Thanks All. I had looked at Stock and Yogo, but I cannot really get
the intuition of the Cragg-Donald test.
Austin, hope I can ask for a clarification. If the third endogenous
variable is not pushed around by Z, then wouldn't the simple F-test
(excluded instruments) be very small? It seems this would tell me
already that I have a weak identification problem. What I cannot see
is what is the additional piece of information that I can gather from
the Cragg-Donald test.
Erasmo
On Mon, Sep 28, 2009 at 5:52 PM, Austin Nichols <[email protected]> wrote:
> Erasmo Giambona <[email protected]>:
> This is discussed by Stock and Yogo (reference given in the help file
> for -ivreg2- on SSC), among others. Basically, the matrix version of
> the first-stage F-test gives the smallest effect of the various
> directions in which the endog X vars are pushed around by excluded
> instruments Z. If two out of three endog X variables are strongly
> pushed around by Z, but one is hardly affected at all, you still have
> a weak instruments problem--and all of this is conditional on whatever
> other covariates are in the model, of course.
>
> On Mon, Sep 28, 2009 at 11:12 AM, Erasmo Giambona <[email protected]> wrote:
>> Dear Statalist,
>>
>> I am estimating a model with multiple endogenous variables using panel
>> data. I understand that one cannot use the F-test of excluded
>> instruments in the case of multiple endogenous variables to test for
>> weak identification. I understand that one should use instead the
>> Cragg-Donals F-statistic. What is the intuition of this test? Suppose
>> we have two endogenous variable (X and Y). Is the Cragg-Donals a
>> joint test of the null hypothesis that we have at least one good
>> instrument for X and one good instrument for Y?
>>
>> Any comments and recommendation for readings would be appreciated?
>
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