[R-sig-Geo] Trouble with Durbin Model

[adjemian]

Hey everyone, 

I'm puzzled about a recent result, and I'm wondering if
anyone can help explain it.  Essentially, I have a set of
data that is positively spatially autocorrelated (Moran's I
is highly significant).  According to LM tests on the OLS
residuals, I find that the spatial lag model is preferred. 
After estimating the lag specification with a group of
covariates, the spatial parameter is positive and
significant at the 1% level.  This indicates that the
spatial clustering in the dependent variable is robust to
the potential confounding influence of the covariates.

However, when I estimate the spatial Durbin specification by
including a set of distanced covariates, the spatial
parameter is still significant, but with the *opposite*
sign.  Something that may be of interest: the errors of the
lag model are not spatially autocorrelated; while the errors
of the Durbin model are.

I wonder why the sign of spatial influence flips.  Has
anybody faced a similar situation?  How should I select the
proper model?

Software used: Geoda, R.

Thanks! 
Mike