On Thu, 11 Jul 2019, Amitha Puranik wrote:
Hi Prof. Roger,
I am using the approach proposed by Prof Paul Erhorst for choosing a
spatial model in his paper '*Applied spatial econometrics: raising the
bar*' . As per the strategy, one has to check the likelihood ratio test
for theta (spatial autocorrelation in exogenous (independent) variables)
and also in theta+rho*beta (spatial autocorrelation in residuals).
Suppose I fit a spatial durbin model and use the code LR1.sarlm(sp.dm),
how would I know whether the likelihood ratio test checks for
autocorrelation in dependent variable or autocorrelation in the
independent variable?
The spatialreg::LR1.sarlm() test simply between the fitted model and the
same model assuming the spatial coefficients are zero, so it only tests
the possible benefit of including (a) spatial process(es).
spatialreg::LR.sarlm() lets you test between nested models, and works like
lmtest::lrtest(). The models need to be nested, so you can test SDM/SLM,
SDM/SEM (equivalent to a Common Factor test), and so on, but only if the
models nest (not SEM/SLM, because they do not nest).
Hope this helps,
Roger
Thanks in advance.
Amitha Puranik.
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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.biv...@nhh.no
https://orcid.org/0000-0003-2392-6140
https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
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