European Local Indicators of Poverty and Living Conditions: traditional and new survey techniques in the era of data deluge and Big data
Prof. in charge: Monica Pratesi
Typology: Lecture
Semester: Fall
ECTS: 9
Final valuation: written exam
Schedule of lectures and classes

The course aims to provide definition and measure of local indicators that be coherent and comparable across Europe and be useful and used by local stakeholders. It provides knowledge on the traditional data collections methods used in EU Surveys (e.g EU-Survey Income Living Conditions, Household Budget Surveys, Labour Force Survey) and a general introduction to the usage of administrative data sets and also large datasets as sources of statistical data (Big Data), with a focus on multi-frame surveys. It will tackle the most important topics in big data ranging from data collection, analysis and visualization, as well as applications of statistical models to Big data. At the end of the module student should be able to be confident with the theme of local indicators and Big Data in Official and should know the main problems/challenges linked to their usage as source of statistical data.
Students will learn traditional and new survey techniques and what might be the problems that arise in the definition and measure of local indicators of poverty and living conditions.

Handling Missing Data, Statistical Data Editing and Imputation
Prof. in charge: Natalie Shlomo
Typology: Intensive course
Semester: Fall

The course will provide students with knowledge and skills in advanced methods for compensating for missing data: alternative survey weighting methods for unit non-response and alternative methods of imputation for item-nonresponse. To introduce students to the concept of edit restrictions for identifying erroneous values and an overview of statistical data editing techniques.
Students will learn the fundamental small area methods and what might be the problems that arise in the application of them and in the definition of their statistical quality.

The estimation and computation of Income, Consumption and PPPs in the European Statistical System
Prof. in charge: Luigi Biggeri
Typology: Intensive course
Semester: Fall

The intensive course will be structured into two modules: i) European Statistical System; ii) Sources of data on Income Consumption and PPPs in the European Statistical System
The course will introduce to the principles of the ESS with attention to the data production model, statistical burden and privacy issues.
Students will learn the fundamental principles of the ESS and what might be the problems that arise in the application of them across the EU Member States and their National Statistical Agencies.

Analysis of European Data by Small Area Methods
Prof. in charge: Monica Pratesi
Typology: Lecture
Semester: Spring
ECTS: 9
Final valuation: written exam

The course will be structured in the following parts 1) Analysis of the collected data for estimation and testing for the phenomenon under study; definition of planned and unplanned domains. 2) Direct and indirect estimates for unplanned domains; R codes for the application of the SAE estimators (EURAREA and SAMPLE project libraries) 3) quality issues in SAE and usage of SAE in European Statistical System.
At the end of the module student will be able to deal with small area estimation both at the theoretical and empirical level.
Students will learn the fundamental small area methods and what might be the problems that arise in the application of them and in the definition of their statistical quality.

Reweighting estimates from European Sample Surveys
Prof. in charge: Risto Lehtonen
Typology: Intensive course
Semester: Spring

The intensive course will focus on weighting, reweighting and integration of sample surveys and data archives under a design-based approach.
Students will learn the fundamental principles of weighting and reweighting sample data to compensate for non sampling errors and integration under a design–based approach.

Variance estimation of some EU-SILC based indicators at regional level
Prof. in charge: Ralf Muennich
Typology: Intensive course
Semester: Spring

Aim of the course is to provide an in-depth insight to methods and problems of variance estimation in survey statistics and in complex indicators. The course also introduces students on how to implement the considered methods in R.
Students acquire profound methodological knowledge and are, therewith, prepared to thoroughly understand and judge respective methods from a theoretical as well as from a practical point of view.

Robustness of some EU-SILC based indicators at regional level
Prof. in charge: Francesca Gagliardi
Typology: Intensive course
Semester: Spring

The course will address some statistical aspects related to the construction from EU-SILC data of indicators of poverty and social exclusion for sub-national regions. Conceptual and methodological issues in going from the national level – for which EU-SILC surveys are primarily designed– to the regional level are discussed.
Students will learn the fundamental problems that arise in the construction from EU-SILC data of indicators of poverty and social exclusion for sub-national regions