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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 15:55:27 +0100 |

Christina, -xtivreg2- will do this. Or, since you have a small number of T and N fixed effects, you could add the FEs by hand. --Mark > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > christina sakali > Sent: 20 September 2011 15:48 > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: RE: xtscc and small samples (equal size T and N) > > Mark, > > thank you, this is clear now. > > In the older versions of Stata, het-robust SE were produced > with either - xtreg ..., fe robust- OR -xtreg ..., fe > vce(robust)- which both gived identical results. > > However, as far as I know these commands have changed in the > newer versions. Is it possible to obtain the standard > het-robust SE in the newer versions and how? > > > > On 20 September 2011 17:15, Schaffer, Mark E > <M.E.Schaffer@hw.ac.uk> wrote: > > Christina, > > > > The factor in front of bias term in eqn 5 is 1/(T-1). As T > gets bigger, this term gets smaller. For T=11, the bias term > is being multiplied by 1/10, i.e., by 0.1. > > > > -xtivreg2-, like -ivreg2-, can estimate straight OLS as > well as IV. The underlying logic is GMM. OLS, IV, FE, RE, > etc., are all GMM estimators. > > > > --Mark > > > >> -----Original Message----- > >> From: owner-statalist@hsphsun2.harvard.edu > >> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of > christina > >> sakali > >> Sent: 20 September 2011 15:03 > >> To: statalist@hsphsun2.harvard.edu > >> Subject: Re: st: RE: xtscc and small samples (equal size T and N) > >> > >> 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/ > >> > > > > > > -- > > 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/ > -- 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/

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

**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>

**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>

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

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