Estimation of ergodic agent-based models by simulated minimum distance
Authored by Jakob Grazzini, Matteo Richiardi
Date Published: 2015
DOI: 10.1016/j.jedc.2014.10.006
Sponsors:
European Union
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Mathematical description
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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. (C) 2014 Elsevier B.V. All rights reserved.
Tags
Heterogeneity
Aggregation
growth
income
Macroeconomics
General equilibrium-models
Stock