Essays in Econometrics 2 Volume Paperback Set

Volume I: Introduction to Volumes I and II; 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.