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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.
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.
Gourieroux is Director of the Laboratory for Finance and Insurance at the Center for Research in Economics and Statistics in Paris.
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.
This is the first volume in a major two-volume set of advanced texts in econometrics.
This is the first volume in a major two-volume set of advanced texts in econometrics. It is a work of synthesis that covers both the basic and the more sophisticated statistical models. The books are distinctive for their attention to intuitive reasoning and the presentation of many real-world economic examples.
This is the first volume in a major two-volume set of advanced texts in econometrics. It is a work of synthesis that covers both the basic and the more sophisticated statistical models. The books are distinctive for their attention to intuitive reasoning and the presentation of many real-world economic examples.