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Table of contents (6 chapters)
Keywords
About this book
Broadly viewed, information theory analyzes the uncertainty of a given set of data and its probabilistic characteristics. Whereas the economic theory of information emphasizes the value of information to agents in a market, the entropy theory stresses the various aspects of imprecision of data and their interactions with the subjective decision processes. The tools of information theory, such as the maximum entropy principle, mutual information and the minimum discrepancy are useful in several areas of statistical inference, e.g., Bayesian estimation, expected maximum likelihood principle, the fuzzy statistical regression. This volume analyzes the applications of these tools of information theory to the most commonly used models in econometrics.
The outstanding features of Econometrics of Information and Efficiency are:
- A critical survey of the uses of information theory in economics and econometrics;
- An integration of applied information theory and economic efficiency analysis;
- The development of a new economic hypothesis relating information theory to economic growth models;
- New lines of research are emphasized.
Reviews
The Statistician, 44:2, 1995
Authors and Affiliations
Bibliographic Information
Book Title: Econometrics of Information and Efficiency
Authors: Jati K. Sengupta
Series Title: Theory and Decision Library B
DOI: https://doi.org/10.1007/978-94-015-8202-5
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media B.V. 1993
Hardcover ISBN: 978-0-7923-2353-2Published: 31 July 1993
Softcover ISBN: 978-90-481-4288-0Published: 08 December 2010
eBook ISBN: 978-94-015-8202-5Published: 14 March 2013
Edition Number: 1
Number of Pages: X, 258
Topics: Econometrics, Operations Research/Decision Theory, Systems Theory, Control, Optimization