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Time Series Analysis (ISE)

by James Douglas Hamilton Princeton University Press
Pub Date:
01/1994
ISBN:
9780691042893
Format:
Hbk 816 pages
Price:
AU$113.00 NZ$119.13
Product Status: Not Our Publication - we no longer distribute
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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. Review: '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 Endorsement: '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


Preface
1Difference Equations1
2Lag Operators25
3Stationary ARMA Processes43
4Forecasting72
5Maximum Likelihood Estimation117
6Spectral Analysis152
7Asymptotic Distribution Theory180
8Linear Regression Models200
9Linear Systems of Simultaneous Equations233
10Covariance-Stationary Vector Processes257
11Vector Autoregressions291
12Bayesian Analysis351
13The Kalman Filter372
14Generalized Method of Moments409
15Models of Nonstationary Time Series435
16Processes with Deterministic Time Trends454
17Univariate Processes with Unit Roots475
18Unit Roots in Multivariate Time Series544
19Cointegration571
20Full-Information Maximum Likelihood Analysis of Cointegrated Systems630
21Time Series Models of Heteroskedasticity657
22Modeling Time Series with Changes in Regime677
A Mathematical Review704
B Statistical Tables751
C Answers to Selected Exercises769
D Greek Letters and Mathematical Symbols Used in the Text786
Author Index789
Subject Index792




"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

James D. Hamilton is Professor of Economics at the University of California, San Diego.