Three essays on commodity markets
Keri L. Jacobs
The three essays that constitute this dissertation aim to understand the role of agribusiness organizational structures in competition, the risk management practices of grain producers, and the characteristics of the U.S. corn harvest futures price.
The cooperative (co-op) model is held up as a novel solution to many kinds of market failures. It integrates the business successes and members’ utilities and provides a countervailing force to the market power of investor-owned firms (IOFs). A traditional cooperative business is characterized as being owned and controlled by its member-users, to whom benefits are intended to primarily accrue. The user-benefit principle has given rise to diverse assumptions regarding the objectives of co-ops in the existing literature. And the theoretical literature has yet to reconcile the extent to which operating objectives of a cooperative business deviate from profit maximization. Chapter 2 adds to the literature by developing a model of duopsony competition from which the strategic interactions of a cooperative firm and an investor owned firm (IOF) under output price uncertainty are interpreted. I analyze the way in which the market equilibrium varies as the co-op takes on different objectives.
Crop producers’ risk management practices have long been understood using either survey based data or aggregate trading data. These studies suggest there is limited relevance of Expected Utility (EU) optimal hedging theory as farmers may deviate from rationality. There are two impediments to this line of research. First, hedging theories that rely on alternative utility paradigms may be too complicated to test with data. Second, there is a lack of data on the actual hedging activities of producers. Chapter 3 provides a solution that partially overcomes these two problems. I investigate the role of reference-dependence, a central feature of most utility paradigms other than EU in the optimal hedging theory under the EU framework. The theoretical predictions facilitate a direct comparison of optimal hedge ratios with and without a reference price. I then test the model’s results with a unique database of forward contracting transactions of Iowa corn producers over a five-year period. The corn producers’ hedging pattern indeed appears to be reference-dependent: more hedges are placed when futures prices rise above the recent price trend. This finding has important implications for future research on grain producers’ marketing practices because if the futures markets are efficient, price-based triggers as a motivation for hedging may not be beneficial to farm income.
A well-known phenomenon in the corn futures market, weather premium, suggests that producers may enhance their marketing strategies by forward contracting early in the season. This is because the commodity futures market for grain over-predicts the actual harvest price more often than not. Chapter 4 formally defines the weather premium, and recovers the potential weather premium in the corn futures market. I show theoretically that the size of weather premium depends on the expected supply at harvest, which consists of the carryout from last year and the expected new harvest. These two covariates partially explain the variation of the forecast error of the December futures contract price from 1968 to 2015. However, the existence of weather premium does not imply the biasness in the futures, i.e. risk premium. The Sharpe ratio of the passive strategy of routinely shorting the corn December futures in spring is too small to justify such an approach.