Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/25833 
Year of Publication: 
2006
Series/Report no.: 
CESifo Working Paper No. 1789
Publisher: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Abstract: 
The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error structure. This paper extends this work and examines the important case where the unobserved common factors follow unit root processes and could be cointegrated. It is found that the presence of unit roots does not affect most theoretical results which continue to hold irrespective of the integration and the cointegration properties of the unobserved factors. This finding is further supported for small samples via an extensive Monte Carlo study. In particular, the results of the Monte Carlo study suggest that the cross-sectional average based method is robust to a wide variety of data generation processes and has lower biases than all of the alternative estimation methods considered in the paper.
JEL: 
C12
C13
C33
Document Type: 
Working Paper
Appears in Collections:

Files in This Item:
File
Size
433.77 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.