Iowa State University (ISU) to evaluate the impact that the implementation of the renewable fuel standard (RFS) would have on the amount of ethanol produced and consumed during the 2012/2013 corn marketing year, and the resulting impacts, if any, on agricultural and other industries.
Our goal in writing this series of columns on the EPA decision on the request for a waiver of the RFS is not to argue for or against the decision. Rather we feel that is important that all sides of the debate understand the process by which the EPA came to its conclusion. As a result much of the information we provide is taken directly from the decision itself. We hope that our columns on this topic will stimulate readers will take the time to read the complete text of the 25 page decision.
“To assess the impact of implementation of the RFS…[the EPA] evaluated two scenarios: one in which no waiver is granted and another in which a waiver of the total renewable fuel mandate is granted” the EPA writes in its “Notice of Decision Regarding Requests for a Waiver on the Renewable Fuel Standard,”
According to the EPA, “the ISU model is a stochastic equilibrium model that projects, among other outputs, the prices of corn, ethanol and blended fuel given uncertainty in six variables: U.S. corn yields; U.S., Brazilian, and Argentinean soybean yields; U.S. wholesale gasoline prices; and Brazilian ethanol production.
“The analysis simulates 500 scenarios, and for each one the model independently picks a value for each exogenous factor (such as U.S. corn yield) by randomly selecting from a probability distribution curve for that factor. Since the probability of the specific value of a given corn yield is built into the distribution curve for corn yields, the greater the probability of a certain corn yield, the more likely it is that the model will pick that value for any scenario. The result is that the distribution of the random draws for each exogenous factor fairly reflects the probability of the various uncertain variables.
“For each of the 500 scenarios, the model projects ethanol production and the prices of corn, ethanol, and blended fuel based on the values picked for the exogenous factors for that run. As mentioned above, [the EPA] ran the model with and without a waiver, modeling 500 different scenarios, to assess the impact of a waiver.”