Dear Austin,
Many thanks for this, and for the papers that are
really useful!
I have another question about ivreg2.
For endogeneity tests, after the ivreg2 regression
under iid (no robust command), when using the ivendog
command, I get two statistics for endogeneity tests:
the Wu-Hausman and the Durbin-Wu-Hausman.
If I want to control for heteroskedasticity (and
therefore add the robust option as well), the ivendog
command is not valid and instead I need to add the
option endog ( ), and this gives me the results for
one statistic only.
I've read that "the ivendog option unavailable in
ivreg2 is the Wu-Hausman F-test version of the
endogeneity test". Does this mean that the endog ( )
option provides me with the equivalent of the
Durbin-Wu-Hausman statistic but under non iid
disturbances?
Many thanks!
Alice.
>
> Austin Nichols <[email protected]> wrote:
> Alice--
>
> The Kleibergen-Paap statistic is indeed the
> generalization of the
> Cragg-Donald statistic. There is no table of
> critical values, but you
> can use the critical values for the Cragg-Donald
> statistic from Stock
> and Yogo until someone generates a newer version. A
> Cragg-Donald
> statistic of 100 is good news, assuming you have not
> generated
> instruments that have artificially high correlations
> with the
> endogenous variables. You can also do OverID tests
> if you construct
> new excluded instruments by taking products and
> squares of your
> existing excluded instruments, or products with
> exogenous variables.
> See these 3 working papers:
> http://fmwww.bc.edu/EC-P/WP545.pdf
> http://fmwww.bc.edu/EC-P/WP667.pdf
> http://pped.org/stata/ciwod.pdf
> for more.
>
> I am copying the Statalist, which I recommend you
> join, if you
> anticipate having more questions about -ivreg2- (Kit
> Baum and Mark
> Schaffer are regular contributors). You should be
> aware that all
> Statalist posts are available on the web, including
> originating email
> addresses, which can dramatically increase your
> volume of spam if you
> are unprotected. A free gmail.com address is a good
> solution to this
> problem.
>
> On Jan 9, 2008 2:09 PM, wrote:
> > Dear Austin,
> >
> > I wish to test for weak instruments using Stata
> and found a presentation of
> > yours on Stata's website, and thought I might
> email you to get some advice
> > from you. Basically I wish to estimate a
> regression of the type
> >
> > y = c + az + bx + e
> >
> > where z are two endogenous variables I need to
> instrument, and x is a set of
> > exogenous variables. My model is just identified
> as I only consider two
> > excluded instruments to instrument z.
> >
> > I just uploaded the new version of ivreg2 which
> contains much more
> > information than in the previous version, such as
> the Stock and Yogo
> > critical values for the Cragg-Donald statistic,
> which makes things simpler
> > as I was not sure whether I should use Table 1 or
> 2 in Stock and Yogo for my
> > critical values.
> >
> > From what I understand, if the Cragg-Donald
> statistic is larger than the
> > critical values, then I can reject the null
> hypothesis of weak instruments.
> > My calculated statistic is always huge, and
> depending on specifications it
> > is even larger than 100. Do you think this is
> plausible and makes sense?
> >
> > I also understand that this statistic, as well as
> the Stock and Yogo
> > critical values are valid only under
> homoskedasticity, i.e. when I do not
> > include the robust command. However, in my
> regressions I wanted to control
> > for heteroskedasticity by adding the robust
> command. In that case, ivreg2
> > instead reports the Kleibergen-Paap statistic. Is
> this the equivalent to the
> > Cragg-Donald statistic but under
> heteroskedasticity? I am asking this as I
> > would prefer to control for heteroskedasticity but
> the Cragg-Donald does not
> > allow me to do so.
> >
> > Apart from that I am also using the ivendog
> command to obtain the Wu-Hausman
> > and Durbin-Wu-Hausman statistics to test for
> endogeneity. I am not sure
> > whether I should also test for other things,
> especially as I am a bit
> > concerned by the huge value of the Cragg-Donald
> statistic I obtain.
> >
> > Many thanks for your suggestions!!!
> >
> > Best wishes,
> >
> > Alice.
>
>
>
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