Time Series and Dynamic Models

Description

Concisely written and up-to-date, this book provides a unified and comprehensive analysis of the full range of topics that comprise modern time series econometrics. While it does demand a good quantitative grounding, it does not require a high mathematical rigor or a deep knowledge of economics. One of the book's most attractive features is the close attention it pays throughout to economic models and phenomena. The authors provide a sound analysis of the statistical origins of topics such as seasonal adjustment, causality, exogeneity, cointegration, prediction, and forecasting. Their treatment of Box-Jenkins models and the Kalman filter represents a synthesis of the most recent theoretical and applied work in these areas.

'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