For the fourth cours on Inequalities, we will get back on the quantile regression, and discuss welfare functions as well as poverty indices. Slides are now online
To illustrate, we will use the following datasets
uk88 <- read.csv("http://www.vcharite.univ-mrs.fr/pp/lubrano/cours/fes88.csv",sep=";",header=FALSE)$V1 uk92 <- read.csv("http://www.vcharite.univ-mrs.fr/pp/lubrano/cours/fes92.csv",sep=";",header=FALSE)$V1 uk96 <- read.csv("http://www.vcharite.univ-mrs.fr/pp/lubrano/cours/fes96.csv",sep=";",header=FALSE)$V1 cpi <- c(421.7, 546.4, 602.4) y88 <- uk88/cpi[1] y92 <- uk92/cpi[2] y96 <- uk96/cpi[3]
and for the part on applications of quantile regression
salary <- read.table("http://data.princeton.edu/wws509/datasets/salary.dat",header=TRUE)
OpenEdition suggests that you cite this post as follows:
Arthur Charpentier (February 4, 2015). Inequality, Poverty and Welfare. Freakonometrics. Retrieved March 20, 2025 from https://doi.org/10.58079/ouyg