Classical and Bayesian aspects of robust unit root inference

Henk Hoek*, André Lucas, Herman K. van Dijk

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This paper has two themes. First, we classify some effects which outliers in the data have on unit root inference. We show that, both in a classical and a Bayesian framework, the presence of additive outliers moves 'standard' inference towards stationarity. Second, we base inference on an independent Student-t instead of a Gaussian likelihood. This yields results that are less sensitive to the presence of outliers. Application to several time series with outliers reveals a negative correlation between the unit root and degrees of freedom parameter of the Student-t distribution. Therefore, imposing normality may incorrectly provide evidence against the unit root.

Original languageEnglish
Pages (from-to)27-59
Number of pages33
JournalJournal of Econometrics
Volume69
Issue number1
DOIs
Publication statusPublished - 1995

Keywords

  • Bayesian analysis
  • Outliers
  • Robustness
  • Student-t distribution
  • Unit root inference

Fingerprint Dive into the research topics of 'Classical and Bayesian aspects of robust unit root inference'. Together they form a unique fingerprint.

Cite this