The course aims at the definition and measurement of coherent and comparable multidimensional local indicators of poverty and vulnerabilities that can be useful for local stakeholders for monitoring Sustainable Development Goals. The traditional data collections methods used in EU Surveys (e.g EU-Survey Income Living Conditions, Household Budget Surveys, Labour Force Survey) are introduced, focusing on the sampling design, sample weighting and estimation. The course also offers a general introduction to the usage of administrative data and large datasets as sources of statistical data (Big Data), with an emphasis on multi-frame surveys. The data sources from the big data repositories are listed and examined, highlighting their potentialities and limitations in the study of poverty and living conditions. Students will learn both traditional and new survey techniques focusing on the problems that might arise in the definition and measure of local indicators of poverty and living conditions.

At the end of the module, students should be familiar with the theme of local indicators and should be aware of the main problems/challenges regarding the usage of different data sources on poverty.