Why Frequency Matters for Unit Root Testing

H. Peter Boswijk () and Franc Klaassen ()

No 04-119/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: It is generally believed that for the power of unit root tests, only the time span and not the observation frequency matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for financial time series such as exchange rate returns. Our claim builds on recent work on unit root and cointegration testing based non-Gaussian likelihood functions. The essential idea is that such methods will yield power gains in the presence of fat tails and persistent volatility clustering, and the strength of these features (and hence the power gains) increases with the observation frequency. This is illustrated using both Monte Carlo simulations and empirical applications to real exchange rates.

Keywords: Fat tails; GARCH; mean reversion; observation frequency; purchasing-power parity; unit roots (search for similar items in EconPapers)
JEL-codes: C12 C22 F31 (search for similar items in EconPapers)
Date: 2005-11-05
View list of references View citations in EconPapers

Downloads: (external link)
http://www.tinbergen.nl/discussionpapers/04119.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:dgr:uvatin:20040119

Access Statistics for this paper

More papers in Tinbergen Institute Discussion Papers from Tinbergen Institute
Series data maintained by Walther Schoonenberg ().