Periodicity and Stochastic Trends in Economic Time Series
Series: Advanced Texts in Econometrics;
- Publisher's listprice GBP 40.99
-
19 582 Ft (18 650 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 10% (cc. 1 958 Ft off)
- Discounted price 17 624 Ft (16 785 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
19 582 Ft
Availability
printed on demand
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Publisher OUP Oxford
- Date of Publication 15 August 1996
- ISBN 9780198774549
- Binding Paperback
- No. of pages242 pages
- Size 232x156x14 mm
- Weight 372 g
- Language English
- Illustrations line figures, tables 0
Categories
Short description:
This is an advanced graduate textbook in econometrics. A large proportion of the data studied by econometricians are series of observations of the same variables made over time (time series). This book provides a comprehensive account of how to allow for seasonal fluctuations in these data by using periodic models.
MoreLong 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 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.
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.
Table of Contents:
Introduction
Concepts in Time Series Analysis
An introduction to seasonal time series
Seasonal adjustment
Seasonal integration and cointegration
Are seasons, trends, and cycles always independent?
Periodic autoregressive time series models
Periodic integration
Periodic cointegration
Conclusion
Data Appendix
