Advanced Search
MyIDEAS: Login

The PCSE Estimator is Good — Just Not As Good As You Think

Contents:

Author Info

  • W. Robert Reed

    (University of Canterbury)

  • Rachel Webb

    (University of Canterbury)

Abstract

This paper investigates the properties of the Panel-Corrected Standard Error (PCSE) estimator. The PCSE estimator is commonly used when working with time-series, cross-sectional (TSCS) data. In an influential paper, Beck and Katz (1995) (henceforth BK) demonstrated that FGLS produces coefficient standard errors that are severely underestimated. They report Monte Carlo experiments in which the PCSE estimator produces accurate standard error estimates at no or little loss in efficiency compared to FGLS. Our study further investigates the properties of the PCSE estimator. We first reproduce the main experimental results of BK using their Monte Carlo framework. We then show that the PCSE estimator does not perform as well when tested in data environments that better resemble “practical research situations.†When (i) the explanatory variable(s) are characterized by substantial persistence, (ii) there is serial correlation in the errors, and (iii) the time span of the data series is relatively short, coverage rates for the PCSE estimator frequently fall between 80 and 90 percent. Further, we find many “practical research situations†where the PCSE estimator compares poorly with FGLS on efficiency grounds.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1032&context=jtse
Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by De Gruyter in its journal Journal of Time Series Econometrics.

Volume (Year): 2 (2010)
Issue (Month): 1 ()
Pages: 8

as in new window
Handle: RePEc:bpj:jtsmet:v:2:y:2010:i:1:n:8

Contact details of provider:
Web page: http://www.degruyter.com

Order Information:
Web: http://www.degruyter.com/view/j/jtse

Related research

Keywords: C23; C15; panel data; Monte Carlo analysis; FGLS; Parks; PCSE; finite sample;

Find related papers by JEL classification:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:bpj:jtsmet:v:2:y:2010:i:1:n:8

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla).

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.