Seasonal Integration and the Evolving Seasonals Model

International Journal of Forecasting, Vol. 13, 1997

Posted: 25 Mar 1998

See all articles by Svend Hylleberg

Svend Hylleberg

Aarhus University - Department of Economics

Adrian Pagan

Australian National University (ANU) - Research School of Social Sciences (RSSS); UNSW Australia Business School, School of Economics

Multiple version iconThere are 2 versions of this paper

Abstract

NOTE: This is a description of the paper and not the actual abstract.

In this paper it is argued that describing seasonal patterns as an evolving seasonals model in which the coefficients attached to seasonal trigonometric terms follow simple autoregressive processes can be very useful when one is faced with the task of extending well known results obtained for non-seasonal time series to the seasonal case. Such a perspective gains its utility from the fact that this evolving seasonal Model (ESM) can be decomposed into quantities that are non-seasonal and the behaviour of these variables can be examined with standard techniques. It emerges that this strategy will deliver methods currently in use for the analysis of seasonal series, and is also flexible enough to suggest some new alternatives.

JEL Classification: C12, C13, C22

Suggested Citation

Hylleberg, Svend and Pagan, Adrian R., Seasonal Integration and the Evolving Seasonals Model. International Journal of Forecasting, Vol. 13, 1997. Available at SSRN: https://ssrn.com/abstract=4593

Svend Hylleberg (Contact Author)

Aarhus University - Department of Economics ( email )

University Park
DK-8000 Aarhus C
Denmark
+45 8942 1133 (Phone)
+45 8613 6334 (Fax)

Adrian R. Pagan

Australian National University (ANU) - Research School of Social Sciences (RSSS) ( email )

Canberra, Australian Capital Territory 0200
Australia
+61 2 6249 2216 (Phone)
+61 06 249 0182 (Fax)

UNSW Australia Business School, School of Economics

High Street
Sydney, NSW 2052
Australia

Register to save articles to
your library

Register

Paper statistics

Abstract Views
449
PlumX Metrics