Zusatztext "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." Informationen zum Autor James D. Hamilton is professor of economics at the University of California, San Diego. Klappentext "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 Zusammenfassung A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments. Inhaltsverzeichnis Preface Difference Equations 2Lag Operators 3Stationary ARMA Processes 4Forecasting 5Maximum Likelihood Estimation 6Spectral Analysis 7Asymptotic Distribution Theory 8Linear Regression Models 9Linear Systems of Simultaneous Equations 10Covariance-Stationary Vector Processes 11Vector Autoregressions 12Bayesian Analysis 13The Kalman Filter 14Generalized Method of Moments 15Models of Nonstationary Time Series 16Processes with Deterministic Time Trends 17Univariate Processes with Unit Roots 18Unit Roots in Multivariate Time Series 19Cointegration 20Full-Information Maximum Likelihood Analysis of Cointegrated Systems 21Time Series Models of Heteroskedasticity 22Modeling 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 Subject Index

"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."

Autorentext

James D. Hamilton

Klappentext

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.

Zusammenfassung
A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments.

Inhalt
Preface Difference Equations 2Lag Operators 3Stationary ARMA Processes 4Forecasting 5Maximum Likelihood Estimation 6Spectral Analysis 7Asymptotic Distribution Theory 8Linear Regression Models 9Linear Systems of Simultaneous Equations 10Covariance-Stationary Vector Processes 11Vector Autoregressions 12Bayesian Analysis 13The Kalman Filter 14Generalized Method of Moments 15Models of Nonstationary Time Series 16Processes with Deterministic Time Trends 17Univariate Processes with Unit Roots 18Unit Roots in Multivariate Time Series 19Cointegration 20Full-Information Maximum Likelihood Analysis of Cointegrated Systems 21Time Series Models of Heteroskedasticity 22Modeling 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 Subject Index