Time series analysis / James Douglas Hamilton.

By: Hamilton, James DouglasPublisher: [S.l.] : Princeton University Press, 1994Edition: 1st edDescription: 820 p. ; 26 cmISBN: 0691042896; 9780691042893Subject(s): Business/Economics | Economics: Professional & General | Econometrics | Time Series Analysis | Investment & securities | Probability & statistics | Mathematics | Business & Economics | Time-series analysis | Business & Economics / Investments & Securities | Investments & Securities - General | Mathematics / Probability & Statistics / General | Probability & Statistics - GeneralDDC classification: 519.55 Online resources: Amazon.com | Amazon customer reviews Summary: 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.
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Central Library (CL)
519.55 HAM (Browse shelf) Write Off Write off File No.0908/IRC/NBS Dated Aug 16, 2018 NBS5497
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Hardcover.

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.

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