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Applying Maximum Entropy to Econometric Problems Vol: 12

Product Details
25 Jul 1997
Emerald Group Publishing Limited
374 pages - 156 x 234 x 22mm
Advances in Econometrics


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.
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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