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Modelling Nonlinear Economic Time Series
Timo Teräsvirta, Dag Tjøstheim, and Clive W. J. Granger
592 pages
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Numerous figures and tables
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234x156mm
978-0-19-958714-8
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Hardback
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16 December 2010
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- Contains recent developments in nonlinear time series that go beyond the existing literature
- Accessible and self-contained chapters
- Contains both parametric and nonparametric methods
- Encourages the reader to apply nonlinear models to their practical modelling problems
- The wide variety of topics covered makes this volume unique
- Complex theory is explained without being overly technical. Relevant references for technical detail are provided
This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For this purpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time
series models is carried out using numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.
Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter is devoted to state space models. As a whole, the book is an indispensable tool for researchers interested
in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.Readership: Academics, researchers, graduates and advanced undergraduates of econometrics, particularly academics in time series econometrics.
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Timo Teräsvirta, Professor of Economics, CREATES, Aarhus University, Denmark, Dag Tjøstheim, Professor, Department of Mathematics, University of Bergen, Norway, and Clive W. J. Granger
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1: Concepts, models and definitions
2: Nonlinear models in economic theory
3: Parametric nonlinear models
4: The nonparametric approach
5: Parametric linearity tests
6: Testing parameter constancy
7: Nonparametric specification tests
8: Conditional heteroskedasticity
9: State space models
10: Nonparametric models
11: Nonlinear and nonstationary models
12: Estimating parametric models
13: Basic nonparametric estimates
14: Forecasting from nonlinear models
15: Nonlinear impulse responses
16: Building nonlinear models
17: Other topics
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The specification in this catalogue, including without limitation price, format, extent, number of illustrations, and month of publication, was as accurate as possible at the time the catalogue was compiled. Occasionally, due to the nature of some contractual restrictions, we are unable to ship a specific product to a particular territory. Jacket images are provisional and liable to change before publication.
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