A Practical Guide to Inference in Simulation Models
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.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||Mar 2006|
|Date of revision:|
|Contact details of provider:|| Postal: Deutschhausstrasse 10, 35032 Marburg|
Web page: http://www.uni-marburg.de/fb19/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- S.G. Winter & Y.M. Kaniovski & G. Dosi, 1997.
"A Baseline Model of Industry Evolution,"
ir97013, International Institute for Applied Systems Analysis.
- 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.
- Giorgio Fagiolo & Giovanni Dosi, 2002.
"Exploitation, Exploration and Innovation in a Model of Endogenous Growth with Locally interacting Agents,"
LEM Papers Series
2002/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- 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.
- Thomas Brenner & Claudia Werker, 2004.
"Empirical Calibration of Simulation Models,"
Computing in Economics and Finance 2004
89, Society for Computational Economics.
- Claudia Werker & Thomas Brenner, 2004. "Empirical Calibration of Simulation Models," Papers on Economics and Evolution 2004-10, Philipps University Marburg, Department of Geography.
- Werker, C. & Brenner, T., 2004. "Empirical calibration of simulation models," Working Papers 04.13, Eindhoven Center for Innovation Studies.
- Eliasson, Gunnar & Johansson, Dan & Taymaz, Erol, 2004.
"Simulating the New Economy,"
Structural Change and Economic Dynamics,
Elsevier, vol. 15(3), pages 289-314, September.
- 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.
- 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.
- Creedy, John & Duncan, Alan, 2002. " Behavioural Microsimulation with Labour Supply Responses," Journal of Economic Surveys, Wiley Blackwell, vol. 16(1), pages 1-39, February.
When requesting a correction, please mention this item's handle: RePEc:esi:evopap:2006-02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christoph Mengs)
If references are entirely missing, you can add them using this form.