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From |
"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: RE: xtscc and small samples (equal size T and N) |

Date |
Tue, 20 Sep 2011 14:45:01 +0100 |

Oops. I meant > Eicker-Huber-White-robust VCV is biased with small-T large-N Sorry about that! --Mark > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > Schaffer, Mark E > Sent: 20 September 2011 14:24 > To: statalist@hsphsun2.harvard.edu > Subject: RE: st: RE: xtscc and small samples (equal size T and N) > > Christina, > > With respect to your last point, you might actually be OK here. > > Stock & Watson show that the standard > Eicker-Huber-White-robust VCV is biased with small-N large-T > panels. But if you check the paper (eqn 5), you'll see that > the bias term has a 1/(T-1) in front of it. In other words, > the bias is decreasing in T. In your case, T=11 may be > enough for you to justify using the standard het-robust VCV. > > There is an as-yet undocumented option in -xtivreg2-, sw, > that implements the Stock-Watson correction to the standard > het-robust VCV. (It's still not documented because I haven't > yet verified it against a published output or another > package.) If the sw option gives you SEs that are similar to > the standard het-robust SEs, you've got grounds to believe > that T is indeed large enough to justify using the latter. > > HTH, > Mark > > NB: If anyone can point me to an example of Stock-Watson SEs > that I can try to replicate, I'd be most grateful. > > References: > > Stock & Watson (2008), > http://www.princeton.edu/~mwatson/papers/ecta6489.pdf > > > -----Original Message----- > > From: owner-statalist@hsphsun2.harvard.edu > > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > christina > > sakali > > Sent: 20 September 2011 13:17 > > To: statalist@hsphsun2.harvard.edu > > Subject: Re: st: RE: xtscc and small samples (equal size T and N) > > > > Dear Gordon, thanks for the response. > > > > From your as well as Mark's suggestions, I get the idea > that perhaps > > the simple two way fixed effects model is the most > appropriate choice > > for my data, although I do understand than none of the options is > > ideal with such a small panel sample. > > > > In other, previous papers with similar sample sizes and > topic, I have > > seen that they usually either go for a simple one or two way fixed > > effects model or rely on simple robust SE such as White SE. > However I > > am aware that Stock and Watson > > (2008) showed that these are inconsistent, so this option is also > > ruled out for my data.. > > > > On 20 September 2011 13:29, Gordon Hughes > <G.A.Hughes@ed.ac.uk> wrote: > > > You will probably get almost as many views about what constitutes > > > large T and/or large N as the number of people you consult. The > > > answer is very dependent upon the type of data which you are > > > analysing, because panel data comes in many different > > forms. However, > > > as Mark says, no one would believe that 11 gets close. > > > > > > For -xtscc- you are dealing with large T asymptotics, so > > the reference > > > point would be time series asymptotics. If you have > annual data I > > > doubt whether anyone would rely on large T results for T > > much below 30 > > > and some might be much stricter. The problem, of course, > > is that many > > > panel datasets don't meet that criterion, in which case > you have to > > > start to think carefully about what you are trying to > > estimate. That > > > is the point which underlies Mark's original suggestion. Your > > > response indicates that you may be trying to get too much > > out of some rather noisy - or complex - data. > > > > > > Gordon Hughes > > > g.a.hughes@ed.ac.uk > > > > > > ===================================== > > > > > > Date: Tue, 20 Sep 2011 02:12:43 +0300 > > > From: christina sakali <christina.sakali@googlemail.com> > > > Subject: Re: st: RE: xtscc and small samples (equal size T and N) > > > > > > Dear Mark, thanks a lot for the advice and recommendations. > > > > > > I am a bit reluctant to go for just the simple 2-way > fixed effects > > > model, since after implementing the necessary tests, I have > > found that > > > my residuals suffer from both heteroscedasticity and > > cross-sectional > > > dependence, so I am looking for an estimator to account > for both of > > > these problems. > > > > > > Does the inclusion of time fixed effects correct for > > > heteroscedasticity and/or cross-sectional dependence and > > how exactly > > > is this achieved? (or can you suggest some reference where > > I can find > > > some more information on this issue). > > > > > > Can you also please clarify this for me: What is the > > minimum (more or > > > less) sample size required for the use of estimators that rely on > > > large T and N asymptotics? > > > > > > Thank you again. > > > > > > Christina > > > > > > > > > * > > > * For searches and help try: > > > * http://www.stata.com/help.cgi?search > > > * http://www.stata.com/support/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/statalist/faq > > * http://www.ats.ucla.edu/stat/stata/ > > > > > -- > Heriot-Watt University is a Scottish charity registered under > charity number SC000278. > > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > -- Heriot-Watt University is a Scottish charity registered under charity number SC000278. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: RE: xtscc and small samples (equal size T and N)***From:*Gordon Hughes <G.A.Hughes@ed.ac.uk>

**Re: st: RE: xtscc and small samples (equal size T and N)***From:*christina sakali <christina.sakali@googlemail.com>

**RE: st: RE: xtscc and small samples (equal size T and N)***From:*"Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>

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