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Estimating standard errors for the Parks model: Can jackknifing help?

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  • Reed, W. Robert
  • Webb, Rachel S.
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.

Suggested Citation

  • 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 (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-14.
  • Handle: RePEc:zbw:ifweej:20111
    DOI: 10.5018/economics-ejournal.ja.2011-1
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    References listed on IDEAS

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    1. Beck, Nathaniel & Katz, Jonathan N., 1995. "What To Do (and Not to Do) with Time-Series Cross-Section Data," American Political Science Review, Cambridge University Press, vol. 89(3), pages 634-647, September.
    2. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    3. Robert Breunig, 2002. "Bias correction for inequality measures: an application to China and Kenya," Applied Economics Letters, Taylor & Francis Journals, vol. 9(12), pages 783-786.
    4. Reed W. Robert & Webb Rachel, 2010. "The PCSE Estimator is Good -- Just Not As Good As You Think," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-26, September.
    5. Roll, Richard & Schwartz, Eduardo & Subrahmanyam, Avanidhar, 2009. "Options trading activity and firm valuation," Journal of Financial Economics, Elsevier, vol. 94(3), pages 345-360, December.
    6. Roger Congleton & Feler Bose, 2010. "The rise of the modern welfare state, ideology, institutions and income security: analysis and evidence," Public Choice, Springer, vol. 144(3), pages 535-555, September.
    7. W. Robert Reed & Haichun Ye, 2009. "Which panel data estimator should I use?," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 985-1000.
    8. Sunil Sapra, 2002. "A jackknife maximum likelihood estimator for the probit model," Applied Economics Letters, Taylor & Francis Journals, vol. 9(2), pages 73-74.
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    More about this item

    Keywords

    Panel data estimation; Parks model; cross-sectional correlation; jackknife; Monte Carlo;
    All these keywords.

    JEL classification:

    • 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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