Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/59035 
Year of Publication: 
2012
Citation: 
[Journal:] Economics: The Open-Access, Open-Assessment E-Journal [ISSN:] 1864-6042 [Volume:] 6 [Issue:] 2012-20 [Publisher:] Kiel Institute for the World Economy (IfW) [Place:] Kiel [Year:] 2012 [Pages:] 1-18
Publisher: 
Kiel Institute for the World Economy (IfW), Kiel
Abstract: 
The authors address the issue of estimation and inference in dependent non-stationary panels of small cross-section dimensions. The main conclusion is that the best results are obtained applying bootstrap inference to single-equation estimators, such as fully modified ordinary least squares and dynamic ordinary least squares. Seemingly unrelated regression estimators perform badly, or are even unfeasible, when the time dimension is not very large compared to the cross-section dimension.
Subjects: 
panel cointegration
fully modified ordinary least squares
fully modified seemingly unrelated regression
dynamic ordinary least squares
dynamic seemingly unrelated regression
JEL: 
C15
C23
C33
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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