Time Series Analysis
By: James D. Hamilton.
Publisher: Princeton University Press
Published: 1994
Place of publication: Princeton, NJ, USA
Language: eng
Format: Hardcover
Number of pages: 799
ISBN-13: 9780691042893
Copyright date: 1994
Subjects: Time-series analysis
Description: The last decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This book synthesizes these recent advances and makes them accessible to first-year graduate students. James Hamilton provides the first adequate text-book treatments of important innovations such as vector autoregressions, generalized 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 analyzing 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 analyzing 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.
source: https://press.princeton.edu/titles/5386.html
Notes: Includes bibliographical references and indexes.
Table of contents: title: Difference equations --; title: Lag operators --; title: Stationary ARMA processes --; title: Forecasting --; title: Maximum likelihood estimation --; title: Spectral analysis --; title: Asymptotic distribution theory --; title: Linear regression models --; title: Linear systems of simultaneous equations --; title: Covariance-stationary vector processes --; title: Vector autoregressions --; title: Bayesian analysis --; title: The Kalman filter --; title: Generalized method of moments --; title: Models of sonstationary time series --; title: Processes with deterministic time trends --; title: Univariate processes with unit roots --; title: Unit roots in multivariate time series --; title: Cointegration --; title: Full-information maximum likelihood analysis of cointegrated systems --; title: Time series models of heteroskedasticity --; title: Modeling time series with changes in regime.