Competencies and objectives


Course context for academic year 2023-24

Even though the course is self-contained, statistics and econometrics at an advanced undergraduate level are recommended. Computer applications will be based on GAUSS or MATLAB but no prior knowledge of this specific software is required because it will be quickly taught at the beginning.



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)

No data



Specific objectives stated by the academic staff for academic year 2023-24

The course is intended to provide participants with the necessary tools to apply state of the art techniques for the forecasting of macroeconomic and financial variables and turning points, with special emphasis on recent developments in “nowcasting” The course covers the required econometric theory but with the intention of putting it into practice in specific forecasting situations. Students will receive computer codes that exactly match the techniques covered in class in order to guarantee their applicability to real data.

Each session starts with the presentation of a forecasting technique, followed by the review of the econometric theory required for its analysis, and the detailed explanation of computer programs that can be used to obtain the forecasts. The syllabus covers a wide range of forecasting problems and linear and non-linear econometric methods, but it is designed to be self-contained.




Code: 41240
Lecturer responsible:
Credits ECTS: 5,00
Theoretical credits: 1,20
Practical credits: 0,40
Distance-base hours: 3,40

Departments involved

    Theoretical credits: 1,2
    Practical credits: 0,4
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught