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Estimating Standard Errors For The Parks Model: Can Jackknifing Help?

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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.

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  • W. Robert Reed & Rachel S. Webb, 2009. "Estimating Standard Errors For The Parks Model: Can Jackknifing Help?," Working Papers in Economics 09/18, University of Canterbury, Department of Economics and Finance.
    • Handle: RePEc:cbt:econwp:09/18
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    1. 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.
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    3. 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.
    4. 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.
    5. 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.
    6. W. Robert Reed & Haichun Ye, 2009. "Which panel data estimator should I use?," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 985-1000.
    7. 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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    1. Economou, Athina & Gavroglou, Stavros & Kollias, Christos, 2013. "Economic fluctuations and political self-placement," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 46(C), pages 57-65.
    2. Murshed, Muntasir & Rashid, Seemran, 2020. "An Empirical Investigation of Real Exchange Rate Responses to Foreign Currency Inflows: Revisiting the Dutch Disease phenomenon in South Asia," MPRA Paper 98756, University Library of Munich, Germany.

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    More about this item

    Keywords

    Panel Data estimation; Parks model; cross-sectional correlation; jackknife; Monte Carlo;

    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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