A systems model of similarities between cotton & lumber futures: An economic isomorphological comparison

According to Ludwig Von Bertalanffy in one way or another we are forced to deal with complexities. He believed that rather than having a specific special theory there should be universal principles applying to systems in general. General System Theory contains certain properties and as a consequence of those properties, the appearances of structural similarities or isomorphism’s in different fields are observable. This knowledge of isomorphisms can assist in handling complexity and bridging knowledge gaps. The following research is a case study in finding isomorphism within the commodities of corn, cotton and lumber. Corn and cotton commodities have traditionally been associated along with their economic modeling tools. Yet, cotton may be isomorphic with respect to its agricultural processing and economic behavior with other commodities such as lumber. The purpose of this research is to identify and test for structural similarities (isomorphisms) in different commodities and determine if financial tools may have crossover applications. Isomorphisms between lumber and cotton systems are observed and compared using non-parametric statistics. Results suggest that over a six year period, cotton is moving away from acting as a seasonally produced commodity due to international market demand for cotton futures. Traditionally cotton has been a seasonal crop due to the large domestic demand of textile mills, and has now changed with the vast majority of cotton is now being exported. With this change in demand, the change of seasonal basis and geographical diversity, cotton may now share many isomorphism’s with lumber. The isomorphic analysis suggests that the cotton and lumber futures market share isomorphisms (homologically similar economic/mathematical market structured). This suggest that cotton and lumber may be more inline when it comes to export/import market characteristics. The work in this paper has determined that cotton futures prices are affected by physical inventories and USDA usage adjustments. Regression models for the domestic U.S. level need to take into account the world usage and appears in many ways to validate the theory of storage and the efficient market hypothesis. The regression model using just WASDE announcements and interactions actually appears to simplify our initial causal loop analysis.