24 August 1998 Predicting U.S. food demand in the 20th century: a new look at system dynamics
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Abstract
The paper describes a new methodology for predicting the behavior of macroeconomic variables. The approach is based on System Dynamics and Fuzzy Inductive Reasoning. A four- layer pseudo-hierarchical model is proposed. The bottom layer makes predications about population dynamics, age distributions among the populace, as well as demographics. The second layer makes predications about the general state of the economy, including such variables as inflation and unemployment. The third layer makes predictions about the demand for certain goods or services, such as milk products, used cars, mobile telephones, or internet services. The fourth and top layer makes predictions about the supply of such goods and services, both in terms of their prices. Each layer can be influenced by control variables the values of which are only determined at higher levels. In this sense, the model is not strictly hierarchical. For example, the demand for goods at level three depends on the prices of these goods, which are only determined at level four. Yet, the prices are themselves influenced by the expected demand. The methodology is exemplified by means of a macroeconomic model that makes predictions about US food demand during the 20th century.
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Mukund Moorthy, Mukund Moorthy, Francois E. Cellier, Francois E. Cellier, Jeffrey T. LaFrance, Jeffrey T. LaFrance, } "Predicting U.S. food demand in the 20th century: a new look at system dynamics", Proc. SPIE 3369, Enabling Technology for Simulation Science II, (24 August 1998); doi: 10.1117/12.319350; https://doi.org/10.1117/12.319350
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