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A Maxent Model For Macroscenario Analysis

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Author Info
SIMONE LANDINI () (IRES Piemonte–Socioeconomic Research Institute of Piedmont, via Nizza 18, 10125, Turin, Italy)
CORRADO DI GUILMI () (Department of Economics, Universitá Politecnica delle Marche, P.le Martelli 8, 60121, Ancona, Italy)
MAURO GALLEGATI () (Department of Economics, Universitá Politecnica delle Marche, P.le Martelli 8, 60121, Ancona, Italy)

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Abstract

In this paper, starting from Jaynes' MaxEnt methodology [10, 11], we follow the original idea of Aoki [1] to implement a canonical MaxEnt inference model for the replication of industrial firms' dynamics over a space of economic states. We develop an aggregate model to infer the distributions of agents at meso level using representative states. In particular, we estimate the access probability for agents in different states consistently with macroscopic economic constraints. The model is calibrated on the basis of a sample of firms, drawn from the AMADEUS database, within the manufacturing industry made up of nine sectors of economic activity from 1995 to 2004, and results come to experimental proof at aggregate macroscopic level.

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Publisher Info
Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal Advances in Complex Systems.

Volume (Year): 11 (2008)
Issue (Month): 05 ()
Pages: 719-744
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Handle: RePEc:wsi:acsxxx:v:11:y:2008:i:05:p:719-744

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Related research
Keywords: Statistical mechanics; canonical ensemble; MaxEnt; Gibbs distribution; econophysics; Cobb–Douglas technology;

Cited by:
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  1. Di Guilmi, Corrado & Gallegati, Mauro & Landini, Simone, 2008. "Modeling Maximum Entropy and Mean-Field Interaction in Macroeconomics," Economics Discussion Papers 2008-36, Kiel Institute for the World Economy. [Downloadable!]
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This page was last updated on 2009-11-13.


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