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Modelling industrial dynamics with "History-friendly" simulations

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  • Garavaglia, Christian

Abstract

The use of simulation techniques has increased greatly in recent years. In economics the industrial dynamics approach makes use of simulation techniques to understand the complexity of the industrial process of continuous change. Among these models, a new branch of studies known as "History-friendly" models aims at establishing a close link between formal theory, developing stand-alone theoretical simulation models, and empirical evidence. In this paper, we study "History-friendly" analyses and counterfactuals. Some examples of "History-friendly" models are widely examined. Finally, the paper makes a critical contribution to "History-friendly" methodology and defines the role of "History-friendly" models in the debate on the empirical validation of simulations.

Suggested Citation

  • Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.
  • Handle: RePEc:eee:streco:v:21:y:2010:i:4:p:258-275
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    Citations

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    Cited by:

    1. Christian Garavaglia & Franco Malerba & Luigi Orsenigo & Michele Pezzoni, 2012. "Technological regimes and demand structure in the evolution of the pharmaceutical industry," Journal of Evolutionary Economics, Springer, vol. 22(4), pages 677-709, September.
    2. Roberto Fontana & Lorenzo Zirulia, 2015. "“…then came Cisco, and the rest is history”: a ‘history friendly’ model of the Local Area Networking industry," Journal of Evolutionary Economics, Springer, vol. 25(5), pages 875-899, November.
    3. Herrmann, Johannes & Savin, Ivan, 2015. "Evolution of the electricity market in Germany: Identifying policy implications by an agent-based model," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112959, Verein für Socialpolitik / German Economic Association.
    4. Garavaglia Christian & Malerba Franco & Orsenigo Luigi & Pezzoni Michele, 2014. "Innovation and Market Structure in Pharmaceuticals: An Econometric Analysis on Simulated Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(2-3), pages 274-298, April.
    5. Herrmann, J.K. & Savin, I., 2017. "Optimal policy identification: Insights from the German electricity market," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 71-90.
    6. Landini, Fabio & Lee, Keun & Malerba, Franco, 2017. "A history-friendly model of the successive changes in industrial leadership and the catch-up by latecomers," Research Policy, Elsevier, vol. 46(2), pages 431-446.
    7. repec:spr:italej:v:3:y:2017:i:3:d:10.1007_s40797-017-0049-z is not listed on IDEAS
    8. Marcelo De Carvalho Pereira, 2014. "When Competition May Hinder Technologydiffusion: The Case Of Internet Access Services In Brazil," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 152, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

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