Time Series Analysis / Edition 1

by James D. Hamilton

Overview

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.

Product Details

ISBN-13:	9780691042893
Publisher:	Princeton University Press
Publication date:	01/31/1994
Edition description:	New Edition
Pages:	816
Sales rank:	953,302
Product dimensions:	6.00(w) x 9.00(h) x (d)
Age Range:	18 Years

About the Author

James D. Hamilton is professor of economics at the University of California, San Diego.

Table of Contents

Preface

1 Difference Equations 1

2 Lag Operators 25

3 Stationary ARMA Processes 43

4 Forecasting 72

5 Maximum Likelihood Estimation 117

6 Spectral Analysis 152

7 Asymptotic Distribution Theory 180

8 Linear Regression Models 200

9 Linear Systems of Simultaneous Equations 233

10 Covariance-Stationary Vector Processes 257

11 Vector Autoregressions 291

12 Bayesian Analysis 351

13 The Kalman Filter 372

14 Generalized Method of Moments 409

15 Models of Nonstationary Time Series 435

16 Processes with Deterministic Time Trends 454

17 Univariate Processes with Unit Roots 475

18 Unit Roots in Multivariate Time Series 544

19 Cointegration 571

20 Full-Information Maximum Likelihood Analysis of Cointegrated Systems 630

21 Time Series Models of Heteroskedasticity 657

22 Modeling Time Series with Changes in Regime 677

A Mathematical Review 704

B Statistical Tables 751

C Answers to Selected Exercises 769

D Greek Letters and Mathematical Symbols Used in the Text 786

Author Index 789

Subject Index 792

What People are Saying About This

From the Publisher

"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."—John H. Cochrane, University of Chicago

Cochrane

I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students.
— John H. Cochrane, University of Chicago

Recipe

"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."—John H. Cochrane, University of Chicago

Editorial Reviews

"A carefully prepared and well written book. . . . Without doubt, it can be recommended as a very valuable encyclopedia and textbook for a reader who is looking for a mainly theoretical textbook which combines traditional time series analysis with a review of recent research areas."

Journal of Economics

"I am extremely enthusiastic about this book. I think it will quickly become a classic. Like Sargent's and Varian's texts, it will be a centerpiece of the core cirriculum for graduate students."—John H. Cochrane, University of Chicago

From the Publisher