How to test spatial dependence in errorsarlm

So testing for spatial dependence on the residuals by means of the
lm.LMtests (option LMerr, the only that works with residuals) is wrong,
isn't it? I had read in some forum that this was a posible way to test it...

In my case the Moran test and the LM tests (both LMerr and LMlag, and also
their robust versions) are strongly rejected (p-values between 4.307e-06
and 2.2e-16). As the rejection is stronger for the spatial error model, my
suspicion was that this could be the best model to capture the spatial
dependence (in fact the log-likelihood is bigger for the spatial error
model, and the AIC lower). However, how can I know whether the spatial error
model is a good option if I cannot test the absence of spatial dependence in
the residuals? And how can I know, as you suspect, whether I have a
misspecification problem? Moreover, I also estimated the Durbin model, and
in this case the LM test on the residuals suggests no spatial dependence
(for the spatial lag model I get the opposite conclusion), but due to the
nature of my regression I don't think that this model is suitable (the
regressors are characteristics of houses such as size, number of rooms,
etc).

Thanks a lot for your time.
Best
Javi     

-----Mensaje original-----
De: Roger Bivand [mailto:Roger.Bivand at nhh.no] 
Enviado el: domingo, 13 de agosto de 2017 12:45
Para: Javier Garc?a
CC: r-sig-geo at r-project.org
Asunto: Re: [R-sig-Geo] How to test spatial dependence in errorsarlm

Hello everybody:



I have estimated a spatial error model and now I would like to test 
whether that model has really ?deleted? the spatial dependence. For 
the spatial lag model and for the Durbin model the function lagsarlm 
gives the LM test for residual autocorrelation test value, but the

function errorsarlm does not.

Does anyone know how to do it in R?

As you should be aware from the literature, the only LM test that has been
written (the maths) is a test for residual error autocorrelation for spatial
lag models. Doing it in R will not help until someone (you?) does the maths.
Computing a value is easy, but knowing what to infer from it is hard. By
definition, if your model is well-specified, the residual autocorrelation is
fully captured by its coefficient. I suspect that your model suffers from
mis-specification problems.

Roger

Thanks a lot in advance.



Javi






JAVIER GARC?A



Departamento de Econom?a Aplicada III (Econometr?a y Estad?stica)

Facultad de Econom?a y Empresa (Secci?n Sarriko)
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Roger Bivand
Department of Economics, Norwegian School of Economics,
Helleveien 30, N-5045 Bergen, Norway.
voice: +47 55 95 93 55; e-mail: Roger.Bivand at nhh.no
Editor-in-Chief of The R Journal, https://journal.r-project.org/index.html
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