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Advances in Info-MetricsInformation and Information Processing across Disciplines$
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Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah

Print publication date: 2020

Print ISBN-13: 9780190636685

Published to Oxford Scholarship Online: December 2020

DOI: 10.1093/oso/9780190636685.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 16 June 2021

Information Recovery Related to Adaptive Economic Behavior and Choice

Information Recovery Related to Adaptive Economic Behavior and Choice

Chapter:
(p.145) 5 Information Recovery Related to Adaptive Economic Behavior and Choice
Source:
Advances in Info-Metrics
Author(s):

George Judge

Publisher:
Oxford University Press
DOI:10.1093/oso/9780190636685.003.0005

In this chapter, we emphasize the connection between adaptive economic behavior and causal entropy maximization and suggest methods consistent with information recovery in an open dynamic economic system. This entropy-based causal adaptive behavior framework permits the use of a family of information-theoretic estimation and inference methods as a basis for linking the data and the unknown and unobservable system behavioral parameters. Several econometric models and applications are demonstrated, and economic-econometric implications of the information-theoretic approach are discussed. We end the chapter with a question concerning the use of traditional estimation and inference methods that do not have a connection to economic behavior and choice data.

Keywords:   information-theoretic methods, adaptive behavior, causal entropy maximization, Markov processes, binary network, nonlinear time series, dynamic economic systems

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