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...

Full description

Saved in:
Bibliographic Details
Main Authors: Hunter, John (Author), Burke, Simon P. (Author), Canepa, Alessandra (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: London : Palgrave Macmillan UK : Imprint: Palgrave Macmillan, 2017.
Edition:2nd ed. 2017.
Series:Palgrave texts in econometrics.
Subjects:
Online Access: Full text (Wentworth users only)
Description
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 equations methods to develop topics, and as examples of the notion of cointegration, Burke, Hunter, and Canepa provide direction and guidance to the now vast literature facing students and graduate economists.
Physical Description:XIII, 502 pages : online resource.
ISBN:9781137313034
DOI:10.1057/978-1-137-31303-4