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LEARNING IN COBWEB EXPERIMENTS

Published online by Cambridge University Press:  09 November 2007

CARS HOMMES ,
JOEP SONNEMANS ,
JAN TUINSTRA  and
HENK VAN DE VELDEN
CARS HOMMES
Affiliation:
University of Amsterdam
JOEP SONNEMANS
Affiliation:
University of Amsterdam
JAN TUINSTRA
Affiliation:
University of Amsterdam
HENK VAN DE VELDEN
Affiliation:
University of Amsterdam
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Abstract

Different theories of expectation formation and learning usually yield different outcomes for realized market prices in dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental environment. Subjects are asked to predict the next period's aggregate price in a dynamic commodity market model with feedback from individual expectations. Subjects have no information about underlying market equilibrium equations, but can learn by observing past price realizations and predictions. We conduct a stable, an unstable, and a strongly unstable treatment. In the stable treatment, rational expectations (RE) yield a good description of observed aggregate price fluctuations: prices remain close to the RE steady state. In the unstable treatments, prices exhibit large fluctuations around the RE steady state. Although the sample mean of realized prices is close to the RE steady state, the amplitude of the price fluctuations as measured by the variance is significantly larger than the amplitude under RE, implying persistent excess volatility. However, agents' forecasts are boundedly rational in the sense that fluctuations in aggregate prices are unpredictable and exhibit no forecastable structure that could easily be exploited.

Keywords

ExpectationsLearningCobweb DynamicsExcess Volatility

Information

Type
ARTICLES
Information
Macroeconomic Dynamics , Volume 11 , Supplement S1: Interacting Agents and Market Behavior , November 2007 , pp. 8 - 33
Copyright
© 2007 Cambridge University Press

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