Synopses & Reviews
The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. This book brings together recent research at the frontiers of the subject and analyzes the areas of time series analysis of most importance to applied economics. The author discusses three basic areas of time series analysis: univariate models, multivariate models, and nonlinear models. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. It is an up-to-date text, extending the basic techniques of analysis to cover the development of methods that can be used to analyze a wide range of economic problems.
Review
"...I am favorably impressed with TSTE's clear exposition and numerous empirical examples....The author is to be congratulated for his diligent efforts in providing students and researchers a very good synthesis of the time series econometrics literature and a very comprehensive and useful bibliography." Econometrics Reviews
Review
"...this book is admirable. It should be widely read, and is likely to persuade many readers of the value of time series methods, expanding the range of sensible applications of these methods to economic data." Paul Newbold, Journal of Economic Literature
Table of Contents
Preface; 1. Introduction; Part I. Exploratory Analysis of Economic Time Series: 2. The graphical display of time series; 3. Summarising time series; 4. Transforming and smoothing time series; Part II. The Modelling of Univariate Economic Time Series: 5. Stationary stochastic time series models; 6. Modelling nonstationary processes; 7. Forecasting using ARIMA models; 8. ARIMA model building; 9. Exponential smoothing and its relationship to ARIMA modelling; 10. Modelling seasonal time series; 11. Further topics in univariate time series modelling; Part III. The Modelling of Multivariate Economic Time Series: 12. Intervention analysis and the detection of outliers; 13. Transfer function-noise models; 13. Transfer function-noise models; 14. Multiple time series modelling; Part IV. Nonlinear Time Series Models: 15. Conditional variance models and related topics; 16. State dependent models; References; Index.