Bayesian estimation of agent-based models

Grazzini, Jakob and Richiardi, Matteo and Tsionas, Efthymios (2017) Bayesian estimation of agent-based models. Journal of Economic Dynamics and Control, 77. pp. 26-47. ISSN 0165-1889

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We consider Bayesian inference techniques for Agent-Based (AB) models, as an alternative to simulated minimum distance (SMD). Three computationally heavy steps are involved: (i) simulating the model, (ii) estimating the likelihood and (iii) sampling from the posterior distribution of the parameters. Computational complexity of AB models implies that efficient techniques have to be used with respect to points (ii) and (iii), possibly involving approximations. We first discuss non-parametric (kernel density) estimation of the likelihood, coupled with Markov chain Monte Carlo sampling schemes. We then turn to parametric approximations of the likelihood, which can be derived by observing the distribution of the simulation outcomes around the statistical equilibria, or by assuming a specific form for the distribution of external deviations in the data. Finally, we introduce Approximate Bayesian Computation techniques for likelihood-free estimation. These allow embedding SMD methods in a Bayesian framework, and are particularly suited when robust estimation is needed. These techniques are first tested in a simple price discovery model with one parameter, and then employed to estimate the behavioural macroeconomic model of De Grauwe (2012), with nine unknown parameters.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Economic Dynamics and Control
Additional Information:
This is the author’s version of a work that was accepted for publication in Journal of Economic Dynamics and Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Economic Dynamics and Control, 77, 2017 DOI: 10.1016/j.jedc.2017.01.014
Uncontrolled Keywords:
?? agent-basedestimationbayesapproximate bayesian computationlikelihoodcontrol and optimizationeconomics and econometricsapplied mathematics ??
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Deposited On:
06 Feb 2017 09:52
Last Modified:
20 Feb 2024 00:45