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Estimation of Ergodic Agent-Based Models by Simulated Minimum Distance

Author

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  • Jakob Grazzini

    (Catholic University of Milan, Dept of Economics and Finance)

  • Matteo Richiardi

    (Institute for New Economic Thinking, Nuffield College, Oxford and Collegio Carlo Alberto)

Abstract

Two diculties arise in the estimation of AB models: (i) the criterion function has no simple analytical expression, (ii) the aggregate properties of the model cannot be analytically understood. In this paper we show how to circumvent these diculties and under which conditions ergodic models can be consistently estimated by simulated minimum distance techniques, both in a long-run equilibrium and during an adjustment phase.

Suggested Citation

  • Jakob Grazzini & Matteo Richiardi, 2014. "Estimation of Ergodic Agent-Based Models by Simulated Minimum Distance," Economics Papers 2014-W07, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:1407
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    More about this item

    Keywords

    Agent-based Models; Consistent Estimation; Method of Simulated Moments.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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