Time Series Techniques for Economists

Time Series Techniques for Economists

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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. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. 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. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.show more

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'... the level of exposition is appropriate for a course required of all graduate students in economics ... this book is admirable. It should be widely read.' Journal of Economic Literatureshow more

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.show more