Maximum Entropy Econometrics: Robust Estimation with Limited Data: 16 (Financial Economics and Quantitative Analysis Series) - Hardcover

Golan, Amos; Judge, George G.; Miller, Douglas

Hardcover

ISBN 10: 0471953113 ISBN 13: 9780471953111

Publisher: Wiley, 1996

Synopsis

In the theory and practice of econometrics the model, the method and the data are all interdependent links in information recovery-estimation and inference. Seldom, however, are the economic and statistical models correctly specified, the data complete or capable of being replicated, the estimation rules optimal and the inferences free of distortion. Faced with these problems, Maximum Entropy Economeirics provides a new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined and the data are partial or incomplete. By extending the maximum entropy formalisms used in the physical sciences, the authors present a new set of generalized entropy techniques designed to recover information about economic systems. 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.

About this title

About the Author

Amos Golan is a professor of economics and directs the Info-Metrics Institute at American University. He is also an External Professor at the Santa Fe Institute and a Senior Associate at Pembroke College, Oxford. His research is primarily in the interdisciplinary field of info-metrics - the science and practice of information processing, modeling, inference, and problem solving with insufficient information. He has published in economics, econometrics, statistics, mathematics, physics and philosophy journals. His books include Maximum Entropy Econometrics: Robust Estimation with Limited Data (coauthored with Judge and Miller) and Information and Entropy Econometrics - A Review and Synthesis.

Synopsis

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. While the book contains technical and theoretical material, it also presents many applied examples which will make it accessible for those not interested in the theoretical underpinning.

Edition details

• Publisher: Wiley
• Publication date: 1996
• ISBN 10: 0471953113
• ISBN 13: 9780471953111
• Binding: Hardcover
• Language: English
• Edition number: 1
• Number of pages: 329