EconPapers    
Economics at your fingertips  
 

On the impact of error cross-sectional dependence in short dynamic panel estimation

Vasilis Sarafidis () and Donald Robertson

Econometrics Journal, 2009, vol. 12, issue 1, 62-81

Abstract: This paper explores the impact of error cross-sectional dependence (modelled as a factor structure) on a number of widely used IV and generalized method of moments (GMM) estimators in the context of a linear dynamic panel data model. It is shown that, under such circumstances, the standard moment conditions used by these estimators are invalid -- a result that holds for any lag length of the instruments used. Transforming the data in terms of deviations from time-specific averages helps to reduce the asymptotic bias of the estimators, unless the factor loadings have mean zero. The finite sample behaviour of IV and GMM estimators is investigated by means of Monte Carlo experiments. The results suggest that the bias of these estimators can be severe to the extent that the standard fixed effects estimator is not generally inferior anymore in terms of root median square error. Time-specific demeaning alleviates the problem, although the effectiveness of this transformation decreases when the variance of the factor loadings is large. Copyright The Author(s). Journal compilation Royal Economic Society 2008

Date: 2009
References: Add references at CitEc
Citations View citations in EconPapers (45) Track citations by RSS feed

Downloads: (external link)
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1368-423X.2008.00260.x link to full text (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ect:emjrnl:v:12:y:2009:i:1:p:62-81

Ordering information: This journal article can be ordered from
http://www.ectj.org

Access Statistics for this article

Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Series data maintained by Wiley-Blackwell Digital Licensing ().

 
Page updated 2017-10-04
Handle: RePEc:ect:emjrnl:v:12:y:2009:i:1:p:62-81