Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/288362 
Year of Publication: 
2020
Citation: 
[Journal:] Statistical Papers [ISSN:] 1613-9798 [Volume:] 62 [Issue:] 4 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2020 [Pages:] 1997-2030
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
There are various competing procedures to determine whether fractional cointegration is present in a multivariate time series, but no standard approach has emerged. We provide a synthesis of this literature and conduct a detailed comparative Monte Carlo study to guide empirical researchers in their choice of appropriate methodologies. Special attention is paid on empirically relevant issues such as assumptions about the form of the underlying process and the ability of the procedures to distinguish between short-run correlation and long-run equilibria. It is found that several approaches are severely oversized in presence of correlated short-run components and that the methods show different performance in terms of power when applied to common-component models instead of triangular systems.
Subjects: 
Long memory
Fractional cointegration
Semiparametric estimation and testing
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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