Econometrics Foundations
Ron C. Mittelhammer, George G. Judge, Douglas J. Miller
Résumé
This integrated textbook and CD-ROM develop step by step a modern approach to econometric problems. Aimed at upper-level undergraduates, graduate students, and professionals, they describe the principles and procedures for processing and recovering information from samples of economic data. In the real world such data are usually limited or incomplete, and the parameters sought are unobserved and not subject to direct observation or measurement. The text provides a complete working knowledge of a rich set of estimation and inference tools for mastery of such data, including traditional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjunction with the computer to address economic problems. The CD-ROM contains reviews of probability theory and principles of classical estimation and inference in text-searchable electronic documents, a review ofhandling ill-posed inverse problems, an interactive Matrix Review Manual with Gauss software, an electronic Examples Manual, and solutions to the questions and problems in the text. An electronic tutorial is available separately.
L'auteur - Ron C. Mittelhammer
Ron C. Mittelhammer is a professor at Washington State University and author of Mathematical Statistics for Economics and Business {Springer-Verlag, 1996) as well as book chapters and numerous articles in refereed economics, statistics, and econometrics journals. His skill as a teacher of statistics and econometrics has evolved over more than two decades of graduate-level teaching and is documented by teaching evaluations and awards.
L'auteur - George G. Judge
George G. Judge is a professor at the University of California, Berkeley. He is the coauthor or editor of 14 books in econometrics and related fields, and author or coauthor of over 150 articles in refereed journals. A Fellow of the Econometric Society. Professor Judge's research explores specification and evaluation of statistical decision rules, improved inference methods, and parametric and semiparamctric estimation.
L'auteur - Douglas J. Miller
Douglas J. Miller is an Assistant Professor at Purdue University. Over the past five years, his primary teaching assignment has been graduate-level econometrics. He is coauthor of Maximum Entropy Econometrics: Robust Estimation with Limited Data.
Sommaire
- Information Processing and Recovery
- Regression Model - Estimation and inherence
- Extremum Estimators and Nonlinear and Nonnormal Regression Models
- Avoiding the Parametric Likelihood
- Generalized Regression Models
- Simultaneous Equation probability Models and general Moment-based Estimation and Inference
- Model Discovery
- Special Econometric Topics
- Bayesian Estimation and Inference
- Epilogue
- CD Rom
Caractéristiques techniques
PAPIER | |
Éditeur(s) | Cambridge University Press |
Auteur(s) | Ron C. Mittelhammer, George G. Judge, Douglas J. Miller |
Parution | 27/04/2004 |
Nb. de pages | 756 |
Format | 18 x 26 |
Couverture | Relié |
Poids | 1540g |
Intérieur | Noir et Blanc |
EAN13 | 9780521623940 |
ISBN13 | 978-0-521-62394-0 |
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