Multivariate Modelling of Non-Stationary Economic Time Series - pr_262284

Multivariate Modelling of Non-Stationary Economic Time Series

By John Hunter, Simon P. Burke, Alessandra Canepa

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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.

Product code: 9780230243316

ISBN 9780230243316
Dimensions (HxWxD in mm) H210xW148
Series Palgrave Texts in Econometrics
No. Of Pages 502
Publisher Palgrave Macmillan
Edition Softcover reprint of the original 2nd ed. 2017
This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.