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Essays in Econometrics

Essays in Econometrics
Collected Papers of Clive W. J. Granger
2 Volume Hardback Set

£206.00

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, R. Ashley, R. Schmalensee, A. A. Weiss, S. Hylleberg, B. S. Yoo, A. D. Hall, H. M. Anderson, J. Gonzalo, N. Haldrup, J. Hallman, N. R. Swanson, R. Joyeux, Z. Ding
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  • Date Published: October 2001
  • availability: Available
  • format: Multiple copy pack
  • isbn: 9780521804073

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About the Authors
  • This two-volume set of books in the Econometric Society Monographs series (ESM numbers 32 and 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 these volumes explore topics in spectral analysis, seasonality, nonlinearity, methodology, forecasting, 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 analyis, including forecasting, seasonality, and nonlinearity
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    Product details

    • Date Published: October 2001
    • format: Multiple copy pack
    • isbn: 9780521804073
    • dimensions: 237 x 160 x 59 mm
    • weight: 1.462kg
    • contains: 77 b/w illus. 125 tables
    • availability: Available
  • Table of Contents

    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.

  • Author

    Clive W. J. Granger

    Editors

    Eric Ghysels, University of North Carolina, Chapel Hill

    Norman R. Swanson, Texas A & M University

    Mark Watson, Princeton University, New Jersey

    Contributors

    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, R. Ashley, R. Schmalensee, A. A. Weiss, S. Hylleberg, B. S. Yoo, A. D. Hall, H. M. Anderson, J. Gonzalo, N. Haldrup, J. Hallman, N. R. Swanson, R. Joyeux, Z. Ding

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