atol=1e-3 doesn't work to distinguish normal from t distribution, given that they are 0.000

precision from tvalues is larger than the difference between normal and t distributions, I guess. 

It looks like, we need to use our own tvalues to check the distribution in this case
```
+        pvals = scipy.stats.t.sf(self.res1.tvalues.ix[idx] , self.res2.df_r) 
+        assert_allclose(np.ravel(self.res1.pvalues.ix[idx]), 
+                        pvals, rtol=1e-10???) 
```