Competencies and objectives
- Course context for academic year 2023-24
- Course content (verified by ANECA in official undergraduate and Master’s degrees)
- Learning outcomes (Training objectives)
- Specific objectives stated by the academic staff for academic year 2023-24
Course context for academic year 2023-24
Second year optional course on of the PhD Programme in Quantitative Economics
Course content (verified by ANECA in official undergraduate and Master’s degrees)
General Competences (CG)
- CG1 : Capacity to carry out research work.
- CG2 : Capacity to find data (natural and experimental) and analyse it.
- CG3 : Capacity to apply economic theory to represent real situations.
- CG4 : Capacity for teamwork.
- CG5 : Capacity for self-learning.
- CG6 : Ethical commitment and social responsibility at work, respecting the environment, being aware and understanding the importance of respect for fundamental rights, equal opportunities for men and women, universal accessibility for the disabled and respect for the values of a peaceful, democratic society.
- CG7 : Analyse problems using critical reasoning, without prejudice and with precision and rigor.
- CG8 : Capacity for synthesis.
Specific Competences (CE)
- CE1 : Capacity to read Economic research articles in a reasoned fashion and evaluate them critically, understand their essential contributions and weaknesses.
- CE2 : Capacity to understand how the technical problems faced by authors of research articles have been resolved in each case.
- CE3 : Capacity to test theorems and propositions.
- CE4 : Capacity to understand and reproduce empirical analyses and simulation experiments on which the conclusions of research articles written by other authors are based.
- CE5 : Capacity to present important economic problems precisely and respond adequately to said problems by using the techniques learnt on the different courses, using theoretical and empirical analyses or simulations if necessary.
Learning outcomes (Training objectives)
Specific objectives stated by the academic staff for academic year 2023-24
This course will focus on the evaluation of social programs and will provide a thorough understanding of randomized evaluations. Through a combination of lectures and case studies from real randomized evaluations, the course will focus on the benefits and methods of randomization, choosing an appropriate sample size, and common threats and pitfalls to the validity of the experiment.
In addition to the lecture sequences, the course also includes various case studies. The case studies explore the concepts and issues discussed in the lecture sequences and involve some readings, followed by discussion topics. The discussion topics include multiple choice questions open response assessments. Students will also take multiple choice tests during the course that will be linked to the lectures’ contents and the compulsory readings for the case studies.