Intermediate Statistics and Econometrics
A Comparative Approach
A thoroughly modern, comprehensive treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model.
The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses—giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set—the Challenger space shuttle disaster—that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.
HardcoverOut of Print ISBN: 9780262161497 731 pp. | 10 in x 7 in
Paperback$108.00 X ISBN: 9780262660945 731 pp. | 10 in x 7 in
This book is unlike any other that I have read. The major difference is its comparative approach. It is also far more comprehensive than standard introductory texts but is much more accessible than advanced statistics texts. It contains material that is important for econometricians such as regression analysis, which is often not incorporated in statistical textbooks. It represents a significant contribution to the field.
Faculty of Economics and Politics, Cambridge University
Dale Poirier brings the probability and statistics foundations of econometrics in the '90s. In particular, the likelihood function and the likelihood principle, which form the cornerstone for the pedagogical approach adopted by the author, are concepts that both unify and challenge traditional methodology. Poirier succeeds admirably in distilling these types of methodological issues down to the essence that truly impacts how students think. The work is very original and the scholarship is rock solid.
Stanley E. Zin
Graduate School of Industrial Administration, Carnegie Mellon University and the National Bureau of Economic Research
This is a solid book that stakes out some unclaimed ground. It is unique in what it tries to achieve.
Graduate School of Business, University of Chicago