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A Taxonomy of Inference in Simulation Models

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  • Thomas Brenner
  • Claudia Werker

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  • Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 227-244, October.
    • Handle: RePEc:kap:compec:v:30:y:2007:i:3:p:227-244
    DOI: 10.1007/s10614-007-9102-6
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    5. 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.
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    8. J. Richard Harrison, 2004. "Models of growth in organizational ecology: a simulation assessment," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(1), pages 243-261, February.
    9. Claudia Werker & Thomas Brenner, 2004. "Empirical Calibration of Simulation Models," Papers on Economics and Evolution 2004-10, Philipps University Marburg, Department of Geography.
    10. Windrum, Paul & Birchenhall, Chris, 1998. "Is product life cycle theory a special case? Dominant designs and the emergence of market niches through coevolutionary-learning," Structural Change and Economic Dynamics, Elsevier, vol. 9(1), pages 109-134, March.
    11. John Creedy & Alan Duncan, 2002. "Behavioural Microsimulation with Labour Supply Responses," Journal of Economic Surveys, Wiley Blackwell, vol. 16(1), pages 1-39, February.
    12. 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.
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    14. Scott Moss & Bruce Edmonds, 2005. "Towards Good Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-13.
    15. Sylvia Kaufmann, 2000. "Measuring business cycles with a dynamic Markov switching factor model: an assessment using Bayesian simulation methods," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 39-65.
    16. T. Brenner & P. Murmann, 2003. "The Use of Simulations in Developing," Papers on Economics and Evolution 2003-03, Philipps University Marburg, Department of Geography.
    17. Sidney Winter & Yuri Kaniovski & Giovanni Dosi, 2003. "A baseline model of industry evolution," Journal of Evolutionary Economics, Springer, vol. 13(4), pages 355-383, October.
    18. Merz, Joachim, 1991. "Microsimulation -- A survey of principles, developments and applications," International Journal of Forecasting, Elsevier, vol. 7(1), pages 77-104, May.
    19. Pavitt, Keith, 1984. "Sectoral patterns of technical change: Towards a taxonomy and a theory," Research Policy, Elsevier, vol. 13(6), pages 343-373, December.
    20. Andrew Brown & Gary Slater & David A. Spencer, 2002. "Driven to abstraction? Critical realism and the search for the 'inner connection' of social phenomena," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 26(6), pages 773-788, November.
    21. Paul Downward & John H. Finch & John Ramsay, 2002. "Critical realism, empirical methods and inference: a critical discussion," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 26(4), pages 481-500, July.
    22. Eliasson, Gunnar & Johansson, Dan & Taymaz, Erol, 2004. "Simulating the New Economy," Structural Change and Economic Dynamics, Elsevier, vol. 15(3), pages 289-314, September.
    23. Franco Malerba & Luigi Orsenigo, 2002. "Innovation and market structure in the dynamics of the pharmaceutical industry and biotechnology: towards a history-friendly model," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(4), pages 667-703, August.
    24. Tsionas, Efthymios G., 2000. "Bayesian model comparison by Markov chain simulation: Illustration using stock market data," Research in Economics, Elsevier, vol. 54(4), pages 403-416, December.
    25. Chang-Wook Kim & Keun Lee, 2003. "Innovation, technological regimes and organizational selection in industry evolution: a 'history friendly model' of the DRAM industry," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 12(6), pages 1195-1221, December.
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    Cited by:

    1. Carreira, Carlos & Teixeira, Paulino, 2011. "Entry and exit as a source of aggregate productivity growth in two alternative technological regimes," Structural Change and Economic Dynamics, Elsevier, vol. 22(2), pages 135-150, June.
    2. Thomas Brenner & Matthias Duschl, 2014. "Modelling Firm and Market Dynamics - A Flexible Model Reproducing Existing Stylized Facts," Working Papers on Innovation and Space 2014-07, Philipps University Marburg, Department of Geography.
    3. Іllyusha S., 2015. "Modeling Ukraine's technological approaching to the developed countries," Economy and Forecasting, Valeriy Heyets, issue 3, pages 104-122.
    4. Brenner Thomas, 2008. "Cluster dynamics and policy implications," ZFW – Advances in Economic Geography, De Gruyter, vol. 52(1), pages 146-162, October.
    5. Anna Klabunde & Frans Willekens, 2016. "Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges," European Journal of Population, Springer;European Association for Population Studies, vol. 32(1), pages 73-97, February.
    6. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    7. Andreas Pyka & Claudia Werker, 2009. "The Methodology of Simulation Models: Chances and Risks," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-1.
    8. Vermeulen, Ben & Pyka, Andreas, 2016. "Agent-based modeling for decision making in economics under uncertainty," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-33.
    9. Leonardo Bargigli & Luca Riccetti & Alberto Russo & Mauro Gallegati, 2020. "Network calibration and metamodeling of a financial accelerator agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 413-440, April.
    10. Giorgio Fagiolo & Mattia Guerini & Francesco Lamperti & Alessio Moneta & Andrea Roventini, 2017. "Validation of Agent-Based Models in Economics and Finance," LEM Papers Series 2017/23, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    11. Giovanni Dosi & Giorgio Fagiolo & Andrea Roventini, 2009. "The microfoundations of business cycles: an evolutionary, multi-agent model," Springer Books, in: Uwe Cantner & Jean-Luc Gaffard & Lionel Nesta (ed.), Schumpeterian Perspectives on Innovation, Competition and Growth, pages 161-180, Springer.
    12. Müller, Matthias & Kudic, Muhamed & Vermeulen, Ben, 2021. "The influence of the structure of technological knowledge on inter-firm R&D collaboration and knowledge discovery: An agent-based simulation approach," Journal of Business Research, Elsevier, vol. 129(C), pages 570-579.
    13. Stuart Rossiter & Jason Noble & Keith R.W. Bell, 2010. "Social Simulations: Improving Interdisciplinary Understanding of Scientific Positioning and Validity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-10.
    14. Thomas Brenner & Claudia Werker, 2009. "Policy Advice Derived from Simulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-2.
    15. Gräbner, Claudius, 2016. "From realism to instrumentalism - and back? Methodological implications of changes in the epistemology of economics," MPRA Paper 71933, University Library of Munich, Germany.
    16. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(2), pages 277-293, October.
    17. Simon Deichsel & Andreas Pyka, 2009. "A Pragmatic Reading of Friedman's Methodological Essay and What It Tells Us for the Discussion of ABMs," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-6.
    18. Troost, Christian & Huber, Robert & Bell, Andrew R. & van Delden, Hedwig & Filatova, Tatiana & Le, Quang Bao & Lippe, Melvin & Niamir, Leila & Polhill, J. Gareth & Sun, Zhanli & Berger, Thomas, 2023. "How to keep it adequate: A protocol for ensuring validity in agent-based simulation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 159, pages 1-21.
    19. Thomas Brenner & Matthias Duschl, 2018. "Modeling Firm and Market Dynamics: A Flexible Model Reproducing Existing Stylized Facts on Firm Growth," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 745-772, October.
    20. Thomas Brenner & Johann Peter Murmann, 2016. "Using simulation experiments to test historical explanations: the development of the German dye industry 1857-1913," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 907-932, October.
    21. 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;Society for Computational Economics, vol. 30(3), pages 195-226, October.
    22. Bargigli, Leonardo & Gallegati, Mauro & Riccetti, Luca & Russo, Alberto, 2014. "Network analysis and calibration of the “leveraged network-based financial accelerator”," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 109-125.

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    More about this item

    Keywords

    Methodology; Simulation models; Theory; Empirical data; B41; B52; C63;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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