Nonstationary Time Series Analysis and Cointegration

By Colin P. Hargreaves | Go to book overview

1
Introduction

The analysis of nonstationary time series, unit roots and cointegration has developed dramatically over the last 12 years. The papers here variously describe new methods, they evaluate methods, they provide useful overviews and they show detailed implementations that are helpful to practitioners. However these papers show not only developments in methods of estimating long-ran relations (for seasonally unadjusted as well as adjusted data, for instance), but also how the whole subject matter is broadening out to have a profound affect on econometric analysis in general. Michael Clements and David Hendry's discussion of economic forecasting is based around an integral understanding of integration and cointegration including an analysis of whether one should use differenced models. Fabio Canova, Mary Finn and Adrian Pagan's analysis of evaluating real business cycle models and Steven Durlauf and Mark Hooker's analysis of Cagan's hyperinflation model equally work from an understanding of the different time series properties to be found in nonstationary versus stationary data. The concepts of integration and cointegration are here to stay although some of the demands made on the data are very high as we shall discuss later.

The first paper by Michael Clements and David Hendry is a substantive and innovative contribution to analysing economic forecasting, looking at the various sources of error such as 'parameter non-constancy, estimation uncertainty, variable uncertainty, innovation uncertainty, and model misspecification', and trying to organise these into a coherent theory of economic forecasting. This approach appears to have great potential and certainly leads to a better appreciation of the use of intercept adjustments to improve forecasting. One could see this sort of approach being used also for a well-organised analysis of the many different types

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Nonstationary Time Series Analysis and Cointegration
Table of contents

Table of contents

  • Title Page iii
  • Contents v
  • List of Figures vii
  • List of Tables xiii
  • List of Contributors xv
  • Foreword xvii
  • 1 - Introduction 1
  • References 8
  • 2 - Towards a Theory of Economic Forecasting 9
  • Appendix 48
  • References 50
  • 3 - Bayes Models and Forecasts of Australian Macroeconomic Time Series 53
  • References 86
  • 4 - A Review of Methods of Estimating Cointegrating Relationships 87
  • References 129
  • 5 - A Test of the Null Hypothesis of Cointegration 133
  • References 151
  • 6 - Modelling Seasonal Variation 153
  • References 176
  • 7 - Cointegration, Seasonality, Encompassing, and the Demand for Money in the Uk 179
  • Appendix A. the Data 214
  • Appendix B. Sequential Reduction Analysis 216
  • References 220
  • 8 - Evaluating a Real Business Cycle Model 225
  • Appendix 252
  • References 254
  • 9 - Misspecification Versus Bubbles in the Cagan Hyperinflation Model 257
  • References 281
  • 10 Regime Switching with Time-Varying Transition Probabilities 283
  • Appendix 299
  • References 302
  • Name Index 303
  • Subject Index 307
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