Use Quandl to download country-year observations from the Luxembourg Income Study.

LIS.r

setwd("~/Documents/Data/LIS")

## list of countries

lis = read.csv("lis.tsv", sep = "\t", header = FALSE)
lis$ctn = countrycode(lis$V1, "country.name", "continent")
len = sapply(lis$V1, function(x) max(lis$V3[lis$V1 == x]) - min(lis$V2[lis$V1 == x]))
qplot(data = lis, y = reorder(V1, len, mean), yend = V1, x = V2, xend = V3, 
      size = I(2), geom = "segment") + 
  theme_minimal(16) +
  labs(y = NULL, x = NULL)

lis = toupper(lis[, 1])
# lis = c("AUSTRIA", "BELGIUM", "BRAZIL", "CANADA", "CHINA", "COLOMBIA", 
#         "CZECH REPUBLIC", "DENMARK", "ESTONIA", "FINLAND", "FRANCE", 
#         "GERMANY", "GREECE", "GUATEMALA", "HUNGARY", "INDIA", "IRELAND", 
#         "ISRAEL", "ITALY", "JAPAN", "LUXEMBOURG", "MEXICO", "NETHERLANDS", 
#         "NORWAY", "PERU", "POLAND", "ROMANIA", "RUSSIA", "SLOVAK REPUBLIC", 
#         "SLOVENIA", "SOUTH AFRICA", "SOUTH KOREA", "SPAIN", "SWEDEN", 
#         "SWITZERLAND", "TAIWAN", "UNITED KINGDOM", "UNITED STATES", "URUGUAY")

## ask for the data

library(Quandl)
library(plyr)
library(reshape)

lis = lapply(lis, function(country) {
  q = Quandl(paste0("LIS/LIS_", gsub("\\s", "", country)), collapse = "annual", 
             authcode = "[TOKEN]")
  q = melt(q, id = "Year")
  year = as.numeric(substr(q$Year, 0, 4))
  q = cbind(country, year, q)
  q$Year = NULL
  return(q)
})
lis = rbind.fill(lis)
sort_df(lis, c("cty", "year"))
str(lis)

if(!file.exists("lis.rda")) save(lis, file = "lis.rda")
load("lis.rda")

## plot

library(countrycode)
library(ggplot2)
library(RColorBrewer)

eur = (countrycode(lis$country, "country.name", "continent") == "Europe")
usa = (lis$country == "UNITED STATES")
var = "Percentile Ratio (90/10)"
LIS = subset(lis[eur | usa, ], variable == var)

(mu = mean(LIS$value, na.rm = TRUE))
(sd = sd(LIS$value, na.rm = TRUE))

simpleCap <- function(x) {
  s <- strsplit(x, " ")[[1]]
  paste(toupper(substring(s, 1,1)), substring(s, 2),
        sep="", collapse=" ")
}
LIS$country = sapply(as.character(tolower(LIS$country)), simpleCap)

qplot(data = LIS, x = year, y = value, group = country, 
      colour = factor(as.integer(value)), size = I(1), geom = "line") + 
  geom_hline(y = mu, linetype = "dashed", colour = "grey") +
  geom_hline(y = mu + sd, linetype = "dotted", colour = "grey") +
  geom_hline(y = mu - sd, linetype = "dotted", colour = "grey") +
  scale_colour_manual("", values = rev(brewer.pal(5, "RdYlGn"))) +
  facet_wrap(~ country) +
  theme_minimal(16) +
  theme(axis.line.y = element_line(size = 1, colour = "black"), 
        panel.grid = element_blank(),
        legend.position = "none") +
  labs(x = NULL, y = paste0(var, "\n"))

LIS.README.md

You will need to insert your authentification token where the code says [TOKEN].

The data availability ranges from null to full in function of the country of interest:

Here's a quick plot of the 90/10 percentile ratio for European countries:

The capitalization of country names is performed by a function from Stack Overflow.

lis.tsv

Australia  1981	2003
Austria	1987	2004
Belgium	1985	2000
Brazil	2006	2006
Canada	1971	2007
China	2002	2002
Colombia	2004	2010
Czech Republic	1992	2004
Denmark	1987	2004
Estonia	2000	2004
Finland	1987	2004
France	1979	2005
Germany	1973	2010
Greece	1995	2010
Guatemala	2006	2006
Hungary	1991	2005
India	2004	2004
Ireland	1987	2004
Israel	1979	2007
Italy	1986	2010
Japan	2008	2008
Luxembourg	1985	2004
Mexico	1984	2004
Netherlands	1983	2004
Norway	1979	2004
Peru	2004	2004
Poland	1986	2004
Romania	1995	1997
Russia	2000	2000
Slovak Republic	1992	2010
Slovenia	1997	2004
South Africa	2008	2010
South Korea	2006	2006
Spain	1980	2010
Sweden	1967	2005
Switzerland	1982	2004
Taiwan	1981	2005
United Kingdom	1969	2010
United States	1974	2010
Uruguay	2004	2004