Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems

In this paper, we borrow some of the key concepts of nonequilibrium statistical systems, to develop a framework for analyzing a self-organizing-optimizing system of independent interacting agents, with nonlinear dynamics at the macro level that is based on stochastic individual behavior at the micro...

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Main Author: George Judge
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Econometrics
Subjects:
Online Access:https://www.mdpi.com/2225-1146/6/4/46
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author George Judge
author_facet George Judge
author_sort George Judge
collection DOAJ
description In this paper, we borrow some of the key concepts of nonequilibrium statistical systems, to develop a framework for analyzing a self-organizing-optimizing system of independent interacting agents, with nonlinear dynamics at the macro level that is based on stochastic individual behavior at the micro level. We demonstrate the use of entropy-divergence methods and micro income data to evaluate and understand the hidden aspects of stochastic dynamics that drives macroeconomic behavior systems and discuss how to empirically represent and evaluate their nonequilibrium nature. Empirical applications of the information theoretic family of power divergence measures-entropic functions, interpreted in a probability context with Markov dynamics, are presented.
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spelling doaj.art-50f6ed87368e42a1b3478d50254f127b2022-12-22T02:53:33ZengMDPI AGEconometrics2225-11462018-12-01644610.3390/econometrics6040046econometrics6040046Micro-Macro Connected Stochastic Dynamic Economic Behavior SystemsGeorge Judge0ARE, Graduate School and Giannini Foundation, 207 Giannini Hall, University of California Berkeley, Berkeley, CA 94720, USAIn this paper, we borrow some of the key concepts of nonequilibrium statistical systems, to develop a framework for analyzing a self-organizing-optimizing system of independent interacting agents, with nonlinear dynamics at the macro level that is based on stochastic individual behavior at the micro level. We demonstrate the use of entropy-divergence methods and micro income data to evaluate and understand the hidden aspects of stochastic dynamics that drives macroeconomic behavior systems and discuss how to empirically represent and evaluate their nonequilibrium nature. Empirical applications of the information theoretic family of power divergence measures-entropic functions, interpreted in a probability context with Markov dynamics, are presented.https://www.mdpi.com/2225-1146/6/4/46adaptive behaviorcausal entropy maximizationinformation theoretic methodsminimum power divergencestatistical equilibriumMarkov dynamics
spellingShingle George Judge
Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
Econometrics
adaptive behavior
causal entropy maximization
information theoretic methods
minimum power divergence
statistical equilibrium
Markov dynamics
title Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
title_full Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
title_fullStr Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
title_full_unstemmed Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
title_short Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems
title_sort micro macro connected stochastic dynamic economic behavior systems
topic adaptive behavior
causal entropy maximization
information theoretic methods
minimum power divergence
statistical equilibrium
Markov dynamics
url https://www.mdpi.com/2225-1146/6/4/46
work_keys_str_mv AT georgejudge micromacroconnectedstochasticdynamiceconomicbehaviorsystems