First, load in some CPS data I had lying around:

library(ggplot2)
library(dplyr)
## 
## Attaching package: 'dplyr'
## 
## The following object is masked from 'package:stats':
## 
##     filter
## 
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
load("/media/john/Shared Linux_Windows Files1/MSA Level Inequality/Data/CPS_MSA_micro.rda")
CPI <- read.csv("/media/john/Shared Linux_Windows Files1/MSA Level Inequality/Data/CPI.csv")
CPS.work.hh<-merge(CPS.work.hh, CPI, by="year")
CPS.work.hh$cellmean_equivinc <- CPS.work.hh$cellmean_equivinc*(229.604/CPS.work.hh$CPI)
income_quantiles <- CPS.work.hh %>% group_by(., year) %>% 
  summarise(q10 = quantile(cellmean_equivinc, 0.1),
            q20 =quantile(cellmean_equivinc, 0.2),
            q30 =quantile(cellmean_equivinc, 0.3),
            q40 =quantile(cellmean_equivinc, 0.4),
            q50 =quantile(cellmean_equivinc, 0.5),
            q60 =quantile(cellmean_equivinc, 0.6),
            q70 =quantile(cellmean_equivinc, 0.7),
            q80 =quantile(cellmean_equivinc, 0.8),
            q90 =quantile(cellmean_equivinc, 0.9))

The income definition used here is equivilized household income. I essentially adjust for household size by using a square root equivalence scale. So each member of a household is assigned \(EHHI = \frac{HHI}{\sqrt{N}}\) in equivalent income. I also adjust for inflation using the CPI-U. How have incomes at the 10th, 50th (median) and 90th percentiles of the income distribution evolved over time?

ggplot(income_quantiles, aes(x=year, y=q10))+geom_point()+geom_line()+geom_smooth(method="lm")+
  labs(title="10th Percentile Household Income, 1968-2012")+xlab("Year")+ylab("Size-Adjusted Household Income")

ggplot(income_quantiles, aes(x=year, y=q50))+geom_point()+geom_line()+geom_smooth(method="lm")+
  labs(title="Median Household Income, 1968-2012")+xlab("Year")+ylab("Size-Adjusted Household Income")

ggplot(income_quantiles, aes(x=year, y=q90))+geom_point()+geom_line()+geom_smooth(method="lm")+
  labs(title="90th Percentile Household Income, 1968-2012")+xlab("Year")+ylab("Size-Adjusted Household Income")