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Graphs_SustainabilityPaper0723.R
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Graphs_SustainabilityPaper0723.R
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library(readxl)
library(Rcpp)
library(dplyr)
library(tidyverse)
library(FSA)
library(psych)
library(GGally)
library(PerformanceAnalytics)
library(dendextend)
library(plotly)
library(foreign)
library(writexl)
library(ggalt)
library(ggforce)
library(gghighlight)
library(gridExtra)
library(Hmisc)
library(corrplot)
library(xtable)
library(networkD3)
### Graphs and Tables for SDG Paper
### Author: Diana Garcia
### Import data
LaoSDG_ALL_LC <- read_excel("~/SDG paper/Graphs/IndicatorPSN_1221.xlsx")
### Transform data
LaoSDG_ALL_LC$Natpop<-LaoSDG_ALL_LC$Natpop15-LaoSDG_ALL_LC$Natpop05
#LaoSDG_ALL_LC$LNatpop<-LaoSDG_ALL_LC$LNatpop15-LaoSDG_ALL_LC$LNatpop05
LaoSDG_ALL_LC$LNatpop<-log(LaoSDG_ALL_LC$Natpop15)-log(LaoSDG_ALL_LC$Natpop05)
LaoSDG_ALL_LC$Croppop<-LaoSDG_ALL_LC$Croppop15-LaoSDG_ALL_LC$Croppop05
LaoSDG_ALL_LC$LCroppop<-LaoSDG_ALL_LC$LCroppop15-LaoSDG_ALL_LC$LCroppop05
LaoSDG_ALL_LC$Orchpop<-LaoSDG_ALL_LC$Orchpop15-LaoSDG_ALL_LC$Orchpop05
LaoSDG_ALL_LC$LOrchpop<-LaoSDG_ALL_LC$LOrchpop15-LaoSDG_ALL_LC$LOrchpop05
LaoSDG_ALL_LC$Grasspop<-LaoSDG_ALL_LC$Grasspop15-LaoSDG_ALL_LC$Grasspop05
LaoSDG_ALL_LC$LGrasspop<-LaoSDG_ALL_LC$LGrasspop15-LaoSDG_ALL_LC$LGrasspop05
LaoSDG_ALL_LC$Prov<-round(LaoSDG_ALL_LC$Dcode/100)
LaoSDG_ALL_LC$tot_pop<-LaoSDG_ALL_LC$tot_pop15-LaoSDG_ALL_LC$tot_pop05
LaoSDG_ALL_LC$tot_popgr<-(LaoSDG_ALL_LC$tot_pop15-LaoSDG_ALL_LC$tot_pop05)/LaoSDG_ALL_LC$tot_pop05
LaoSDG_ALL_LC$Agric05<-LaoSDG_ALL_LC$cropland05+LaoSDG_ALL_LC$orchard05 +LaoSDG_ALL_LC$grasslands05
LaoSDG_ALL_LC$Agric15<-LaoSDG_ALL_LC$cropland15+LaoSDG_ALL_LC$orchard15 +LaoSDG_ALL_LC$grasslands15
LaoSDG_ALL_LC$Agric<-LaoSDG_ALL_LC$Agric15-LaoSDG_ALL_LC$Agric05
LaoSDG_ALL_LC$AgricPop05<-LaoSDG_ALL_LC$Agric05/LaoSDG_ALL_LC$tot_pop05
LaoSDG_ALL_LC$LAgricPop05<-log(LaoSDG_ALL_LC$Agric05/LaoSDG_ALL_LC$tot_pop05)
LaoSDG_ALL_LC$AgricPop15<-LaoSDG_ALL_LC$Agric15/LaoSDG_ALL_LC$tot_pop15
LaoSDG_ALL_LC$LAgricPop15<-log(LaoSDG_ALL_LC$Agric15/LaoSDG_ALL_LC$tot_pop15)
LaoSDG_ALL_LC$AgricPop<-LaoSDG_ALL_LC$AgricPop15-LaoSDG_ALL_LC$AgricPop05
LaoSDG_ALL_LC$LAgricPop<-LaoSDG_ALL_LC$LAgricPop15-LaoSDG_ALL_LC$LAgricPop05
LaoSDG_ALL_LC$LAgricPop2<-(log(LaoSDG_ALL_LC$Agric15)/LaoSDG_ALL_LC$tot_pop15)-(log(LaoSDG_ALL_LC$Agric05)/LaoSDG_ALL_LC$tot_pop05)
LaoSDG_ALL_LC$LCroppop2<-(log(LaoSDG_ALL_LC$cropland15)/LaoSDG_ALL_LC$tot_pop15)-(log(LaoSDG_ALL_LC$cropland05)/LaoSDG_ALL_LC$tot_pop05)
LaoSDG_ALL_LC$LNatpop2<-(log(LaoSDG_ALL_LC$PerNatural15)/LaoSDG_ALL_LC$tot_pop15)-(log(LaoSDG_ALL_LC$PerNatural05)/LaoSDG_ALL_LC$tot_pop05)
LaoSDG_ALL_LC$NatArea<-(LaoSDG_ALL_LC$Natpop15*LaoSDG_ALL_LC$tot_pop15)-(LaoSDG_ALL_LC$Natpop05*LaoSDG_ALL_LC$tot_pop05)
#write_xlsx(LaoSDG_ALL_LC,"~/SDG paper/Graphs/IndicatorAll_0721.xlsx")
### Appendix B.
#Initial Values (1200x400)
Corr_In<-select(LaoSDG_ALL_LC,PovChange,`PovChange 1T 10%`,StuntChange, Pov05, `StuntChangeSE 1T 10%`, Stunt05, PerNatural05, NatChange) #Final one
Corr_S<-rcorr(as.matrix(Corr_In[(Corr_In$`StuntChangeSE 1T 10%`==1),c(3,6)] ))
Corr_P<-rcorr(as.matrix(Corr_In[(Corr_In$`PovChange 1T 10%`==1),c(1,4)] ))
Corr_N<-rcorr(as.matrix(Corr_In[,c(7,8)]))
fitP<-lm(PovChange~Pov05, LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1),])
fitS<-lm(StuntChange~Stunt05, LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),])
fitN<-lm((-NatChange)~PerNatural05, LaoSDG_ALL_LC)
fitLN<-lm((-LNatpop)~LNatpop05, LaoSDG_ALL_LC)
p1<-ggplot(LaoSDG_ALL_LC, aes(x=Pov05, y=PovChange))+
geom_point(aes(colour=factor(`PovChange 1T 10%`)),size=2)+
geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
xlab("Poverty 2005") + ylab("Poverty Change (p.p.)")+
scale_colour_discrete(name="Significance Poverty",labels=c("No","Yes"))+
theme(legend.position = "bottom")+
labs(title = paste("B. Corr =",signif(Corr_P$r[1,2], 2),
" P value =",signif(Corr_P$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
p2<-ggplot(LaoSDG_ALL_LC, aes(x=Stunt05, y=StuntChange))+
geom_point(aes(colour=factor(`StuntChangeSE 1T 10%`)),size=2)+
geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),] ,method='lm', formula= y~x, se=TRUE)+
xlab("Stunting 2005") + ylab("Stunting Change (p.p.)")+
scale_colour_discrete(name="Significance Stunting",labels=c("No","Yes"))+
theme(legend.position = "bottom")+
labs(title = paste("A. Corr =",signif(Corr_S$r[1,2], 2),
" P value =",signif(Corr_S$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
p3<-ggplot(LaoSDG_ALL_LC, aes(x=PerNatural05, y=-NatChange))+ #Final
geom_point(colour="turquoise3",size=2)+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Natural Area 2005") + ylab("Natural Area Reduction (p.p.)")+
labs(title = paste("C. Corr =",signif(Corr_N$r[1,2], 2),
" P value =",signif(Corr_N$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
# ggplot(LaoSDG_ALL_LC, aes(x=LNatpop05, y=-LNatpop))+
# geom_point(colour="turquoise3",size=2)+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Ln Natural Area p.c. 2005") + ylab("Ln Natural Degradation p.c.")+
# labs(title = paste(" Slope =",signif(fitLN$coef[[2]], 4),
# " P value =",signif(summary(fitLN)$coef[2,4], 4)))
grid.arrange(p2,p1,p3,nrow=1)
rm(fitLN, fitN, fitP, fitS)
rm(p1,p2,p3)
rm(Corr_In, Corr_N, Corr_P, Corr_S)
### Figure 2
#Change (1200x400)
# fitP_S<-lm(StuntChange~PovChange, LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1 & LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),])
# fitP_LN<-lm(-LNatpop~PovChange, LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1),])
# fitS_LN<-lm(-LNatpop~StuntChange, LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),])
#
# p1<-ggplot(LaoSDG_ALL_LC, aes(x=PovChange, y=StuntChange))+ #Pov vs Stunt
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`PovChange 1T 10%`),shape=factor(`StuntChangeSE 1T 10%`)),size=2)+
# geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1 & LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
# xlab("Poverty Change (p.p.)") + ylab("Stunting Change (p.p.)")+
# scale_colour_discrete(name="Signif. Pov.",labels=c("No","Yes"))+
# scale_shape_discrete(name="Signif. Stunt.", labels=c("No","Yes"))+
# theme(legend.position = "bottom")+
# labs(title = paste("C. Slope =",signif(fitP_S$coef[[2]], 2),
# " P value =",signif(summary(fitP_S)$coef[2,4], 2)))+
# theme(plot.title = element_text(size=12))
#
# p2<-ggplot(LaoSDG_ALL_LC, aes(x=PovChange, y=-LNatpop))+ #Pov vs Nat
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`PovChange 1T 10%`)))+
# geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
# xlab("Poverty Change (p.p.)") + ylab("Natural Area Loss p.c. (log)")+
# scale_colour_discrete(name="Significance Poverty",labels=c("No","Yes"))+
# theme(legend.position = "bottom")+
# labs(title = paste("B. Slope =",signif(fitP_LN$coef[[2]], 2),
# " P value =",signif(summary(fitP_LN)$coef[2,4], 2)))+
# theme(plot.title = element_text(size=12))
#
# p3<-ggplot(LaoSDG_ALL_LC, aes(x=StuntChange, y=-LNatpop))+ #Stunt vs Nat
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`StuntChangeSE 1T 10%`)))+
# geom_smooth(data=LaoSDG_ALL_LC[( LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
# xlab("Stunting Change (p.p.)") + ylab("Natural Area Loss p.c. (log)")+
# scale_colour_discrete(name="Significance Stunting",labels=c("No","Yes"))+
# theme(legend.position = "bottom")+
# labs(title = paste("A. Slope =",signif(fitS_LN$coef[[2]], 2),
# " P value =",signif(summary(fitS_LN)$coef[2,4], 2)))+
# theme(plot.title = element_text(size=12))
#
# #When checking population effect use ,size=(tot_popgr-min(tot_popgr)) on aes()
# grid.arrange(p3,p2,p1,nrow=1)
#Change with correlation (1200x400) FINAL
Correlation3Lpc_CH<-select(LaoSDG_ALL_LC,PovChange,`PovChange 1T 10%`,StuntChange,`StuntChangeSE 1T 10%`,LNatpop) #Final one
Corr_SP<-rcorr(as.matrix(Correlation3Lpc_CH[(Correlation3Lpc_CH$`PovChange 1T 10%`==1 & Correlation3Lpc_CH$`StuntChangeSE 1T 10%`==1),c(1,3)] ))
Corr_SN<-rcorr(as.matrix(Correlation3Lpc_CH[( Correlation3Lpc_CH$`StuntChangeSE 1T 10%`==1),c(3,5)] ))
Corr_PN<-rcorr(as.matrix(Correlation3Lpc_CH[(Correlation3Lpc_CH$`PovChange 1T 10%`==1),c(1,5)] ))
Correlation3ALpc_CH<-select(LaoSDG_ALL_LC,PovChange,`PovChange 1T 10%`,StuntChange,`StuntChangeSE 1T 10%`,LAgricPop) #Final one
Corr_PA<-rcorr(as.matrix(Correlation3ALpc_CH[(Correlation3ALpc_CH$`PovChange 1T 10%`==1),c(1,5)] ))
Corr_SA<-rcorr(as.matrix(Correlation3ALpc_CH[(Correlation3ALpc_CH$`StuntChangeSE 1T 10%`==1),c(3,5)] ))
p1<-ggplot(LaoSDG_ALL_LC, aes(x=PovChange, y=StuntChange))+ #Pov vs Stunt
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`PovChange 1T 10%`),shape=factor(`StuntChangeSE 1T 10%`)),size=2)+
geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1 & LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
xlab("Poverty Change (p.p.)") + ylab("Stunting Change (p.p.)")+
scale_colour_discrete(name="Signif. Pov.",labels=c("No","Yes"))+
scale_shape_discrete(name="Signif. Stunt.", labels=c("No","Yes"))+
theme(legend.position = "bottom")+
labs(title = paste("C. Corr =",signif(Corr_SP$r[1,2], 2),
" P value =",signif(Corr_SP$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
p2<-ggplot(LaoSDG_ALL_LC, aes(x=PovChange, y=-LNatpop))+ #Pov vs Nat
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`PovChange 1T 10%`)))+
geom_smooth(data=LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
xlab("Poverty Change (p.p.)") + ylab("Natural Area Loss p.c. (log)")+
scale_colour_discrete(name="Significance Poverty",labels=c("No","Yes"))+
theme(legend.position = "bottom")+
labs(title = paste("B. Corr =",signif(Corr_PN$r[1,2], 2),
" P value =",signif(Corr_PN$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
p3<-ggplot(LaoSDG_ALL_LC, aes(x=StuntChange, y=-LNatpop))+ #Stunt vs Nat
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`StuntChangeSE 1T 10%`)))+
geom_smooth(data=LaoSDG_ALL_LC[( LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],method='lm', formula= y~x, se=TRUE)+
xlab("Stunting Change (p.p.)") + ylab("Natural Area Loss p.c. (log)")+
scale_colour_discrete(name="Significance Stunting",labels=c("No","Yes"))+
theme(legend.position = "bottom")+
labs(title = paste("A. Corr =",signif(Corr_SN$r[1,2], 2),
" P value =",signif(Corr_SN$P[1,2], 2)))+
theme(plot.title = element_text(size=12))
#When checking population effect use ,size=(tot_popgr-min(tot_popgr)) on aes()
grid.arrange(p3,p2,p1,nrow=1)
### Table 1
# Note: using previous correlation output from Fig 2 and eliminating outliers on Agro indicator only
# We dont eliminate outliers on Nat indicator because correlations do not change significantly
Correlation4ALpc_05<-LaoSDG_ALL_LC |>
select(Pov05, Stunt05, LNatpop05, LNatpop15, LAgricPop05,LAgricPop15) |>
mutate(LAgricPop05=ifelse((LAgricPop05 < -2 | LAgricPop15 < -2) ,NA, LAgricPop05))|>
#mutate(LNatpop05=ifelse((LNatpop05 < -2 | LNatpop15 < -2) ,NA, LNatpop05))|>
select(-LAgricPop15,-LNatpop15)
Correlation4ALpc_15<-LaoSDG_ALL_LC |>
select(Pov15, Stunt15,LNatpop05, LNatpop15,LAgricPop05, LAgricPop15) |>
mutate(LAgricPop15=ifelse((LAgricPop05 < -2 | LAgricPop15 < -2) ,NA, LAgricPop15))|>
#mutate(LNatpop15=ifelse((LNatpop05 < -2 | LNatpop15 < -2) ,NA, LNatpop15))|>
select(-LAgricPop05,-LNatpop05)
Corr_05<-rcorr(as.matrix(Correlation4ALpc_05))
Corr_15<-rcorr(as.matrix(Correlation4ALpc_15))
Corr_tab<-matrix(0, 5, 3)
colnames(Corr_tab) = c('2005','2015', '2015-2005')
rownames(Corr_tab) <- c('Stunting Rate – Poverty Headcount',
'Stunting Rate – Natural land per capita (log)',
'Poverty Headcount – Natural land per capita (log)',
'Stunting Rate – Agricultural land per capita (log)',
'Poverty Headcount – Agricultural land per capita (log)')
Corr_tab[c(1:2,4),1]<-Corr_05$r[c(1,3:4),2]
Corr_tab[c(3,5),1]<-Corr_05$r[c(3:4),1]
Corr_tab[c(1:2,4),2]<-Corr_15$r[c(1,3:4),2]
Corr_tab[c(3,5),2]<-Corr_15$r[c(3:4),1]
Corr_tab[1,3]<-Corr_SP$r[1,2]
Corr_tab[2,3]<-Corr_SN$r[1,2]
Corr_tab[3,3]<-Corr_PN$r[1,2]
Corr_tab[4,3]<-Corr_SA$r[1,2]
Corr_tab[5,3]<-Corr_PA$r[1,2]
View(Corr_tab)
rm(list = ls(pattern = "^Corr"))
rm(list = ls(pattern = "^p"))
### Appendix C.
LaoSDG_LC_change <- as.data.frame(read_excel("~/SDG paper/Graphs/ChangeLC0515_FV2.xlsx", sheet = "Final4"))
nodes <- data.frame( name=c(LaoSDG_LC_change$Source,
LaoSDG_LC_change$Target) %>% unique() )
LaoSDG_LC_change$IDsource=match(LaoSDG_LC_change$Source, nodes$name)-1
LaoSDG_LC_change$IDtarget=match(LaoSDG_LC_change$Target, nodes$name)-1
ColourScal ='d3.scaleOrdinal() .range(["#35B779FF","#FDE725FF","#B4DE2CFF",
"#FFB833","#5F33FF","#FF61B7","#35B779FF", "#482878FF","#440154FF","#26828EFF","#31688EFF","#3E4A89FF", "#61FFFE" ])'
sankeyNetwork(Links = LaoSDG_LC_change, Nodes = nodes,
Source = "IDtarget", Target = "IDsource",
Value = "Area [degree^2]", NodeID = "name",
fontSize= 14, width = 500, height= 500,
colourScale=ColourScal,sinksRight=FALSE)
rm(LaoSDG_LC_change, nodes, ColourScal)
### Appendix D.
# Correlation Graphs (700x500) FINAL
Correlation3Lpc_15<-select(LaoSDG_ALL_LC,Pov15,Stunt15,LNatpop15) #Final one
ggpairs(Correlation3Lpc_15,lower=list(continuous=wrap("smooth_loess",size=0.1)),
title = "B. Indicators 2015",
columnLabels = c("Poverty Headcount", "Stunting Rate", "Natural Area p.c. (log)"))
Correlation3Lpc_05<-select(LaoSDG_ALL_LC,Pov05,Stunt05,LNatpop05) #Final one
ggpairs(Correlation3Lpc_05,lower=list(continuous=wrap("smooth_loess",size=0.1)),
title = "A. Indicators 2005",
columnLabels = c("Poverty Headcount", "Stunting Rate", "Natural Area p.c. (log)"))
rm(Correlation3Lpc_05, Correlation3Lpc_15)
# Other Correlations:
# Correlation3Lpc_CH<-select(LaoSDG_ALL_LC,PovChange,StuntChange,LNatpop)
#
# ggpairs(Correlation3Lpc_CH,lower=list(continuous=wrap("smooth_loess",size=0.1)),
# title = "B. Correlation SDGs Change",
# columnLabels = c("Poverty Headcount", "Stunting Rate", "Natural Area p.c."))
# res15 <- rcorr(as.matrix(Correlation3Lpc_15))
# corrplot(res15$r, type = "upper", order = "hclust",
# p.mat = res15$P, sig.level = 0.01, insig = "blank",tl.col = "black", tl.srt = 45)
#
# res05 <- rcorr(as.matrix(Correlation3Lpc_05))
# corrplot(res05$r, type = "upper", order = "hclust",
# p.mat = res05$P, sig.level = 0.01, insig = "blank",tl.col = "black", tl.srt = 45)
# CorrelationLpc_All<-select(LaoSDG_ALL_LC,
# Pov05,Stunt05,LNatpop05,LAgricPop05,Pov15,Stunt15,LNatpop15,LAgricPop15,PovChange,StuntChange,LNatpop,LAgricPop,NatArea,Agric) #Final one
#CorrelationLpc_All<-select(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$`PovChange 1T 10%`==1 & LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],
# Pov05,Stunt05,LNatpop05,LAgricPop05,Pov15,Stunt15,LNatpop15,LAgricPop15,PovChange,StuntChange,LNatpop,LAgricPop,NatArea,Agric) #Final one
#CorrelationLpc_All<-select(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],
# Pov05,Stunt05,LNatpop05,LAgricPop05,Pov15,Stunt15,LNatpop15,LAgricPop15,PovChange,StuntChange,LNatpop,LAgricPop,NatArea,Agric) #Final one
# CorrelationLpc_All<-select(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2 & LaoSDG_ALL_LC$`PovChange 1T 10%`==1 & LaoSDG_ALL_LC$`StuntChangeSE 1T 10%`==1),],
# Pov05,Stunt05,LNatpop05,LAgricPop05,Pov15,Stunt15,LNatpop15,LAgricPop15,PovChange,StuntChange,LNatpop,LAgricPop,NatArea,Agric) #Final one
#
# res<-cor(CorrelationLpc_All)
# resAll <- rcorr(as.matrix(CorrelationLpc_All))
# colnames(resAll$r) <- c("Poverty Rate 2005","Stunting Rate 2005","Natural Area p.c 2005 (log)","Agricultural area p.c. 2005 (log)",
# "Poverty Rate 2015","Stunting Rate 2015","Natural Area p.c 2015 (log)","Agricultural area p.c. 2015 (log)",
# "\u0394 Poverty Rate","\u0394 Stunting Rate",
# "\u0394 Natural area p.c (log)","\u0394 Agricultural area p.c. (log)",
# "\u0394 Natural area","\u0394 Agricultural area")
# rownames(resAll$r) <- c("Poverty Rate 2005","Stunting Rate 2005","Natural Area p.c 2005 (log)","Agricultural area p.c. 2005 (log)",
# "Poverty Rate 2015","Stunting Rate 2015","Natural Area p.c 2015 (log)","Agricultural area p.c. 2015 (log)",
# "\u0394 Poverty Rate","\u0394 Stunting Rate",
# "\u0394 Natural area p.c (log)","\u0394 Agricultural area p.c. (log)",
# "\u0394 Natural area","\u0394 Agricultural area")
# corrplot(resAll$r, type = "upper", order = "original", p.mat = resAll$P,
# sig.level = 0.05, insig = "blank",tl.col = "black",tl.srt = 40)
#
#corstars(CorrelationLpc_All) #Check function at the end
## Tests for Agricultural land area
## Graphs with Ln Agro per capita
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC)
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC)
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC)
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC)
#
# p1<-ggplot(LaoSDG_ALL_LC,aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC,aes(x=LAgricPop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC,aes(x=LAgricPop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC,aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #Graphs with Ln Agro per capita (w/o Vientiane Cap)
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
#
# p1<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LAgricPop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LAgricPop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #For legend
#
# ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)),color='Province')
#
# #Graphs with Ln Agro per capita (w/o Vientiane Cap or high -2)
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital' & LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),])
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital'& LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),])
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital' & LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),])
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital'& LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital' & LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),],aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital'& LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),],aes(x=LAgricPop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital' & LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),],aes(x=LAgricPop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Province!='Vientiane Capital' & LaoSDG_ALL_LC$LAgricPop05>=-2 & LaoSDG_ALL_LC$LAgricPop15>=-2),],aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #Graphs with Ln Agro per capita (w/o low Agri change and low increase of population)
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #legend
# ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)),color='Province')
#
# #Graphs with Ln Agro per capita (w low increase of population)
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),])
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitApc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[( LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LAgricPop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(Province,Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitApc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitApc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
### Appendix E.1
#Ln Agro per capita (High than -2) FINAL (800x500)
sample<-LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),]
eliminated<-LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05< -2 | LaoSDG_ALL_LC$LAgricPop15< -2),]
# fitApc_stunt05L<-lm(Stunt05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),])
# fitApc_stunt15L<-lm(Stunt15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),])
# fitApc_pov05L<-lm(Pov05~LAgricPop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),])
# fitApc_pov15L<-lm(Pov15~LAgricPop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),])
Corr_agro<-select(LaoSDG_ALL_LC,Stunt05,Stunt15,Pov05,Pov15,LAgricPop05,LAgricPop15)
Corr_Sa05<-rcorr(as.matrix(Corr_agro[(Corr_agro$LAgricPop05>-2 & Corr_agro$LAgricPop15>-2),c(1,5)] ))
Corr_Sa15<-rcorr(as.matrix(Corr_agro[(Corr_agro$LAgricPop05>-2 & Corr_agro$LAgricPop15>-2),c(2,6)] ))
Corr_Pa05<-rcorr(as.matrix(Corr_agro[(Corr_agro$LAgricPop05>-2 & Corr_agro$LAgricPop15>-2),c(3,5)] ))
Corr_Pa15<-rcorr(as.matrix(Corr_agro[(Corr_agro$LAgricPop05>-2 & Corr_agro$LAgricPop15>-2),c(4,6)] ))
p1<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],aes(x=LAgricPop05, y=Stunt05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
labs(title = paste("A. Corr =",signif(Corr_Sa05$r[1,2], 2),
" P value =",signif(Corr_Sa05$P[1,2], 2)))+theme(legend.position = "none")
p2<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],aes(x=LAgricPop15, y=Stunt15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Agricultural land p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
labs(title = paste("B. Corr =",signif(Corr_Sa15$r[1,2], 2),
" P value =",signif(Corr_Sa15$P[1,2], 2)))+theme(legend.position = "none")
p3<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],aes(x=LAgricPop05, y=Pov05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Agricultural land p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
labs(title = paste("C. Corr =",signif(Corr_Pa05$r[1,2], 2),
" P value =",signif(Corr_Pa05$P[1,2], 2)))+theme(legend.position = "none")
p4<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],aes(x=LAgricPop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Agricultural land p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(title = paste("D. Corr =",signif(Corr_Pa15$r[1,2], 2),
" P value =",signif(Corr_Pa15$P[1,2], 2)))+theme(legend.position = "none")
grid.arrange(p1,p2,p3,p4,nrow=2)
#For side legend (ordered provinces from north to south)
ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LAgricPop05>-2 & LaoSDG_ALL_LC$LAgricPop15>-2),],aes(x=LAgricPop05, y=Stunt05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Agricultural land p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
labs(color='Province')
rm(sample, eliminated)
rm(list = ls(pattern = "^fit"))
rm(list = ls(pattern = "^Corr"))
rm(list = ls(pattern = "^p"))
## Tests for Cropland
#
# #Graphs with Ln Crop per capita (w/o Vietiane Cap)
# fitCpc_stunt05L<-lm(Stunt05~LCroppop05,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitCpc_stunt15L<-lm(Stunt15~LCroppop15,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitCpc_pov05L<-lm(Pov05~LCroppop05,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
# fitCpc_pov15L<-lm(Pov15~LCroppop15,LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',])
#
# p1<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LCroppop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitCpc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LCroppop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitCpc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LCroppop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitCpc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LCroppop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitCpc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #For legend
# ggplot(LaoSDG_ALL_LC[LaoSDG_ALL_LC$Province!='Vientiane Capital',],aes(x=LCroppop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitCpc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_pov15L)$coef[2,4], 2)),color='Province')
#
# #Graphs with Ln Crop per capita (with low agro and low increase pop)
# fitCpc_stunt05L<-lm(Stunt05~LCroppop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitCpc_stunt15L<-lm(Stunt15~LCroppop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitCpc_pov05L<-lm(Pov05~LCroppop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitCpc_pov15L<-lm(Pov15~LCroppop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LCroppop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitCpc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LCroppop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitCpc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LCroppop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitCpc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LCroppop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Cropland p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitCpc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitCpc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
### Appendix E.2
#Graphs with Ln Crop per capita (800x500)
# fitCpc_stunt05L<-lm(Stunt05~LCroppop05,LaoSDG_ALL_LC)
# fitCpc_stunt15L<-lm(Stunt15~LCroppop15,LaoSDG_ALL_LC)
# fitCpc_pov05L<-lm(Pov05~LCroppop05,LaoSDG_ALL_LC)
# fitCpc_pov15L<-lm(Pov15~LCroppop15,LaoSDG_ALL_LC)
Corr_crop<-select(LaoSDG_ALL_LC,Stunt05,Stunt15,Pov05,Pov15,LCroppop05,LCroppop15)
Corr_Sc05<-rcorr(as.matrix(Corr_crop[,c(1,5)]))
Corr_Sc15<-rcorr(as.matrix(Corr_crop[,c(2,6)]))
Corr_Pc05<-rcorr(as.matrix(Corr_crop[,c(3,5)]))
Corr_Pc15<-rcorr(as.matrix(Corr_crop[,c(4,6)]))
p1<-ggplot(LaoSDG_ALL_LC,aes(x=LCroppop05, y=Stunt05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(`Province`,`Position`)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Cropland p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
labs(title = paste("A. Corr =",signif(Corr_Sc05$r[1,2], 2),
" P value =",signif(Corr_Sc05$P[1,2], 2)))+theme(legend.position = "none")
p2<-ggplot(LaoSDG_ALL_LC,aes(x=LCroppop15, y=Stunt15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(`Province`,`Position`)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Cropland p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
labs(title = paste("B. Corr =",signif(Corr_Sc15$r[1,2], 2),
" P value =",signif(Corr_Sc15$P[1,2], 2)))+theme(legend.position = "none")
p3<-ggplot(LaoSDG_ALL_LC,aes(x=LCroppop05, y=Pov05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(`Province`,`Position`)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Cropland p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
labs(title = paste("C. Corr =",signif(Corr_Pc05$r[1,2], 2),
" P value =",signif(Corr_Pc05$P[1,2], 2)))+theme(legend.position = "none")
p4<-ggplot(LaoSDG_ALL_LC,aes(x=LCroppop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(`Province`,`Position`)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Cropland p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(title = paste("D. Corr =",signif(Corr_Pc15$r[1,2], 2),
" P value =",signif(Corr_Pc15$P[1,2], 2)))+theme(legend.position = "none")
grid.arrange(p1,p2,p3,p4,nrow=2)
#For side legend (ordered provinces from north to south)
ggplot(LaoSDG_ALL_LC,aes(x=LCroppop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(`Province`,`Position`)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Cropland p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(color='Province')
rm(list = ls(pattern = "^fit"))
rm(list = ls(pattern = "^Corr"))
rm(list = ls(pattern = "^p"))
##Test for orchard
# #Graphs with Ln Orch per capita
# fitOpc_stunt05L<-lm(Stunt05~LOrchpop05,LaoSDG_ALL_LC)
# fitOpc_stunt15L<-lm(Stunt15~LOrchpop15,LaoSDG_ALL_LC)
# fitOpc_pov05L<-lm(Pov05~LOrchpop05,LaoSDG_ALL_LC)
# fitOpc_pov15L<-lm(Pov15~LOrchpop15,LaoSDG_ALL_LC)
#
# p1<-ggplot(LaoSDG_ALL_LC,aes(x=LOrchpop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchards p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitOpc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC,aes(x=LOrchpop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchards p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitOpc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC,aes(x=LOrchpop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchards p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitOpc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC,aes(x=LOrchpop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchards p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitOpc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
#
# #Graphs with Ln Orch per capita (with low agro and low increase pop)
# fitOpc_stunt05L<-lm(Stunt05~LOrchpop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitOpc_stunt15L<-lm(Stunt15~LOrchpop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitOpc_pov05L<-lm(Pov05~LOrchpop05,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
# fitOpc_pov15L<-lm(Pov15~LOrchpop15,LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LOrchpop05, y=Stunt05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchard/Plantations p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
# labs(title = paste(" Slope =",signif(fitOpc_stunt05L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_stunt05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p2<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LOrchpop15, y=Stunt15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchard/Plantations p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
# labs(title = paste(" Slope =",signif(fitOpc_stunt15L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_stunt15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p3<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LOrchpop05, y=Pov05))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchard/Plantations p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
# labs(title = paste(" Slope =",signif(fitOpc_pov05L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_pov05L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# p4<-ggplot(LaoSDG_ALL_LC[(abs(LaoSDG_ALL_LC$Agric)>100 & LaoSDG_ALL_LC$tot_pop<15000),],aes(x=LOrchpop15, y=Pov15))+
# geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
# geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
# geom_smooth(method='lm', formula= y~x, se=TRUE)+
# xlab("Orchard/Plantations p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
# labs(title = paste(" Slope =",signif(fitOpc_pov15L$coef[[2]], 2),
# " P value =",signif(summary(fitOpc_pov15L)$coef[2,4], 2)))+theme(legend.position = "none")
#
# grid.arrange(p1,p2,p3,p4,nrow=2)
### Appendix E.3
# Graphs with Ln Orch per capita (800x500)
# Outliers: with high -5
sample<-LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),]
eliminated<-LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05< -5 | LaoSDG_ALL_LC$LOrchpop15< -5),]
# fitOpc_stunt05L<-lm(Stunt05~LOrchpop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),])
# fitOpc_stunt15L<-lm(Stunt15~LOrchpop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),])
# fitOpc_pov05L<-lm(Pov05~LOrchpop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),])
# fitOpc_pov15L<-lm(Pov15~LOrchpop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),])
Corr_crop<-select(LaoSDG_ALL_LC,Stunt05,Stunt15,Pov05,Pov15,LOrchpop05,LOrchpop15)
Corr_So05<-rcorr(as.matrix(Corr_crop[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),c(1,5)]))
Corr_So15<-rcorr(as.matrix(Corr_crop[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),c(2,6)]))
Corr_Po05<-rcorr(as.matrix(Corr_crop[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),c(3,5)]))
Corr_Po15<-rcorr(as.matrix(Corr_crop[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),c(4,6)]))
p1<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),],aes(x=LOrchpop05, y=Stunt05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Orchards p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
labs(title = paste("A. Corr =",signif(Corr_So05$r[1,2], 2),
" P value =",signif(Corr_So05$P[1,2], 2)))+theme(legend.position = "none")
p2<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),],aes(x=LOrchpop15, y=Stunt15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Orchards p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
labs(title = paste("B. Corr =",signif(Corr_So15$r[1,2], 2),
" P value =",signif(Corr_So15$P[1,2], 2)))+theme(legend.position = "none")
p3<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),],aes(x=LOrchpop05, y=Pov05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Orchards p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
labs(title = paste("C. Corr =",signif(Corr_Po05$r[1,2], 2),
" P value =",signif(Corr_Po05$P[1,2], 2)))+theme(legend.position = "none")
p4<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),],aes(x=LOrchpop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Orchards p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(title = paste("D. Corr =",signif(Corr_Po15$r[1,2], 2),
" P value =",signif(Corr_Po15$P[1,2], 2)))+theme(legend.position = "none")
grid.arrange(p1,p2,p3,p4,nrow=2)
#For side legend (ordered provinces from north to south)
ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$LOrchpop05>-5 & LaoSDG_ALL_LC$LOrchpop15>-5),],aes(x=LOrchpop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Orchards p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(color='Province')
rm(sample, eliminated)
rm(list = ls(pattern = "^fit"))
rm(list = ls(pattern = "^Corr"))
rm(list = ls(pattern = "^p"))
## Appendix E. 4 (WHERE I STOPPED)
#Graphs with Ln Grass per capita
Corr_grass<-select(LaoSDG_ALL_LC,Stunt05,Stunt15,Pov05,Pov15,LGrasspop05,LGrasspop15)
Corr_Sg05<-rcorr(as.matrix(Corr_grass[,c(1,5)]))
Corr_Sg15<-rcorr(as.matrix(Corr_grass[,c(2,6)]))
Corr_Pg05<-rcorr(as.matrix(Corr_grass[,c(3,5)]))
Corr_Pg15<-rcorr(as.matrix(Corr_grass[,c(4,6)]))
# fitGpc_stunt05L<-lm(Stunt05~LGrasspop05,LaoSDG_ALL_LC)
# fitGpc_stunt15L<-lm(Stunt15~LGrasspop15,LaoSDG_ALL_LC)
# fitGpc_pov05L<-lm(Pov05~LGrasspop05,LaoSDG_ALL_LC)
# fitGpc_pov15L<-lm(Pov15~LGrasspop15,LaoSDG_ALL_LC)
p1<-ggplot(LaoSDG_ALL_LC,aes(x=LGrasspop05, y=Stunt05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Grasslands p.c. 2005 (Log)") + ylab("Stunting rate 2005")+
labs(title = paste("A. Corr =",signif(Corr_Sg05$r[1,2], 2),
" P value =",signif(Corr_Sg05$P[1,2], 2)))+theme(legend.position = "none")
p2<-ggplot(LaoSDG_ALL_LC,aes(x=LGrasspop15, y=Stunt15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Grasslands p.c. 2015 (Log)") + ylab("Stunting rate 2015")+
labs(title = paste("B. Corr =",signif(Corr_Sg15$r[1,2], 2),
" P value =",signif(Corr_Sg15$P[1,2], 2)))+theme(legend.position = "none")
p3<-ggplot(LaoSDG_ALL_LC,aes(x=LGrasspop05, y=Pov05))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Grasslands p.c. 2005 (Log)") + ylab("Poverty rate 2005")+
labs(title = paste("C. Corr =",signif(Corr_Pg05$r[1,2], 2),
" P value =",signif(Corr_Pg05$P[1,2], 2)))+theme(legend.position = "none")
p4<-ggplot(LaoSDG_ALL_LC,aes(x=LGrasspop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Grasslands p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(title = paste("D. Corr =",signif(Corr_Pg15$r[1,2], 2),
" P value =",signif(Corr_Pg15$P[1,2], 2)))+theme(legend.position = "none")
grid.arrange(p1,p2,p3,p4,nrow=2)
# For the side legend
ggplot(LaoSDG_ALL_LC,aes(x=LGrasspop15, y=Pov15))+
geom_hline(yintercept = 0)+geom_vline(xintercept=0)+
geom_point(aes(colour=factor(`Province`,levels = levels(reorder(LaoSDG_ALL_LC$Province,LaoSDG_ALL_LC$Position)))))+
geom_smooth(method='lm', formula= y~x, se=TRUE)+
xlab("Grasslands p.c. 2015 (Log)") + ylab("Poverty rate 2015")+
labs(color='Province')
rm(list = ls(pattern = "^fit"))
rm(list = ls(pattern = "^Corr"))
rm(list = ls(pattern = "^p"))
#Tests for Grassland
# #Graphs with Ln Grass per capita (No zeros)
# fitGpc_stunt05L<-lm(Stunt05~LGrasspop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Grasspop05!=0 & LaoSDG_ALL_LC$Grasspop15!=0),])
# fitGpc_stunt15L<-lm(Stunt15~LGrasspop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Grasspop05!=0 & LaoSDG_ALL_LC$Grasspop15!=0),])
# fitGpc_pov05L<-lm(Pov05~LGrasspop05,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Grasspop05!=0 & LaoSDG_ALL_LC$Grasspop15!=0),])
# fitGpc_pov15L<-lm(Pov15~LGrasspop15,LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Grasspop05!=0 & LaoSDG_ALL_LC$Grasspop15!=0),])
#
# p1<-ggplot(LaoSDG_ALL_LC[(LaoSDG_ALL_LC$Grasspop05!=0 & LaoSDG_ALL_LC$Grasspop15!=0),],aes(x=LGrasspop05, y=Stunt05))+