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A Practical Guide to Inference in Simulation Models

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Author Info

  • Thomas Brenner
  • Claudia Werker

Abstract

This paper introduces a categorization of simulation models. It provides an explicit overview of the steps that lead to a simulation model. We highlight the advantages and disadvantages of various simulation approaches by examining how they advocate different ways of constructing simulation models. To this end, it discusses a number of relevant methodological issues, such as how realistic simulation models are obtained and which kinds of inference can be used in a simulation approach. Finally, the paper presents a practical guide on how simulation should and can be conducted.

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Bibliographic Info

Paper provided by Philipps University Marburg, Department of Geography in its series Papers on Economics and Evolution with number 2006-02.

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Length: 33 pages
Date of creation: Mar 2006
Date of revision:
Handle: RePEc:esi:evopap:2006-02

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Keywords: Methodology; Simulation Models; Practical Guide;

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References

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  1. 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.
  2. Thomas Brenner & Claudia Werker, 2004. "Empirical Calibration of Simulation Models," Computing in Economics and Finance 2004 89, Society for Computational Economics.
  3. Eliasson, Gunnar & Johansson, Dan & Taymaz, Erol, 2004. "Simulating the New Economy," Ratio Working Papers 52, The Ratio Institute.
  4. Sidney G. Winter & Yuri M. Kaniovski & Giovanni Dosi, 2003. "A Baseline Model of Industry Evolution," LEM Papers Series 2003/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  5. Atkinson, Tony, et al, 2002. "Microsimulation of Social Policy in the European Union: Case Study of a European Minimum Pension," Economica, London School of Economics and Political Science, vol. 69(274), pages 229-43, May.
  6. Malerba, Franco, et al, 1999. "'History-Friendly' Models of Industry Evolution: The Computer Industry," Industrial and Corporate Change, Oxford University Press, vol. 8(1), pages 3-40, March.
  7. Creedy, John & Duncan, Alan, 2002. " Behavioural Microsimulation with Labour Supply Responses," Journal of Economic Surveys, Wiley Blackwell, vol. 16(1), pages 1-39, February.
  8. 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.
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Citations

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Cited by:
  1. Robert Marks, 2007. "Validating Simulation Models: A General Framework and Four Applied Examples," Computational Economics, Society for Computational Economics, vol. 30(3), pages 265-290, October.
  2. Robert E. Marks, 2013. "Validation and Functional Complexity," Discussion Papers 2013-30, School of Economics, The University of New South Wales.
  3. 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.

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