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# Re: st: Biprobit and clustering standard errors

 From Stas Kolenikov To statalist@hsphsun2.harvard.edu Subject Re: st: Biprobit and clustering standard errors Date Wed, 7 Sep 2011 09:09:57 -0500

```Yes. You will have (at least) two issues.

1. Your variance-covariance matrix, -vce-, will not be of full rank.
Hence, you won't be able to estimate variances of certain combinations
of parameters (there is no telling which combinations will be affected
though).

2. If you have but few clusters, the assumptions of the asymptotic
behavior may not be satisfied. The standard errors will suffer from
small sample biases, and the test statistics (z-statistics or
likelihood ratios) will have distributions different from their
asymptotic targets (normal or chi-squared distributions,
respectively).

As a background, Stata (or any other statistical software) needs to
compute the likelihood scores, i.e., the derivatives of the likelihood
wrt to the parameters of the model. For variance estimation purposes,
you would need to have as many scores (represented by temporary
variables used in -robust- or -cluster- calculations) as you have
parameters. So this is not the number of variables, really, but the
number of parameters that matters.

On Wed, Sep 7, 2011 at 5:20 AM, Lina C <linacs81@gmail.com> wrote:
> Hello everybody.
>
> I'm running a biprobit clustering the standard errors as follows:
>
> biprobit ( y1 = y2 x ) ( y2 = z x), robust cluster(area)
>
> The "x" vector of regressors is much below the number of clusters
> (areas), however Stata cannot calculate the chi_2. What I have noticed
> is that STATA use the sum of the X in both equations as the total
> number of regressors, and in this way the "x" of the first probit and
> the "x" of the second probit sum up a number that is above the number
> of clusters. Once I reduced the X to be, the sum in the first probit
> and in the second probit, below the number of clusters, the chi2
> appears..
>
> The problem is that I need to use more regressors..Is there a problem
> if I rely on that estimation with the missing estimation of the chi2?
>
> Thank you.
> Lina.
> *
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>

--
Stas Kolenikov, also found at http://stas.kolenikov.name
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```