Arbeitspapier
On detection of unit roots generalizing the classic Dickey-Fuller approach
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.
- Language
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Englisch
- Bibliographic citation
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Series: Technical Report ; No. 2005,09
- Subject
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Unit Root Test
Theorie
- Event
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Geistige Schöpfung
- (who)
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Steland, Ansgar
- Event
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Veröffentlichung
- (who)
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Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
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Dortmund
- (when)
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2005
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Steland, Ansgar
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2005
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Unit roots and structural breaks
On detection of unit roots generalizing the classic Dickey-Fuller approach
Constructing and generalizing multivariate copulas: a generalizing approach
Spatial Unit Roots
Unit root testing
Generalizing heuristic switching models
Generalizing the Scotogenic model
Generalizing algebraically defined norms
Generalizing Heuristic Switching Models
Generalizing Choi-Like Maps
Generalizing the Taylor principle: Comment
Generalizing cell segmentation and quantification