Commerce, Complexity, and Evolution Book contents
- Frontmatter
- Contents
- Series editor's preface
- Volume editors' preface
- Editors
- List of contributors
- I Philosophical and methodological implications of complexity and evolution in economic systems
- II Finance and the macroeconomy
- III Market and sectoral dynamics
- 10 Evolutionary patterns of multisectoral growth dynamics
- 11 The detection of evolutionary change in nonlinear economic processes: a new statistical methodology
- 12 Ergodic chaos in a piecewise linear cobweb model
- 13 The cobweb model and a modified genetic algorithm
- 14 The convergence of genetic learning algorithms, with particular reference to recent cobweb models
- IV Marketing and interdependent behavior
13 - The cobweb model and a modified genetic algorithm
Published online by Cambridge University Press: 05 December 2011
- Frontmatter
- Contents
- Series editor's preface
- Volume editors' preface
- Editors
- List of contributors
- I Philosophical and methodological implications of complexity and evolution in economic systems
- II Finance and the macroeconomy
- III Market and sectoral dynamics
- 10 Evolutionary patterns of multisectoral growth dynamics
- 11 The detection of evolutionary change in nonlinear economic processes: a new statistical methodology
- 12 Ergodic chaos in a piecewise linear cobweb model
- 13 The cobweb model and a modified genetic algorithm
- 14 The convergence of genetic learning algorithms, with particular reference to recent cobweb models
- IV Marketing and interdependent behavior
Summary
An important characteristic of markets for certain goods is the significant time lag between the time at which the economic agents (producers) make their decisions to supply the good and the time of the market at which the good is actually sold. Agricultural markets typically have this feature. The simplest models describing the behavior of these markets are the cobweb models of price and quantity adjustment in a single market. A huge literature on these has developed. Chiarella (1990) has given a comprehensive review of these from their inception with Leontief (1934; see Leontief 1966 for a more accessible text) up to 1990.
The range of behavior with different versions of the cobweb model is appreciable and under suitable assumptions even chaotic behavior is possible (see, for example, Jenson and Urban 1984 and Chiarella 1988). However, data from real markets do not support the conclusions about market instability (see, for example, Meadows 1970). Furthermore, these conclusions are also not supported by the data from experimental markets (Carlson 1967, Holt and Williamil 1986). Struck by the stability he had observed in the experimental market, Carlson (1968) showed that for normally sloped demand-and-supply curves, if economic agents base their price forecasts on an arithmetic average of all previous prices, the cobweb model is always stable.
The evidence of experimental markets provided an inspiration for a study of a cobweb model by Arifovic (1994), who used a genetic algorithm (GA). Her paper broke fresh ground in several ways and is discussed in a number of places in the book of Dawid (1996) on the modeling of adaptive learning by GAs.
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- Commerce, Complexity, and EvolutionTopics in Economics, Finance, Marketing, and Management: Proceedings of the Twelfth International Symposium in Economic Theory and Econometrics, pp. 267 - 276Publisher: Cambridge University PressPrint publication year: 2000