Spatial Hausman Test for Maximum Likelihood estimated models

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----- Original Message -----
From: "Rafael Terra" <rflterra at yahoo.com.br>
To: r-sig-geo at r-project.org
Sent: Thursday, September 15, 2011 3:00:43 PM
Subject: [R-sig-Geo] Spatial Hausman Test for Maximum Likelihood estimated	models

Dear R users,

I have a Panel data and I've just estimated spatial fixed and random
effects models by Maximum likelihood using splm library. Having the
estimates for both models,? now I must decide which one is better.
I've looked around and I found a Spatial Hausman Test implemented
under the name of sphtest in R. But I'm not sure you can use? it for
Maximum likelihood estimated models. Does anyone knows hoe to
perform this test for ML estimated models? I tried
I am not familiar with the splm library but think if you are attempting to "decide which one is better" then AIC would be the metric of choice

The spatial Hausman test is used to determine if there is significant differences between coefficients from the two models, not necessarily which model is 'best'
sarre10307<- spml(formula=basic, data=panel0307,
index=c("GEOCODIG_M","ano"), listw=nlist0307, model ="random",?
effect =c("individual"),? lag=TRUE, method="eigen",
spatial.error="none")
sarfe10307<- spml(formula=basic, data=panel0307,
index=c("GEOCODIG_M","ano"), listw=nlist0307, model ="within",?
effect =c("individual"),? lag=TRUE, method="eigen",
spatial.error="none")

and then
test2<-sphtest(sarre10307, sarfe10307)
Error in if (x$ef.sph == x2$ef.sph) stop("Effects should be
different") :
? argument is of length zero

My dataset is reasonably large, so I apologize for not making the
data available so you can reproduce the problem. If? necessary I can
reduce my dataset and post it.

Thank you so much!
Rafael Terra
PhD Candidate in Economics - Sao Paulo School of Economics
Sao Paulo, Brazil
email: rflterra at yahoo.com.br

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