رکورد قبلیرکورد بعدی

" Information and entropy econometrics : "


Document Type : BL
Record Number : 1005770
Doc. No : b760140
Main Entry : Golan, Amos.
Title & Author : Information and entropy econometrics : : a review and synthesis /\ Amos Golan.
Publication Statement : Hanover, Mass. :: Now Publishers,, ©2008.
Series Statement : Foundations and trends in econometrics,; v. 2, issue 1-2, p. 1-145
Page. NO : 1 online resource (145 pages)
ISBN : 1601981058
: : 9781601981059
: 9781601981042
Bibliographies/Indexes : Includes bibliographical references (pages 133-145).
Contents : Abstract -- 1. Introductory statement, motivation, and objective -- 2. Historical perspective -- 3. Information and entropy, background, definitions, and examples -- 4. The classical maximum entropy principle -- 5. Information-theoretic methods of estimation: I: Basics and zero moments -- 6. Information-theoretic methods of estimation: II: Stochastic moments -- 7. IT, likelihood and inference, synthesis via a discrete choice, matrix balancing example -- 8. Concluding remarks and related work not surveyed -- References -- Updates.
Abstract : The overall objectives of this review and synthesis are to study the basics of information-theoretic methods in econometrics, to examine the connecting theme among these methods, and to provide a more detailed summary and synthesis of the sub-class of methods that treat the observed sample moments as stochastic. Within the above objectives, this review focuses on studying the inter-connection between information theory, estimation, and inference. To achieve these objectives, it provides a detailed survey of information-theoretic concepts and quantities used within econometrics. It also illustrates the use of these concepts and quantities within the subfield of information and entropy econometrics while paying special attention to the interpretation of these quantities. The relationships between information-theoretic estimators and traditional estimators are discussed throughout the survey. This synthesis shows that in many cases information-theoretic concepts can be incorporated within the traditional likelihood approach and provide additional insights into the data processing and the resulting inference.
Subject : Econometrics.
Subject : Entropy (Information theory)
Subject : Information theory in economics.
Subject : BUSINESS ECONOMICS-- Econometrics.
Subject : BUSINESS ECONOMICS-- Statistics.
Subject : Econometrics.
Subject : Entropy (Information theory)
Subject : Information theory in economics.
Dewey Classification : ‭330.015195‬
LC Classification : ‭HB139‬
: ‭HB139‬‭.G655 2008‬
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