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Nonstationary time series analysis and cointegration / [edited by] Colin P. Hargreaves.

Contributor(s): Material type: TextTextSeries: Advanced texts in econometricsPublication details: Oxford : Oxford University Press, 2003.Description: xviii, 308 pages : illustrations ; 24 cmISBN:
  • 9780198773924 (alk. paper) :
Subject(s): DDC classification:
  • 330.015195 23 H279
Contents:
1. Introduction -- 2. Towards a Theory of Economic Forecasting / Michael P. Clements and David F. Hendry -- 3. Bayes Models and Forecasts of Australian Macroeconomic Time Series / Peter C.B. Phillips -- 4. A Review of Methods of Estimating Cointegrating Relationships / Colin Hargreaves -- 5. A Test of the Null Hypothesis of Cointegration / David Harris and Brett Inder -- 6. Modelling Seasonal Variation / Svend Hylleberg -- 7. Cointegration, Seasonality, Encompassing, and the Demand for Money in the United Kingdom / Neil R. Ericsson, David F. Hendry and Hong-Anh Tran -- 8. Evaluating a Real Business Cycle Model / Fabio Canova, Mary Finn and Adrian R. Pagan -- 9. Misspecification versus bubbles in the Cagan hyperinflation model / Steven N. Durlauf and Mark A. Hooker -- 10. Regime Switching with Time-Varying Transition Probabilities / Francis X. Diebold, Joon-Haeng Lee and Gretchen C. Weinbach.
Summary: This book shows major developments in the econometric analysis of the long run (non-stationary and cointegration) - a field which has developed dramatically over the last twelve years. The papers here describe and evaluate new methods, provide useful overviews, and show detailed implementations helpful to practitioners. Papers include Michael Clements and David Hendry's substantive analysis of economic forecasting, necessarily based around an integral understanding of integration and cointegration. The paper by Fabio Canova, Mary Finn and Adrian Pagan evaluates the real business cycles models using the new techniques. Other topics ocvered include an overview of the different estimators of cointegrating relationships, and a new test of cointegration. Applications are shown finding roots in macroeconomic series, testing the Fisher Hypoethesis, testing money demand functions, to testing for inflationary bubbles. This book provides a good coverage of the depth of this literature showing the importance of an understanding of non-stationarity and cointegration.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 330.015195 H279 (Browse shelf(Opens below)) Available 137899
Total holds: 0

Includes bibliographical references and indexes.

1. Introduction --
2. Towards a Theory of Economic Forecasting / Michael P. Clements and David F. Hendry --
3. Bayes Models and Forecasts of Australian Macroeconomic Time Series / Peter C.B. Phillips --
4. A Review of Methods of Estimating Cointegrating Relationships / Colin Hargreaves --
5. A Test of the Null Hypothesis of Cointegration / David Harris and Brett Inder --
6. Modelling Seasonal Variation / Svend Hylleberg --
7. Cointegration, Seasonality, Encompassing, and the Demand for Money in the United Kingdom / Neil R. Ericsson, David F. Hendry and Hong-Anh Tran --
8. Evaluating a Real Business Cycle Model / Fabio Canova, Mary Finn and Adrian R. Pagan --
9. Misspecification versus bubbles in the Cagan hyperinflation model / Steven N. Durlauf and Mark A. Hooker --
10. Regime Switching with Time-Varying Transition Probabilities / Francis X. Diebold, Joon-Haeng Lee and Gretchen C. Weinbach.

This book shows major developments in the econometric analysis of the long run (non-stationary and cointegration) - a field which has developed dramatically over the last twelve years. The papers here describe and evaluate new methods, provide useful overviews, and show detailed implementations helpful to practitioners. Papers include Michael Clements and David Hendry's substantive analysis of economic forecasting, necessarily based around an integral understanding of integration and cointegration. The paper by Fabio Canova, Mary Finn and Adrian Pagan evaluates the real business cycles models using the new techniques. Other topics ocvered include an overview of the different estimators of cointegrating relationships, and a new test of cointegration. Applications are shown finding roots in macroeconomic series, testing the Fisher Hypoethesis, testing money demand functions, to testing for inflationary bubbles.
This book provides a good coverage of the depth of this literature showing the importance of an understanding of non-stationarity and cointegration.

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