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Validating and Calibrating Agent-based Models: a Case Study

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Author Info
Pasquale Cirillo () (Institute of Quantitative Methods Bocconi University Milan)
Carlo Bianchi (Università di Pisa)
Mauro Gallegati (Università Politecnica Marche)
Pietro Vagliasindi (Università di Parma)

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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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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2006 with number 277.

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Date of creation: 04 Jul 2006
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Handle: RePEc:sce:scecfa:277

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Related research
Keywords: ace models; validation; indirect inference; goodness of fit; shape parameters; fat tails;

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions
D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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  1. Bruce C. Greenwald & Joseph E. Stiglitz, 1990. "Macroeconomic Models with Equity and Credit Rationing," NBER Chapters, in: Asymmetric Information, Corporate Finance, and Investment, pages 15-42 National Bureau of Economic Research, Inc. [Downloadable!]
    Other versions:
  2. Winmker, P. & Gilli, M., 2001. "Indirect Estimation of the Parameters of Agent Based Models of Financial Markets," Papers 38, Manitoba - Department of Economics.
    Other versions:
  3. Giulio Bottazzi & Angelo Secchi, 2005. "Explaining the Distribution of Firms Growth Rates," LEM Papers Series 2005/16, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
    Other versions:
  4. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March. [Downloadable!] (restricted)
  5. Corrado Di Guilmi & Edoardo Gaffeo & Mauro Gallegati, 2003. "Power Law Scaling in the World Income Distribution," Economics Bulletin, Economics Bulletin, vol. 15(6), pages 1-7. [Downloadable!]
  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. [Downloadable!] (restricted)
  7. Domenico Delli Gatti & Corrado Di Guilmi & Edoardo Gaffeo & Gianfranco Giulioni & Mauro Gallegati & Antonio Palestrini, 2004. "Business Cycle Fluctuations And Firms' Size Distribution Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 223-240. [Downloadable!] (restricted)
  8. Bruce C. Greenwald & Joseph E. Stiglitz, 1993. "Financial Market Imperfections and Business Cycles," NBER Working Papers 2494, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  9. 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. [Downloadable!]
  10. Kleijnen, J.P.C., 1997. "Experimental design for sensitivity analysis, optimization, and validation of simulation models," Discussion Paper 52, Tilburg University, Center for Economic Research. [Downloadable!]
  11. Klevmarken, N. Anders, 1998. "Statistical Inference in Micro Simulation Models: Incorporating external information," Working Paper Series 1998:20, Uppsala University, Department of Economics. [Downloadable!]
    Other versions:
  12. Mauro Gallegati & Gianfranco Giulioni & Nozomi Kichiji, 2003. "Complex Dynamics And Financial Fragility In An Agent-Based Model," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(03), pages 267-282. [Downloadable!] (restricted)
    Other versions:
  13. Gatti, Domenico Delli & Guilmi, Corrado Di & Gaffeo, Edoardo & Giulioni, Gianfranco & Gallegati, Mauro & Palestrini, Antonio, 2005. "A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 489-512, April. [Downloadable!] (restricted)
  14. Domenico Delli Gatti, Mauro Gallegati, Gianfranco Giulioni, Antonio Palestrini, -DISCUSSANT: Thomas Brenner, 2000. "Financial Fragility, Patterns Of Firms' Entry And Exit And Aggregate Dynamics," Computing in Economics and Finance 2000 282, Society for Computational Economics. [Downloadable!]
    Other versions:
  15. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
  16. R. Quandt, 1966. "Old and new methods of estimation and the pareto distribution," Metrika, Springer, vol. 10(1), pages 55-82, December. [Downloadable!] (restricted)
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