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A Maxent Model For Macroscenario Analysis

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  • 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)

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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Bibliographic 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;

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Cited by:
  1. Carl Chiarella & Corrado Di Guilmi, 2011. "Limit Distribution of Evolving Strategies in Financial Markets," Research Paper Series 294, Quantitative Finance Research Centre, University of Technology, Sydney.
  2. 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.

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