Periodicity And Stochastic Trends In Economic Time Series (Advanced Texts In Econometrics) - Couverture souple

Franses, Philip Hans

Couverture souple

ISBN 10 : 0198774540 ISBN 13 : 9780198774549

Editeur : Oxford University Press, U.S.A., 2002

Synopsis

This book provides a self-contained account of periodic models for seasonally observed economic time series with stochastic trends. Two key concepts are periodic integration and periodic cointegration. Periodic integration implies that a seasonally varying differencing filter is required to remove a stochastic trend. Periodic cointegration amounts to allowing cointegration paort-term adjustment parameters to vary with the season. The emphasis is on useful econrameters and shometric models that explicitly describe seasonal variation and can reasonably be interpreted in terms of economic behaviour. The analysis considers econometric theory, Monte Carlo simulation, and forecasting, and it is illustrated with numerous empirical time series. A key feature of the proposed models is that changing seasonal fluctuations depend on the trend and business cycle fluctuations. In the case of such dependence, it is shown that seasonal adjustment leads to inappropriate results. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

A propos du livre

Présentation de l'éditeur

This book provides a self-contained account of periodic models for seasonally observed economic time series with stochastic trends. Two key concepts are periodic integration and periodic cointegration. Periodic integration implies that a seasonally varying differencing filter is required to remove a stochastic trend. Period cointegration amounts to allowing cointegration part-term adjustment parameters to vary with the season. The emphasis is on econometric models that explicitly describe seasonal variation and can reasonably be interpreted in terms of economic behaviour. The analysis considers econometric theory, Monte Carlo simulation, and forecasting, and it is illustrated with numerous empirical time series. A key feature of the proposed models is that changing seasonal fluctuations depend on the trend and business cycle fluctuations. In the case of such dependence, it is shown that seasonal adjustment leads to inappropriate results.

Revue de presse

The book can be recommended to those who want a comprehensive introduction to modern analysis of seasonality or who want to give a post-graduate course on the subject. (Marten Lof, International Journal of Forecasting, 15, (1999).)

Franses' book takes the reader the whole way from fundamentals of time series analysis to the latest achievements, where the young author's own contribution is impressive ... The book gives many practical state of the art tricks and hints that an applied researcher will appreciate. (Marten Lof, International Journal of Forecasting, 15, (1999).)

Détails de l'édition

• Éditeur: Oxford University Press, U.S.A.
• Date d'édition: 2002
• Langue: anglais
• ISBN 10: 0198774540
• ISBN 13: 9780198774549
• Reliure: Broché
• Nombre de pages: 246
• Coordonnées du fabricant: non disponible
• Personne responsable: Ufficio Anagrafiche Messaggerie; ufficio.anagrafiche@meli.it; ; Via Verdi, 8; Assago Milano; 20090; Italie