Outliers and persistence in threshold autoregressive processes

Yamin Ahmad, Luiggi Donayre

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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 languageEnglish (US)
Pages (from-to)37-56
Number of pages20
JournalStudies in Nonlinear Dynamics and Econometrics
Issue number1
StatePublished - Feb 1 2016

Bibliographical note

Publisher Copyright:
© 2016 by De Gruyter.


  • outliers
  • persistence
  • power
  • size
  • threshold autoregression


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