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R script for making the graphs on the US economy
##############################
# Miles Grimshaw
# April 15th, 2013
# Code for graphs exploring US Economy
# Blog Post:
##############################
getwd()
setwd("~/Desktop/Macro_Paper/Data/")
# Recessions: http://www.nber.org/cycles.html
## Color for recessions
rcol <- rgb(190, 190, 190, alpha=50, maxColorValue=255)
# Standard Margins: [1] 5.1 4.1 4.1 2.1
######### NUMBER OF UNEMPLOYED PERSONS #########
u <- read.csv("./CSV/Unemployed.csv", header=TRUE, as.is=TRUE)
str(u)
u$Date <- as.Date(as.character(u$Date))
u <- u[format(u$Date, '%Y')>1950,]
at = format(u$Date, '%m') == '01' & as.numeric(format(u$Date, '%Y')) %% 5 == 0
pdf(file="Num_Unemployed.pdf",width=11,height=8.5)
par(mar=c(5.1, 5.0, 4.1, 2.1))
plot(u$Date, u$Unemploy, ylim=c(1, 1.1*max(u$Unemploy)), col="red", type='l',
xlab="Date", ylab="Persons (Thousands)", main="Number Of People Unemployed", xaxt='n')
mtext("Source: Current Population Survey", cex=0.8, padj=-1)
axis(side=1, at=u$Date[ at ], labels=format(u$Date[at], '%Y'))
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('2001-03-01'), xright=as.Date('2001-11-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-03-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-11-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1973-11-01'), xright=as.Date('1975-03-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1969-12-01'), xright=as.Date('1970-11-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1000, ytop=1.1*max(u$Unemploy)+1000, density=100, col=rcol)
dev.off()
######### DURATION OF UNEMPLOYMENT #########
d <- read.csv("./CSV/Unemploy_Duration.csv", header=TRUE, as.is=TRUE)
str(d)
d$Date <- as.Date( as.character( d$Date ) )
## 1970-Present
# 5 Year Date Increments
at = format(d$Date, '%m') == '01' & as.numeric(format(d$Date, '%Y')) %% 5 == 0
pdf(file="Duration_Unemployment.pdf",width=11,height=8.5)
par(mar=c(5.1, 5.0, 4.1, 2.1))
plot(d$Date, d$Mean, ylim=c(1, 1.1*max(d$Mean)), col="black", type='l',
xlab="Date", ylab="Weeks", main="Duration of Unemployment", xaxt='n')
mtext("Source: Current Population Survey", cex=0.8, padj=-1)
axis(side=1, at=d$Date[ at ], labels=format(d$Date[at], '%Y'))
points(d$Date, d$Median, col='red', type='l')
legend(x=as.Date('1982-07-01'), y=40, legend=c('Mean', 'Median'),
col=c('black', 'red'), text.col=c('black','black'), lwd=2.2, cex=1.6,
text.width=strwidth("Mean"),
seg.len=0.7, adj=0.1, y.intersp=1.4, bty='n', x.intersp=1)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('2001-03-01'), xright=as.Date('2001-11-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-03-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-11-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1973-11-01'), xright=as.Date('1975-03-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1969-12-01'), xright=as.Date('1970-11-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
dev.off()
######### BEVERIDGE CURVE #########
b <- read.csv("./CSV/Beveridge.csv", header=TRUE, as.is=TRUE)
str(b)
b$Date <- as.Date( as.character( b$Date ) )
year.cat <- function(x) {
year <- as.numeric(format(x, '%Y'))
year <- year-(year %% 2)
}
b$mdate <- sapply(b$Date, FUN=year.cat)
b$mdate <- factor(b$mdate, levels=unique(b$mdate), ordered=TRUE)
mycolors = c("darkgreen", "brown", "turquoise", "orange", "purple", "blue", "red")
pdf(file="Beveridge_Curve.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(b$Unemploy, b$Jobs, ylim=c(0, 1.1*max(b$Jobs)),
xlab="Unemployment Rate (%)", ylab="Vacancy Rate (%)", main="Beveridge Curve 2000-2012",
col=mycolors[b$mdate], pch=20, cex=2)
mtext("Source: Current Population Survey & JOLTs", cex=0.8, padj=-1)
legend("bottomleft", horiz=TRUE, legend=paste(a <- levels(b$mdate),"-", as.numeric(substring(a,3,4))+1, sep=""),
text.col=mycolors, x.intersp=2, y.intersp=5,text.width=0.45, cex=1.3, bty='n')
dev.off()
######### GDP TO EMPLOYMENT #########
e <- read.csv("./CSV/GDP_Employment.csv", header=TRUE, as.is=TRUE)
str(e)
e$Date <- as.Date( as.character( e$Date ) )
year.cat.2 <- function(x) {
year <- as.numeric(format(x, '%Y'))
year <- year-(year %%10)
}
e$mdate <- sapply(e$Date, FUN=year.cat.2)
e$mdate <- factor(e$mdate, levels=unique(e$mdate), ordered=TRUE)
mycolors = c("darkgreen", "brown", "turquoise", "orange", "purple", "green", "blue", "red")
pdf(file="GDP_Employ.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(e$Employed, e$GDP, ylim=c(0, 1.1*max(e$GDP)),
xlab="Employed Persons (Thousands)", ylab="GDP (Billions)", main="GDP & Employed Persons (1948-2012)",
col=mycolors[e$mdate], pch=20, cex=1)
mtext("Source: Establishment Survey & St. Louis Fred", cex=0.8, padj=-1)
legend("topleft", horiz=TRUE,legend=paste(levels(e$mdate), "s", sep=""), text.col=mycolors,
x.intersp=3, y.intersp=3, text.width=1, cex=1.7, bty='n', adj=1)
dev.off()
# Last 14 Years
e2 <- e[ e$Date >= as.Date('1998-01-01'),]
e2$mdate <- sapply(e2$Date, FUN=year.cat)
e2$mdate <- factor(e2$mdate, levels=unique(e2$mdate), ordered=TRUE)
pdf(file="GDP_Employ_2.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(e2$Employed, e2$GDP,
xlab="Employed Persons (Thousands)", ylab="GDP (Billions)",
main="GDP & Employed Persons (1998-2012)",
col=mycolors[e2$mdate], pch=20, cex=1.5)
mtext("Source: Establishment Survey & St. Louis Fred", cex=0.8, padj=-1)
legend("topleft", legend=paste(a <- levels(e2$mdate),"-", as.numeric(substring(a,3,4))+1, sep=""),
text.col=mycolors, cex=1.4,
x.intersp=6, y.intersp=1.5, text.width=4,col=mycolors, adj=1, ncol=2, bty='n')
dev.off()
######### REAl GDP TO EMPLOYMENT (NOVEMBER 1948=100) #########
r <- read.csv("./CSV/Real_GDP_Force_2.csv", header=TRUE, as.is=TRUE)
str(r)
r$Date <- as.Date( as.character( r$Date ) )
r$mdate <- sapply(r$Date, FUN=year.cat.2)
r$mdate <- factor(r$mdate, levels=unique(r$mdate), ordered=TRUE)
mycolors = c("darkgreen", "brown", "turquoise", "orange", "purple", "green", "blue", "red")
pdf(file="REAL_GDP_Employ.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(r$Employ, r$GDP, ylim=c(0, 1.1*max(r$GDP)),
xlab="Employed Persons (Thousands)", ylab="Real GDP Index (November 1948=100)",
main="Real GDP & Employed Persons (1948-2012)",
col=mycolors[r$mdate], pch=20, cex=1)
mtext("Source: Establishment Survey & St. Louis Fred", cex=0.8, padj=-1)
legend("topleft", horiz=TRUE,legend=paste(levels(r$mdate), "s", sep=""), text.col=mycolors,
x.intersp=3, y.intersp=3, text.width=1, cex=1.7, bty='n', adj=1)
dev.off()
######### LABOR FORCE PARTIPATION #########
p <- read.csv("./CSV/Participation.csv", header=TRUE, as.is=TRUE)
str(p)
p$Date <- as.Date( as.character( p$Date ) )
at = format(d$Date, '%m') == '01' & as.numeric(format(d$Date, '%Y')) %% 5 == 0
pdf(file="Labor_Participation.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(p$Date, p$Partic, col="black", type='l', xaxt='n',
xlab="Date", ylab="Participation Rate", main="Labor Force Participation Rate (1948-2012)")
mtext("Source: Current Population Survey", cex=0.8, padj=-1)
abline(h=p$Partic[nrow(p)], col='red', lwd=0.5)
axis(side=1, at=p$Date[ at ], labels=format(p$Date[at], '%Y'))
dev.off()
######### LABOR FORCE TO POPULATION #########
ep <- read.csv("./CSV/Employ_Pop_Ratio.csv", header=TRUE, as.is=TRUE)
str(ep)
ep$Date <- as.Date( as.character( ep$Date ) )
at = format(ep$Date, '%m') == '01' & as.numeric(format(ep$Date, '%Y')) %% 5 == 0
pdf(file="Employ_Population.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(ep$Date, ep$Ratio, col="black", type='l', xaxt='n',
xlab="Date", ylab="Ratio (Thousands / Thousands)",
main="Employment to Population Ratio (1948-2012)")
mtext("Source: Current Population Survey", cex=0.8, padj=-1)
abline(h=ep$Ratio[nrow(ep)], col='red', lwd=0.5)
axis(side=1, at=ep$Date[ at ], labels=format(ep$Date[at], '%Y'))
dev.off()
######### CORPORATE PROFITS / GDP #########
pg <- read.csv("./CSV/Profit_GDP.csv", header=TRUE, as.is=TRUE)
str(pg)
pg$Date <- as.Date( as.character( pg$Date ) )
at = format(pg$Date, '%m') == '01' & as.numeric(format(pg$Date, '%Y')) %% 5 == 0
# PROFIT
pdf(file="Corp_Profit.pdf",width=11,height=8.5)
par(mfrow=c(1,2), mar=c(5.1, 4.8, 4.8, 2.1))
plot(pg$Date, pg$Profit, ylim=c(1, 1.1*max(pg$Profit)), col="red", type='l',
xlab="Date", ylab="Profit (Billions of USD)",
main="Corporate Profits (1947-2012)", xaxt='n')
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=pg$Date[ at ], labels=format(pg$Date[at], '%Y'))
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+2000, density=100, col=rcol)
plot(pg$Date, pg$PG, ylim=c(0, 1.1*max(pg$PG)), col="red", type='l',
xlab="Date", ylab='Profit / GDP (Billions of $ / Billions of $)',
main="Corporate Profits Share Of GDP (1947-2012)", xaxt='n')
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=pg$Date[ at ], labels=format(pg$Date[at], '%Y'))
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1000, ytop=1.1*max(d$Mean)+1000, density=100, col=rcol)
dev.off()
######### WAGES / GDP #########
cg <- read.csv("./CSV/Comp_GDP.csv", header=TRUE, as.is=TRUE)
str(cg)
cg$Date <- as.Date( as.character( cg$Date ) )
# Need to rep Sup
for (i in 1:length(cg$Sup)) {
index <- ((i*4)-3)
sup <- cg$Sup[i]
cg$Supmod[index:(index+3)] <- sup
}
cg$Wagep <- cg$Wage / cg$GDP
cg$Wages <- (cg$Wage + cg$Supmod) / cg$GDP
at = format(cg$Date, '%m') == '01' & as.numeric(format(cg$Date, '%Y')) %% 5 == 0
pdf(file="Labor_Share.pdf",width=11,height=8.5)
par(mfrow=c(1,2), mar=c(5.1, 4.8, 4.8, 2.1))
plot(cg$Date, cg$Wagep, ylab="Wages / GDP (Billions of $ / Billions of $)",
xlab="Date", main="Labor's Share of GDP", type='l', col="red", xaxt='n')
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=cg$Date[ at ], labels=format(cg$Date[at], '%Y'))
abline(h=cg$Wagep[nrow(cg)], col="black", lwd=0.5, lty=2)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=0, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
plot(cg$Date, cg$Wages, ylab="Wages + Supplements / GDP",
xlab="Date", main="Labor's Share (+ Supplements) of GDP",
type='l', col="red", xaxt='n')
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=cg$Date[ at ], labels=format(cg$Date[at], '%Y'))
abline(h=cg$Wages[nrow(cg)], col="black", lwd=0.5, lty=2)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1, ytop=1, density=100, col=rcol)
dev.off()
######### CORPORATE PROFIT TO WAGE GROWTH #########
pw2 <- read.csv("./CSV/Profit_Comp_1970.csv", header=TRUE, as.is=TRUE)
str(pw2)
pw2$Date <- as.Date( as.character( pw2$Date ) )
at = format(pw2$Date, '%m') == '01' & as.numeric(format(pw2$Date, '%Y')) %% 5 == 0
pdf(file="Labor_VS_Corp.pdf",width=11,height=8.5)
par(mfrow=c(1,2), mar=c(5.1, 4.8, 4.8, 2.1))
plot(pw2$Date, pw2$WASCUR, ylab="Billions of $", xlab="Date",
main="Wages & Corporate Profits",type='l', col="blue", xaxt='n')
points(pw2$Date, pw2$CP, type='l', col='red')
legend(x=as.Date("1973-01-01"), y=6500, legend=c('Wages', 'Corporate Profits'),
col=c('blue', 'red'), text.col="black", lwd=2, cex=1,
text.width=3, seg.len=1.2, y.intersp=1.5, bty='n', x.intersp=2, adj=0 )
axis(side=1, at=pw2$Date[ at ], labels=format(pw2$Date[at], '%Y'))
plot(pw2$Date, pw2$CPT, type='l',
ylab="% Change Since 1970", xlab="Date", main="Change in Wages & Corporate Profits 1970 - 2012",
xaxt='n', col='red')
points(pw2$Date, pw2$WageT, type='l', col='blue')
axis(side=1, at=pw2$Date[ at ], labels=format(pw2$Date[at], '%Y'))
legend(x=as.Date("1973-01-01"), y=3400, legend=c('Wages', 'Corporate Profits'),
col=c('blue', 'red'), text.col="black", lwd=2, cex=1,
text.width=3, seg.len=1.2, y.intersp=1.5, bty='n', x.intersp=2, adj=0 )
dev.off()
######### JOB GROWHT BY DECADE #########
te <- read.csv("./CSV/Total_Employ.csv", header=TRUE, as.is=TRUE)
str(te)
te$Date <- as.Date( as.character( te$Date ) )
te <- te[format(te$Date, '%Y') >= "1940",]
at = as.numeric(format(te$Date, '%Y')) %% 10 == 0 & format(te$Date, '%m') == "01"
at2 = substring(format(te$Date, '%Y'),1,3) == "194" & format(te$Date, '%m') =="01"
years <- seq(1,10, by=1)
for (i in 1:nrow(te)) {
a <- ((i-1)%/% 120)
init <- te$Employ[((a*120)+1)]
te$Perc[i] <- 100*((te$Employ[i]-init)/init)
}
mycolors = c("darkgreen", "brown", "turquoise", "orange", "purple", "blue", "red")
pdf(file="Employment_Growth.pdf",width=11,height=8.5)
par(mar=c(5.1, 5.0, 4.1, 2.1))
plot(te$Perc[which(at)[1]:(which(at)[2]-1)],
type="l", xaxt='n', col=mycolors[1], ylim=c(2*min(te$Perc), 1.1*max(te$Perc)),
ylab="Cumulative Percent Change", xlab="Years Into The Decade", main="Employment Growth By Decade (1940s-2000s)")
axis(1, at=c(13, 25, 37, 49, 61, 73, 85, 97, 109, 121), labels=years)
mtext("Source: Bureau of Labor Statistics", cex=0.8, padj=-1)
text(x=120, y=(te$Perc[which(at)[2]-1]+2),
labels=paste(format(te$Date[which(at)[1]], '%Y'), "s", sep = ""),
col=mycolors[1], cex=1.2)
for (i in 2:(length(which(at))-1)){
points(te$Perc[which(at)[i]:(which(at)[i+1]-1)],
type="l", xaxt='n', col=mycolors[i])
h <- te$Perc[which(at)[i+1]-1]
if (i==6)
h <- h-3
if (i==5)
h <- h+1
text(x=120, y=h, labels=paste(format(te$Date[which(at)[i]], '%Y'), "s", sep = ""),
col=mycolors[i], cex=1.2)
}
dev.off()
gg <- read.csv("./CSV/GDP_Growth.csv", header=TRUE, as.is=TRUE)
str(gg)
gg$Date <- as.Date( as.character( gg$Date ) )
at = as.numeric(format(gg$Date, '%Y')) %% 10 == 0 & format(gg$Date, '%m') == "01"
at2 = substring(format(gg$Date, '%Y'),1,3) == "195" & format(gg$Date, '%m') =="01"
for (i in 1:nrow(gg)) {
a <- ((i-1)%/% 40)
init <- gg$GDP[((a*40)+1)]
gg$Perc[i] <- 100*((gg$GDP[i]-init)/init)
}
pdf(file="GDP_Growth.pdf",width=11,height=8.5)
par(mar=c(5.1, 5.0, 4.1, 2.1))
plot(gg$Perc[which(at)[1]:(which(at)[2]-1)],
type="l", xaxt='n', col=mycolors[1], ylim=c(2*min(gg$Perc), 1.1*max(gg$Perc)),
ylab="Cumulative Percent Change", xlab="Years Into The Decade", main="GDP Growth By Decade (1950s-2000s)")
axis(1, at=c(5, 9, 13, 17, 21, 25, 29, 33, 37, 40), labels=years)
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
text(x=40, y=(gg$Perc[which(at)[2]-1]+2)-8,
labels=paste(format(gg$Date[which(at)[1]], '%Y'), "s", sep = ""),
col=mycolors[1], cex=1.2)
for (i in 2:(length(which(at))-1)){
points(gg$Perc[which(at)[i]:(which(at)[i+1]-1)],
type="l", xaxt='n', col=mycolors[i])
h <- gg$Perc[which(at)[i+1]-1]
if (i==2)
h <- h+3
text(x=40, y=h, labels=paste(format(gg$Date[which(at)[i]], '%Y'), "s", sep = ""),
col=mycolors[i], cex=1.2)
}
dev.off()
pdf(file="GDP_VS_Employment_Growth.pdf",width=11,height=8.5)
par(mfrow=c(1,2), mar=c(5.1, 5.0, 4.1, 2.1))
at = as.numeric(format(te$Date, '%Y')) %% 10 == 0 & format(te$Date, '%m') == "01" & format(te$Date,'%Y') > "1940"
mycolors = c("brown", "darkgreen", "orange", "purple", "blue", "red")
plot(te$Perc[which(at)[1]:(which(at)[2]-1)],
type="l", xaxt='n', col=mycolors[1],
ylim=c(2*min(te$Perc), 1.1*max(te$Perc[format(te$Date,'%Y')>="1950"])),
ylab="Cumulative Percent Change", xlab="Years Into The Decade",
main="Employment Growth By Decade (1950s-2000s)")
axis(1, at=c(13, 25, 37, 49, 61, 73, 85, 97, 109, 121), labels=years)
mtext("Source: Bureau of Labor Statistics", cex=0.8, padj=-1)
text(x=115, y=(te$Perc[which(at)[2]-1]+2),
labels=paste(format(te$Date[which(at)[1]], '%Y'), "s", sep = ""),
col=mycolors[1], cex=1.2)
for (i in 2:(length(which(at))-1)){
points(te$Perc[which(at)[i]:(which(at)[i+1]-1)],
type="l", xaxt='n', col=mycolors[i])
h <- te$Perc[which(at)[i+1]-1]
if (i==6)
h <- h-3
if (i==5)
h <- h+1
text(x=115, y=h, labels=paste(format(te$Date[which(at)[i]], '%Y'), "s", sep = ""),
col=mycolors[i], cex=1.2)
}
at = as.numeric(format(gg$Date, '%Y')) %% 10 == 0 & format(gg$Date, '%m') == "01"
plot(gg$Perc[which(at)[1]:(which(at)[2]-1)],
type="l", xaxt='n', col=mycolors[1], ylim=c(2*min(gg$Perc), 1.1*max(gg$Perc)),
ylab="Cumulative Percent Change", xlab="Years Into The Decade", main="GDP Growth By Decade (1950s-2000s)")
axis(1, at=c(5, 9, 13, 17, 21, 25, 29, 33, 37, 40), labels=years)
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
text(x=38.5, y=(gg$Perc[which(at)[2]-1]+2)-8,
labels=paste(format(gg$Date[which(at)[1]], '%Y'), "s", sep = ""),
col=mycolors[1], cex=1.2)
for (i in 2:(length(which(at))-1)){
points(gg$Perc[which(at)[i]:(which(at)[i+1]-1)],
type="l", xaxt='n', col=mycolors[i])
h <- gg$Perc[which(at)[i+1]-1]
if (i==2)
h <- h+3
text(x=38.5, y=h, labels=paste(format(gg$Date[which(at)[i]], '%Y'), "s", sep = ""),
col=mycolors[i], cex=1.2)
}
dev.off()
######### LABOR SHARE #########
# Non Farm Business Sector
le <- read.csv("./CSV/Labor_Share.csv", header=TRUE, as.is=TRUE)
str(le)
le$Date <- as.Date( as.character( le$Date ) )
at = format(le$Date, '%m') == '01' & as.numeric(format(le$Date, '%Y')) %% 5 == 0
pdf(file="Labor_Share_Value_Add.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(le$Date, le$Share, type="l", col="red",
xlab="Date", ylab="Index: March 2001 = 100",
main="Labor's Share of Value Add", xaxt='n')
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=le$Date[ at ],labels=format(le$Date[at], '%Y'))
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-1, ytop=120, density=100, col=rcol)
dev.off()
######### QUITS #########
q <- read.csv("./CSV/Quits.csv", header=TRUE, as.is=TRUE)
str(q)
q$Date <- as.Date( as.character( q$Date ) )
pdf(file="Quits_Rate.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(q$Date, q$Quit, xlab="Date", ylab="Quits Rate",
main="Quits Rate (2000-2013)", type='l', col="red")
mtext("Source: JOLTS", cex=0.8, padj=-1)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-1, ytop=4, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-1, ytop=4, density=100, col=rcol)
dev.off()
######### SOFTWARE INVESTMENT PER WORKER #########
se <- read.csv("./CSV/Software_Employ.csv", header=TRUE, as.is=TRUE)
str(se)
se$Date <- as.Date( as.character( se$Date ) )
at = format(se$Date, '%m') == '01' & as.numeric(format(se$Date, '%Y')) %% 5 == 0
pdf(file="Investment_Per_Worker.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 4))
plot(se$Date, se$Perc, xlab="Date", ylab="Investment per Employed Person (Billions of $ / Thousands of Persons)",
main="Private Nonresidential Investment in Equipment & Software", type='l', col="red",
xaxt='n', yaxt='n')
text(x=se$Date[which(format(se$Date,'%Y')=="1981")[4]], y=0.45,
labels="Investment per Employee", col="red", cex=1)
axis(2, pretty(c(0, 1.1*max(se$Perc))), col='red')
mtext("Source: FRED National Accounts Data, Bureau of Labor Statistics", cex=0.8, padj=-1)
axis(side=1, at=se$Date[ at ],labels=format(se$Date[at], '%Y'))
par(new=T)
plot(se$Date, se$Invest, type='l', col="blue", xaxt='n', axes=F, , ylab='', xlab='')
text(x=se$Date[which(format(se$Date,'%Y')=="2000")[1]], y=400,
labels="Total Investment", col="blue", cex=1)
axis(4, pretty(c(0, 1.1*max(se$Invest))), col='blue')
mtext("Private Fixed Investment (Billions of $)", 4,padj=4, cex=1)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=-500, ytop=1500, density=100, col=rcol)
dev.off()
######### PRODUCTIVITY WAGE GROWTH SEPERATION #########
#output per hour
#Real compensation per hour
#January 1980 = 100
pp <- read.csv("./CSV/Output_Comp.csv", header=TRUE, as.is=TRUE)
str(pp)
pp$Date <- as.Date( as.character( pp$Date ) )
at = format(le$Date, '%m') == '01' & as.numeric(format(le$Date, '%Y')) %% 5 == 0
pdf(file="Productivity_Compensation_2.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(pp$Date, pp$Output, xlab="Date", ylab="Output Per Hour & Real Wages Per Hour (1980=100)",
main="Wage Productivity Gap",
type='l', col="blue", xaxt='n')
points(pp$Date, pp$Comp, type='l', col="red")
mtext("Source: FRED National Accounts Data", cex=0.8, padj=-1)
axis(side=1, at=pp$Date[ at ],labels=format(se$Date[at], '%Y'))
text(x=pp$Date[which(format(pp$Date,'%Y')=="2000")[1]], y=100,
labels="Real Wages Per Hour", col="red", cex=1.2)
text(x=pp$Date[which(format(pp$Date,'%Y')=="1990")[1]], y=140,
labels="Output Per Hour", col="blue", cex=1.2)
rect(xleft=as.Date('2007-10-01'), xright=as.Date('2009-07-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('2001-04-01'), xright=as.Date('2001-10-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1990-07-01'), xright=as.Date('1991-04-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1981-07-01'), xright=as.Date('1982-10-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1973-10-01'), xright=as.Date('1975-04-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1969-10-01'), xright=as.Date('1970-11-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1960-04-01'), xright=as.Date('1961-01-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1957-10-01'), xright=as.Date('1958-04-01'),
ybottom=0, ytop=200, density=100, col=rcol)
rect(xleft=as.Date('1953-07-01'), xright=as.Date('1954-04-01'),
ybottom=0, ytop=200, density=100, col=rcol)
dev.off()
######### PRODUCTIVITY vs MEDIAN INCOME #########
# Data is from: http://stateofworkingamerica.org/charts/productivity-and-real-median-family-income-growth-1947-2009/
pm <- read.csv("./CSV/Product_Median.csv", header=TRUE, as.is=TRUE)
str(pm)
pdf(file="Productivity_vs_Median_Income.pdf",width=11,height=8.5)
par(mar=c(5.1, 4.8, 4.8, 2.1))
plot(pm$Year, pm$Product, xlab="Date", ylab="Cumulative Percent Change Since 1947",
main="Productivity vs Real Median Family Income (1947-2011)",
type='l', col="blue")
points(pm$Year, pm$Median, type='l', col='red')
mtext("Source: www.stateofworkingamerica.org", cex=0.8, padj=-1)
text(x=2000, y=pm$Median[pm$Year==2000]-0.6, labels="Real Median Family Income", col="red", cex=1.2)
text(x=1990, y=pm$Product[pm$Year==2000]-0.2, labels="Productivity", col="blue", cex=1.2)
dev.off()
#############################################
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