A Method for Agent-Based Models Validation

29 Pages Posted: 30 Apr 2016

See all articles by Mattia Guerini

Mattia Guerini

Scuola Superiore Sant'Anna di Pisa; OFCE - SciencesPo

Alessio Moneta

Institute of Economics, Sant'Anna School of Advanced Studies

Date Written: April 28, 2016


This paper proposes a new method to empirically validate simulation models that generate artificial time series data comparable with real-world data. The approach is based on comparing structures of vector autoregression models that are estimated from both artificial and real-world data by means of causal search algorithms. This relatively simple procedure is able to tackle both the problem of confronting theoretical simulation models with the data and the problem of comparing different models in terms of their empirical reliability. The paper also provides an application of the validation procedure to the Dosi et al. (2015) macro-model.

Keywords: Agent-Based models; Causality; Structural Vector Autoregressions

JEL Classification: C32, C52, E37

Suggested Citation

Guerini, Mattia and Moneta, Alessio, A Method for Agent-Based Models Validation (April 28, 2016). Institute for New Economic Thinking Working Paper Series No. 42, Available at SSRN: https://ssrn.com/abstract=2772133 or http://dx.doi.org/10.2139/ssrn.2772133

Mattia Guerini (Contact Author)

Scuola Superiore Sant'Anna di Pisa ( email )

Piazza Martiri della Liberta, n. 33
Pisa, 56127

OFCE - SciencesPo ( email )

69 Quai d'Orsay
Paris 75004

Alessio Moneta

Institute of Economics, Sant'Anna School of Advanced Studies ( email )

Piazza Martiri della Liberta', 33-I-56127
Pisa, PI
56127 (Fax)

HOME PAGE: http://https://mail.sssup.it/~amoneta/

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