This paper uses Monte Carlo simulations to investigate the effects of outlier observations on the properties of linearity tests against threshold autoregressive (TAR) processes. By considering different specifications and levels of persistence for the data-generating processes, we find that additive outliers distort the size of the test and that the distortion increases with the level of persistence. In addition, we also find that larger additive outliers can help to improve the power of the test in the case of persistent TAR processes.
|Original language||English (US)|
|Number of pages||20|
|Journal||Studies in Nonlinear Dynamics and Econometrics|
|State||Published - Feb 1 2016|
Bibliographical notePublisher Copyright:
© 2016 by De Gruyter.
- threshold autoregression