On detection of unit roots generalizing the classic Dickey-Fuller approach

dc.contributor.author	Steland, A.	de
dc.date.accessioned	2005-03-08T15:24:02Z
dc.date.available	2005-03-08T15:24:02Z
dc.date.issued	2005	de
dc.description.abstract	If we are given a time series of economic data, a basic question is whether the series is stationary or a random walk, i.e., has a unit root. Whereas the problem to test the unit root null hypothesis against the alternative of stationarity is well studied in the context of classic hypothesis testing in the sense of Neyman, sequential and monitoring approaches have not been studied in detail yet. We consider stopping rules based on a sequential version of the well known Dickey-Fuller test statistics in a setting, where the asymptotic distribution theory becomes a nice and simple application of weak convergence of Ito integrals. More sophisticated extensions studied elsewhere are outlined. Finally, we present a couple of simulations.	en
dc.format.extent	127705 bytes
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/2003/20159
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-8051
dc.language.iso	en	de
dc.publisher	Universität Dortmund	de
dc.subject.ddc	310	de
dc.title	On detection of unit roots generalizing the classic Dickey-Fuller approach	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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