Modelling Autoregressive Processes with a Shifting Mean
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Andrés González
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).
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Modelling Autoregressive Processes with a Shifting Mean
- Rank-based Entropy Tests for Serial Independence
- Cointegration with Structural Breaks: An Application to the Feldstein-Horioka Puzzle
- Evaluation of Surrogate and Bootstrap Tests for Nonlinearity in Time Series
- Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem
- Linear Cointegration of Nonlinear Time Series with an Application to Interest Rate Dynamics
Articles in the same Issue
- Article
- Modelling Autoregressive Processes with a Shifting Mean
- Rank-based Entropy Tests for Serial Independence
- Cointegration with Structural Breaks: An Application to the Feldstein-Horioka Puzzle
- Evaluation of Surrogate and Bootstrap Tests for Nonlinearity in Time Series
- Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem
- Linear Cointegration of Nonlinear Time Series with an Application to Interest Rate Dynamics
