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Applied Time Series Modelling and Forecasting by Richard Harris, Robert Sollis, (2003) Publisher: John Wiley ISBN: 0-470-84443-4 Pages: 312 pages Price: £32.99 +p&p |
Contents Table of Contents Book Order Form |
| Table of Contents Preface 1. Introduction and Overview Some Initial Concepts Forecasting Outline of the Book 2. Short- and Long-run Models Long-run Models Stationary and Non-stationary Time Series Spurious Regressions Cointegration Short-run Models Conclusion 3. Testing for Unit Roots The Dickey–Fuller Test Augmented Dickey–Fuller Test Power and Level of Unit Root Tests Structural Breaks and Unit Root Tests Seasonal Unit Roots Structural Breaks and Seasonal Unit Root Tests Periodic Integration and Unit Root-testing Conclusion on Unit Root Tests 4. Cointegration in Single Equations The Engle-Granger (EG) Approach Testing for Cointegration with a Structural Break Alternative Approaches Problems with the Single Equation Approach Estimating the Short-run Dynamic Model Seasonal Cointegration Periodic Cointegration Asymmetric Tests for Cointegration Conclusions 5. Cointegration in Multivariate Systems The Johansen Approach Testing the Order of Integration of the Variables Formulation of the Dynamic Model Testing for Reduced Rank Deterministic Components in the Multivariate Model Testing of Weak Exogeneity and VECM with Exogenous I (l) Variables Testing for Linear Hypotheses on Cointegration Relations Testing for Unique Cointegration Vectors Joint Tests of Restrictions on α and β Seasonal Unit Roots Seasonal Cointegration Conclusions Appendix 1: Programming in SHAZAM 6. Modelling the Short-run Multivariate System Introduction Estimating the Long-run Cointegration Relationships Parsimonious VECM Conditional PVECM Structural Modelling Structural Macroeconomic Modelling 7. Panel Data Models and Cointegration Introduction Panel Data and Modelling Techniques Panel Unit Root Tests Testing for Cointegration in Panels Estimating Panel Cointegration Models Conclusion on Testing for Unit Roots and Cointegration in Panel Data 8. Modelling and Forecasting Financial Times Series Introduction ARCH and GARCH Multivariate GARCH Estimation and Testing An Empirical Application of ARCH and GARCH Models ARCH-M Asymmetric GARCH Models Integrated and Fractionally Integrated GARCH Models Conditional Heteroscedasticity, Unit Roots and Cointegration Forecasting with GARCH Models Further Methods for Forecast Evaluation Conclusions on Modelling and Forecasting Financial Time Series Appendix: Cointegration Analysis Using the Johansen Technique: A Practitioner's Guide to PcGive 10.1 Statistical Appendix References Index |
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