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
'This is a well done introduction to both classical and modern time series models and techniques. Throughout, the authors have managed to keep a sound balance between mathematical rigor (which is always present, but never emphasized or celebrated for its own sake) and user-friendliness of presentation. I found this mixture very easy to digest. Another strong point of the book is its technical competence. In almost every line, one feels that two of the most brilliant present-day theoretical econometricians are at work. Review in Statistical Papers
Product details
March 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.
