Previous versions of this paper were presented at the 6th Nordic Econometric Meeting in Sandbjerg and seminars at universities in Gothenburg, Lund and Melbourne.
A computationally convenient unit root test with covariates, conditional heteroskedasticity and efficient detrending†
Article first published online: 21 MAR 2013
© 2013 Wiley Publishing Ltd.
Journal of Time Series Analysis
Volume 34, Issue 4, pages 477–495, July 2013
How to Cite
Westerlund, J. (2013), A computationally convenient unit root test with covariates, conditional heteroskedasticity and efficient detrending. Journal of Time Series Analysis, 34: 477–495. doi: 10.1111/jtsa.12025
- Issue published online: 18 JUN 2013
- Article first published online: 21 MAR 2013
- Manuscript Received: 3 JUL 2012
- Unit root test;
- GLS detrending
When testing for a unit root in a time series, in spite of the well-known power problem of univariate tests, it is quite common to use only the information regarding the autoregressive behaviour contained in that series. In a series of influential papers, Elliott et al. (Efficient tests for an autoregressive unit root, Econometrica 64, 813–836, 1996), Hansen (Rethinking the univariate approach to unit root testing: using covariates to increase power, Econometric Theory 11, 1148–1171, 1995a) and Seo (Distribution theory for unit root tests with conditional heteroskedasticity, Journal of Econometrics 91, 113–144, 1999) showed that this practice can be rather costly and that the inclusion of the extraneous information contained in the near-integratedness of many economic variables, their heteroskedasticity and their correlation with other covariates can lead to substantial power gains. In this article, we show how these information sets can be combined into a single unit root test.