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Econometrics 2018, 6(4), 46; https://doi.org/10.3390/econometrics6040046

Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems

ARE, Graduate School and Giannini Foundation, 207 Giannini Hall, University of California Berkeley, Berkeley, CA 94720, USA
Received: 8 November 2018 / Revised: 30 November 2018 / Accepted: 30 November 2018 / Published: 4 December 2018
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Abstract

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. View Full-Text
Keywords: adaptive behavior; causal entropy maximization; information theoretic methods; minimum power divergence; statistical equilibrium; Markov dynamics adaptive behavior; causal entropy maximization; information theoretic methods; minimum power divergence; statistical equilibrium; Markov dynamics
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Judge, G. Micro-Macro Connected Stochastic Dynamic Economic Behavior Systems. Econometrics 2018, 6, 46.

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