1. A profile: the ET Interview: Professor Clive Granger; Part I. Spectral Analysis:
2. Spectral analysis of New York Stock Market prices O. Morgenstern;
3. The typical spectral shape of an eonomic variable; Part II. Seasonality:
4. Seasonality: causation, interpretation and implications A. Zellner;
5. Is seasonal adjustment a linear or nonlinear data-filtering process? E. Ghysels and P. L. Siklos; Part III. Nonlinearity:
6. Non-linear Time Series Modeling A. Anderson;
7. Using the correlation exponent to decide whether an economic series is chaotic T. Liu and W. P. Heller;
8. Testing for neglected nonlinearity in Time Series Models: a comparison of neural network methods and alternative tests;
9. Modeling nonlinear relationships between extended-memory variables;
10. Semiparametric estimates of the relation between weather and electricity sales R. F. Engle, J. Rice and A. Weiss; Part IV. Methodology:
11. Time Series Modeling and interpretation M. J. Morris;
12. On the invertibility of Time Series Models A. Anderson;
13. Near normality and some econometric models;
14. The Time Series approach to econometric model building P. Newbold;
15. Comments on the evaluation of policy models;
16. Implications of aggregation with common factors; Part V. Forecasting:
17. Estimating the probability of flooding on a tidal river;
18. Prediction with a generalized cost of error function;
19. Some comments on the evaluation of economic forecasts P. Newbold;
20. The combination of forecasts;
21. Invited review: combining forecasts - twenty years later;
22. The combination of forecasts using changing weights M. Deutsch and T. Terasvirta;
23. Forecasting transformed series;
24. Forecasting white noise A. Zellner;
25. Can we improve the perceived quality of economic forecasts? Short-run forecasts of electricity loads and peaks R. Ramanathan, R. F. Engle, F. Vahid-Araghi and C. Brace.

Volume II: 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.