Statistics and Econometric Models
Subtitle: Volume 1: General Concepts, Estimation, Prediction and Algorithms
Series: Statistics and Econometric Models; Themes in Modern Econometrics
Publisher: Cambridge University Press
Published: 1995
Place of publication: Cambridge
Language: eng
Format: Paperback
ISBN-13: 9780521477444
Copyright date: 1995
Description: This is the first volume in a major two-volume set of advanced texts in econometrics. It is essentially a text in statistics which is adapted to deal with economic phenomena. Christian Gourieroux and Alain Monfort have written a text which synthesises a great deal of material scattered across a variety of books and journals. They present both the basic and the more sophisticated statistical models which are crucial to an understanding of econometric models, and have taken care to employ mathematical tools with which a majority of students with a basic course in econometrics will be familiar. One of the most attractive features of the books is the liberal use throughout of real-world economic examples. They are also distinctive for their emphasis on promoting an intuitive understanding of the models and results at the expense of overly technical discussions.

Major new econometrics text by two of the world's foremost econometricians
Provides comprehensive synthesis within a single framework of all the important models and approaches
Will be indispensable to all advanced students, teachers, and researchers in econometrics
source: https://www.cambridge.org/nl/academic/subjects/economics/econometrics-statistics-and-mathematical-economics/statistics-and-econometric-models-volume-1?format=PB
Table of contents: title: Preface; title: 1. Models; title: 2. Statistical problems and decision theory; title: 3. Statistical information: classical approach; title: 4. Bayesian interpretations of sufficiency, ancillarity and identification; title: 5. Elements of estimation theory; title: 6. Unbiased estimation; title: 7. Maximum likelihood estimation; title: 8. M-estimation; title: 9. Methods of moments and their generalizations; title: 10. Estimation under equality constraints; title: 11. Prediction; title: 12. Bayesian estimation; title: 13. Numerical procedures.