A Common Protocol for Agent-Based Social Simulation
Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.
|Date of creation:||2005|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.laboratoriorevelli.it/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-41, June.
- Kleijnen, J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments," Discussion Paper 1995-4, Tilburg University, Center for Economic Research.
- Attanasio, Orazio P & Weber, Guglielmo, 1993. "Consumption Growth, the Interest Rate and Aggregation," Review of Economic Studies, Wiley Blackwell, vol. 60(3), pages 631-49, July.
- Weisbuch, G. & Kirman, A.P. & Herreiner, D., 1996.
96a20, Universite Aix-Marseille III.
- Joachim Merz, 1994.
"Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy,"
09, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)), LEUPHANA University Lüneburg.
- Merz, Joachim, 1994. "Microsimulation - A Survey of Methods and Applications for Analyzing Economic and Social Policy," MPRA Paper 7232, University Library of Munich, Germany.
- Leigh Tesfatsion, 2000. "Agent-Based Computational Economics: A Brief Guide to the Literature," Computational Economics 0004001, EconWPA.
- Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-93, May.
- Thomas Brenner & Claudia Werker, 2004.
"Empirical Calibration of Simulation Models,"
Computing in Economics and Finance 2004
89, Society for Computational Economics.
- Claudia Werker & Thomas Brenner, 2004. "Empirical Calibration of Simulation Models," Papers on Economics and Evolution 2004-10, Philipps University Marburg, Department of Geography.
- Werker, C. & Brenner, T., 2004. "Empirical calibration of simulation models," Working Papers 04.13, Eindhoven Center for Innovation Studies.
- Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-37, February.
- Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, EconWPA, revised 15 Aug 2002.
- Jorgen W. Weibull, 1997. "Evolutionary Game Theory," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262731215, June.
- Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
- Nelson Minar & Rogert Burkhart & Chris Langton & Manor Askenazi, 1996. "The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations," Working Papers 96-06-042, Santa Fe Institute.
When requesting a correction, please mention this item's handle: RePEc:cca:wplabo:47. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Giovanni Bert)
If references are entirely missing, you can add them using this form.