Skip to content
Register Sign in Wishlist
Essays in Econometrics

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

Volume 1. Spectral Analysis, Seasonality, Nonlinearity, Methodology, and Forecasting

$74.99 (C)

Part of Econometric Society Monographs

Eric Ghysels, Norman R. Swanson, Mark W. Watson, A. Zellner, P. L. Siklos, A. Anderson, T. Liu, W. P. Heller, R. F. Engle, J. Rice, A. Weiss, M. J. Morris, P. Newbold, M. Deutsch, T. Terasvirta, R. Ramanathan, F. Vahid-Araghi, C. Brace
View all contributors
  • Date Published: July 2001
  • availability: Available
  • format: Paperback
  • isbn: 9780521774963

$ 74.99 (C)

Add to cart Add to wishlist

Other available formats:
Hardback, eBook

Looking for an examination copy?

If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact providing details of the course you are teaching.

Product filter button
About the Authors
  • This book, and its companion volume, 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.

    • Major essays of arguably the world's leading active econometrician
    • Granger is internationally known, author of 1999 Press title Empirical Modeling in Economics
    • Topics cover major areas of econometrics and time series analysis, including forecasting, seasonality, and nonlinearity
    Read more

    Reviews & endorsements

    "All the articles are a delight to read and give a deep historical and methodological insight...These two volumes are a must-read for any student or researcher in econometrics." Journal of the American Statistical Association

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

    See more reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    Product details

    • Date Published: July 2001
    • format: Paperback
    • isbn: 9780521774963
    • length: 544 pages
    • dimensions: 231 x 153 x 29 mm
    • weight: 0.72kg
    • contains: 33 b/w illus. 76 tables
    • availability: Available
  • Table of Contents

    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

  • Author

    Clive W. J. Granger


    Eric Ghysels, University of North Carolina, Chapel Hill

    Norman R. Swanson, Rutgers University, New Jersey

    Mark W. Watson, Princeton University, New Jersey


    Eric Ghysels, Norman R. Swanson, Mark W. Watson, A. Zellner, P. L. Siklos, A. Anderson, T. Liu, W. P. Heller, R. F. Engle, J. Rice, A. Weiss, M. J. Morris, P. Newbold, M. Deutsch, T. Terasvirta, R. Ramanathan, F. Vahid-Araghi, C. Brace

Sign In

Please sign in to access your account


Not already registered? Create an account now. ×

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.