Time Series Analysis

The last decade has brought dramatic changes in the way researchers analyse economic and financial time series. This book synthesises these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate textbook treatments of important innovations such as vector autoregressions, generalised method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models.

In addition, he presents basic tools for analysing dynamic systems (including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter) in a way that integrates economic theory with the practical difficulties of analysing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results.

The book is intended to provide students and researchers with a self-contained survey of time series analysis. It starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.