Modelling Non-Stationary Economic Time Series

Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems. This book provides direction and guidance to the now vast literature facing students and graduate economists. Econometric theory is linked to practical issues such as how to identify equilibrium relationships, how to deal with structural breaks associated with regime changes and what to do when variables are of different orders of integration.

Autorentext
SIMON P. BURKE is a Lecturer in Economics at the University of Reading, UK. His research interests include Time Series Econometrics and Computational Econometrics.

JOHN HUNTER is Lecturer in Economics at Brunel University, UK. His research interests include Multivariate Time Series, Exogeneity, Econometric Identification and Simulation, Classification, Specification and Testing of Discrete Data using Neural Networks, Semi-Parametric and Parametric Methods.

Inhalt
PART 1: INTRODUCTION: COINTEGRATION, ECONOMIC EQUILIBRIUM AND THE LONG RUN PART 2: UNIVARIATE AND SINGLE EQUATION METHODS Introduction Non-Stationarity Univariate Statistical Time Series Models and Non-Stationarity Testing for Non-Stationarity in Single Series Conclusion PART 3: RELATIONSHIPS BETWEEN NON-STATIONARITY TIME SERIES Introduction Equilibrium and Equilibrium Correction Cointegration and Equilibrium Regression Amongst Cointegrated Variables Conclusion PART 4: MULTIVARIATE TIME SERIES APPROACH TO COINTEGRATION Introduction The VMA, the VAR and the VECM VAR - Based Tests of Cointegration The Smith-McMillan-Yoo Form Johansen's VAR Representation of Cointegration Johansen's Approach to Testing for Cointegration in Systems Tests of Cointegration in VAR Models Alternative Representations PART 5: EXOGENEITY AND IDENTIFICATION An Introduction to Exogeneity Identification Exogeneity and Identification Empirical Examples Conclusion PART 6: FURTHER TOPICS IN THE ANALYSIS OF NON-STATIONARY TIME SERIES Introduction Inference and Estimation When Series Are Not I(1) Forecasting in Cointegrated Systems Models with Short-Run Dynamics Induced by Expectations Conclusion PART 7: CONCLUSION Approximation Alternative Methods Structural Breaks Last Comments Notes Appendices References Index