IDEAS home Printed from https://ideas.repec.org/p/cbt/econwp/09-18.html
   My bibliography  Save this paper

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

Author

Listed:

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

  • 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
    as

    Download full text from publisher

    File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/0918.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    2. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cbt:econwp:09/18. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Albert Yee). General contact details of provider: http://edirc.repec.org/data/decannz.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.