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Maximum Entropy Econometrics
Robust Estimation with Limited Data
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This book offers solutions to the problems commonly encountered by economists trying to squeeze information out of partial or incomplete data--which is usually what they have to work with.
The authors compare the generalized entropy techniques with the performance of the relevant traditional methods of information recovery and clearly demonstrate theories with applications including Pure inverse problems that include first order Markov processes, and input-output, multisectoral or SAM models to Inverse problems with noise that include statistical models subject to ill-conditioning, non-normal errors, heteroskedasticity, autocorrelation, censored, multinomial and simultaneous response data, as well as model selection and non-stationary and dynamic control problems Maximum Entropy Econometrics will be of interest to econometricians trying to devise procedures for recovering information from partial or incomplete data, as well as quantitative economists in finance and business, statisticians, and students and applied researchers in econometrics, engineering and the physical sciences.
|Publisher||John Wiley & Sons Ltd|
|Published in||United Kingdom|
The Classical Maximum Entropy Formalism: A Review.
PURE INVERSE PROBLEMS.
Basic Maximum Entropy Principle: Formulation and Extensions.
Formulation and Solution of Pure Inverse Problems.
Generalized Pure Inverse Problems.
LINEAR INVERSE PROBLEMS WITH NOISE.
Generalized Maximum Entropy (GME) and Cross-Entropy (GCE) Formulations.
Finite Sample Extensions of GME-GCE.
GENERAL LINEAR MODEL APPLICATIONS OF GME-GCE.
GME-GCE Solutions to Ill-conditioned Problems.
General Linear Statistical Model with a Non-scalar Identity Covariance Matrix Statistical Model Selection.
A SYSTEM OF ECONOMIC STATISTICAL RELATIONS.
Sets of Linear Statistical Models.
Simultaneous Equations Statistical Model.
LINEAR AND NON-LINEAR DYNAMIC SYSTEMS.
Estimation and Inference of Dynamic Linear Inverse Problems.
Linear and Non-linear Dynamic Systems with Control.
DISCRETE CHOICE-CENSORED PROBLEMS.
Recovering Information from Multinomial Response Data.
Recovering Information from Censored Response Data.
Computing GME-GCE Solutions.