Did the Renewable Fuel Standard Shift Market Expectations of the Price of Ethanol?

Abstract

It is commonly believed that the response of the price of corn ethanol (and hence of the price of corn) to shifts in biofuel policies operates in part through market expectations and shifts in storage demand, yet to date it has proved difficult to measure these expectations and to empirically evaluate this view. We utilize a recently proposed methodology to estimate the market's expectations of the prices of ethanol, unfinished motor gasoline and crude oil at horizons from three months to one year. We quantify the extent to which price changes were anticipated by the market, the extent to which they were unanticipated, and how the risk premium in these markets has evolved. We show that the Renewable Fuel Standard (RFS) is likely to have increased ethanol price expectations by as much $1.45 in the year before and in the year after the implementation of the RFS had started. Our analysis of the term structure of expectations provides support for the view that a shift in ethanol storage demand starting in 2005 caused an increase in the price of ethanol. There is no conclusive evidence that the tightening of the RFS in 2008 shifted market expectations, but our analysis suggests that policy uncertainty about how to deal with the blend wall raised the risk premium in the ethanol futures market in mid-2013 by as much as 50 cents at longer horizons. Finally, we present evidence against a tight link from ethanol price expectations to corn price expectations and hence to storage demand for corn in 2005-06. JEL Code: Q18, Q28, Q42, Q58

Using Market Expectations to Test for Speculative Bubbles in the Crude Oil Market

“…Oil price expectations, besides their use in forward-looking economic models, play a central role in generating economic projections, in understanding the extent to which energy markets anticipate changes in economic policy, and in the determination of the value and size of strategic petroleum reserves (Baumeister and Kilian 2016b, Baumeister, Ellwanger and Kilian 2017, Newell and Prest 2017. Given their importance and wide use, it is no surprise that different expectation measures have been proposed in the literature.…”

Price Stickiness in US-Corn Market: Evidence from Dsge-Var Simulation

“…demand for agricultural commodities (Baumeister, Ellwanger, & Kilian, 2017). This predictability in the supply and demand sides of the U.S corn market is assumed to form some sources of price distortion and volatility across different harvest periods (Johnson & Plott, 1989).…”