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Re: st: Petersen (2009) vs Thompson (2011) - Estimating standard errors in panel data sets
From
"Julia Ke" <[email protected]>
To
[email protected], [email protected]
Subject
Re: st: Petersen (2009) vs Thompson (2011) - Estimating standard errors in panel data sets
Date
Tue, 04 Dec 2012 21:59:05 +0100
Dear Roger,
The papers Thomas mentioned are the ones I was referring to. Thanks for sending this, Thomas.
Kind regards,
and many thanks,
Julia
-------- Original-Nachricht --------
> Datum: Tue, 4 Dec 2012 21:33:20 +0100
> Von: thomas bourveau <[email protected]>
> An: [email protected]
> Betreff: Re: st: Petersen (2009) vs Thompson (2011) - Estimating standard errors in panel data sets
> Dear Roger,
>
> I have a similar question on my current project, so I get your point
> and here are the full references of the abovementioned paper :
>
> - Petersen, M. A. (2009) "Estimating standard errors in finance panel
> data sets: Comparing approaches" Review of Financial Studies, vol. 22
> pp. 435-480.
>
> - Thompson, S. B. (2011) "Simple formulas for standard errors that
> cluster by both firm and time" Journal of Financial Economics, vol. 99
> pp. 1-10.
>
> 2012/12/4 Roger B. Newson <[email protected]>:
> > It is probably a good idea here to give the references in full, ie with
> the
> > journal title, volume and pages. Otherwise, very few of us will know
> which
> > paper you are referring to.
> >
> > Best wishes
> >
> > Roger
> >
> > Roger B Newson BSc MSc DPhil
> > Lecturer in Medical Statistics
> > Respiratory Epidemiology and Public Health Group
> > National Heart and Lung Institute
> > Imperial College London
> > Royal Brompton Campus
> > Room 33, Emmanuel Kaye Building
> > 1B Manresa Road
> > London SW3 6LR
> > UNITED KINGDOM
> > Tel: +44 (0)20 7352 8121 ext 3381
> > Fax: +44 (0)20 7351 8322
> > Email: [email protected]
> > Web page: http://www.imperial.ac.uk/nhli/r.newson/
> > Departmental Web page:
> >
> http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/
> >
> > Opinions expressed are those of the author, not of the institution.
> >
> >
> > On 04/12/2012 17:45, Julia Ke wrote:
> >>
> >> Dear Statalist,
> >>
> >> I am running a panel regression. It is a rather small sample with
> multiple
> >> firms and a few years.
> >>
> >> I was reading into which method to use, which came down to the
> following:
> >> If one dimension has far more units than the other, clustering on one
> >> dimension and using dummies on the other seems to be used (especially
> in
> >> smaller panels).
> >>
> >> My question concerns which unit to cluster and which one to use dummies
> >> on. The below two authors seem to state the opposite which is confusing
> me a
> >> bit...
> >>
> >> Petersen (2009): "Since most panel data sets have more firms than
> years,
> >> the most common approach is to include dummy variables each year (to
> absorb
> >> the time effect) and then cluster by firm."
> >> "When there are only a few clusters in one dimension, clustering by the
> >> more frequent cluster yields results that are almost identical to
> clustering
> >> by both firm and time."
> >>
> >> Thompson (2011): If there are far more firms than time periods,
> clustering
> >> by time eliminates most of the bias unless within-firm correlations are
> much
> >> larger than within-time period correlations.
> >>
> >> Many thanks in advance,
> >> Julia
> >>
> >>
> >>
> >> Papers mentioned:
> >> Petersen (2009), "Estimating Standard Errors in Finance Panel Data
> Sets"
> >> Thompson (2011), "Simple Formulas for Standard Errors that Cluster by
> Both
> >> Firm and Time"
> >> *
> >> * For searches and help try:
> >> * http://www.stata.com/help.cgi?search
> >> * http://www.stata.com/support/faqs/resources/statalist-faq/
> >> * http://www.ats.ucla.edu/stat/stata/
> >>
> > *
> > * For searches and help try:
> > * http://www.stata.com/help.cgi?search
> > * http://www.stata.com/support/faqs/resources/statalist-faq/
> > * http://www.ats.ucla.edu/stat/stata/
>
>
>
> --
> Thomas Bourveau
> [email protected]
> 0637573925
> *
> * For searches and help try:
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*
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