Analysis of Integrated and Cointegrated Time Series with R (Use R!)

The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but enables him to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks, and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as an accompanying text book to computer lab classes. The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other. The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book not only introduces the reader to this topic but also enables him to conduct the various unit root tests and co-integration methods on his own by utilising the free statistical programming environment R. The book encompasses seasonal unit roots, fractional integration, coping with structural breaks and multivariate time series models. The book is enriched by numerous programming examples to artificial and real data so that it is ideally suited as a accompanying text book to computer lab classes. The second edition adds a discussion of vector autoregressive, structural vector autoregressive and structural vector error-correlation models Front Matter....Pages i-xx Univariate Analysis of Stationary Time Series....Pages 3-21 Multivariate Analysis of Stationary Time Series....Pages 23-51 Non-stationary Time Series....Pages 53-71 Cointegration....Pages 73-87 Testing for the Order of Integration....Pages 91-105 Further Considerations....Pages 107-118 Single-Equation Methods....Pages 121-127 Multiple-Equation Methods....Pages 129-159 Back Matter....Pages 161-188 The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics. This book enables the reader to conduct the various unit root tests and co-integration methods on his own by utilizing the free statistical programming environment R This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.