Abstract
Working with seventeen quarterly UK macroeconomic variables, characterized as periodically integrated in Franses and Romijn (1993), we have found that unconstrained periodic models do not beat time invariant alternatives in forecasting, even when cointegrating relationships among the seasons are taken into account. However, when appropriately constrained, the forecasting performance of periodic models can be much better than that of non-periodic models. Homogeneity restrictions among some seasons seem to be very important in that respect, which motivates us to propose switching for specific quarters between a periodic model and a non-periodic univariate AR to better capture the behaviour of these variables. Once season homogeneity is taken into account, incorporating the cointegrating relationships among the seasons through periodic error correction models achieves a substantial additional forecasting improvement.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
