Autori:
Richiardi, Matteo,
Grazzini, JakobTitolo:
Consistent Estimation of Agent-Based Models by Simulated Minimum DistancePeriodico:
Università degli studi di Torino. Dip. Di Economia e Statistica Cognetti de Martiis. Working paper seriesAnno:
2013 - Volume:
7 - Fascicolo:
35 - Pagina iniziale:
1 - Pagina finale:
38Agent-based (AB) models are considered a promising tool for macroeconomic analysis. However, until estimation of AB models become a common practice, they will not get to the center stage of macroeconomics. Two diculties arise in the estimation of AB models: (i) the criterion function has
no simple analytical expression, and (ii) the aggregate properties of the model cannot be analytically understood. The rst one calls for simulation-based estimation techniques; the second requires additional statistical testing in order to ensure that the simulated quantities are consistent estimators of the theoretical quantities. The possibly high number of parameters involved and the non-linearities in the
theoretical quantities used for estimation add to the complexity of the problem. As these diculties are also shared, though to a dierent extent, by DSGE models, we rst look at the lessons that can be learned from this literature. We identify simulated minimum distance (SMD) as a practical approach
to estimation of AB models, and we discuss the conditions which ensure consistency of SMD estimators in AB models
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