die.sub = na.omit(die.sub)
die.location = die.sub[-die.length,2] - die.sub[-1,2]
View(die.sub)
die.location = die.sub[-die.length,2] - die.sub[-1,2]
die.location = which(die.location != 0 )
View(die.sub)
die.sub = die[die[,1] < i,]
die.sub = rbind(die.sub, c(NA,NA))
die.length = length(die.sub[,1])-1
die.sub = die[die[,1] < i,]
die.sub = rbind(die.sub, c(NA,NA))
die.length = length(die.sub[,1])-1
die.sub = na.omit(die.sub)
c(13778,16248,19621,22815,29352.38878,52977,85014,110693)
x = c(13778,16248,19621,22815,29352.38878,52977,85014,110693)
ineq(x)
library(ineq)
ineq(x)
qlnorm(c(0.25, 0.5, 0.75), 1, 1)
qlnorm(c(0.25, 0.5, 0.75), 10, 1)
qlnorm(c(0.25, 0.5, 0.75), 10, 0.5)
qlnorm(c(0.25, 0.5, 0.75), 10, 0.2)
qlnorm(c(0.25, 0.5, 0.75), 8, 0.2)
qlnorm(c(0.25, 0.5, 0.75), 9.5, 0.2)
y = rlnorm(10^5, 9.5, 0.2)
ineq(y)
ineq(x)/ineq(y)
mean(y)
n = exp(seq(log(100), log(10^6), length.out = 1000))
n = round(n)
n
x = rlnorm(n[i], 10, 1)
x = rlnorm(n[i], 10, 1)
i = 10
x = rlnorm(n[i], 10, 1)
max(x)/mean(x)
for (i in 1:l){
x = rlnorm(n[i], 10, 1)
CEO.ratio[i] = max(x)/mean(x)
}
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
CEO.ratio = rep(NA, l)
source('~/Desktop/Lognorm Firm CEO.R')
plot(n, CEO.ratio)
plot(n, CEO.ratio, log="xy")
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
n = rlnorm(10^5, 20, 4)
hist(log(n))
hist(log10(n))
n = rlnorm(10^5, 15, 4)
hist(log10(n))
n = rlnorm(10^5, 11, 4)
hist(log10(n))
n = rlnorm(10^5, 11, 2)
hist(log10(n))
summary(n)
n = rlnorm(10^5, 11, 1.5)
hist(log10(n))
summary(n)
n = rlnorm(10^5, 11, 1)
summary(n)
n = rlnorm(10^5, 10, 1)
summary(n)
source('~/Desktop/Lognorm Firm CEO.R')
r = lm(log(CEO.ratio) ~ log(n))
summary(r)$r.squared
source('~/Desktop/Lognorm Firm CEO.R')
summary(r)$r.squared
source('~/Desktop/Lognorm Firm CEO.R')
summary(r)$r.squared
source('~/Desktop/Lognorm Firm CEO.R')
source('~/Desktop/Lognorm Firm CEO.R')
x = rlnorm(10^5, 10, 1.5)
library(ineq)
x = rlnorm(10^5, 10, 1.5)
ineq(x)
source('~/Desktop/Lognorm Firm CEO.R')
x = rlnorm(10^5, 10, 1.1)
ineq(x)
source('~/Desktop/Lognorm Firm CEO.R')
x = rlnorm(10^5, 10, 0.8)
ineq(x)
x = rlnorm(10^5, 10, 0.5)
ineq(x)
source('~/Desktop/Lognorm Firm CEO.R')
exp = 1:10
b = 10^5
exp = 0:10
b = 10^5
l = b*(0.5)^exp
l = floor(l)
sum(l)
l
exp = 0:20
b = 10^5
l = b*(0.5)^exp
l = floor(l)
l
p = 1.1^exp
p
pay = cumprod(p)
pay
mu = log(pay)
sigma = 0.2
firm = data.frame(l,pay)
View(firm)
firm = firm[firm$l != 0 ]
firm = firm[firm$l != 0 ,]
View(firm)
l = length(firm[,1])
source('~/Desktop/CEO TEst.R')
library(ineq)
hist(payroll)
hist(log(payroll))
hist(log(payroll), breaks  = 100)
ineq(payroll)
max(payroll)/mean(payroll)
View(firm)
p = 1.02^exp
pay = cumprod(p)
firm = data.frame(l,pay)
View(firm)
source('~/Desktop/CEO TEst.R')
max(payroll)/mean(payroll)
ineq(payroll)
source('~/Desktop/CEO TEst.R')
g = ineq(payroll)
CEO = max(payroll)/mean(payroll)
source('~/Desktop/CEO TEst.R')
View(firm)
s = 1.1^exp
l = b*(s)^exp
l = floor(l)
p = 1.05^exp
pay = cumprod(p)
mu = log(pay)
sigma = 0.2
View(firm)
l = b*(1/s)^exp
l = floor(l)
p = 1.05^exp
pay = cumprod(p)
mu = log(pay)
sigma = 0.2
firm = data.frame(l,pay)
source('~/Desktop/CEO TEst.R')
View(firm)
plot(l)
exp = 0:20
b = 10^5
s = 1.1^exp
l = b*(1/s)^exp
l = floor(l)
plot(l)
g = ineq(payroll)
CEO = max(payroll)/mean(payroll)
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
plot(l)
View(firm)
plot(firm$l)
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
source('~/Desktop/CEO TEst.R')
plot(pay)
plot(log(pay)
plot(log(pay))
plot(log(pay))
View(firm)
library(ineq)
x = c(31321, 1611)
ineq(x)
between = c(31321, 1611)
ineq(between)
gini.between = ineq(between)
gini.within = mean(c(0.64,0.48))
gini.between/gini.within
between = c(38328, 3571)
gini.between = ineq(between)
gini.within = mean(c(0.64,0.48))
gini.between/gini.within
x = rlnorm(10^6, 10, 2)
p = 10^6*0.01
x = sort(x)
y = head(x, p)
hist(y)
y = x[p, 2*p]
y = x[p:2*p]
y = x[p:(2*p)]
hist(y)
library(ineq)
ineq(y)
y = x[(3p):(4*p)]
y = x[(3*p):(4*p)]
ineq(y)
hist(y)
ineq(y)
y = x[(99*p):(100*p)]
ineq(y)
hist(y)
ineq(y)
y = x[(80*p):(81*p)]
ineq(y)
hist(y)
hist(log(y))
y = x[(95*p):(95*p)]
ineq(y)
y = x[(95*p):(96*p)]
ineq(y)
hist(log(y))
y = x[(98*p):(99*p)]
ineq(y)
hist(log(y))
y = x[(99*p):(100*p)]
ineq(x)
x = rlnorm(10^6, 10, 1)
x = sort(x)
ineq(x)
p = 10^6*0.01
y = x[(99*p):(100*p)]
ineq(y)
hist(log(y))
y = x[(98*p):(99*p)]
ineq(y)
hist(log(y))
y = tail(x, p)
ineq(y)
hist(log(y))
hist(log(y), breaks = 100)
mean(y)
sd(y)/mean(y)
y = x[(98*p):(99*p)]
mean(y)
sd(y)/mean(y)
hist(y, breaks = 100)
y = x[(90*p):(91*p)]
ineq(y)
mean(y)
sd(y)/mean(y)
hist(y, breaks = 100)
ineq(y)
ineq(y)
y = x[(70*p):(71*p)]
ineq(y)
mean(y)
sd(y)/mean(y)
hist(y, breaks = 100)
x, breaks = 100)
hist(100), breaks = 100)
hist(x, breaks = 100)
hist(x, breaks = 100, xlim = c(0, 10^5))
hist(x, breaks = 1000, xlim = c(0, 10^5))
p = quantile(x, probs = seq(0,1, length.out = 100))
p
p = data.frame(quantile(x, probs = seq(0,1, length.out = 100)))
View(p)
p = data.frame(quantile(x, probs = seq(0,1, 0.01)))
View(p)
ineq(x)
p = quantile(x, probs = seq(0,1, 0.01))
test = ineq(p)
test = ineq(p[1:99])
ineq(p[1:99])
ineq(x)
x = rlnorm(10^6, 10, 1)
x = sort(x)
ineq(x)
p = quantile(x, probs = seq(0,1, 0.01))
ineq(p[1:99])
p
p = quantile(x, probs = seq(0,1, 0.1))
ineq(p[1:99])
ineq(p[1:10])
p
install.packages("XML")
install.packages("XML")
library(XML)
test = xmlToList("Test.xml")
test = xmlToList("Test.XML")
1+NA
x = NA
y = 10
x+y
library(ineq)
x = rlnorm(10^5, 10, 0.8)
ineq(x)
plnorm(10, 10, 0.8)
qlnorm(10, 10, 0.8)
?lnorm
?qlnorm
plnorm(10, 10, 0.8)
qlnorm(0.1, 10, 0.8)
qlnorm(0.9, 10, 0.8)
qlnorm(0.25, 10, 0.8)
mu = log(36)
sd = sqrt(2*(log(48) - mu))
sigma = sqrt(2*(log(48) - mu))
library(NORMT3)
erf(sigma/2)
erf(sigma/2)
year = 1994:2015
l = length(year)
url = "http://www.census.gov/data/tables/time-series/demo/income-poverty/cps-pinc/pinc-06.2015.html"
final = NULL
t = year[i]
i = 1
t = year[i]
t.sub = as.character(t)
url.year = gsub("2015", t, url)
doc = htmlParse(url.year)
library(readr)
library(XML)
doc = htmlParse(url.year)
links <- xpathSApply(doc, "//a/@href")
links
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima")
library(readr)
library(readr)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
View(l2)
l1$x = round(l1$x)
View(l1)
l1$x = l1$x + 1900
View(l1)
l1 = aggregate(l1, list(l1$x), FUN = mean)
View(l1)
l1 = l1[,-1]
View(l1)
library(reshape2)
l1 = melt(l1)
View(l1)
library(readr)
library(reshape2)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
l1$x = round(l1$x)
l1$x = l1$x + 1900
l1 = aggregate(l1, list(l1$x), FUN = mean)
l1 = l1[,-1]
View(l1)
?melt
l1 = melt(l1, l1$x)
l1 = melt(l1, 1995)
l1 = melt(l1," 1995")
l1 = melt(l1)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(l1)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(l1)
View(test)
library(readr)
library(reshape2)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
l1$x = round(l1$x)
l1$x = l1$x + 1900
l1 = aggregate(l1, list(l1$x), FUN = mean)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
year = rep(l1$x,4)
View(l1)
year = rep(l1$x, 7)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
View(l1)
l1 = aggregate(l1, list(l1$x), FUN = mean)
long = l1[,3:9]
View(long)
View(l1)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
l1$x = round(l1$x)
l1$x = l1$x + 1900
View(l1)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
l1$x = round(l1$x)
l1$x = l1$x + 1900
l1 = aggregate(l1, list(l1$x), FUN = mean)
View(l1)
long = l1[,3:9]
View(long)
long = melt(long)
View(long)
View(l1)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
long = long[order(long$year),]
View(long)
View(l2)
View(long)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
long$level = rep(7:1, 5)
View(long)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
library(readr)
library(reshape2)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
l1$x = round(l1$x)
l1$x = l1$x + 1900
l1 = aggregate(l1, list(l1$x), FUN = mean)
long = l1[,3:9]
long = melt(long)
long$year = rep(l1$x, 7)
long$level = rep(7:1, 5)
View(long)
long$level = rep(7:1, each = 5)
View(long)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(long)
View(l2)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
l2$Pay[l2$Level %in% long$level,]
l2$Pay[l2$Level %in% long$level]
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(l1)
View(l2)
sigma = sqrt(log((l2$`COV (Total Wage)`/100)^2 +1))
g = erf(sigma/2)
library(NORMT3)
sigma = sqrt(log((l2$`COV (Total Wage)`/100)^2 +1))
g = erf(sigma/2)
sigma
sigma[is.na(sigma)] = 0
sigma
g = Re(erf(sigma/2))
erf(0.24/2)
erf(0.3/2)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
output = data.frame(Year = l2$Year, Level = l2$Level, Mean = l2$Pay, Gini = g, Source = l2$Source)
View(output)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(output)
output = na.omit(output)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
View(output)
write_csv(output, "Limi Level Results.csv")
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima")
lima = read_csv("Lima Level Results.csv")
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima")
lima = read_csv("Lima Level Results.csv")
setwd("~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima")
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Lima/Lima Analysis.R')
lima = read_csv("Lima Level Results.csv")
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
span.plot
gini.plot
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
pay.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
span.plot
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Plot.R')
span.plot
gini.plot
View(d)
setwd("/home/blair/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Lima")
library(readr)
library(reshape2)
library(NORMT3)
l1 = read_csv("Lima_1.csv")
l2 = read_csv("Lima Data.csv")
View(l1)
View(l2)
source('~/Desktop/Empirical Research/Income Distribution/Gini Ratio/Hierarchical Levels/Empirical/Case Studies/Lima/Lima Analysis.R')
