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Validating and Calibrating Agent-Based Models: A Case Study

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  • Carlo Bianchi
  • Pasquale Cirillo

    ()

  • Mauro Gallegati
  • Pietro Vagliasindi

Abstract

In this paper we deal with the validation of an agent-based model and, in particular, with the technical validation process, that is to say all the set of test and methods used to analyze if the results of a simulation agree with reality. Today, thanks to some important studies, validation techniques are more and more complete and reliable: many distributional and goodness-of-fit tests have been developed, while several graphical tools have been studied to give the researcher a quick comprehension of actual and simulated data. In particular, the aim of this paper is to propose a good way to calibrate and validate a simple agent-based model of industrial dynamics we have developed. To achieve our goal we consider actual micro-level data of a sample of Italian manufacturing firms included in the Centrale dei Bilanci's database for the period 1983-2001, with no missing data and reliable values. The sample has been selected on the basis of appropriate requisites we discuss further in this paper. The validation results (both graphical and analytical) are quite promising. As calibration process, we use the method of indirect inference due to Gourieroux and Monfort(1996) to guarantee more accurate parameters, minimizing the differences between simulated and actual data. Even in this case the results we get are promising

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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 30 (2007)
Issue (Month): 3 (October)
Pages: 245-264

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Handle: RePEc:kap:compec:v:30:y:2007:i:3:p:245-264

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Web page: http://www.springerlink.com/link.asp?id=100248
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Keywords: Validation; Calibration; Agent-based models; Indirect inference; Size distribution; Tail analysis; EVT;

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Cited by:
  1. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
  2. Edoardo Gaffeo & Domenico Delli Gatti & Saul Desiderio & Mauro Gallegati, 2008. "Adaptive Microfoundations for Emergent Macroeconomics," Eastern Economic Journal, Palgrave Macmillan, vol. 34(4), pages 441-463.
  3. Grazzini, Jakob & Richiardi, Matteo, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201335, University of Turin.
  4. Kotaro Ohori & Shingo Takahashi, 2012. "Market design for standardization problems with agent-based social simulation," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 49-77, January.
  5. Pasquale Cirillo & Mauro Gallegati, 2012. "The Empirical Validation of an Agent-based Model," Eastern Economic Journal, Palgrave Macmillan, vol. 38(4), pages 525-547.
  6. Bianchi, Carlo & Cirillo, Pasquale & Gallegati, Mauro & Vagliasindi, Pietro A., 2008. "Validation in agent-based models: An investigation on the CATS model," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 947-964, September.
  7. Grazzini Jakob, 2011. "Estimating Micromotives from Macrobehavior," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201111, University of Turin.
  8. Jakob Grazzini, 2011. "Consistent Estimation of Agent Based Models," LABORatorio R. Revelli Working Papers Series 110, LABORatorio R. Revelli, Centre for Employment Studies.
  9. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer, vol. 8(2), pages 277-293, October.
  10. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
  11. Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.

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