Synopses & Reviews
This two-volume set aims to present as completely as possible the methods of statistical inference with special reference to their economic applications. 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. The authors have sought to avoid an overly technical presentation and go to some lengths to encourage an intuitive understanding of the results by providing numerous examples throughout. The breadth of approaches and the extensive coverage of the two volumes provide for a thorough and entirely self-contained course in modern econometrics. 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 two-volume set of advanced texts in econometrics.
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.