# New challenges in the measurement of economic inequalities and injustices

I will be in Aix this week for the workshop “New challenges in the measurement of economic inequalities and injustices” organized by Nicolas Gravel, Brice Magdalou and Patrick Moyes.

# Inequalities and Poverty #4

The fourth part of the graduate course on inequalities and povertywill be based on the slides below

# Inequalities and Poverty #3

The third part of the graduate course on inequalities and povertywill be based on the slides below

# Inequalities and Poverty #2

The second part of the graduate course on inequalities and poverty will be based on the slides below

Here are some reading for the course on inequalities,

# Inequality, Poverty and Welfare

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
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)`

# Modeling Incomes and Inequalities

Last week, in our Inequality course, we’ve been looking at data. We started with some simulated data, only a few of them

```> library("ineq")
> (income=sort(income))
[1]  19233  23707  53297  61667 218662```

How could we say that there is inequality in this sample? If we look at the wealth owned by the poorest, the poorest person (1 out of 5) owns 5% of the wealth; the bottom two (2 out of 5) own 11%, etc

```> income[1]/sum(income)
[1] 0.05107471
> sum(income[1:2])/sum(income)
[1] 0.1140305
> sum(income[1:3])/sum(income)
[1] 0.2555648
> sum(income[1:4])/sum(income)
[1] 0.4193262```

If we plot those values, we get Lorenz curve

```> plot(Lc(income))
> points(c(0:5)/5,c(0,cumsum(income)/sum(income)),pch=19,col="blue")
```

# Inequalities, course 2

As mentioned last week, tomorrow, we will work with datasets, and start the part on the econometrics of inequality. I have uploded some slides, but additional concepts and tools will be mentioned on the black board (or on the computer, while coding). We will use some simulated data (mentioned in the slides), as well as us_income, on binned data.

# Inequalities, course 1

The afternoon, we will have the first course on Inequalities. Slides are available from here.