- Docente: Michele Costa
- Credits: 5
- SSD: SECS-S/01
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in STATISTICAL SCIENCES (cod. 8054)
Learning outcomes
The purpose of the course is to introduce the most widespread methods for inequality measurement and human capital evaluation. A particular emphasis is used to uncover the Gini inequality index, the entroy indexes and the decomposition of inequality indicators.
Course contents
Statistical methods for inequality measurement
The measurement of total inequality
The inequality decomposition
Gini index and generalized entroy indices
Unidimensional measurement of poverty
Poverty lines, headcount ratio H, human poverty index HPI
Multidimensional measurement of poverty
Latent variables models for human capital measurement
Readings/Bibliography
A. Sen, On economic inequality, Clarendon, 1997
Teaching methods
Italian households micro data on social and economic conditions collected by the Bank of Italy are analyzed at computer laboratory
Assessment methods
oral exam
Teaching tools
Computer laboratory
Office hours
See the website of Michele Costa