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Applied Time Series Modelling and Forecasting provides a relatively non-technical introduction to
applied time series econometrics and forecasting involving non-stationary data. The emphasis is very
much on the why and how and, as much as possible, the authors confine technical material to boxes or
point to the relevant sources for more detailed information.
This book is based on an earlier title Using Cointegration Analysis in Econometric Modelling by Richard
Harris. As well as updating material covered in the earlier book, there are two major additions
involving panel tests for unit roots and cointegration and forecasting of financial time series. Harris
and Sollis have also incorporated as many of the latest techniques in the area as possible including:
testing for periodic integration and cointegration; GLS detrending when testing for unit roots;
structural breaks and season unit root testing; testing for cointegration with a structural break;
asymmetric tests for cointegration; testing for super-exogeniety; seasonal cointegration in multivariate
models; and approaches to structural macroeconomic modelling. In addition, the discussion of certain
topics, such as testing for unique vectors, has been simplified.
Applied Time Series Modelling and Forecasting has been written for students taking courses in financial
economics and forecasting, applied time series, and econometrics at advanced undergraduate and
postgraduate levels. It will also be useful for practitioners who wish to understand the application of
time series modelling e.g. financial brokers.
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