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Statistics and Econometric Models

Statistics and Econometric Models

Statistics and Econometric Models

Volume 1: General Concepts, Estimation, Prediction and Algorithms
Christian Gourieroux, CREST-INSEE, Paris
Alain Monfort, CREST-INSEE, Paris
Quang Vuong
October 1995
1. General Concepts, Estimation, Prediction and Algorithms
Paperback
9780521477444

    This two-volume work aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. It is a well-integrated textbook presenting a wide diversity of models in a coherent and unified framework. The reader will find a description not only of the classical concepts and results of mathematical statistics, but also of concepts and methods recently developed for the specific needs of econometrics. Although the two volumes do not demand a high level of mathematical knowledge, they do draw on linear algebra and probability theory. The breadth of approaches and the extensive coverage of this two-volume work provide for a thorough and entirely self-contained course in modern economics.
    Volume 1 provides an introduction to general concepts and methods in statistics and econometrics, and goes on to cover estimation and prediction. Volume 2 focuses on testing, confidence regions, model selection, and asymptotic theory.

    • 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

    Product details

    October 1995
    Paperback
    9780521477444
    524 pages
    228 × 151 × 30 mm
    0.863kg
    16 b/w illus. 5 tables
    Available

    Table of Contents

    • Preface
    • 1. Models
    • 2. Statistical problems and decision theory
    • 3. Statistical information: classical approach
    • 4. Bayesian interpretations of sufficiency, ancillarity and identification
    • 5. Elements of estimation theory
    • 6. Unbiased estimation
    • 7. Maximum likelihood estimation
    • 8. M-estimation
    • 9. Methods of moments and their generalizations
    • 10. Estimation under equality constraints
    • 11. Prediction
    • 12. Bayesian estimation
    • 13. Numerical procedures.
      Authors
    • Christian Gourieroux , CREST-INSEE, Paris
    • Alain Monfort , CREST-INSEE, Paris
    • Translator
    • Quang Vuong