首页 | 本学科首页   官方微博 | 高级检索  
     


Modelling trigonometric seasonal components for monthly economic time series
Authors:Irma Hindrayanto  John A.D. Aston  Marius Ooms
Affiliation:1. Department of Economic Research , De Nederlandsche Bank , Amsterdam , The Netherlands;2. Department of Statistics , University of Warwick , Warwick , UK;3. Department of Econometrics , VU University Amsterdam , De Boeleloan 1105, Amsterdam , The Netherlands
Abstract:The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this article, we explore a generalization of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal frequencies have different variances for their disturbances. The contribution of the article is two-fold. The first aim is to investigate the dynamic properties of this frequency-specific Basic Structural Model (BSM). The second aim is to relate the model to a comparable generalized version of the Airline model developed at the US Census Bureau. By adopting a quadratic distance metric based on the restricted reduced form moving-average representation of the models, we conclude that the generalized models have properties that are close to each other compared to their default counterparts. In some settings, the distance between the models is almost zero so that the models can be regarded as observationally equivalent. An extensive empirical study on disaggregated monthly shipment and foreign trade series illustrates the improvements of the frequency-specific extension and investigates the relations between the two classes of models.
Keywords:frequency-specific model  Kalman filter  model-based seasonal adjustment  unobserved components time series model
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号