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The Use of Simulations in Developing

Author

Listed:
  • T. Brenner
  • P. Murmann

Abstract

The paper develops a simulation method that can be used to develop knowledge inductively and test hypotheses about causal processes in social systems. Combining existing simulation methods in novel ways, it describes in detail the uses and requirements for carrying out history-friendly simulation experiments. The second part of the paper illustrates the value of the methodology by developing inductively information about the precise causal impact of (1) the initial number of organic chemists at the start of the industry (1857) and (2) the responsiveness of the German university system on the German global market share in the synthetic dye industry in 1913.

Suggested Citation

  • T. Brenner & P. Murmann, 2003. "The Use of Simulations in Developing," Papers on Economics and Evolution 2003-03, Philipps University Marburg, Department of Geography.
    • Handle: RePEc:esi:evopap:2003-03
    Note: The paper will be emailed on request. Please contact evopapers@econ.mpg.de
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. M. Mouchart & R. Orsi & G. Wunsch, 2020. "Causality in Econometric Modeling. From Theory to Structural Causal Modeling," Working Papers wp1143, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Gianluca Capone & Franco Malerba & Richard R. Nelson & Luigi Orsenigo & Sidney G. Winter, 2019. "History friendly models: retrospective and future perspectives," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(1), pages 1-23, March.
    5. Werker, C. & Brenner, T., 2004. "Empirical calibration of simulation models," Working Papers 04.13, Eindhoven Center for Innovation Studies.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.
    11. Chao Bi & Jingjing Zeng & Wanli Zhang & Yonglin Wen, 2020. "Modelling the Coevolution of the Fuel Ethanol Industry, Technology System, and Market System in China: A History-Friendly Model," Energies, MDPI, vol. 13(5), pages 1-26, February.

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