[R] different dimensions in W and my data in moran and spatial model
Bert Gunter
bgunter@4567 @end|ng |rom gm@||@com
Thu Apr 15 00:42:02 CEST 2021
Almost certainly better posted on R-Sig-geo, not here.
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Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Apr 14, 2021 at 3:32 PM maria jesus herrerias <
mjherreriast using gmail.com> wrote:
> Hello everyone,
>
> I am writing my code in R to run the spatial models. I am learning this
> at the moment.
> I have my data for 116 countries over the period 1990-2014,
> and I got the shapefile from the website below.
> The objective is to get the matrix to run the spatial models.
> In the code below, I can get the matrix for the world and also for the
> subsample.
> But when I try to run the moran test or sar model I get an error.
> The error is related to the dimension of W (listw) and my dataset. So
> any help,
> I would be grateful.
>
> Below my code just in case someone can help here.
>
> # Load the required Packages.
>
> `library(spdep) # Spatial Dependence: Weighting Schemes,
> Statistics
> `library(rgdal) # to read shapefiles
>
> #shapefiles (world map from diva-gis)
>
> # Read the panel data from stata format for the regression analysis
> below.
>
> `library(foreign)
>
> `mydata <- read.dta("C:/Users/Usuario/Desktop/instituciones/revision
> energy economics/
> spatial panel in stata/countries_shp/neworiginal.dta")
>
> `fix(mydata)
> `attach(mydata)
>
> my data contains 116 countries from 1990 to 2014 in panel.
>
> # Prepare the dataset for panel data analysis in R.
>
> `library(plm)
>
> `mydata <- pdata.frame(mydata, index = c("id", "year"))
>
>
> # Read the shapefile and set up the working directory.
>
> `setwd("C:/Users/Usuario/Desktop/instituciones/revision energy
> economics/spatial panel in stata/countries_shp")
>
> `worlddata <- readOGR("countries.shp")
> `names(worlddata)
> `summary(worlddata)
>
> # Get the centroids
>
> `coords <-coordinates(worlddata)
>
> A. Contiguity based relations
>
> 1. First Order Queen Contiguity
>
> `queen.nb = poly2nb(worlddata, queen=TRUE)
> `summary(queen.nb)
> `plot(queen.nb,coords)
>
>
> # the numbers of neighbours of regions in the neighbours list.
>
> `cards <- card(queen.nb)
>
> # convert into a listw type based on contiguity row normalized
>
> `queen.listw <- nb2listw(queen.nb,style="W", zero.policy = TRUE)
> `summary(queen.listw,zero.policy=TRUE)
>
> #marginal effects
> `impacts(reg2, listw = listw1,zero.policy=TRUE)
>
> #marginal effects with p-values
> `summary(impacts(reg2, listw = listw1), R= 500, zstats =
> TRUE,zero.policy=TRUE)
>
> `attributes(queen.listw)
>
> #Selection of a subset of countries to fit with mydataset (116
> countries, the previous ones I did for all countries in the shapefile)
>
>
> `setwd("C:/Users/Usuario/Desktop/instituciones/revision energy
> economics/spatial panel in stata/countries_shp")
>
> `worlddata <- readOGR("countries.shp")
>
> `queen.nb = poly2nb(worlddata, queen=TRUE)
>
> `coords <-coordinates(worlddata)
>
> `plot(queen.nb, coords)
>
>
> Following Roger Bivand example:
>
> `to.be.dropped <- c(1, 2, 5, 6, 8, 9, 10, 13, 14, 18, 20, 21, 23, 26,
> 28, 29, 31, 34, 36, 37, 39, 40, 41, 45, 46, 47, 48, 51, 52, 53, 55, 56, 58,
> 59, 62, 63, 64, 66, 68, 69, 74, 75, 77, 78, 79, 80, 81, 82, 85, 86, 87, 89,
> 90, 94, 95, 97, 98, 99, 100, 102, 103, 104, 105, 107, 109, 110, 118, 123,
> 124, 125, 127, 130, 131, 133, 134, 137, 138, 139, 140, 143, 145, 146, 148,
> 149, 151, 152, 153, 155, 157, 159, 161, 162, 166, 167, 170, 173, 175, 176,
> 177, 178, 181, 182, 183, 184, 186, 190, 193, 194, 195, 198, 199, 200, 201,
> 202, 203, 204, 205, 206, 207, 208, 211, 212, 213, 215, 216, 218, 219, 221,
> 222, 224, 226, 227, 228, 229, 232, 233, 237, 239, 240, 242, 246, 247, 248,
> 255, 258, 259, 260, 261, 265)
> sub.queen.nb <- subset(queen.nb,
> !(1:length(queen.nb) %in% to.be.dropped))
> which(!(attr(queen.nb, "region.id") %in%
> attr(sub.queen.nb, "region.id")))
>
> `sub.queen.listw <- nb2listw(sub.queen.nb,style="W", zero.policy =
> TRUE)
>
> so now, I have my 116 countries in the queen matrix.
>
> # My data and variables
> `y <- cbind(lei)
> `x <- cbind(lgdppcnew, lgdppcnew2, industryg, importsg, fdig)
> `xy <- cbind(mydata$x, mydata$y)
> `listw1 <- sub.queen.listw
> `coords <- coords
>
> #Define formula
>
> `reg.ols <- y ~ x
>
>
> # Autocorrelation test
> `lm.morantest(ols.eq1,listw1,zero.policy=TRUE)
> `plot.moran(ols.eq1,listw1)
>
> (here I get the error where it is said the objects have different
> dimensions)
>
> `reg2 <- lagsarlm(ols.eq1, data = mydata, listw1, zero.policy=TRUE)
> `summary(reg2,correlation=TRUE, Nagelkerke=TRUE, Hausman=TRUE,
> zero.policy=TRUE)
>
> (here I get the error where it is said the objects have different
> dimensions)
>
> #marginal effects
>
> `impacts(reg2, listw = listw1,zero.policy=TRUE)
>
> #marginal effects with p-values
>
> `summary(impacts(reg2, listw = listw1), R= 500, zstats =
> TRUE,zero.policy=TRUE)
>
> I don't know if it is for my panel data, the missing values or
> something else.
> I tried also in Stata having similar issues.
>
> thanks in advance and my apologies if it is very naive question, but I
> am stuck.
>
> all the best
> Maria Jesus
>
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>
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