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ESSAYS IN ECONOMETRICS 2 VOLUME PAPERBACK SET

W. J. Granger Clive

Oprawa:
MIĘKKA

Wydawca:
Cambridge University Press

Data premiery:
2001-07-23

ISBN:
9780521796972

525,53 PLN
Wysyłamy w 21 dni

Opis produktu

Clive W. J. Grangers major essays in spectral analysis seasonality nonlinearity methodology forecasting causality integration and cointegration and long memory.These essays by Clive W. J. Granger span more than four decades and explore topics in spectral analysis seasonality nonlinearity methodology forecasting causality integration and cointegration and long memory. The introduction places the essays in context and demonstrates their enduring value.These essays by Clive W. J. Granger span more than four decades and explore topics in spectral analysis seasonality nonlinearity methodology forecasting causality integration and cointegration and long memory. The introduction places the essays in context and demonstrates their enduring value.This twovolume 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.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 datafiltering process? E. Ghysels and P. L. Siklos: Part III. Nonlinearity: 6. Nonlinear 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 extendedmemory 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. Terasv

Data Publikacji: 2001-07-23
Wymiary: 228 mm 152 mm 50 mm 1270 gr

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