Nonlinearities and Outliers: Robust Speciication of Star Models

Outliers and nonlinearity may easily be mistaken. This paper uses Monte Carlo methods to examine and compare the behavior of two competing speciication procedures for Smooth Transition AutoRegressive STAR] models under various diierent circumstances (linear and nonlinear data generating processes, with and without outlier contamination). The extensive simulation evidence demonstrates that the use of outlier-robust variants of the linearity tests which are involved leads to procedures with more desirable properties. An application to several real exchange rate series illustrates the potential usefulness of the robust speciication procedures, especially in case one is not certain whether or not aberrant observations are present.