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Time Series Analysis

The last decade has brought dramatic changes in the way that researchers analyze time series data. This much-needed book synthesizes all of the major recent advances and develops a single, coherent presentation of the current state of the art of this increasingly important field. James Hamilton provides for the first time a thorough and detailed textbook account of important innovations such as vector autoregressions, estimation by generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, Hamilton presents traditional tools for analyzing dynamic systems, including linear representations, autocovariance, generating functions, spectral analysis, and the Kalman filter, illustrating their usefulness both for economic theory and for studying and interpreting real-world data. This book is intended to provide students, researchers, and forecasters with a definitive, self-contained survey of dy