Time series analyzing is very important tool for economic and
financial system. However, recent developments show that financial systems are
known in a structural change. Therefore, nonlinear time series have been
analyzed for past decades because of these changes. In this paper, we consider
Threshold Autoregressive (TAR) model. The most popular method for estimating
the parameters and threshold value is least square (LS) method. However, LS
method is not robust to the outliers and departures from normality. Therefore,
we propose a robust version of estimation in order to provide robust results.
JEL classification numbers: C01, C22, C13.
Keywords: Threshold Autoregressive Model, Iterated Weighted Least
Square, Skew Normal, Long Tailed Symmetric Distribution, Robustness.