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Periodicity and Stochastic Trends in Economic Time Series
Contributor(s): Franses, Philip Hans (Author)

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ISBN: 0198774540     ISBN-13: 9780198774549
Publisher: OUP Oxford
OUR PRICE: $66.50  

Binding Type: Paperback - See All Available Formats & Editions
Published: October 1996
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Annotation: 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.
Additional Information
BISAC Categories:
- Business & Economics | Econometrics
Dewey: 330.015
LCCN: 96000420
Lexile Measure: 1520(Not Available)
Physical Information: 0.51" H x 6.14" W x 9.21" L (0.76 lbs) 248 pages
Features: Bibliography, Index
 
Descriptions, Reviews, Etc.
Publisher Description:
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.
 
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