Estimating Standard Errors For The Parks Model: Can Jackknifing Help?
AbstractNon-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.
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Bibliographic InfoPaper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 09/18.
Length: 12 pages
Date of creation: 15 Nov 2009
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Panel Data estimation; Parks model; cross-sectional correlation; jackknife; Monte Carlo;
Other versions of this item:
- Reed, W. Robert & Webb, Rachel S., 2011. "Estimating standard errors for the Parks model: Can jackknifing help?," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 5(1), pages 1-14.
- Reed, W. Robert & Webb, Rachel S., 2010. "Estimating standard errors for the Parks model: Can jackknifing help?," Economics Discussion Papers 2010-23, Kiel Institute for the World Economy.
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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