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




TABLE OF CONTENTS:

	Preface	[/td]
1	Difference Equations	1[/td]
2	Lag Operators	25[/td]
3	Stationary ARMA Processes	43[/td]
4	Forecasting	72[/td]
5	Maximum Likelihood Estimation	117[/td]
6	Spectral Analysis	152[/td]
7	Asymptotic Distribution Theory	180[/td]
8	Linear Regression Models	200[/td]
9	Linear Systems of Simultaneous Equations	233[/td]
10	Covariance-Stationary Vector Processes	257[/td]
11	Vector Autoregressions	291[/td]
12	Bayesian Analysis	351[/td]
13	The Kalman Filter	372[/td]
14	Generalized Method of Moments	409[/td]
15	Models of Nonstationary Time Series	435[/td]
16	Processes with Deterministic Time Trends	454[/td]
17	Univariate Processes with Unit Roots	475[/td]
18	Unit Roots in Multivariate Time Series	544[/td]
19	Cointegration	571[/td]
20	Full-Information Maximum Likelihood Analysis of Cointegrated Systems	630[/td]
21	Time Series Models of Heteroskedasticity	657[/td]
22	Modeling Time Series with Changes in Regime	677[/td]
	A Mathematical Review	704[/td]
	B Statistical Tables	751[/td]
	C Answers to Selected Exercises	769[/td]
	D Greek Letters and Mathematical Symbols Used in the Text	786[/td]
	Author Index	789[/td]
	Subject Index