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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 17:47:54 +0300 |

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/

**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>

**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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