Standardization for Agent-based Modeling in Economics

Li, Xi Hao (2013): Standardization for Agent-based Modeling in Economics.

Abstract

By combining the general characteristics of economic system and economic agents with methodologies of multi-agent system analysis and development in the scope of software engineering and computer science, this work proposes an integrative framework that provides standardization for agent-based modeling in economics. This framework serves as a standard for analyzing from `bottom-up' the economic system that embeds with the properties of complexity in structure, heterogeneity in agents' beliefs, and interactions among agents' behaviors. It serves as a guidance on designing a standardized agent-based model for economic system. This standardized agent-based model works as the system model of economic system that can be used and reused among interdisciplinary research across economists and computer scientists.

• Item Type: MPRA Paper
• Language: English
• Keywords: agent-based modeling, economic system, software engineering, complexity, standard.
• Subjects: B - History of Economic Thought, Methodology, and Heterodox Approaches > B4 - Economic Methodology; C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling

References

Battiston, S., Delli Gatti, D., Gallegati, M., Greenwald, B. & Stiglitz, J. E. (2012a). Liaisons dangereuses: Increasing connectivity, risk sharing, and systemic risk. Journal of Economic Dynamics and Control 36(8), 1121–1141.

Battiston, S., Gatti, D. D., Gallegati, M., Greenwald, B. & Stiglitz, J. E. (2012b). Default cascades: When does risk diversification increase stability? Journal of Financial Stability 8(3), 138–149.

Blaha, M. & Rumbaugh, J. (2004). Object-Oriented Modeling and Design with UML. Prentice Hall, second edition ed.

Caccioli, F., Catanach, T. & Farmer, J. (2012). Heterogeneity, correlations and financial contagion. Advances in Complex Systems 15(2).

Camerer, C. F., Loewenstein, G. . & Rabin, M. (eds.) (2003). Advances in Behavioral Economics. Princeton University Press.

Delli Gatti, D., Gallegati, M., Greenwald, B. C., Russo, A. & Stiglitz, J. E. (2012). Mobility constraints, productivity trends, and extended crises. Journal of Economic Behavior & Organization 83(3), 375–393.

d’Inverno, M., Luck, M., Georgeff, M., Kinny, D. & Wooldridge, M. (2004). The dmars architechure: A specification of the distributed multi-agent reasoning system. Journal of Autonomous Agents and Multi-Agent Systems , 5–53.

Gallegati, M., Palestrini, A. & Rosser, J. B. (2011). The period of financial distress in speculative markets: Interacting heterogeneous agents and financial constraints. Macroeconomic Dynamics 15(01), 60–79.

Jackson, M. O. (2008). Social and Economic Networks. Princeton, NJ, USA: Princeton University Press.

Jennings, N. R. (2000). On agent-based software engineering. Artificial intelligence 117(2), 277–296.

Kahneman, D. & Tversky, A. (eds.) (2000). Choices, Values, and Frames. Cambridge University Press.

Landini, S., Gallegati, M., Stiglitz, J. E., Li, X. & Di Guilmi, C. (2013). Learning social atoms: Effects on macro dynamics. forthcoming .

Pindyck, R. & Rubinfeld, D. (2001). Microeconomics. Prentice Hall, 5th edition ed.

Potts, J. (2000). The new evolutionary microeconomics. New horizons in institutional and evolutionary economics. Elgar. Rao, A. S. & Georgeff, M. P. (1995). Formal models and decision procedures for multi-agent systems. Technical Note 61, Australian AI Institute.

Russell, S. J. & Norvig, P. (2003). Artificial ntelligence, a Modern Approach. Prentice Hall series in artificial intelligence. Prentice Hall, 2. ed.

Stiglitz, J. E. (2011). Rethinking macroeconomics: What failed, and how to repair it. Journal of the European Economic Association 9(4), 591–645.

Stiglitz, J. E. & Gallegati, M. (2011). Heterogeneous interacting agent models for understanding monetary economies. Eastern Economic Journal 37(1), 6–12.

Tesfatsion, L. S. (2006). Agent-based computational economics: A contructive approach to economic theory. In: Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics (Tesfatsion, L. S. & Judd, K. L., eds.). North-Holland.

Tesfatsion, L. S. & Judd, K. L. (2006). Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics. Handbooks in Economics Series. North-Holland.

Trichet, J.-C. (2010). Reflections on the nature of monetary policy non-standard measures and finance theory. Opening address at the ecb central banking conference, frankfurt, 18 november 2010, European Central Bank.

Wooldridge, M. (1997). Agent-based software engineering. IEE Proceedings-software 144(1), 26–37.

Wooldridge, M., Jennings, N. R. & Kinny, D. (2000). The gaia methodology for agent-oriented analysis and design. Journal of Autonomous Agents and Multi-Agent Systems 3(3), 285–312.

Zambonelli, F., Jennings, N. R. & Wooldridge, M. (2003). Developing multiagent systems: The gaia methodology. ACM Transactions on Software Engineering Methodology 12(3), 317–370.