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A micro-meso-macro perspective on the methodology of evolutionary economics: integrating history, simulation and econometrics



Applied economics has long been dominated by multiple regression techniques. In this regard, econometrics has tended to have a narrower focus than, for example, psychometrics in psychology. Over the last two decades, the simulation and calibration approach to modeling has become more popular as an alternative to traditional econometric strategies. However, in contrast to the well-developed methodologies that now exist in econometrics, simulation/calibration remains exploratory and provisional, both as an explanatory and as a predictive modelling technique although clear progress has recently been made in this regard (see Brenner and Werker (2006)). In this paper, we suggest an approach that can usefully integrate both of these modelling strategies into a coherent evolutionary economic methodology.

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  • Prof John Foster, 2007. "A micro-meso-macro perspective on the methodology of evolutionary economics: integrating history, simulation and econometrics," Discussion Papers Series 343, School of Economics, University of Queensland, Australia.
  • Handle: RePEc:qld:uq2004:343

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    References listed on IDEAS

    1. Finn E. Kydland & Edward C. Prescott, 1996. "The Computational Experiment: An Econometric Tool," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 69-85, Winter.
    2. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    3. Kurt Dopfer & John Foster & Jason Potts, 2004. "Micro-meso-macro," Journal of Evolutionary Economics, Springer, vol. 14(3), pages 263-279, July.
    4. John Foster, 2000. "Competitive selection, self-organisation and Joseph A. Schumpeter," Journal of Evolutionary Economics, Springer, vol. 10(3), pages 311-328.
    5. Peter E. Earl & Jason Potts, 2004. "The market for preferences," Cambridge Journal of Economics, Oxford University Press, vol. 28(4), pages 619-633, July.
    6. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
    7. Foster, John & Wild, Phillip, 1999. "Econometric Modelling in the Presence of Evolutionary Change," Cambridge Journal of Economics, Oxford University Press, vol. 23(6), pages 749-770, November.
    8. Hoover, Kevin D, 1995. "Facts and Artifacts: Calibration and the Empirical Assessment of Real-Business-Cycle Models," Oxford Economic Papers, Oxford University Press, vol. 47(1), pages 24-44, January.
    9. Foster, John, 1993. "Economics and the Self-Organisation Approach: Alfred Marshall Revisited," Economic Journal, Royal Economic Society, vol. 103(419), pages 975-991, July.
    10. John Foster & Phillip Wild, 1999. "Detecting self-organisational change in economic processes exhibiting logistic growth," Journal of Evolutionary Economics, Springer, vol. 9(1), pages 109-133.
    11. Thomas Brenner & Claudia Werker, 2006. "A Practical Guide to Inference in Simulation Models," Papers on Economics and Evolution 2006-02, Philipps University Marburg, Department of Geography.
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    Cited by:

    1. Ancelmo José Vega Armenta, 2010. "El marco conceptual del sistema nacional de innovación y las economías menos desarrolladas," REVISTA CIFE, UNIVERSIDAD SANTO TOMÁS, December.
    2. Domenico Gatti & Edoardo Gaffeo & Mauro Gallegati, 2010. "Complex agent-based macroeconomics: a manifesto for a new paradigm," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(2), pages 111-135, December.
    3. João Ferreira Brito & Pedro Cosme Costa Vieira, 2013. "Economic Growth as the Result of Firms’ Aggregate Performance: Evidence from the OECD Countries," Economics and Management Research Projects: An International Journal, Open Access International Journals, vol. 3(1), pages 24-31, December.

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