Time Series Analysis

James D. Hamilton, James Douglas Hamilton

• Publisher: Princeton University Press
• Year: 2020
• Print ISBN:
  9780691042893
• eBook ISBN:
  9780691218632
• Topic: Business
• Subtopic: Investments & Securities
• Index: Business

An authoritative, self-contained overview of time series analysis for students and researchers

The past decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This textbook synthesizes these advances and makes them accessible to first-year graduate students. James Hamilton provides comprehensive 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.

This invaluable book 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.

Table of contents

• Cover Page
• Half-title Page
• Title Page
• Copyright Page
• Contents
• Preface
• 1 Difference Equations
• 2. Lag Operators
• 3. Stationary ARMA Processes
• 4. Forecasting
• 5. Maximum Likelihood Estimation
• 6. Spectral Analysis
• 7. Asymptotic Distribution Theory
• 8. Linear Regression Models
• 9. Linear Systems of Simultaneous Equations
• 10. Covariance-Stationary Vector Processes
• 11. Vector Autoregressions
• 12. Bayesian Analysis
• 13. The Kalman Filter
• 14. Generalized Method of Moments
• 15. Models of Nonstationary Time Series
• 16. Processes with Deterministic Time Trends
• 17. Univariate Processes with Unit Roots
• 18. Unit Roots in Multivariate Time Series
• 19. Cointegration
• 20. Full-Information Maximum Likelihood Analysis of Cointegrated Systems
• 21. Time Series Models of Heteroskedasticity
• 22. Modeling Time Series with Changes in Regime
• A. Mathematical Review
• B. Statistical Tables
• C. Answers to Selected Exercises
• D. Greek Letters and Mathematical Symbols Used in the Text
• Author Index
• Subject Index