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Empirical Validation of Agent-Based Models: Alternatives and Prospects

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Abstract

This paper addresses a set of methodological problems arising in the empirical validation of agent-based (AB) economics models and discusses how these are currently being tackled. These problems are generic for all those engaged in AB modelling, not just economists. The discussion is therefore of direct relevance to JASSS readers. The paper has two objectives. The first objective is the identification of a set of issues that are common to all modellers engaged in empirical validation. This gives rise to a novel taxonomy that captures the relevant dimensions along which AB modellers differ. The second objective is a focused discussion of three alternative methodological approaches being developed in AB economics - indirect calibration, the Werker-Brenner approach, and the history-friendly approach – and a set of (as yet) unresolved issues for empirical validation that require future research.

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  • Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
  • Handle: RePEc:jas:jasssj:2006-40-2
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    1. Giorgio Fagiolo & Luigi Marengo & Marco Valente, 2004. "Endogenous Networks In Random Population Games," Mathematical Population Studies, Taylor & Francis Journals, vol. 11(2), pages 121-147.
    2. John B. Davis & D. W. Hands & Uskali Mäki (ed.), 1998. "The Handbook of Economic Methodology," Books, Edward Elgar Publishing, number 741.
    3. Werker, C. & Brenner, T., 2004. "Empirical calibration of simulation models," Working Papers 04.13, Eindhoven Center for Innovation Studies.
    4. Fagiolo, Giorgio & Dosi, Giovanni, 2003. "Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 237-273, September.
    5. Koesrinartoto, D. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An agent-based computational laboratory for testing the economic reliability of wholesale power market designs," ISU General Staff Papers 200501010800001043, Iowa State University, Department of Economics.
    6. G. Fagiolo & G. Dosi & R. Gabriele, 2004. "Matching, Bargaining, And Wage Setting In An Evolutionary Model Of Labor Market And Output Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 157-186.
    7. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    8. Giovanni Dosi & Richard R. Nelson, 2000. "An Introduction to Evolutionary Theories in Economics," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 11, pages 327-346, Edward Elgar Publishing.
    9. Uskali Maki, 2005. "Models are experiments, experiments are models," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(2), pages 303-315.
    10. P. Windrum, 2007. "Neo-Schumpeterian Simulation Models," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 26, Edward Elgar Publishing.
    11. Tesfatsion, Leigh, 1995. "How Economists Can Get Alife," Economic Reports 18196, Iowa State University, Department of Economics.
    12. Johann Peter Murmann & Thomas Brenner, 2003. "The Use of Simulations in Developing Robust Knowledge about Causal Processes: Methodological Considerations and an Application to Industrial Evolution," Computing in Economics and Finance 2003 66, Society for Computational Economics.
    13. T. Brenner & P. Murmann, 2003. "The Use of Simulations in Developing," Papers on Economics and Evolution 2003-03, Philipps University Marburg, Department of Geography.
    14. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
    15. Liebowitz, S J & Margolis, Stephen E, 1990. "The Fable of the Keys," Journal of Law and Economics, University of Chicago Press, vol. 33(1), pages 1-25, April.
    16. Lane, David A, 1993. "Artificial Worlds and Economics, Part I," Journal of Evolutionary Economics, Springer, vol. 3(2), pages 89-107, May.
    17. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    18. Paul Windrum, 2005. "Heterogeneous preferences and new innovation cycles in mature industries: the amateur camera industry 1955--1974," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 14(6), pages 1043-1074, December.
    19. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    20. Sawyer, K. R. & Beed, Clive & Sankey, H., 1997. "Underdetermination in Economics. The Duhem-Quine Thesis," Economics and Philosophy, Cambridge University Press, vol. 13(1), pages 1-23, April.
    21. Alessio Moneta, 2005. "Causality in macroeconometrics: some considerations about reductionism and realism," Journal of Economic Methodology, Taylor & Francis Journals, vol. 12(3), pages 433-453.
    22. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 29, Edward Elgar Publishing.
    23. Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2006. "An Evolutionary Model of Endogenous Business Cycles," Computational Economics, Springer;Society for Computational Economics, vol. 27(1), pages 3-34, February.
    24. Saviotti, Pier Paolo & Pyka, Andreas, 2004. "Economic development, qualitative change and employment creation," Structural Change and Economic Dynamics, Elsevier, vol. 15(3), pages 265-287, September.
    25. Gerald Silverberg & Giovanni Dosi & Luigi Orsenigo, 2000. "Innovation, Diversity and Diffusion: A Self-Organisation Model," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 14, pages 410-432, Edward Elgar Publishing.
    26. Giovanni Dosi, 2000. "Sources, Procedures, and Microeconomic Effects of Innovation," Chapters, in: Innovation, Organization and Economic Dynamics, chapter 2, pages 63-114, Edward Elgar Publishing.
    27. Brenner, Thomas, 2006. "Agent Learning Representation: Advice on Modelling Economic Learning," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 18, pages 895-947, Elsevier.
    28. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    29. Richard R. Nelson, 1995. "Recent Evolutionary Theorizing about Economic Change," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 48-90, March.
    30. Brock, W A, 1999. "Scaling in Economics: A Reader's Guide," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 8(3), pages 409-446, September.
    31. Dawid, Herbert, 2006. "Agent-based Models of Innovation and Technological Change," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 25, pages 1235-1272, Elsevier.
    32. Luigi Marengo & Marc Willinger, 1997. "Alternative methodologies for modelling evolutionary dynamics: Introduction," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 331-338.
    33. Windrum, Paul, 1999. "Simulation models of technological innovation: A Review," Research Memorandum 005, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    34. Giovanni Dosi & Christopher Freeman & Richard Nelson & Gerarld Silverberg & Luc Soete (ed.), 1988. "Technical Change and Economic Theory," LEM Book Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number dosietal-1988, March.
    35. Lane, David A, 1993. "Artificial Worlds and Economics, Part II," Journal of Evolutionary Economics, Springer, vol. 3(3), pages 177-197, August.
    36. Gatti, Domenico Delli & Guilmi, Corrado Di & Gaffeo, Edoardo & Giulioni, Gianfranco & Gallegati, Mauro & Palestrini, Antonio, 2005. "A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 489-512, April.
    37. Roberto Leombruni, 2002. "The Methodological Status of Agent-Based Simulations," LABORatorio R. Revelli Working Papers Series 19, LABORatorio R. Revelli, Centre for Employment Studies.
    38. Delli Gatti, Domenico & Gallegati, Mauro & Giulioni, Gianfranco & Palestrini, Antonio, 2003. "Financial fragility, patterns of firms' entry and exit and aggregate dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 51(1), pages 79-97, May.
    39. Malerba, Franco, et al, 1999. "'History-Friendly' Models of Industry Evolution: The Computer Industry," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 8(1), pages 3-40, March.
    40. G. Silverberg & B. Verspagen, 1995. "Evolutionary Theorizing on Economic Growth," Working Papers wp95078, International Institute for Applied Systems Analysis.
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