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Multivariate Modelling of Non-Stationary Economic Time Series /

This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering...

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Bibliographic Details
Main Authors: Hunter, John
Corporate Authors: SpringerLink Online service
Group Author: Burke, Simon P; Canepa, Alessandra
Published: Palgrave Macmillan UK : Imprint: Palgrave Macmillan,
Publisher Address: London :
Publication Dates: 2017.
Literature type: eBook
Language: English
Edition: Second edition.
Series: Palgrave Texts in Econometrics
Subjects:
Econometrics
Economics
Online Access: http://dx.doi.org/10.1057/978-1-137-31303-4
Summary: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models. The authors provide a detailed and extensive study of impulse responses and forecasting in the stationary and non-stationary context, considering small sample correction, volatility and the impact of different orders of integration. Models with expectations are considered along with alternate methods such as Singular Spectrum Analysis (SSA), the Kalman Filter and Structural Time Series, all in relation to cointegration. Using single equati
Carrier Form: 1 online resource(XIII,336pages).
ISBN: 9781137313034
Index Number: HB139
CLC: F224
Contents: Chapter 1. Introduction: Time Series, Common Trends and Equilibrium -- Chapter 2. Multivariate Time Series -- Chapter 3. Cointegration -- Chapter 4. Testing for Cointegration: Under Standard and Non-Standard Conditions -- Chapter 5. Structure and Evaluation -- Chapter 6. Testing in VECMs with Small Sample -- Chapter 7. Heteroscedasticity and Multivariate Volatility -- Chapter 8. Models with Alternative Orders of Integration -- Chapter 9. The Structural Analysis of Time Series.

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