subordinates = d[, .(N.sub =   sub.func(N)), by = .(Source, Year )]
pay.to.base  = d[, .(P.norm =   pay.func(Mean)), by = .(Source, Year )]
result = data.table(subordinates, P.norm = pay.to.base$P.norm) %>% na.omit
d = data.table(d, N.sub = subordinates$N.sub, P.norm = pay.to.base$P.norm)
View(d)
d[Source == "Treble et al. " & Year == "1989-1997", 10] = N.sub$V1
d = subset(d, is.na(d$N.sub) == F & is.na(d$P.norm) == F)
View(d)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Income v Subordinates.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Income v Subordinates.R')
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv")
View(d)
test = rep(d$N.sub, d$N)
View(d)
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
setwd("/home/blair/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies")
d = read_csv("Case Results.csv") %>% data.table
d$ID = 1:length(d$Year)
d$Source =  d$Source %>%
gsub("BGH", "Baker et al.", .) %>%
gsub("et al", "et al.", .) %>%
gsub('[0-9]*', '' , .)
# analysis of main data
sub.func = function(x){
n.sub =  cumsum(x)[-length(x)] / x[-1]
n.sub = c(1, n.sub+1)
}
pay.func = function(x){x/x[1]}
subordinates = d[, .(N.sub =   sub.func(N)), by = .(Source, Year )]
pay.to.base  = d[, .(P.norm =   pay.func(Mean)), by = .(Source, Year )]
result = data.table(subordinates, P.norm = pay.to.base$P.norm) %>% na.omit
d = data.table(d, N.sub = subordinates$N.sub, P.norm = pay.to.base$P.norm)
# add treble data
N =  d[d$Source == "Treble et al. "] %>%
.[ , mean(N, na.rm = T), by = "Level"] %>%
subset(. , is.finite(V1) == T )
View(N)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv")
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv")
test = rep(d$N.sub, d$N)
test = rep(d$N.sub, round(d$N))
View(d)
summary(d$N.sub)
summary(d$N)
View(d)
setwd("/home/blair/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies")
d = read_csv("Case Results.csv") %>% data.table
d$ID = 1:length(d$Year)
d$Source =  d$Source %>%
gsub("BGH", "Baker et al.", .) %>%
gsub("et al", "et al.", .) %>%
gsub('[0-9]*', '' , .)
View(d)
View(d)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
View(d)
d = subset(d, Source != "Grund  ")
d = subset(d, Source != "Grund")
d = subset(d, Source != "Grund  ")
d = subset(d, Source != "Grund   ")
table(d$Source)
d = subset(d, Source != "Grund")
d = subset(d, Source != "Grund ")
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates v2.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Income v Subordinates.R')
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv")
test = rep(d$N.sub, round(d$N))
ineq(test)
x = d[1,]
payroll = rep(x$N.sub, round(x$N))
g = ineq(payroll)
summary(payroll)
View(d)
x = d[1:6,]
payroll = rep(x$N.sub, round(x$N))
g = ineq(payroll)
ineq(x$N.sub)
result = cbind(g, x$Source[1], x$Year[1])
gini.func = function(x){
payroll = rep(x$N.sub, round(x$N))
g = ineq(payroll)
return(g)
}
gini.func(x)
d = read_csv("Subordinates Results.csv") %>% data.table
g = d[ , gini.func, by = .(Source, Year)]
g = d[ , gini.func(N.sub)  , by = .(Source, Year)]
payroll.func = function(x){
payroll = rep(x$N.sub, round(x$N))
return(payroll)
}
payroll.func = function(x){
payroll = rep(x$N.sub, round(x$N))
return(list(payroll))
}
test = apply(d, 1, payroll.func)
payroll.func = function(x){
payroll = rep(x[3], round(x[10]))
return(list(payroll))
}
test = apply(d, 1, payroll.func)
x = data.table(d$N, d$N.sub)
payroll.func = function(x){
payroll = rep(x[3], round(x[10]))
return(list(payroll))
}
test = apply(x, 1, payroll.func)
d = read_csv("Subordinates Results.csv") %>% data.table
x = data.table(d$N, d$N.sub)
payroll.func = function(x){
payroll = rep(x[3], round(x[10]))
return(list(payroll))
}
test = apply(x, 1, payroll.func)
x = data.table(d$N, d$N.sub)
payroll.func = function(x){
payroll = rep(x[1], round(x[2]))
return(list(payroll))
}
test = apply(x, 1, payroll.func)
test[[1]]
test[[2]]
d = read_csv("Subordinates Results.csv") %>% data.table
x = data.table(d$N, d$N.sub)
payroll.func = function(x){
payroll = rep(x[2], round(x[1]))
return(list(payroll))
}
test = apply(x, 1, payroll.func)
test[[2]]
x = cbind(d$N, d$N.sub)
x = cbind(d$N, d$N.sub)
payroll.func = function(x){
payroll = rep(x[2], round(x[1]))
return(list(payroll))
}
test = apply(x, 1, payroll.func)
test[[2]]
test[[3]]
d$ID = paste(d$Source, d$Year)
View(d)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
View(d)
l = length(unique(d$ID))
id = unique(d$ID)
l = length(id)
i = 1
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
g = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
View(result)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
final = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
g = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
final = rbind(final, result)
}
View(final)
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
g.power = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
g = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
g.power = rbind(g.power, result)
}
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
g.power = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
g = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
g.power = rbind(g.power, result)
}
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
# gini index of power within firms
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
g.power = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
Gini = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
g.power = rbind(g.power, result)
}
setwd("/home/blair/Desktop/Empirical Research/Papers/Dissertation Proposal/Proposal II/Productivity")
gini.nation = read.csv("Gini.csv") %>%
na.omit  %>%
select(Gini)  %>%
(function(x){x/100})
m.power.y =  gini.power$Gini %>% mean %>% (gini.power$Gini %>% density %>% approxfun)
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
# gini index of power within firms
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
gini.power = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
Gini = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], g)
gini.power = rbind(gini.power, result)
}
setwd("/home/blair/Desktop/Empirical Research/Papers/Dissertation Proposal/Proposal II/Productivity")
gini.nation = read.csv("Gini.csv") %>%
na.omit  %>%
select(Gini)  %>%
(function(x){x/100})
m.power.y =  gini.power$Gini %>% mean %>% (gini.power$Gini %>% density %>% approxfun)
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
# gini index of power within firms
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
d$ID = paste(d$Source, d$Year)
id = unique(d$ID)
l = length(id)
gini.power = NULL
for(i in 1:l){
d.sub = subset(d, d$ID == id[i])
payroll = rep(d.sub$N.sub, d.sub$N)
Gini = ineq(payroll)
result = data.table(Source = d.sub$Source[1], Year = d.sub$Year[1], Gini)
gini.power = rbind(gini.power, result)
}
setwd("/home/blair/Desktop/Empirical Research/Papers/Dissertation Proposal/Proposal II/Productivity")
gini.nation = read.csv("Gini.csv") %>%
na.omit  %>%
select(Gini)  %>%
(function(x){x/100})
m.power.y =  gini.power$Gini %>% mean %>% (gini.power$Gini %>% density %>% approxfun)
m.nation.y =  gini.nation$Gini %>% mean %>% (gini.nation$Gini %>% density %>% approxfun)
m.power = paste("Mean = ",   sprintf("%.2f", round(mean(gini.power$Gini),2)) )
m.nation = paste("Mean = ",  sprintf("%.2f", round(mean(gini.nation$Gini),2)))
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
View(gini.power)
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
plot(density(gini.power$Gini))
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
test = density(gini.power$Gini)
test = density(gini.power$Gini)
plot(test$x, test$y)
hist(gini.power)
hist(gini.power$Gini)
test = density(gini.power$Gini) %>% select(x)
test = density(gini.power$Gini) %>% [[x]]
test = density(gini.power$Gini) %>% .$x
test = density(gini.power$Gini) %>% c(.$x, .$.y)
test = density(gini.power$Gini) %>% c(.$x, .$.y)
test = density(gini.power$Gini) %>% c(.$x, .$y)
test = density(gini.power$Gini) %>% cbind(.$x, .$y)
test = density(gini.power$Gini) %>% .$x
power.dens = density(gini.power$Gini) %>%
# plot
power = ggplot() +
geom_density(data = gini.power, aes(Gini), alpha = 0.5, fill = "red", trim = F) +
geom_density(data = gini.nation, aes(Gini), alpha = 0.5, fill = "dodgerblue3") +
geom_segment(aes( x = mean(gini.power$Gini), y = 0, xend = mean(gini.power$Gini), yend = m.power.y ),
col = "red", linetype = "dashed") +
geom_segment(aes( x = mean(gini.nation$Gini), y = 0, xend = mean(gini.nation$Gini), yend = m.nation.y ),
col = "dodgerblue3", linetype = "dashed") +
scale_x_continuous(breaks = seq(0, 1, 0.1)) +
coord_cartesian(xlim = c(0.05, 0.95)) +
labs(x = "Gini Index", y = "Density") +
theme_bw() +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
plot.title = element_text(face="bold", hjust = 0.5),
legend.box.just = "left",
legend.position = c(0.6, 0.75),
legend.key.size = unit(0.35, "cm"),
legend.key.height = unit(0.5, "cm"),
legend.key.width = unit(0.5, "cm"),
legend.text = element_text(size = rel(0.7)),
legend.title = element_blank(),
axis.line = element_line(color = "black"),
axis.title.x=element_text(vjust=-0.3, size=rel(0.9)),
axis.title.y=element_text(vjust= 1.1, size=rel(0.9)),
axis.text.x = element_text(margin=margin(5,5,0,0,"pt")),
axis.text.y = element_text(margin=margin(3,5,0,3,"pt")),
axis.ticks.length = unit(-0.7, "mm"),
text=element_text(size=9, family="Times")) +
annotate("text", x = 0.32, y = 1, label = m.nation,  family = "Times", size = 2 ) +
annotate("text", x = 0.15, y = 3.8,
label = "Income Inequality \nWithin Nation-States", family = "Times", size = 2.5 ) +
annotate("text", x = 0.72 , y = 1, label = m.power, family = "Times", size = 2 ) +
annotate("text", x = 0.75, y = 4,
label = "Power Inequality \nWithin Firm Hierarchies", family = "Times", size = 2.5 )
power.dens = density(gini.power$Gini)
power.dens = data.frame(power.dens$x, power.dens$y)
power.dens = density(gini.power$Gini)
power.dens = data.frame(power.dens$x, power.dens$y)
power.dens = data.frame(x = power.dens$x, y =  power.dens$y)
power.dens = data.frame(x = power.dens$x, ymin = 0, ymax =  power.dens$y)
power.dens = density(gini.power$Gini)
power.dens = data.frame(x = power.dens$x, ymin = 0, ymax =  power.dens$y)
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Subordinates Gini.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Productivity.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Productivity.R')
plot(density(gini.prod$Gini))
library(ineq)
library(NORMT3)
library(ggplot2)
library(grid)
library(readr)
library(dplyr)
library(data.table)
setwd("/home/blair/Desktop/Empirical Research/Papers/Dissertation Proposal/Proposal II/Productivity")
sigma = function(x){sqrt(log((x/100)^2 +1))}
g = function(x){ Re(erf(x/2))}
gini.prod =   read.csv("Output SD Low Medium.csv") %>%
na.omit %>% select(SD) %>%
(sigma) %>%
(g) %>%
data.frame %>%
`colnames<-`(c("Gini"))
gini.nation = read.csv("Gini.csv") %>%
na.omit  %>%
select(Gini)  %>%
(function(x){x/100})
m.prod.y =  gini.prod$Gini %>% mean %>% (gini.prod$Gini %>% density %>% approxfun)
m.nation.y =  gini.nation$Gini %>% mean %>% (gini.nation$Gini %>% density %>% approxfun)
m.productivity = paste("Mean = ",   sprintf("%.2f", round(mean(gini.prod$Gini),2)) )
m.nation = paste("Mean = ",  sprintf("%.2f", round(mean(gini.nation$Gini),2)))
prod.dens = density(gini.prod$Gini, adjust = 1.5)
prod.dens = data.frame(x = prod.dens$x, ymin = 0, ymax =  prod.dens$y)
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Productivity.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Productivity.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Productivity.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
0.2^2
0.99^2
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
source('~/Desktop/Empirical Research/Plots/Group Income Effect/Sensitivity Plot.R')
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
library(ggplot2)
library(readr)
library(boot)
library(magrittr)
library(data.table)
library(dplyr)
library(grid)
library(ineq)
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates")
d = read_csv("Subordinates Results.csv") %>% data.table
unique(d$Source)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates Workbook.R')
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
dir
workspace = gsub(dir, "Number of Subordinates", "")
setwd(workspace)
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
workspace = gsub(dir, "Number of Subordinates", "")
workspace
workspace = gsub("Number of Subordinates", "", dir)
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
workspace = gsub("Number of Subordinates", "", dir)
setwd(workspace)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Number of Subordinates/Subordinates Workbook.R')
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
workspace = paste(dir, "/Treble", sep = "")
setwd(workspace)
workspace
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
workspace = paste(dir, "/Data", sep = "")
setwd(workspace)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Treble/Treble Analysis.R')
dir = dirname(rstudioapi::getActiveDocumentContext()$path)
workspace = paste(dir, "/Data", sep = "")
setwd(workspace)
treble = read_csv("Treble Data.csv")
t1 = read_csv("Treble_4a.csv")
t1$x = round(t1$x +0.2) +1
t2 = read_csv("Treble_4b.csv")
t2$x = round(t2$x +0.2) + 6
t = rbind(t1, t2)
t = aggregate(t, list(t$x), FUN = mean)
View(t)
