- Analyzes modern developments in time series analysis and their application to economic problems
- Introduces the fundamental concept of a stationary time series and the basic properties of covariance
- Helps students develop a deeper understanding of theory and better command of the models that are vital to the field
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- About this Textbook
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This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.
- About the authors
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Prof. Klaus Neusser
- Reviews
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“The present monograph is a practical and comprehensive introduction to an area that lies at the core of econometrics. … It requires minimal prerequisites, and is almost surely accessible to senior undergraduate or beginning graduate students, and certainly to independent researchers … . I find this book to be a valuable addition to the monographic literature on time series.” (Giuseppe Castellacci, Mathematical Reviews, October, 2017)
- Table of contents (18 chapters)
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Introduction and Basic Theoretical Concepts
Pages 3-24
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Autoregressive Moving-Average Models
Pages 25-44
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Forecasting Stationary Processes
Pages 45-66
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Estimation of the Mean and the Autocorrelation Function
Pages 67-85
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Estimation of ARMA Models
Pages 87-108
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Table of contents (18 chapters)
- Download Preface 1 PDF (36.1 KB)
- Download Sample pages 1 PDF (320.7 KB)
- Download Table of contents PDF (60.3 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Time Series Econometrics
- Authors
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- Klaus Neusser
- Series Title
- Springer Texts in Business and Economics
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-319-32862-1
- DOI
- 10.1007/978-3-319-32862-1
- Hardcover ISBN
- 978-3-319-32861-4
- Softcover ISBN
- 978-3-319-81387-5
- Series ISSN
- 2192-4333
- Edition Number
- 1
- Number of Pages
- XXIV, 409
- Number of Illustrations
- 2 b/w illustrations, 64 illustrations in colour
- Topics
