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Re: st: xttobit and xtprobit missing standard errors

From   "Alejandro Lopez-Feldman" <>
To   <>
Subject   Re: st: xttobit and xtprobit missing standard errors
Date   Fri, 19 Nov 2004 11:00:34 -0800


Thanks for the help. I used superxt and it worked out well.
I just have a quick question. Convergence wasn't achieved with the default
options for superxt so I tried type(2) but it didn't work so I changed rho
from the default of .5 to the value that I was getting from the xttobit
(rho=.01), that is convergence was achieved with type(2) rho(.01).  The
weird thing (at least to me) is that after convergence the result of rho was
.57. My question is why I didn't achieve convergence using type(2) and the
default rho that is close to the "true" value?


----- Original Message ----- 
From: "Guillaume Frechette" <>
To: <>
Sent: Friday, November 19, 2004 6:28 AM
Subject: RE: st: xttobit and xtprobit missing standard errors

> You could try superxt ( or
> just try different starting values or different number of quadrature
> g
> >From: "Alejandro Lopez-Feldman" <>
> >Reply-To:
> >To:
> >Subject: st: xttobit and xtprobit missing standard errors
> >Date: Wed, 17 Nov 2004 16:33:58 -0800 (PST)
> >
> >Hi Stata users,
> >
> >I am using xtprobit and xttobit to estimate a couple of models with
> >effects but there seems to be a problem with my results.  When I run the
> >xtprobit command everything seems to be fine (no warning messages,
> >convergence achieved after 5 iterations and many significant
> >but no standard errors are estimated for lnsig2u and therefore none s.e.
> >for sigma and rho, although the likelihood ratio test for rho= appears
> >(Prob >= chibar2 = 0.029) . I have a similar problem when I run xttobit,
> >get s.e for sigma_e but not for sigma_u and therefore none for rho.
> >
> >It seems to me that stata is trying to tell me that there is something
> >wrong with my results but I don't know how bad the problem is. Are my
> >estimates valid at all? Are the s.e for the coefficients meaningfull? Is
> >there a way to get around this problem? I am interested in getting s.e
> >rho in both cases because in both cases I want to test the hypothesis
> >the panel estimator isn't different from the pooled estimator.
> >
> >Thanks,
> >Alejandro
> >*
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