Startseite Modelling Autoregressive Processes with a Shifting Mean
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

Modelling Autoregressive Processes with a Shifting Mean

  • Andrés González und Timo Teräsvirta
Veröffentlicht/Copyright: 14. März 2008
Veröffentlichen auch Sie bei De Gruyter Brill

In this paper we introduce an autoregressive model with a deterministically shifting intercept. This implies that the model has a shifting mean and is thus nonstationary but stationary around a nonlinear deterministic component. The shifting intercept is defined as a linear combination of logistic transition functions with time as the transition variables. The number of transition functions is determined by selecting the appropriate functions from a possibly large set of alternatives using a sequence of specification tests. This selection procedure is a modification of a similar technique developed for neural network modelling by White (2006). A Monte Carlo experiment is conducted to show how the proposed modelling procedure and some of its variants work in practice. The paper contains two applications in which the results are compared with what is obtained by assuming that the time series used as examples may contain structural breaks instead of smooth transitions and selecting the number of breaks following the technique of Bai and Perron (1998).

Published Online: 2008-3-14

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston

Heruntergeladen am 3.11.2025 von https://www.degruyterbrill.com/document/doi/10.2202/1558-3708.1459/html
Button zum nach oben scrollen