Reconstructing Aggregate Dynamics in Heterogeneous Agents Models

Publisher:
Observatoire Francais des Conjonctures Economiques
Publication Type:
Journal Article
Citation:
Revue de l'OFCE, 2012, 124 (5), pp. 117 - 146
Issue Date:
2012
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The Representative Agent (RA) assumption is a methodological shortcut to bypass the problem of dimensionality which arises in heterogeneous agents model. The reasons for dissatisfaction with the RA assumption are well known and have been forcefully discussed in Kirman (1992) and Keen (2011). The efforts to overcome the limits of the exact aggregation (Gorman, 1953) led to methods, such as Lewbel (1992), that are still too restrictive in their basic assumptions to realistically depict an economic system. [2][2] For a review on aggregation methods see Gallegati et... 2 As a consequence of the dissatisfaction with the RA approach, a few analytical frameworks have been developed to cope with the dimensionality problem mentioned above. One of the most promising methods has been introduced by Duncan Foley and Masanao Aoki who borrowed from statistical mechanics the concept of mean-field interaction and imported it into economics. [3][3] See Foley (1994); Aoki (1996, 2002); Aoki and Yoshikawa... 3 In the mean-field interaction approach, agents are classified into clusters or sub-systems according to their state with respect to one particular feature (the so-called micro-state, e.g. the level of production for a firm on a scale of production levels). This clustering determines the characteristics and the evolution of the aggregate (the macro-state, e.g. the total level of output). [4][4] An early economic application of mean-field theory... The focus is not on the single agent, but on the number or fraction of agents occupying a certain state of a state-space at a certain time. These numbers or fractions are governed by a stochastic law, that also defines the functional of the probability distributions of aggregate variables and, if they exist, their equilibrium distributions. The stochastic aggregation is then implemented through master equation techniques, that allow for a description of the dynamics of probability flows among states on a space. These probability flows are originated by the changes in the conditions of agents and determine the aggregate outcomes
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