Search results

Contributors to cobweb theory include many leading economists of the twentieth century. From early beginnings in 1930, cobweb theory played a key role in evolving perceptions of market stability arising from recursive linear models with endogenous dynamics. The focal point of this evolution in cobweb theory is the transition from naive to adaptive to rational price expectations. After a review of the prehistory, this paper examines the first wave of linear cobweb theory initiated by Jan Tinbergen, Henry Schultz, and Umberto Ricci and proceeds to consider the evolution of price expectations in the second wave of cobweb models associated with endogenous cycles in commodity markets. The role of modern cobweb theory in discussions about the stability of market equilibrium and the connection to processes with rational expectations is assessed.

AbstractGlobal industrial metal markets have experienced a drastic price decline over the past years. In this paper we link the dynamics of raw material markets and commodity price fluctuations to a delayed adjustment of supply. Drawing on the classical cobweb theorem we show how the implementation of this theorem using system dynamics may yield a valuable explanation, not only for the recent price decline, but also for possible future price movements. Starting from a simple cobweb model of general industrial markets, we couple the price‐adjusting mechanics to the global copper market and demonstrate how a simple market model can be merged with a physical material flow model. This model captures both market dynamics and technical aspects of raw material processing, recycling and substitution and adds an explanation for the widely accepted fact that the cost structure of the copper industry cannot explain current price levels. Finally, we compare the system dynamics forecasting model with a traditional econometric forecasting method and found the system dynamics model to be more intuitive and better suited to capture and convey the structural market fundamentals. Copyright © 2017 System Dynamics Society