The course deals with the theory and methodology aimed at measuring poverty, inequality and well-being. Particular attention is given to the construction of indicators and to present their main applications. The course also provides an introduction to regression models (cross-sectional and longitudinal) for poverty research.
Part I
Slides, Stata files and other materials provided during the course through the Moodle page.
For the Stata software: Ulrich Kohler and Frauke Kreuter (2013), Data Analysis Using Stata, Third edition, Stata Press.
Part II
OECD and Joint Research Centre-European Commission. (2008). Handbook on constructing composite indicators: methodology and user guide. OECD publishing. Available at: https://www.oecd.org/sdd/42495745.pdf
Haughton, J., & Khandker, S. R. (2009). Handbook on poverty+ inequality. World Bank Publications. Available at: https://sites.suffolk.edu/jonathanhaughton/handbook-on-poverty-and-inequality/
Part III
Materials will be indicated during the classes.
Obiettivi Formativi
The course aims at providing knowledge and competences about the methods to measure and analyze poverty and wellbeing.
Prerequisiti
Knowledge of basic multivariate statistics.
Metodi Didattici
Lectures, seminars and lab sessions.
Use of e-learning platform Moodle where the teaching materials will be uploaded.
Altre Informazioni
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Modalità di verifica apprendimento
A project report based on empirical analyses in Stata and their discussion (details will be given during the course).
Oral exam (including the discussion of the project and theory questions on all topics covered during the course).
Programma del corso
Part I
Data and statistical methods for examining poverty determinants.
- Types of designs and data.
- Distinguishing causality from association in poverty research.
- Cross-sectional and longitudinal data and models for studying poverty.
Part II
Composite indicators: general issues and applications to measuring poverty and wellbeing.
- Steps for constructing a composite indicator.
(Developing a theoretical framework.
Selecting variables. Imputation of missing values. Multivariate analyses. Normalisation of data. Weighting and aggregation. Robustness and sensitivity. Links to other variables. Presentation and dissemination. - Quality assessment of composite indicators. - Measures of poverty and wellbeing (economic and more general measures).
Part III
Seminars
Population and human capital measures for comparisons across countries and within societies.
Comparing human capital, development, and their correlates
Role of families in perpetuating inequality and poverty
Poverty and wellbeing in later life
overview of indicators for measuring poverty and well-being in later life
steps for constructing composite indicators with SHARE survey: frailty (well-being) and social/material deprivation (poverty)