2025
Quantitative Methods in Socioeconomics
Name: Quantitative Methods in Socioeconomics
Code: ECN09808D
6 ECTS
Duration: 15 weeks/162 hours
Scientific Area:
Ciências Económicas e Sociais
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
Introducing the main analytical methods in socio-economics and the mathematical programming as tools for
the decision making.
Develop skills of reading and criticizing/commenting on socio-economic papers and studies.
the decision making.
Develop skills of reading and criticizing/commenting on socio-economic papers and studies.
Contents
Module I Multivariate analysis
An introduction to different methods.
Linear multiple regression model: specification; estimation; statistical inference; prediction.
Factor analysis of a cloud of points.
Simple correspondence analysis. Typical problems. Output interpretation. Multiple correspondence analysis.
Principal component analysis. Output interpretation.
Cluster analysis: classification concepts. Similarity measures. Hierarchical agglomerative and iterative
partitioning methods.
Module II Multi-criteria decision-making
Concepts: Attribute, objective, goal and criteria. Technical versus decisional problems. Optimal solutions and
efficient frontier (condition of Pareto optimum). Trade-offs.
Multi-objective programming and goal programming. Using goal programming for building an indicator of
environmental, social and economic impact.
Compromise Programming. Ideal point, distance metrics, compromise set.
Interactive programming. The displaced ideal method.
An introduction to different methods.
Linear multiple regression model: specification; estimation; statistical inference; prediction.
Factor analysis of a cloud of points.
Simple correspondence analysis. Typical problems. Output interpretation. Multiple correspondence analysis.
Principal component analysis. Output interpretation.
Cluster analysis: classification concepts. Similarity measures. Hierarchical agglomerative and iterative
partitioning methods.
Module II Multi-criteria decision-making
Concepts: Attribute, objective, goal and criteria. Technical versus decisional problems. Optimal solutions and
efficient frontier (condition of Pareto optimum). Trade-offs.
Multi-objective programming and goal programming. Using goal programming for building an indicator of
environmental, social and economic impact.
Compromise Programming. Ideal point, distance metrics, compromise set.
Interactive programming. The displaced ideal method.
Teaching Methods
Theoretical teaching of each method is anticipated by typical problem and complemented by training in simple
problems solving. These problems include the interpretation of model output and/or the mathematical
formulations.
The evaluation of students is organized by modules, for which there are 2 written tests along the semester.
Each two students select a specific problem and solve it by a studied method. Marks in these tests are
combined with those from the student work application.
problems solving. These problems include the interpretation of model output and/or the mathematical
formulations.
The evaluation of students is organized by modules, for which there are 2 written tests along the semester.
Each two students select a specific problem and solve it by a studied method. Marks in these tests are
combined with those from the student work application.
Accreditations and Certifications
