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A Common Protocol for Agent-Based Social Simulation

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Author Info
Roberto Leombruni
Matteo Richiardi
Nicole J. Saam
Michele Sonnessa

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Abstract

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.

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Publisher Info
Paper provided by LABORatorio R. Revelli, Centre for Employment Studies in its series LABORatorio R. Revelli Working Papers Series with number 47.

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Length: 26 pages
Date of creation: 2005
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Handle: RePEc:cca:wplabo:47

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Related research
Keywords: Agent-based; simulations; methodology; calibration; validation.;

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References listed on IDEAS
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.:
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  5. Thomas Brenner & Claudia Werker, 2004. "Empirical Calibration of Simulation Models," Computing in Economics and Finance 2004 89, Society for Computational Economics.
    Other versions:
  6. Weisbuch, Gerard & Alan Kirman & Dorothea K. Herreiner, 1996. "Market Organization," Discussion Paper Serie B 391, University of Bonn, Germany. [Downloadable!]
    Other versions:
  7. Leigh Tesfatsion, 2000. "Agent-Based Computational Economics: A Brief Guide to the Literature," Computational Economics 0004001, EconWPA. [Downloadable!]
  8. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August. [Downloadable!] (restricted)
  9. 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. [Downloadable!] (restricted)
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(explanations, 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.)

  1. Zamac, Jovan & Hallberg, Daniel & Lindh, Thomas, 2008. "Low fertility and long run growth in an economy with a large public sector," CAFO Working Papers 2009:5, Centre for Labour Market Policy Research (CAFO), School of Management and Economics, Växjö University. [Downloadable!]
    Other versions:
  2. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
  3. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer, vol. 30(3), pages 189-194, October. [Downloadable!] (restricted)
  4. Giorgio Fagiolo & Alessio Moneta & Paul Windrum, 2007. "A Critical Guide to Empirical Validation of Agent-Based Models in Economics: Methodologies, Procedures, and Open Problems," Computational Economics, Springer, vol. 30(3), pages 195-226, October. [Downloadable!] (restricted)
  5. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Springer, vol. 30(3), pages 265-290, October. [Downloadable!] (restricted)
  6. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer, vol. 30(3), pages 227-244, October. [Downloadable!] (restricted)
  7. Ian McCarthy, 2008. "Simulating Sequential Search Models with Genetic Algorithms: Analysis of Price Ceilings, Taxes, Advertising and Welfare," Caepr Working Papers 2008-010, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington. [Downloadable!]
  8. Roberto Leombruni & Matteo Richiardi, 2006. "Introduction," Computational Economics, Springer, vol. 27(1), pages 1-1, February. [Downloadable!] (restricted)
  9. Rodolphe Buda, 2008. "Two Dimensional Aggregation Procedure: An Alternative to the Matrix Algebraic Algorithm," Computational Economics, Springer, vol. 31(4), pages 397-408, May. [Downloadable!] (restricted)
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