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.
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