Essays in Econometrics
Collected Papers of Clive W. J. Granger

These are econometrician Clive W. J. Granger's major essays in spectral analysis, seasonality, nonlinearity, methodology, and forecasting.

Clive W. J. Granger (Author), Eric Ghysels (Edited by), Norman R. Swanson (Edited by), Mark W. Watson (Edited by)

9780521772976, Cambridge University Press

Hardback, published 6 August 2001

544 pages, 33 b/w illus. 76 tables
22.9 x 15.2 x 3 cm, 0.89 kg

"It is truly a treat to read all the articles on so many different and important topics." Mathematical Reviews

This book, and its companion volume in the Econometric Society Monographs series (ESM number 33), 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 spectral analysis, seasonality, nonlinearity, methodology, and forecasting. 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. Spectral Analysis: 1. Spectral analysis of New York Stock Market prices O. Morgenstern
2. The typical spectral shape of an eonomic variable
Part II. Seasonality: 3. Seasonality: causation, interpretation and implications A. Zellner
4. Is seasonal adjustment a linear or nonlinear data-filtering process? E. Ghysels and P. L. Siklos
Part III. Nonlinearity: 5. Non-linear time series modeling A. Anderson
6. Using the correlation exponent to decide whether an economic series is chaotic T. Liu and W. P. Heller
7. Testing for neglected nonlinearity in time series models: a comparison of neural network methods and alternative tests
8. Modeling nonlinear relationships between extended-memory variables
9. Semiparametric estimates of the relation between weather and electricity sales R. F. Engle, J. Rice and A. Weiss
Part IV. Methodology: 10. Time series modeling and interpretation M. J. Morris
11. On the invertibility of time series models A. Anderson
12. Near normality and some econometric models
13. The time series approach to econometric model building P. Newbold
14. Comments on the evaluation of policy models
15. Implications of aggregation with common factors
Part V. Forecasting: 16. Estimating the probability of flooding on a tidal river
17. Prediction with a generalized cost of error function
18. Some comments on the evaluation of economic forecasts P. Newbold
19. The combination of forecasts
20. Invited review: combining forecasts - twenty years later
21. The combination of forecasts using changing weights M. Deutsch and T. Terasvirta
22. Forecasting transformed series
23. Forecasting white noise A. Zellner
24. 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
Index.

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