[R-sig-Geo] LM test for spatial dependence with panel data

Tobias Rüttenauer ruettenauer at sowi.uni-kl.de
Mon Feb 15 09:33:44 CET 2016

Dear Roger,

thanks for your answer!

> > Dear list members,
> >
> > I'm currently estimating a fixed effects panel model and I want to
> > control for spatial dependence. Thus, I also estimated two spatial
> > fe-models, one with a spatial error term and one with a spatial error
> > term and spatial lag variable. Both lambda and rho are highly
> > significant and the independent variables of the models differ
> considerably.
> >
> > However, I would like to control the model specifications with a
> > Lagrange Multiplier test. More precisely, I would like to test for
> > spatial lag dependence (while allowing possible spatial error
> > dependence) and for spatial error dependence (while allowing possible
> > spatial lag dependence) like described by Anselin/ Bera/ Florax/ Yoon
> > (1996), which is possible for cross-sectional data using lm.LMtests
> > (spdep). Is there a possibility to estimate a similar test for panel
> > data? If I'm not mistaking, the splm-implemented tests do not account
> spatial lag dependence?
> >
> You may be able to test the pooled model only using lm() on the data and
> taking a Kronecker product of your spatial weights by a time-dimensioned
> identity matrix, and using the function for cross-sectional models, but I
> that this is not what you want. 

I mean, one could argue that a cross-sectional spatial dependence also leads
to spatially correlated variations over time, but this is not necessarily
the case. So you are right, it would be the best to implement an appropriate
test (if feasible).

> You'd need to identify an appropriate test in
> the literature, and see whether it can be implemented (and whether then it
> actually works). In many cases, significant lag and error processes
> are related to missing variables, and to spatial processes not matching
> spatial units - aggregates - you are using.

You mean the error-correlation is a result of one or more omitted variables
that operate independently from the spatial relationship I modeled in the
spatial weights matrix? Then, it may be an idea to compare different
distance/neighborhood measures? Or do you mean it is a problem of the
aggregates itself (like too large spatial units)? 

Thanks again,

> Hope this helps,
> Roger
> > Thank you very much in advance for your help!
> >
> > Best,
> > Tobi
> >
> > _______________________________________________
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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; fax +47 55 95 91 00
> e-mail: Roger.Bivand at nhh.no
> http://orcid.org/0000-0003-2392-6140
> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
> http://depsy.org/person/434412

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