Time Series Analysis

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:	9780691218632
Publisher:	Princeton University Press
Publication date:	09/01/2020
Sold by:	Barnes & Noble
Format:	eBook
Pages:	816
File size:	34 MB
Note:	This product may take a few minutes to download.

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

“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

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