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Reconstructing Aggregate Dynamics in Heterogeneous Agents Models

A Markovian Approach
Authors: Domenico Delli Gatti; Corrado Di Guilmi; Mauro Gallegati; Simone Landini;

Reconstructing Aggregate Dynamics in Heterogeneous Agents Models

Abstract

The restrictive assumptions imposed by the traditional methods of aggregation prevented so far a sound analysis of complex system of feedback between microeconomic variables and macroeconomic outcomes. This issue seems to be crucial in macroeconomic modelling, in particular for the analysis of financial fragility, as conceived in the Keynesian and New Keynesian literature. In the present paper a statistical mechanics aggregation method is applied to a financial fragility model. The result is a consistent representation of the economic system that considers the heterogeneity of firms, their interactive behaviour and the feedback effects between micro, meso and macro level. In this approach, the impact of micro financial variables can be analytically assessed. The whole dynamics is described by a system of dynamic equations that well mimics the evolution of a numerically solved agent based model with the same features.

Keywords

financial fragility, Markov Dynamics, heterogeneity, mean-field interaction, master equation

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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3
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110
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