Dear Russell,
I was not talking about the OLS residuals' (which is indeed expected to behave
better than GLS when there are errors in variables – see the reference I cited
last time) but about the residuals of your GLS fit, since this is this one
which have apparently a suspect slope.
Note
Hi Russell,
Just a hint, but this type of bias (assuming there’s no formatting issues with
the data), often shows up when there’s considerable (non-random) errors in the
predictors (we talk about "error in variable models"). If you plot the
residuals against your predictor they will likely be
