[R-sig-Geo] Common Factors test in R

[Hulényi Martin]

Hello,
I would like to perform a common factor test, conducted using likelihood ratio test on spatial error model and spatial durbin model (both in panel format).
I have not found a command in R, that would help me to conduct the test. Hence, I am trying to perform the test manuallly using the splm package and data available in the splm and plm packages.
Here is my code:
library(splm)
library(plm)

data(Produc, package="plm")
data(usaww)

Produc <- pdata.frame(Produc, index = c("state", "year"))

usaww<- mat2listw(usaww, style="W")

Produc$slagUnemp <- slag(Produc$unemp, listw = usaww)

durbin <- spml(gsp~unemp + slagUnemp,
                data=Produc, listw=usaww,  effect = "twoways", model="within", lag=TRUE, spatial.error = "none", quiet = FALSE)
spem  <- spml(gsp ~ unemp,
                data=Produc, listw=usaww,  effect = "twoways", model="within", lag=FALSE, spatial.error = "b", quiet = FALSE)
Is it correct to take the last value of the function from the console output to compute the likelihood ratio?
Meaning, in this example, to calculate 2*(function(non-nested) - function(nested)) = 2*(10261.79 - 10255.74) = 12.1?
If it is correct, how can I compute the significance values?
If it is not correct, is there a better way to compute this?

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