Error in lag.listw(listw2, u) : Variable contains non-finite values - panel spatial model using splm
On Mon, 10 Jun 2019, Marco Mello via R-sig-Geo wrote:
Dear community,
Please post plain text, not HTML, easier to copy and paste into an R session.
I am working on a panel spatial model in R using the package splm. In particular I am trying to estimate the following model spatpan<-spml(y ~ x, data = data_p, index = NULL, listw = W30, na.action = na.fail, lag = TRUE, spatial.error = "b", model = "within", effect = "twoways",zero.policy=TRUE) but I get the following error and warnings: Error in lag.listw(listw2, u) : Variable contains non-finite values In addition: Warning messages: 1: In lag.listw(listw, u) : NAs in lagged values 2: In lag.listw(listw, u) : NAs in lagged values 3: In lag.listw(listw2, u) : NAs in lagged values 4: In lag.listw(listw2, u) : NAs in lagged values
This is not a reproducible example. Such an example is needed unless you can run traceback() and debug() yourself to solve the problem, but since you have posted, I assume you prefer that someone else runs debug() - and someone will then need a reproducible example, preferably with an adapted standard dataset (add NAs to Produc?). I seem to recall that zero.policy= was not always passed through in some model fitting functions, possibly in splm. If so, set the option with spatialreg::set.ZeroPolicyOption(TRUE) and/or spdep::set.ZeroPolicyOption(TRUE) to avoid that issue if it is present and biting. Of course, had I had a reproducible example, I could have checked and given clearer advice.
Similarly, if I model the spatial correlation only for the error term, spatpan<-spml(y ~ x, data = data_p, index = NULL, listw = W30, na.action = na.fail, lag = FALSE, spatial.error = "b", model = "within", effect = "twoways",zero.policy=TRUE) I get the following warnings 1: In lag.listw(listw, u) : NAs in lagged values ... 3: In lag.listw(listw, TT) : NAs in lagged values ... 35: In optimize(sarpanelerror, interval = interval, maximum = TRUE, ... : NA/Inf replaced by maximum positive value ... In this case however the model turns out to be estimated, despite the standard errors are everywhere NAs and the spatial rho coefficient equal to 1 with weird t stats and p-values. An identical problem to mine was already signalled in this mailing list, unfortunately without receiving any suggestion : http://r-sig-geo.2731867.n2.nabble.com/problems-using-spml-with-a-listw-where-not-everybody-has-a-neighbour-td7587857.html.
Nabble is only an archive, the real link is: https://stat.ethz.ch/pipermail/r-sig-geo/2015-March/022428.html The posting also gave no reproducible example, so nobody had anything to work on. Hope this helps, Roger
I guess that the issue could be due to the n by n spatial weighting matrix W30, which contains some neighbourless observations. However this feature should be taken into account by the zero.policy option. Moreover the same framework perfectly works in the cross-sectional case, by using the function sacsarlm from the package spdep. Please, does anybody know what is causing this and how can I solve this issue? Any help would be really appreciated. Kind Regards, Marco Mello [[alternative HTML version deleted]]
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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.Bivand at nhh.no https://orcid.org/0000-0003-2392-6140 https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en