Austin,
thank you very much for your help,
Sara
--- Dom 6/7/08, Austin Nichols <[email protected]> ha scritto:
> Da: Austin Nichols <[email protected]>
> Oggetto: Re: st: cluster and F test
> A: [email protected]
> Data: Domenica 6 luglio 2008, 16:05
> sara borelli <[email protected]> :
> An individual SE may be OK, in the sense that a test
> involving only
> one coef may have approximately the right size, but e(V)
> has rank M-1
> and so the upper limit on the number of coefs that can
> included in one
> joint test is M-1. The reported SEs ignore the cov between
> the 37
> estimates; they offer a test of one coef each, ignoring the
> fact that
> you can't actually test all 37, or even 14, jointly.
> But in this
> case, a test of even one coef is suspect, because you have
> M-1=13
> which is a very small number to consider close to infinity.
> 50
> clusters, or at the very least 20 large balanced clusters,
> are needed
> to be reasonably sure the size distortion is not too large.
> In
> general, it probably seems like a bad idea to include more
> variables
> than you have effective df, though for the CRSE, Stata will
> let you do
> it, for various reasons. For example, if you had 50
> clusters, 50
> fixed effects for cluster and 120 fixed effects for time,
> you could
> include these 170 effects as 168 dummy variables along with
> one
> explanatory variable of interest. You can never test the
> joint sig of
> the cluster FE nor the joint sig of the time FE, and you
> will (one
> hopes) not be testing smaller groups of these FE either, so
> the only
> test you plan to do in this case is on the one explanatory
> variable of
> interest, with 49 df. In this case, you should be fine.
> Note the
> relevant number is M-k, number of clusters less number of
> constraints.
>
> --Austin
>
> On Sun, Jul 6, 2008 at 5:14 AM, sara borelli
> <[email protected]> wrote:
> > Hi [Austin],
> > thank you very much for your help.
> >
> > When I test (with the F-test) 18 restrictions with 14
> clusters stata drops the 5 constraints because, as you
> said, it can test only 13 constraints.
> > There is something I do not understand, however. With
> the cluster option the number of observations useful to
> estimate the standard errors becomes the number of
> clusters, 14. Thus, if I have 37 standard errors to
> estimate and only 14 clusters, how is that possible that
> stata is able to estimate all the standar errors, but still
> test only 13 constraints?
> > Basically, when the number of clusters is smaller than
> the number of regressors, is only the F-test computed in a
> wrong way or also the standar errors?
> > I am sorry to keep usking about this, but I ma a bit
> confused
> > Thank you
> > Sara
> >
> > --- Sab 5/7/08, Austin Nichols
> <[email protected]> ha scritto:
> >
> >> Da: Austin Nichols <[email protected]>
> >> Oggetto: Re: st: cluster and F test
> >> A: [email protected]
> >> Data: Sabato 5 luglio 2008, 19:01
> >> sara borelli <[email protected]>:
> >> The cluster-robust standard error (CRSE) estimator
> has at
> >> most M-1 df
> >> with M clusters, so with 14 clusters you can test
> the joint
> >> sig. of at
> >> most 13 coefs. But the performance of the
> estimator gets
> >> worse as you
> >> increase the the number of constraints. The
> CRSE's
> >> performance
> >> improves as M-k increases toward infinity, where M
> is the
> >> number of
> >> clusters and k the number of constraints you are
> testing,
> >> and for M-k
> >> at least 20 and clusters balanced you should
> expect good
> >> performance.
> >> Since you have M-k equal to one (the minimum
> possible
> >> value), you
> >> should expect that the estimated variance is too
> low and
> >> the F stat is
> >> too high, on average. Note that clusters are like
> >> super-observations,
> >> for the purposes of the SE of estimated coefs, so
> a
> >> regression on 37
> >> variables with 14 clusters is a bit like a
> regression on 37
> >> vars with
> >> 14 obs--you really don't want to test more
> than one
> >> coef there, and
> >> maybe not even that many. How are your clusters
> defined?
> >> Is there
> >> any possibility of adding more clusters, or
> redefining them
> >> sensibly
> >> so you have more clusters?
> >>
> >> On Fri, Jul 4, 2008 at 5:16 AM, sara borelli
> >> <[email protected]> wrote:
> >> > Dear Stata List members,
> >> >
> >> > I have found some related questions on FAQs,
> but I
> >> cannot fins exactly what I need.
> >> > I am running a regression with the cluster
> option. I
> >> have 37 independent variables (including the
> constant),
> >> 1647 observations, and 14 clusters.
> >> > I want to test the joint significance of 18
> variables.
> >> > If I do NOT use the cluster option the F is
> calculated
> >> correctly as F(18, 1637).
> >> > But once I introduce the cluster option I get
> the
> >> following result:
> >> > (1) x1= 0
> >> > (2) x2 = 0
> >> > (3) x3 = 0
> >> > (4) x3 = 0
> >> > ...
> >> > (18) x18 = 0
> >> > Constraint 1 dropped
> >> > Constraint 2 dropped
> >> > Constraint 3 dropped
> >> > Constraint 4 dropped
> >> > Constraint 14 dropped
> >> >
> >> > F( 13, 13) = 109.42
> >> > Prob > F = 0.0000
> >> >
> >> > I guess stata is doing something on the
> degree of
> >> freedoms, but I have not clear what is going on,
> why it is
> >> dropping the constraints. Is the final F test
> calculated
> >> correct?
> >> > Thank you in advance for any help
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