[R-sig-Geo] moran test - Empty neighbour sets found

[maria jesus herrerias]

Dear Roger,

 I try first with your suggestion for the map:



library(rnaturalearth)

spdf_world <- ne_countries(returnclass="sf")



if (require(sp)) {

  plot(spdf_world)

  }



names(spdf_world)



[1] "scalerank"  "featurecla" "labelrank"  "sovereignt" "sov_a3"

 [6] "adm0_dif"   "level"      "type"       "admin"      "adm0_a3"

[11] "geou_dif"   "geounit"    "gu_a3"      "su_dif"     "subunit"

[16] "su_a3"      "brk_diff"   "name"       "name_long"  "brk_a3"

[21] "brk_name"   "brk_group"  "abbrev"     "postal"     "formal_en"

[26] "formal_fr"  "note_adm0"  "note_brk"   "name_sort"  "name_alt"

[31] "mapcolor7"  "mapcolor8"  "mapcolor9"  "mapcolor13" "pop_est"

[36] "gdp_md_est" "pop_year"   "lastcensus" "gdp_year"   "economy"

[41] "income_grp" "wikipedia"  "fips_10"    "iso_a2"     "iso_a3"

[46] "iso_n3"     "un_a3"      "wb_a2"      "wb_a3"      "woe_id"

[51] "adm0_a3_is" "adm0_a3_us" "adm0_a3_un" "adm0_a3_wb" "continent"

[56] "region_un"  "subregion"  "region_wb"  "name_len"   "long_len"

[61] "abbrev_len" "tiny"       "homepart"   "geometry"





spdf_world$geounit



library(foreign)

library(haven)





setwd("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/spatial test")



x <- read.dta("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/spatial test/high_spatial.dta")



dta_cntries <- unique(x$geounit)



library(sf)



wrld_a <- aggregate(spdf_world, list(spdf_world$geounit), head, n=1)





o <- match(dta_cntries, wrld_a$geounit)



#Check if matching is right



which(is.na(o))

[1] 9

dta_cntries[9] <- "France"

o <- match(dta_cntries, spdf_world$geounit)

o

which(is.na(o))



library(spdep)

row.names(wrld_a) <- wrld_a$geounit

nb <- poly2nb(wrld_a)

nb1 <- subset(nb, 1:nrow(wrld_a) %in% o)



Neighbour list object:

Number of regions: 32

Number of nonzero links: 24

Percentage nonzero weights: 2.34375

Average number of links: 0.75

17 regions with no links:

Angola Dominican Republic East Timor Egypt Falkland Islands Fiji Gambia
Guyana Liberia Malaysia Oman Papua New Guinea Puerto Rico Republic of
Serbia Slovenia Sweden Uruguay

Note for roger: this is wrong as I didn’t include these countries in the
data (17 regions with no links)



wrld_s <- wrld_a[1:nrow(wrld_a) %in% o,]

nb2 <- poly2nb(wrld_s)

all.equal(nb1, nb2, check.attributes=FALSE)

[1] TRUE  # subsetting well-done however.

---------------------------------------------------

I try now with my map:



#Spatial Dependence for Panel 32 regions from 1990-2014



# The Spatial Matrix

# Read the shapefile and set up the working directory.

library(foreign)

library(haven)





setwd("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/spatial test")



x <- read.dta("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/spatial test/high_spatial.dta")



# Matching with stata file and shapefile by ID



dta_cntries <- unique(x$OBJECTID)



library(sf)



wrld <- st_read("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs
enviados/Longitude_Graticules_and_World_Countries_Boundaries-shp/mapa1.shp")

wrld_a <- aggregate(wrld, list(wrld$OBJECTID), head, n=1)





o <- match(dta_cntries, wrld_a$OBJECTID)



#Check if matching is right





which(is.na(o))



o <- match(dta_cntries, wrld$OBJECTID)

o



library(spdep)

row.names(wrld_a) <- wrld_a$OBJECTID

nb <- poly2nb(wrld_a, queen=TRUE)

nb1 <- subset(nb, 1:nrow(wrld_a) %in% o)



nb1llistw <- nb2listw(nb1,style = "W", zero.policy = TRUE)



#high

Neighbour list object:

Number of regions: 32

Number of nonzero links: 82

Percentage nonzero weights: 8.007812

Average number of links: 2.5625



wrld_s <- wrld_a[1:nrow(wrld_a) %in% o,]

nb2 <- poly2nb(wrld_s,queen=TRUE)

all.equal(nb1, nb2, check.attributes=FALSE)

[1] TRUE  # subsetting well-done



subworlddata <- wrld_s







# Tranform the nb object into a matrix row standarised.



sub.queen.w.Mat <- listw2mat(sub.queen.listw) # creates a standardized
matrix (rows sum to 1)

sub.queen.B.Mat <- nb2mat(sub.queen.nb, style='B',zero.policy=TRUE) # a
simple binary matrix (rows sum to the number of neighbors)



rownames(sub.queen.w.Mat) <- subworlddata$OBJECTID

colnames(sub.queen.w.Mat) <- subworlddata$OBJECTID





rownames(sub.queen.B.Mat) <- subworlddata$OBJECTID

colnames(sub.queen.B.Mat) <- subworlddata$OBJECTID




----------------------------------------------------------------------------------------------------------





sub.queen.w.Mat1 <-
read.dta("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/subqueenW.dta")

sub.queen.B.Mat1 <-
read.dta("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/subqueenB.dta")





sub.queen.w.Mat11 <- as.matrix(sub.queen.w.Mat1)

rownames(sub.queen.w.Mat11) <- subworlddata$OBJECTID

colnames(sub.queen.w.Mat11) <- subworlddata$OBJECTID

sub.queen.lw.Mat11 <- mat2listw(sub.queen.w.Mat11)



sub.queen.B.Mat11 <- as.matrix(sub.queen.B.Mat1)

rownames(sub.queen.B.Mat11) <- subworlddata$OBJECTID

colnames(sub.queen.B.Mat11) <- subworlddata$OBJECTID

sub.queen.lB.Mat11 <- mat2listw(sub.queen.B.Mat11)





listw1 <- sub.queen.lw.Mat11

listw2 <- sub.queen.lB.Mat11



sub.queen.lw.listw.Mat21 <- nb2listw(sub.queen.lw.Mat11$neighbours,
style="W",zero.policy=TRUE)

sub.queen.lB.listw.Mat21 <- nb2listw(sub.queen.lB.Mat11$neighbours,
style="B",zero.policy=TRUE)



# Summary Matrix nb object to listw

listw21 <- sub.queen.lw.listw.Mat21

listw22 <- sub.queen.lB.listw.Mat21



---------------------------------------------------





library(plm)



setwd("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/code and data/quantile")



x <- read.dta("C:/Users/Usuario/Desktop/instituciones/revision energy
economics/docs enviados/spatial test/high_spatial.dta")





mydata <- pdata.frame(x, index = c("OBJECTID", "year"))

**************************************

#Variables.



energy <- mydata$leic

gdp <- mydata$lgdppcnewc

gdp2 <- mydata$lgdppcnewc2

fdi <- mydata$fdigc

imports <- mydata$importsgc

industry <- mydata$industrygc

inst <- mydata$kun_legabsc

ID <- mydata$OBJECTID

time <- mydata$year



**********************************

#Define formula



model.1 <- energy ~ gdp + gdp2 + fdi + imports + industry + inst



ols.eq1 <- lm(model.1, data = mydata)

summary(ols.eq1)





lmMoranTest <- lm.morantest(ols.eq1,listw = nb2listw(nb1,style = "W",
zero.policy = TRUE))

lmMoranTest



*Error in nb2listw(neighbours = subnb, glist = NULL, style = style,
zero.policy = zero.policy) : *

*  Empty neighbour sets found*



lmLMtests <- lm.LMtests(ols.eq1, listw = nb2listw(nb1,style = "W",
zero.policy = TRUE), test=c("LMerr", "LMlag", "RLMerr", "RLMlag", "SARMA"))

lmLMtests



*Error in nb2listw(neighbours = subnb, glist = NULL, style = style,
zero.policy = zero.policy) : *

*  Empty neighbour sets found*


many thanks
maria jesus

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