Time Series and Dynamic Models
Time Series and Dynamic Models
In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close attention it pays to economic models and phenomena throughout. The coverage represents a major reference tool for graduate students, researchers and applied economists. The book is divided into four sections. Section one gives a detailed treatment of classical seasonal adjustment or smoothing methods. Section two provides a thorough coverage of various mathematical tools. Section three is the heart of the book, and is devoted to a range of important topics including causality, exogeneity shocks, multipliers, cointegration and fractionally integrated models. The final section describes the main contribution of filtering and smoothing theory to time series econometric problems.
- First textbook integrating traditional and modern time series analysis for econometric modelling
- Completely comprehensive book on time series, which will be invaluable to teachers and students of graduate courses on econometrics
- Written by two of the top econometricians in the world
Reviews & endorsements
"If I wanted to give a good overview of the field to students who already had a course on ARIMA models and some state-space theory, then I would use Time Series and Dynamic Models." Kent D. Wall, JASA
"This book is well organized and provides many insights into time series and dynamic models....this book should be a useful resource not only for the econometrician but also for the person with no background in econometrics who is interested in the general theory of time series." Errol Caby, Technometrics
"In my opinion, it is the best general text on time series analysis available. It is a masterpiece. Organization is impeccable. Results flow seamlessly from one to the next. The writing, for the most part, is very accessible. It nicely balances mathematical formality with a hands-on, tone that tells you what is "really going on."
riskbook.com
Product details
January 1997Paperback
9780521423083
688 pages
229 × 152 × 38 mm
1kg
112 b/w illus. 50 tables
Available
Table of Contents
- Preface
- 1. Introduction
- Part I. Traditional Methods:
- 2. Linear regression for seasonal adjustment
- 3. Moving averages for seasonal adjustment
- 4. Exponential smoothing methods
- Part II. Probabilistic and Statistical Properties of Stationary Processes:
- 5. Some results on the univariate processes
- 6. The Box and Jenkins method for forecasting
- 7. Multivariate time series
- 8. Time-series representations
- 9. Estimation and testing (stationary case)
- Part III. Time-series Econometrics: Stationary and Nonstationary Models:
- 10. Causality, exogeneity, and shocks
- 11. Trend components
- 12. Expectations
- 13. Specification analysis
- 14. Statistical properties of nonstationary processes
- Part IV. State-space Models:
- 15. State-space models and the Kalman filter
- 16. Applications of the state-space model
- References
- Tables
- Index.
