spgm

Thank you very much !
I have one more question regarding the output. I have also one endogenous variable in the model.  Your code worked, but it did not show me the indirect and direct effects for the
endogenous varibale. Here is my regex:
spd_01 <- spgm(gdppcgr~lefpayr+lpopgr+linvr+lagwgipca + laglgdppc,
             data=esifpdata, listw=dm1.lw,
             model="within", lag=TRUE, spatial.error= FALSE, endog = ~ lefpayr,
             instruments=~areaprop,
             method="w2sls")
matrix1 <- kronecker(diag(length(unique(esifpdata$years))), dm1)
listw1 <- mat2listw(matrix1, style="W")
tr <- trW(as(listw1, "CsparseMatrix"), m=100)
impacts(spd_01, listw=listw1)
impacts(spd_01, tr=tr)
summary(impacts(spd_01, tr=tr, R=1000), zstats=TRUE, short=TRUE)

Best,

MArtin Hul?nyi


________________________________________
Od: Roger Bivand <Roger.Bivand at nhh.no>
Odoslan?: 29. septembra 2018 14:52
Komu: Hul?nyi Martin
K?pia: r-sig-geo at r-project.org
Predmet: Re: [R-sig-Geo] spgm

Dear all,


I would like to ask if there is a possibility to apply something
similiar to the "impacts" from spdep package for SAR regressions using
the spgm function from the splm package.

A reprex would have helped. Here is mine:

data(Produc, package = "plm")
data(usaww) # dense row-standardised weights matrix
GM <- spgm(log(gsp)~log(pcap)+log(pc)+log(emp)+unemp, data=Produc,
   listw = usaww, moments="fullweights", lag=TRUE, spatial.error = FALSE)
class(GM)
?impacts.stsls # spdep method for stsls objects
head(Produc)
length(unique(Produc$year)) # T
big <- kronecker(diag(length(unique(Produc$year))), usaww)
listw <- mat2listw(big, style="W")
tr <- trW(as(listw, "CsparseMatrix"), m=100)
impacts(GM, listw=listw)
impacts(GM, tr=tr)
summary(impacts(GM, tr=tr, R=1000), zstats=TRUE, short=TRUE)

The splm:::impacts.splm() method cannot dispatch on stsls objects, so they
try to use the spdep:::impacts.stsls() method, but there the data rows are
n x T but listw is only of n rows. Looking inside splm:::impacts.splm(),
you see that a sparse kronecker product matrix is constructed - either do
the same if your n x T is large, or follow the above using a dense
kronecker product and cast back to listw representation to create the
trace vector.

Hope this clarifies,

Roger

Best regards,


Martin Hul???nyi ?


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Roger Bivand
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