Time Series Analysis [Hardback]The Change Leader′s Roadmapby James D. Hamilton
Usually ships within 2 to 4 working days Description of Time Series AnalysisThe 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.Title Information
Write a review of this book Customer Reviews from AmazonContents of Time Series AnalysisPreface1 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 CovarianceStationary 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 FullInformation 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 |
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