Multivariate Modelling of Non-Stationary Economic Time Series

✍ Scribed by John Hunter, Simon P. Burke, Alessandra Canepa (auth.)

• Publisher: Palgrave Macmillan UK
• Year: 2017
• Tongue: English
• Leaves: 508
• Series: Palgrave Texts in Econometrics
• Edition: 2
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiii
Introduction....Pages 1-19
Multivariate Time Series....Pages 21-75
Cointegration....Pages 77-144
Testing for Cointegration: Standard and Non-Standard Conditions....Pages 145-204
Structure and Evaluation....Pages 205-279
Testing in VECMs with Small Samples....Pages 281-304
Heteroscedasticity and Multivariate Volatility....Pages 305-338
Models with Alternative Orders of Integration....Pages 339-382
The Structural Analysis of Time Series....Pages 383-439
Back Matter....Pages 441-502

✦ Subjects

Econometrics