Abstract
While by all standards the macroeconomic system is qualified to be a complex adaptive system, mainstream macroeconomics is not capable of demonstrating this feature. Recent applications of agent-based modeling to macroeconomics define a new research direction, which demonstrates how the macroeconomic system can be modeled and studied as a complex adaptive system. This paper shall review the development of agent-based computational modeling in macroeconomics.
Chapter PDF
References
Arifovic J. (1994) Genetic algorithms learning and the cobweb model. Journal of Economic Dynamics and Control 18(1), 3–28.
Arifovic J. (1995) Genetic algorithms and inflationary economies. Journal of Monetary Economics 36(1), 219–243.
Arifovic J. (1996) The behavior of the exchange rate in the genetic algorithm and experimental economies. Journal of Political Economy 104(3), 510–541.
Arifovic J. (2001) Evolutionary dynamics of currency substitution. Journal of Economic Dynamics and Control 25, 395–417.
Arifovic J. (2002) Exchange Rate Volatility in the Artificial Foreign Exchange Market. In: Chen S.-H. (Ed.), Evolutionary Computation in Economics and Finance, Physica-Verlag. 125–136.
Arifovic J., Gencay R. (2000) Statistical properties of genetic learning in a model of exchange rate. Journal of Economic Dynamics and Control 24, 981–1005.
Arthur B. (1992) On learning and adaptation in the economy. SFI Economics Research Program, 92-07-038.
Arthur W. B., Holland J., LeBaron B., Palmer R., Tayler P. (1997) Asset pricing under endogenous expectations in an artificial stock market. In: Arthur W. B., Durlauf S., Lane D. (Eds.), The Economy as an Evolving Complex System II. Addison-Wesley, Reading, MA, 15–44.
Azariadis C, Guesnerie R. (1986) Sunspots and cycle. Review of Economic Studies LIII, 725–737.
Bell R., Beare S. (2002) Emulating trade in emissions permits: An application of genetic algorithms. In: Chen S.-H. (Ed.), Evolutionary Computation in Economics and Finance, Heidelberg: Physica-Verlag, 161–175.
Birchenhall, C. R., Lin J.-S. Lin (2002) Learning and Convergence to Pareto Optimality. In: Chen S.-H. (Ed.), Genetic Algorithms and Geentic Programming in Computational Finance, Kluwer, 419–440.
Bullard J. (1992) Samuelson’s model of money with n-period of lifetimes. Federal Reserve Bank of St. Louis Review, May/June, 67–82.
Bullard J., Duffy J. (1998) A model of learning and emulation with artificial adaptive agents. Journal of Economic Dynamics and Control 22, 179–207.
Bullard J., Duffy J. (1998) Learning and the stability of cycles. Macroeconomic Dynamics 2(1), 22–48.
Bullard J., Duffy J. (1999) Using genetic algorithms to model the evolution of heterogeneous beliefs. Computational Economics 13(1), 41–60
Chan, N. T., LeBaron B., Lo, A. W. and Poggio T. (1999). Agent-based models of financial markets: A comparison with experimental markets. Unpublished Working Paper, MIT Artificial Markets Project, MIT, MA.
Chen S.-H. (1997) On the artificial life of the general economic system (I): the role of selection pressure. In: Hara F., Yoshida K. (Eds.), Proceedings of International Symposium on System Life, 233–240.
Chen S.-H. (2001) On the relevance of genetic programming to evolutionary economics. In: Aruka Y. (Ed.), Evolutionary Controversies in Economics: A New Transdisciplinary Approach. Springer-Verlag, Tokyo, 135–150.
Chen S.-H. (2002) Fundamental issues in the use of genetic programming in agentbased computational economics. In: Namatame A., Terano T., Kurumatani K. (Eds), Agent-based Approaches in Economic and Social Complex Systems, IOS Press, 208–220.
Chen S.-H., Hwang Y.-C. (2002) Simulating the evolution of portfolio behavior in a multiple-asset agent-based artificial stock market. AI-ECON Research Center Working Paper, National Chengchi University.
Chen S.-H., Kuo T.-W. (1999) Towards an agent-based foundation of financial econometrics: an approach based on genetic-programming artificial markets. In: Banzhaf W., Daida J., Eiben A. E., Garzon M. H., Honavar V., Jakiela M., Smith R. E. (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference, Vol. 2. Morgan Kaufmann, 966–973.
Chen S.-H, Liao C.-C. (2002a) Price discovery in agent-based computational modeling of artificial stock markets. In Chen S.-H. (Ed), Genetic Algorithms and Genetic Programming in Computational Finance, Kluwer. 333–354
Chen S.-H., Liao C.-C. (2002b) Testing for Granger causality in the stock-price volume relation: A perspective from the agent-based model of stock markets. Information Sciences, forthcoming.
Chen S.-H., Liao C.-C. (2002c) Understanding sunspots: An analysis based on agent-based artificial stock markets. AI-ECON Research Center Working Paper, National Chengchi University.
Chen S.-H., Yeh C.-H. (1996) Genetic programming learning and the cobweb model. In: Angeline P. (Ed.), Advances in Genetic Programming, Vol. 2, Chap. 22. MIT Press, Cambridge, MA, 443–466.
Chen S.-H., Yeh C.-H. (1997) Modeling speculators with genetic programming. In: Angeline P., Reynolds R. G., McDonnell J. R., Eberhart R. (Eds.), Evolutionary Programming VI, Lecture Notes in Computer Science, Vol. 1213. Springer-Verlag, Berlin, 137–147.
Chen S.-H., Yeh C.-H. (1999) Modeling the expectations of inflation in the OLG model with genetic programming. Soft Computing 3(2), 53–62.
Chen S.-H., Yeh C.-H. (2000a) Simulating economic transition processes by genetic programming. Annals of Operation Research 97, 265–286.
Chen S.-H., Yeh C.-H. (2000b) On the Role of Intensive Search in Stock Markets: Simulations Based on Agent-Based Computational Modeling of Artificial Stock Markets. In: Proceedings of the Second Asia-Pacific Conference on Genetic Algorithms and Applications. Global Link Publishing Company, Hong Kong, 397–402.
Chen S.-H., Yeh C.-H. (2000c) On the Consequence of “Following the Herd”: Evidence from the Artificial Stock Market. In: Arabnia H. R. (Ed.) Proceedings of the International Conference on Artificial Intelligence, Vol. II, CSREA Press, 388–394.
Chen S.-H., Yeh C.-H. (2001) Evolving traders and the business school with genetic programming: a new architecture of the agent-based artificial stock market. Journal of Economic Dynamics and Control 25, 363–393.
Chen S.-H., Yeh C.-H. (2002) On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis. Forthcoming in Journal of Economic Behavior and Organization.
Chen S.-H., Yeh C.-H., Liao C.-C. (2002) On AIE-ASM: Software to simulate artificial stock markets with genetic programming, in Chen S.-H. (Ed.), Evolutionary Computation in Economics and Finance, Heidelberg: Physica-Verlag. 107–122.
Dawid H. (1996) Learning of cycles and sunspot equilibria by genetic algorithms. Journal of Evolutionary Economics 6(4), 361–373.
Dawid H., Kopel M. (1998) On economic applications of the genetic algorithm: a model of the cobweb type. Journal of Evolutionary Economics 8(3), 297–315.
Duffy J. (2001) Learning to speculate: Experiments with artificial and real agents. Journal of Economic Dynamics and Control 25, 295–319.
Franke R. (1998) Coevolution and stable adjustments in the cobweb model. Journal of Evolutionary Economics 8(4), 383–406.
Grandmont J.-M. (1985) On endogeneous competitive business cycles. Econometrica 53, 995–1045.
Grossman S. (1976) On the efficiency of competitive stock markets where traders have diverse information. Journal of Finance 31, 573–585.
Grossman S. Stiglitz J. (1980) On the impossibility of informationally efficient markets. American Economic Review 70, 393–408.
Kareken J., Wallace N. (1981) On the indeterminacy of equilibrium exchange rate. Quarterly Journal of Economics 96, 207–222.
Krugman P. (1996) The Self-Organizing Economy, Blackwell.
LeBaron, B. (1999). Building financial markets with artificial agents: Desired goals and present techniques.” In: G. Karakoulas (ed.), Computational Markets, MIT Press.
LeBaron, B. (2001) Evolution and time horizons in an agent based stock market. Macroeconomic Dynamics 5, 225–254.
LeBaron B., Arthur W. B., Palmer R. (1999) Time series properties of an artificial stock market. Journal of Economic Dynamics and Control 23, 1487–1516.
Leijonhufvud A. (1993) Towards a not-too-rational macroeconomics. Southern Economic Journal 60(1), 1–13.
Lucas R. (1986) Adaptive behaviour and economic theory. In: Hogarth R. Reder M. (eds) Rational choice: the contrast between economics and psychology. University of Chicago Press, 217–242.
Mandlebrot B. (1963) The variation of certain speculative prices. Journal of Business 36, 394–419.
Muth J. F. (1961) Rational expectations and the theory of price movements. Econometrics 29, 315–335.
Palmer, R. G., Arthur W. B., Holland J. H., LeBaron B., and Tayler P.(1994). Artificial economic life: a simple model of a stock market. Physica D, 75, 264–274.
Smith V. L., Suchanek G. L., Williams A. W. (1988) Bubbles, crashes, and endogenous expectations in experimental spot asset markets. Econometrica 56(6), 1119–1152.
Tay, N., Linn S. (2001) Fuzzy inductive reasoning, expectation formation and the behavior of security prices. Journal of Economic Dynamics and Control 25, 321–361.
Tayler P. (1995) Modelling artificial stock markets using genetic algorithms. In Goonatilake S., Treleaven P. (Eds.), Intelligent Systems for Finance and Business. Wiley, New York, NY, 271–287.
Tirole, J. (1982) On the possibility of speculation under rational expectations. Econometrica, 50, 1163–1182.
Vriend, N. (2001) On two types of GA-Learning. In: Chen S.-H. (Ed), Evolutionary Computation in Economics and Finance, Heidelberg: Physica-Verlag, 233–243.
Yang J. (2001) The efficiency of an artificial double auction stock market with neural learning agents. In: Chen S.-H. (Ed), Evolutionary Computation in Economics and Finance, Physica Verlag. 87–107.
Yeh C.-H., Chen S.-H. (2001a) Toward an integration of social learning and individual learning in agent-based computational stock markets: The approach based on population genetic programming. Journal of Management and Economics 5.
Yeh C.-H., Chen S.-H. (2001b) Market diversity and market efficiency: The approach based on genetic programming. Journal of Artificial Simulation of Adaptive behavior, Vol. 1, No. 1. 147–167.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Japan
About this paper
Cite this paper
Chen, SH. (2003). Agent-Based Computational Macro-economics: A Survey. In: Terano, T., Deguchi, H., Takadama, K. (eds) Meeting the Challenge of Social Problems via Agent-Based Simulation. Springer, Tokyo. https://doi.org/10.1007/978-4-431-67863-2_10
Download citation
DOI: https://doi.org/10.1007/978-4-431-67863-2_10
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-67982-0
Online ISBN: 978-4-431-67863-2
eBook Packages: Springer Book Archive