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RE: st: first stage results using ivregress with vce(cluster)


From   "Schaffer, Mark E" <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: first stage results using ivregress with vce(cluster)
Date   Thu, 13 Mar 2014 11:40:58 +0000

Souvik, Suryadipta,

> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of Suryadipta Roy
> Sent: 13 March 2014 10:57
> To: [email protected]
> Subject: Re: st: first stage results using ivregress with vce(cluster)
> 
> Souvik,
> The other option (probably the preferred one to me) is to use - ivreg2
> - which comes with a wide array of tests on instrumental validity,
> i.e. testing for weak instruments as well as overidentification. Try -
> help ivreg2 - and the command that is most pertinent to your query is
> -condivreg- .

Actually, if Souvik is going to go down the weak-identification-robust route, -weakiv- rather than -condivreg- is more useful for Souvik's problem.  -weakiv- supports non-iid VCE options such as cluster-robust, unlike -condivreg-.

--Mark

> 
> Best wishes,
> Suryadipta.
> 
> On Wed, Mar 12, 2014 at 8:49 AM, Souvik Banerjee
> <[email protected]> wrote:
> > Yes, by relevance I meant testing for weak instruments. I will try it
> > out. Thanks.
> >
> > Best,
> > Souvik
> >
> > On Wed, Mar 12, 2014 at 8:40 AM, Alfonso Sanchez-Penalver
> > <[email protected]> wrote:
> >> If by relevance of the instruments you mean that they are not weak, which is
> what I think you mean, that is what is tested with -estat firststage- which takes
> into consideration the clustering in the vce. To try it out, do the 2SLS estimation
> with and without vce(cluster clusterid), and try the test right after each
> estimation. You ought to get different results.
> >>
> >> Best,
> >>
> >> Alfonso Sanchez-Penalver
> >>
> >>> On Mar 12, 2014, at 8:20 AM, Souvik Banerjee
> <[email protected]> wrote:
> >>>
> >>> Hi Alfonso,
> >>> I am following up on your response yesterday. Thanks for your help. I
> >>> am aware of the formal tests for endogeneity and instrument validity.
> >>> I was actually referring to the test for relevance of the
> >>> instrument(s), which to my knowledge is just based on the first stage
> >>> results.
> >>>
> >>> Thanks again.
> >>>
> >>> Best,
> >>> Souvik
> >>>
> >>> On Tue, Mar 11, 2014 at 11:03 AM, Alfonso Sánchez-Peñalver
> >>> <[email protected]> wrote:
> >>>> Hi again Souvik,
> >>>>
> >>>> to test for endogeneity and the validity of the instruments more formal
> tests are preferred than just inferencing on the results from the first stage. See
> -help ivregress_postestimation-. Both -estat endogenous- and -estat overid-
> provide Wooldridge's (1995) robust score tests. Also -estat firststage- accounts
> for the robustness of the VCE if I'm not wrong.
> >>>>
> >>>> Wooldridge, J. M. 1995.  Score diagnostics for linear models estimated by
> two stage least squares.  In Advances in Econometrics and Quantitative
> Economics: Essays in Honor of Professor C. R. Rao, ed. G. S. Maddala, P. C. B.
> Phillips, and T. N. Srinivasan, 66-87.  Oxford: Blackwell.
> >>>>
> >>>> Best,
> >>>>
> >>>> Alfonso Sánchez-Peñalver, PhD
> >>>>
> >>>>
> >>>>> On Mar 11, 2014, at 10:13 AM, Souvik Banerjee
> <[email protected]> wrote:
> >>>>>
> >>>>> Hi Alfonso,
> >>>>> Thanks for the response. I agree that  -ivregress 2SLS- is probably
> >>>>> applying the clustering in the second stage only. I, however, feel the
> >>>>> standard errors should be clustered in the first stage as well because
> >>>>> one would need the "correct" standard errors from the first stage
> >>>>> regression to test for the relevalence of the instrumental variable
> >>>>> (z) (which I need to test).
> >>>>>
> >>>>> I apologize for the confusion with the clustering syntax - it is a
> >>>>> typo. The correct code should be:
> >>>>>
> >>>>> ivregress 2sls y x (x1 = z), first vce(cluster x2)
> >>>>> and then manually run:
> >>>>> regress x1 x z, cluster vce(cluster x2)
> >>>>>
> >>>>> Thanks again.
> >>>>>
> >>>>> Best,
> >>>>> Souvik
> >>>>>
> >>>>> On Tue, Mar 11, 2014 at 9:50 AM, Alfonso Sanchez-Penalver
> >>>>> <[email protected]> wrote:
> >>>>>> Hi Souvik,
> >>>>>>
> >>>>>> What you're saying is normal. The first stage regression(s) is only useful
> to predict the values of the endogenous variable(s) so that they can be used in
> the second stage, so for 2SLS estimation purposes the standard errors of the
> first stage are not that important. Therefore my understanding is that -
> ivregress 2SLS- only applies the clustering for the standard errors in the second
> stage, not the first.
> >>>>>>
> >>>>>> Having said that, I'm confused with your syntax. You say that you use -
> vce(cluster clustervariable)- but I don't see this option in your clarifying
> example but rather -cluster(x2)-.
> >>>>>>
> >>>>>> Best,
> >>>>>>
> >>>>>> Alfonso Sanchez-Penalver
> >>>>>>
> >>>>>>> On Mar 11, 2014, at 9:09 AM, Souvik Banerjee
> <[email protected]> wrote:
> >>>>>>>
> >>>>>>> Dear Stata users,
> >>>>>>> I have a question about verifying the first stage regression results
> >>>>>>> obtained using the "first" option with "ivregress 2sls" with those
> >>>>>>> obtained by manually running the first stage regression (using
> >>>>>>> "regress") of the endogenous variable on the IV and other covariates
> >>>>>>> when I use the "vce(cluster clustervariable)" option to allow for
> >>>>>>> clustering. The coefficients are the same in both cases, however the
> >>>>>>> standard errors are different - which should not be the case. Does
> >>>>>>> anyone have any idea why this might happen? However, if I do not
> allow
> >>>>>>> for clustering, the standard errors are the same in both cases - which
> >>>>>>> is correct.
> >>>>>>>
> >>>>>>> To clarify, I run:
> >>>>>>> ivregress 2sls y x (x1 = z), first (cluster x2)
> >>>>>>> and then manually run:
> >>>>>>> regress x1 x z, cluster (x2)
> >>>>>>>
> >>>>>>> Here, y is binary variable, x is vector of covariates (x1, x2, ...
> >>>>>>> xk), x1 is the endogenous variable (binary) and z the instrumental
> >>>>>>> variable.
> >>>>>>>
> >>>>>>> Thanks,
> >>>>>>>
> >>>>>>> Souvik
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