Applying Maximum Entropy to Econometric Problems

 

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Applying Maximum Entropy to Econometric Problems


Thomas Fomby (Editor)
R.Carter Hill (Editor)

 

Hardback

ISBN: 9780762301874

 

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The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty. In 1957 Jaynes made use of Shannon's entropy concept as a basis for estimation and inference in problems that are ill-suited for traditional statistical procedures. This volume contains papers developing econometric methods based on the entropy principle.


The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty in the context of information theory. In 1957 Jaynes made use of Shannon's entropy concept as a basis for estimation and inference in problems that are ill-suited for traditional statistical procedures. This volume consists of two sections. The first section contains papers developing econometric methods based on the entropy principle. An interesting array of applications is presented in the second section of the volume.


 

ISBN 762301872
ISBN13 9780762301874
Publisher Elsevier
Format Hardback
Publication date 25/07/1997
Pages 380
Weight (grammes) 710
Published in Netherlands
Height (mm) 234
Width (mm) 156

Introduction (T.B. Fomby, R. Carter Hill). Section I. Methodology. The maximum entrophy approach to estimation and inference: an overview (A. Golan, G. Judge and D. Miller). Information theoretic regression methods (E. Soofi). The Bayesian method of moments (BMOM): theory and applications (A. Zellner). Information theoretic methods for categorical data (E. Soofi, D.V. Gokhale). Model selection by maximum entrophy (P.H.F.M. van Casteren, J.G. De Gooijer). Maximum-entrophy acceptable-likelihood estimation of population heterogeneity (P.S. Faynzilberg). A Monte Carlo study of a generalized maximum entrophy estimator of the binary choice model (L. Atkins). Constructing a unimodal Bayesian prior distribution from incompletely assessed information (P.L. Brockett, L.L. Golden and K.H. Paick). Recovering wastewater treatment objectives: an application of entrophy estimation for inverse control problems (L. Fernandez). Dart boards and asset prices: introducing the entrophy pricing theory (L. Gulko). Maximum entrophy and derivative securities (R.J. Hawkins). Forecasting the production benefits and incidence of a public program: an integrated survey and estimation procedure applied to the California irrigation management information system (D. Osgood et al.). Another perspective on recent changes in the U.S. income distribution: an index space representation (H. Ryu,
D. Slottje). Omnibus tests for multivariate normality based on a class of maximum entrophy distributions (C. Urzua).

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