Time Series and Dynamic Models in Bloomington, MN

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.