Nirina F <[email protected]>:
The IV estimate is always biased, but is less biased than OLS to the
extent that identification is strong; in the limit of weak
instruments, there would be no improvement over OLS in terms of bias
and the bias would be 100% of OLS, and in the other limit, the bias
would be zero percent. Clearly, you'd like to know where you are on
that spectrum, even if only approximately. There is also a problem
with the size of tests after IV--you think you are rejecting a
hypothesis using a 5% alpha, but it is really 10% or 20%. Stock and
Yogo did simulations to provide "rule of thumb" critical values (or
rule of thumb "critical values" perhaps). Table 1 on page 39 of Stock
and Yogo (http://ksghome.harvard.edu/~jstock/pdf/rfa_6.pdf) shows the
value of the SY stat (a measure of the "strength of identification" or
the predictive power of the excluded instruments) to limit the bias to
20% of OLS for two endogenous variables and three excluded instruments
(n=2, K2=5) is 5.91 (similar values are given to limit the size of
Wald tests in table 2, and stats for LIML estimates in tables 3 and
4).
It's not clear what you don't understand from the Stock and Yogo
paper, so it's hard to comment directly. If you gave your n and K2
values and the SY stat from the output of -ivreg2- I suppose one could
describe directly the situation in which you find yourself.
But the key point is that all IV and IV-type specifications suffer
from bias and size distortions, not to mention inefficiency and
sometimes failures of exclusion restrictions. The SY stat gives you
some measure of how strong your identification is in your sample, but
no information about the validity of your instruments. Hope you also
read BSS2007:
http://econpapers.repec.org/paper/bocbocoec/667.htm
and I expect -ranktest- will generate a new set of papers eventually
(-ssc install ranktest- and -help ranktest- for more).
On 9/25/07, Nirina F <[email protected]> wrote:
> Dear all,
>
> Yes, I read
> Stock, J.H. and Yogo, M. 2005. " Testing for Weak Instruments in
> Linear IV Regression"
>
> but I still don't understand how do I interpret the critical values of
> the Stock&Yogo- maximal IV size when using ivreg2.
>
> I think I compare the critical values from x%maximal IV relative bias
> with the Cragg-Donald stat to test for weak instruments but the
> critical values for the size with what and what it means?
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