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 and R scripts provided during lessons.
Agresti, A. (2018). Statistical methods for the social sciences. Pearson.
Stock, J. H., & Watson, M. W. (2020). Introduction to econometrics. Pearson.
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-andinequality/
Learning Objectives
The course aims at providing knowledge and competences about the methods to measure and analyze poverty and wellbeing.
Prerequisites
Knowledge of basic multivariable statistics.
Teaching Methods
Lectures, seminars and lab sessions.
Use of e-learning platform Moodle where the teaching materials will be uploaded.
Further information
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Type of Assessment
A project report based on empirical analyses preferably in R 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).
Course program
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 on additional topics related to poverty measurement and analysis
Sustainable Development Goals 2030
1 - No Poverty
3 - Good Health and Wellbeing
8 - Decent Work and Economic Growth