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B024217 - STATISTICAL INDICATORS: THEORY AND METHODOLOGY
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Further information
Type of Assessment
Course program
Academic Year 2016-17
Course year
Second year - Second Semester
Belonging Department
Statistics, IT and its applications "G. Parenti" (DISIA)
Course Type
Single education field course
Scientific Area
SECS-S/05 - SOCIAL STATISTICS
Credits
6
Teaching Hours
48
Teaching Term
27/02/2017 ⇒ 01/06/2017
Attendance required
No
Type of Evaluation
Final Grade
Course Content
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Course program
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Lectureship
Teaching Language
English
Course Content
The course deals with the theory and methodology aimed at constructing indicators and presenting their main applications. Particular attention will be given to the indicators of inequality and well-being. The course also provides a short introduction to spatial analisys of statistical indicators.
Suggested readings (Search our library's catalogue)
The textbooks will be announced at the beginning of classes.
Learning Objectives
The course aims at providing knowledge and competences about the indicators construction and application.
Prerequisites
Knowledge of basic multivariate statistics.
Teaching Methods
Lectures, seminars and lab sessions.
Use of e-learning platform Moodle where, in particular, will be upload the teaching materials.
Use of e-learning platform Moodle where, in particular, will be upload the teaching materials.
Further information
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Type of Assessment
The exam format is an individual oral examination based on the written project report (about 6000 words)
Course program
Part I
Steps for constructing a composite indicator
Developing a theoretical framework
Selecting variables
Reducing the complexity
The approaches to reduction
Synthesis of indicators: different perspectives
Synthesis of indicators: technical issues (aggregative-compensative approaches and non-compensative approaches)
Representing the complexity (dashboards)
Explaining the complexity: modelling indicators
Part II
Introduction to the measures of poverty and inequality
Definitions and measurement of economic inequality: size and factoral distributions
Kuznets ratio, Lorenz curve and Gini coefficient
Comparisons across measures
Kuznets’s Inverted-U Hypothesis
Types of poverty and their indicators
Measuring economic poverty: total poverty gap, The Foster-Greer-Thorbecke Index, Multidimensional Poverty Index
Monitoring poverty indicators
Redefining Kuznets’s curve
Within and between country inequality
Globalization and inequality
Indicators of health and education
Human development index: traditional and new approaches
The basics around the OECD framework
Governance statistics in OECD countries and beyond
Developing better well-being metrics
Measuring subjective well-being
Part III
What are the spatial data
Spatial data types
The spatial contiguity
Spatial weighting matrices
The statistical sources of spatial data
Global and local autocorrelation
Global indices of spatial autocorrelation and spatial correlogram
Indices of spatial autocorrelation and local Moran scatterplot
Steps for constructing a composite indicator
Developing a theoretical framework
Selecting variables
Reducing the complexity
The approaches to reduction
Synthesis of indicators: different perspectives
Synthesis of indicators: technical issues (aggregative-compensative approaches and non-compensative approaches)
Representing the complexity (dashboards)
Explaining the complexity: modelling indicators
Part II
Introduction to the measures of poverty and inequality
Definitions and measurement of economic inequality: size and factoral distributions
Kuznets ratio, Lorenz curve and Gini coefficient
Comparisons across measures
Kuznets’s Inverted-U Hypothesis
Types of poverty and their indicators
Measuring economic poverty: total poverty gap, The Foster-Greer-Thorbecke Index, Multidimensional Poverty Index
Monitoring poverty indicators
Redefining Kuznets’s curve
Within and between country inequality
Globalization and inequality
Indicators of health and education
Human development index: traditional and new approaches
The basics around the OECD framework
Governance statistics in OECD countries and beyond
Developing better well-being metrics
Measuring subjective well-being
Part III
What are the spatial data
Spatial data types
The spatial contiguity
Spatial weighting matrices
The statistical sources of spatial data
Global and local autocorrelation
Global indices of spatial autocorrelation and spatial correlogram
Indices of spatial autocorrelation and local Moran scatterplot