Estimating Standard Errors for the Parks Model: Can Jackknifing Help?

Abstract: Non-spherical errors, namely heteroscedasticity, serial correlation and crosssectional 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.

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• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Estimating Standard Errors for the Parks Model: Can Jackknifing Help? ; volume:5 ; number:1 ; year:2011 ; extent:16 ; Economics / Journal articles. Journal articles ; 5, Heft 1 (2011) (gesamt 16)

Contributors, Places and Time

• Creator: Reed, W. Robert ; Webb, Rachel S.

Further information

• DOI: 10.5018/economics-ejournal.ja.2011-1
• URN: urn:nbn:de:101:1-2412121809507.256828785337
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.