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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 15:15:32 +0100 |

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/

**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>

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