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From |
christina sakali <christina.sakali@googlemail.com> |

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Tue, 20 Sep 2011 17:02:41 +0300 |

Mark, this is very useful information. Can you please clarify what exactly you mean by "the bias is decreasing in T". To me this sounds like the bias is decreasing when T is decreasing, but then you say that T=11 may be large enough to justify using the standard het-robust VCV, so I am not sure I completely get what you mean. Also, xtivreg works with instrumental variables, will I be able to implement it with my data? On 20 September 2011 16:23, Schaffer, Mark E <M.E.Schaffer@hw.ac.uk> wrote: > 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/ > * * 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/

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

**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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