Evolutionary Computational Approach in TAR Model Estimation
Ca Foscari University of Venice
Università Ca' Foscari Venezia - Department of Management
November 1, 2011
University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 26/WP/2011
The well-known SETAR model introduced by Tong belongs to the wide class of TAR models that may be specified in several different ways. Here we propose to consider the delay parameter as endogenous, that is we make it to depend on both the past value and the specific past regime of the series. In particular, we consider a system switching between two regimes, each of them is a linear autoregressive of order p, with respect to the value assumed by a delayed self-variable compared with an asymmetric threshold; the peculiarity is that the switching rule also depends on the regime in which the system lies at time t-d.
In this work we consider two identification procedures: the first one follows the classical estimation for SETAR models, the second one proposes to estimate this model using the Particle Swarm Optimization technique.
Number of Pages in PDF File: 19
Keywords: Parameter Estimation, Threshold Autoregressive Models, Particle Swarm Optimization
JEL Classification: C13, C32, C51, C63working papers series
Date posted: January 26, 2012
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