Syllabus

European Indicators of poverty and vulnerabilities for Sustainable Development Goal and Seminars

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.

Maria Pia Sorvillo “Multidimensional Indicators for Sustainable Development Goals in Italy and Europe”

Marina Gandolfo “The implementation of the Agenda 2030 in Europe”

Jan van den Brakel “Big data in Official Statistics in Europe”

Mariola Chrzanowska “Surveying the poor and hard to reach populations in Europe”

Nina Drejerska “Tools for evaluating local policies in Europe”

Written exam.

Students can take the exam for the entire course, “European Indicators of poverty and vulnerabilities for Sustainable Development Goal and Seminars” (9 ECTS), or for the courses “European Statistical System and Data Production Model” (6 ECTS) with reduced program.

This course is part of a Jean Monnet Chair.

Attendance to the lectures is strongly suggested.

Wide reading and deep thinking are strongly recommended.

European Statistical System and Data Production Model

The course will be structured in two parts: i) European Statistical System; ii) and  Data Production Model.

The first module is on European Statistical System (3 ECTS) and focuses on 1) code of practice; 2)peer review; 3) statistical burden; 4) privacy and confidentially issues;

At the end of this module, students should be familiar with the official statistics and the ESS, its organization and activities and should know the main aspects linked to official data collection processes and release procedures.

The second module is on Data Production Model (3 ECTS) and is structured in five parts: i) Official national surveys; ii) Data process and quality: attributes and measurement; iii) Quality matrix; iv) Metadata; v) Monitoring statistical processes.

At the end of this module, students should be able to know how statistical processes are structured and how to manage data quality in official statistics.

At the end of the course student will be able to deal with small area estimation both at theoretical and empirical level.

Written exam.

Students can take the exam for the course “European Statistical System and Data Production Model” (6 ECTS) or for the course “European Indicators of poverty and vulnerabilities for Sustainable Development Goal and Seminars” (9 ECTS) from the Jean Monnet Chair 2018-2021, with expanded program.

This course is borrowed from the course “European Indicators of poverty and vulnerabilities for Sustainable Development Goal and Seminars” (9 ECTS) from the Jean Monnet Chair 2018-2021 (http://sampieuchair.ec.unipi.it/).

Attendance to the lectures is strongly suggested.

Wide reading and deep thinking are strongly recommended.

Small Area Methods for the Analysis of Multidimensional Poverty Data and Seminars

Description

The course offers a review of the main Small Area Estimation Methods and teach how to apply them to European survey data to have a local monitoring of the Sustainable Development Goals and to estimate deprivation and inequality indicators, focusing also in aggregating Multidimensional Indicators and on conceptualizing, defining and measuring poverty under the capability approach. 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 and to apply aggregation methods to indicators from the European survey data.

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.

Seminars and intensive lectures

Nikos Tzavidis: “Poverty mapping to study income and cultural diversity in Europe”

Vincenzo Mauro: “Aggregating Multidimensional Indicators in Europe”

Christian Morabito: “Vulnerable groups: child poverty, migration and gender in Europe”

Textbooks

Readings will be provided by the lecturers during the course.

Written exam.

Students can take the exam for the entire course, “Small Area methods for the analysis of multidimensional poverty data and seminars” (9 ECTS), or for the courses “Analysis of Survey Data and Small Area Estimation” (6 ECTS) with reduced program.

Course website

Other notes

This course is part of a Jean Monnet Chair.

Attendance to the lectures is strongly suggested.

Wide reading and deep thinking are strongly recommended.

Analysis of Survey data and Small Area Estimation

Lecturer

Pratesi Monica

Semester

Spring

ECTS

6

Description

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 course student will be able to deal with small area estimation both at the theoretical and empirical level.

Seminars

The Chair organizes also a cycle of seminars in cooperation with the Centre ASESD Camilo Dagum on spatial differences in price levels, income and poverty

Textbooks

Readings will be provided by the lecturers during the course.

Final valuation

Written exam.

Students can take the exam for the course “Analysis of Survey Data and Small Area Estimation” (6 ECTS) or for the course “Small Area methods for the analysis of multidimensional poverty data and seminars” (9 ECTS) from the Jean Monnet Chair 2018-2021, with expanded program.

Course website

Other notes

This course is borrowed from the course “Small Area methods for the analysis of multidimensional poverty data and seminars” (9 ECTS) from the Jean Monnet Chair 2018-2021 (http://sampieuchair.ec.unipi.it/).

Attendance to the lectures is strongly suggested.

Wide reading and deep thinking are strongly recommended.