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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Format: | Article |
Language: | English |
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MDPI AG
2018-12-01
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Series: | Econometrics |
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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. |
first_indexed | 2024-04-13T08:48:45Z |
format | Article |
id | doaj.art-50f6ed87368e42a1b3478d50254f127b |
institution | Directory Open Access Journal |
issn | 2225-1146 |
language | English |
last_indexed | 2024-04-13T08:48:45Z |
publishDate | 2018-12-01 |
publisher | MDPI AG |
record_format | Article |
series | Econometrics |
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 |