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Estimation of ergodic agent-based models by simulated minimum distance

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  • Grazzini, Jakob
  • Richiardi, Matteo

Abstract

Two difficulties 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 difficulties 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.

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  • Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    • Handle: RePEc:eee:dyncon:v:51:y:2015:i:c:p:148-165
    DOI: 10.1016/j.jedc.2014.10.006
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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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