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The impact of seasonal constants on forecasting seasonally cointegrated time series

โœ Scribed by Robert M. Kunst; Philip Hans Franses

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
240 KB
Volume
17
Category
Article
ISSN
0277-6693

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โœฆ Synopsis

In this paper we focus on the eect of (i) deleting, (ii) restricting or (iii) not restricting seasonal intercept terms on forecasting sets of seasonally cointegrated macroeconomic time series for Austria, Germany and the UK. A ยฎrst empirical result is that the number of cointegrating vectors as well as the relevant estimated parameter values vary across the three models. A second result is that the quality of out-of-sample forecasts critically depends on the way seasonal constants are treated. In most cases, predictive performance can be improved by restricting the eects of seasonal constants. However, we ยฎnd that the relative advantages and disadvantages of each of the three methods vary across the data sets and may depend on sample-speciยฎc features.

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