This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Empirical Calibration of Simulation Models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Thomas Brenner
Claudia Werker

Additional information is available for the following registered author(s):

Abstract

Simulations have become a common tool to study the implications of theoretical models. In addition, computational approaches are frequently used in statistics to adapt models to reality. We aim to merge these approaches. To obtain robust results with significant validity from simulations, empirical data have to be extensively used. We first discuss how inference in economic contexts can be made and then describe our proposed method. It makes extensive use of empirical knowledge for the development of a simulation model whose implications are then examined in the light of empirical data in a Bayesian-like approach. This allows all systems that can be described by the simulation model to be classified into subsets of models. This makes it possible to establish different subsets of models that describe certain realities and to study the characteristics of and causal relationships in these subsets

Download Info
To our knowledge, this item is not available for download. To find whether it is available, there are three options:
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.

Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 89.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:sce:scecf4:89

Contact details of provider:
Email:
Web page: http://comp-econ.org/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: Simulations; Empirics; Methodology;

Other versions of this item:

Find related papers by JEL classification:
B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques

References listed on IDEAS
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.:

  1. Franco Malerba & Luigi Orsenigo, 2002. "Innovation and market structure in the dynamics of the pharmaceutical industry and biotechnology: towards a history-friendly model," Industrial and Corporate Change, Oxford University Press, vol. 11(4), pages 667-703, August.
  2. 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.
  3. Schwerin, Joachim & Werker, Claudia, 2003. "Learning innovation policy based on historical experience," Structural Change and Economic Dynamics, Elsevier, vol. 14(4), pages 385-404, December. [Downloadable!] (restricted)
  4. 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.
  5. Kydland, Finn E & Prescott, Edward C, 1996. "The Computational Experiment: An Econometric Tool," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 69-85, Winter. [Downloadable!] (restricted)
    Other versions:
  6. Dominique Foray & Robin Cowan, 2002. "Evolutionary economics and the counterfactual threat: on the nature and role of counterfactual history as an empirical tool in economics," Journal of Evolutionary Economics, Springer, vol. 12(5), pages 539-562. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, 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.)

  1. Roberto Leombruni & Matteo Richiardi & Nicole J. Saam & Michele Sonnessa, 2005. "A Common Protocol for Agent-Based Social Simulation," LABORatorio R. Revelli Working Papers Series 47, LABORatorio R. Revelli, Centre for Employment Studies. [Downloadable!]
    Other versions:
  2. Robin Cowan & Nicolas Jonard, 2007. "Structural holes, innovation and the distribution of ideas," Journal of Economic Interaction and Coordination, Springer, vol. 2(2), pages 93-110, December. [Downloadable!] (restricted)
    Other versions:
  3. 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. [Downloadable!]
  4. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Springer, vol. 30(3), pages 227-244, October. [Downloadable!] (restricted)
  5. Garavaglia, C., 2004. "History friendly simulations for modelling industrial dynamics," ECIS Working Papers 04.19, Eindhoven Centre for Innovation Studies, Eindhoven University of Technology. [Downloadable!]
  6. T. Brenner & C. Werker, 2006. "A Practical Guide to Inference in Simulation Models," Papers on Economics and Evolution 2006-02, Max Planck Institute of Economics, Evolutionary Economics Group.
  7. 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, vol. 30(3), pages 195-226, October. [Downloadable!] (restricted)
Statistics
Access and download statistics

Did you know? You can create your own reading lists on IDEAS.

This page was last updated on 2009-10-31.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.