'Re-reading all these contributions is fascinating and eye-opening on the fundamental effect that Granger had on research in economics. … this book constitutes a highly recommendable addition to your bookshelf.' De Economist

This book, and its companion volume in the Econometric Society Monographs series (ESM number 32), present a collection of papers by Clive W. J. Granger. His contributions to economics and econometrics, many of them seminal, span more than four decades and touch on all aspects of time series analysis. The papers assembled in this volume explore topics in causality, integration and cointegration, and long memory. Those in the companion volume investigate themes in causality, integration and cointegration, and long memory. The two volumes contain the original articles as well as an introduction written by the editors.

Part I. Causality: 1. Investigating causal relations by econometric models and cross-spectral methods
2. Testing for causality
3. Some recent developments in a concept of causality
4. Advertising and aggregate consumption: an analysis of causality R. Ashley and R. Schmalensee
Part II. Integration and Cointegration: 5. Spurious regressions in econometrics
6. Some properties of time series data and their use in econometric model specification
7. Time series analysis of error correction models A. A. Weiss
8. Co-Integration and error-correction: representation, estimation and testing
9. Developments in the study of cointegrated economic variables
10. Seasonal integration and cointegration S. Hylleberg, R. F. Engle and B. S. Yoo
11. A cointegration analysis of Treasury Bill yields A. D. Hall and H. M. Anderson
12. Estimation of common long-memory components in Cointegrated Systems J. Gonzalo
13. Separation in cointegrated systems and persistent-transitory decompositions N. Haldrup
14. Nonlinear transformations of Integrated Time Series J. Hallman
15. Long Memory Series with attractors J. Hallman
16. Further developments in the study of cointegrated variables N. R. Swanson
Part III. Long Memory: 17. An introduction to long-memory Time Series models and fractional differencing R. Joyeux
18. Long-memory relationships and the aggregation of dynamic models
19. A long memory property of stock market returns and a new model Z. Ding and R. F. Engle.

Subject Areas: Economic forecasting [KCJ], Econometrics [KCH]