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Time Series and Dynamic Models


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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.

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An up-to-date and comprehensive analysis of traditional and modern time series econometrics.


'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
"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."

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