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Open AccessArticle

Entropy Maximization as a Basis for Information Recovery in Dynamic Economic Behavioral Systems

Graduate School, 207 Giannini Hall, University of California Berkeley, Berkeley, CA 94720, USA
Academic Editor: Kerry Patterson
Econometrics 2015, 3(1), 91-100; https://doi.org/10.3390/econometrics3010091
Received: 16 December 2014 / Accepted: 5 February 2015 / Published: 16 February 2015
As a basis for information recovery in open dynamic microeconomic systems, we emphasize the connection between adaptive intelligent behavior, causal entropy maximization and self-organized equilibrium seeking behavior. This entropy-based causal adaptive behavior framework permits the use of information-theoretic methods as a solution basis for the resulting pure and stochastic inverse economic-econometric problems. We cast the information recovery problem in the form of a binary network and suggest information-theoretic methods to recover estimates of the unknown binary behavioral parameters without explicitly sampling the configuration-arrangement of the sample space. View Full-Text
Keywords: information-theoretic methods; adaptive behavior; causal entropy maximization; pure and stochastic inverse problems; binary network; dynamic economic systems information-theoretic methods; adaptive behavior; causal entropy maximization; pure and stochastic inverse problems; binary network; dynamic economic systems
MDPI and ACS Style

Judge, G. Entropy Maximization as a Basis for Information Recovery in Dynamic Economic Behavioral Systems. Econometrics 2015, 3, 91-100.

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