Dear All,
I a estimating the following model:
Y= aX + bY1 + cY2 + u
I am using standard errors robust and clustered at the neighborhood level;
X = vector of eogenous regressors
Y1, Y2 are endogenous
Z1 Z2 excluded instruments
I want to test weather my IVs are non-weak. I know that in the case of a single endogenous variable I should use the "rule of thumb" that the first stage F-statistic >10 (Steiger and Stock 1997).
But Stock and Yogo (2002) say to use the Cragg -Donald Statistics in presence of multiple endogenous regressors. I know this statistics is not valid under heteroskedasticity. I would like to know if there is a way to compute a robust analog of the Cragg-Donal statistics in Stata and in case if it would still be valid to compare it to the tabulated values of Stock and Yogo(2002). Alternatively, would be wrong to simply refer to the old "rule of tumb" that the F-statistics should be at least 10, even in presence of multiple endogenous variables?
Thank you for any help
Sara Borelli
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