Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/40170
Authors: 
Reed, W. Robert
Webb, Rachel S.
Year of Publication: 
2010
Series/Report no.: 
Economics Discussion Papers 2010-23
Abstract: 
Non-spherical errors, namely heteroscedasticity, serial correlation and cross-sectional correlation are commonly present within panel data sets. These can cause significant problems for econometric analyses. The FGLS(Parks) estimator has been demonstrated to produce considerable efficiency gains in these settings. However, it suffers from underestimation of coefficient standard errors, oftentimes severe. Potentially, jackknifing the FGLS(Parks) estimator could allow one to maintain the efficiency advantages of FGLS(Parks) while producing more reliable estimates of coefficient standard errors. Accordingly, this study investigates the performance of the jackknife estimator of FGLS(Parks) using Monte Carlo experimentation. We find that jackknifing can - in narrowly defined situations - substantially improve the estimation of coefficient standard errors. However, its overall performance is not sufficient to make it a viable alternative to other panel data estimators.
Subjects: 
Panel Data estimation
Parks model
cross-sectional correlation
jackknife
Monte Carlo
JEL: 
C23
C15
Creative Commons License: 
http://creativecommons.org/licenses/by-nc/2.0/de/deed.en
Document Type: 
Working Paper

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