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st: RE: xtivreg2 weak-instrument-robust inference
From
"Schaffer, Mark E" <[email protected]>
To
<[email protected]>
Subject
st: RE: xtivreg2 weak-instrument-robust inference
Date
Tue, 13 Jul 2010 16:12:00 +0100
Camden,
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On Behalf Of
> Camden Roberts
> Sent: 13 July 2010 00:49
> To: [email protected]
> Subject: st: xtivreg2 weak-instrument-robust inference
>
> Hello all,
>
> I am attempting to use the xtivreg2 command and have a
> question about the weak-instrument-robust inference
> statistics. In particular, when I estimate the model I
> receive the following missing statistics:
>
> Weak-instrument-robust inference
> Tests of joint significance of endogenous regressors B1 in
> main equation
> Ho: B1=0 and overidentifying restrictions are valid
> Anderson-Rubin Wald test F(0,159)= . P-val= .
> Anderson-Rubin Wald test Chi-sq(0)=. P-val= .
> Stock-Wright LM S statistic Chi-sq(0)=186.00 P-val= .
>
> With the exception of these missing statistics, the other
> tests for identification seem to suggest that the model is
> identified. The output for these tests is below:
>
> --------------------------------------------------------------
> ----------------
> Partial R-squared of excluded instruments: 0.4127
> Test of excluded instruments:
> F( 10, 160) = 11.24
> Prob > F = 0.0000
>
> Summary results for first-stage regressions
> -------------------------------------------
>
> Variable | Shea Partial R2 | Partial R2 | F( 10,
> 160) P-value
> lntotlimclas| 0.4127 | 0.4127 | 11.24
> 0.0000
>
> Underidentification tests
> Ho: matrix of reduced form coefficients has rank=K1-1
> (underidentified)
> Ha: matrix has rank=K1 (identified)
> Anderson canon. corr. N*CCEV LM statistic Chi-sq(10)=76.75
> P-val=0.0000
> Cragg-Donald N*CDEV Wald statistic Chi-sq(10)=130.68
> P-val=0.0000
>
> Weak identification test
> Ho: equation is weakly identified
> Cragg-Donald Wald F-statistic 11.24
> See main output for Cragg-Donald weak id test critical values
>
> Underidentification test (Anderson canon. corr. LM
> statistic): 76.755
> Chi-sq(10)
> P-val = 0.0000
>
> If anyone has an idea of why I may be having this problem, I
> would greatly appreciate any assistance you could provide.
You haven't given us the regression output, but my guess would be that
you are using the cluster-robust covariance estimator, and that have as
many or more excluded instruments than you have clusters (or panel
units).
The artificial regression used for weak-ID-robust inference involves
testing all the excluded instruments. If you have more excluded
instruments than clusters, you will run into problems because the
cluster-robust vcv won't be full rank. In that case, the maximum number
of constraints you can test will be the number of clusters (minus 1, I
think), which isn't enough.
But this is just a guess!
--Mark
> Thank you all,
>
>
> Camden Roberts
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