Competencies and objectives

 

Course context for academic year 2025-26

This is the first econometrics course in the master’s program, designed for students who have completed a prior course in statistics. It builds on foundational statistical concepts to develop core econometric tools.

 

 

Course competencies (verified by ANECA in official undergraduate and Master’s degrees) for academic year 2025-26

Skills/Skills

  • RA05 : Understand how technical problems in research articles have been addressed and be able to replicate the empirical analysis and simulation experiments on which they are based
  • RA13 : Know how to apply data science techniques to real economic problems, both for research and decision-making

 

Conocimientos/Contenidos

  • RA01 : Understand the fundamental theoretical framework of economics at a rigorous formal level

 

Skills/Competences

  • RA02 : Deeply understand and apply descriptive, causal, and predictive analysis methods applied to economics
  • RA04 : Formulate relevant economic problems precisely and provide appropriate solutions using theoretical, empirical, or simulation-based analysis
  • RA14 : Be able to develop and learn autonomously about topics related to Economics and Data Science

 

 

 

Learning outcomes (Training objectives)

-Understand and discuss the consequences of relaxing classical assumptions in the linear regression model.

-Apply and interpret instrumental variable models and the generalized method of moments.

-Apply and interpret panel data models and address unobserved heterogeneity.

 

-Apply and interpret binary response models.

-Know and be able to argue the consequences to #move  of the classical suppositions in the model of linear regression.
-Be able to apply and interpret the models of instrumental variables and of the method generalised of the moments.
-Be able to apply and interpret the models of data of signpost, and argue the problem of heterogeneity no observable.
-Be able to apply and interpret the models of data binary response.

 

 

Specific objectives stated by the academic staff for academic year 2025-26

The objective of this course is to introduce students to the application of statistical methods in econometrics, with an emphasis on estimation and inference in linear models. Specific topics include regression analysis, instrumental variables, panel data models, and discrete choice models.

 

 

General

Code: 49165
Lecturer responsible:
Redondo Gómez, Henry Antonio
Credits ECTS: 5,00
Theoretical credits: 1,60
Practical credits: 0,40
Distance-base hours: 3,00

Departments involved

  • Dept: Economic Analysis
    Area: FOUNDATIONS OF ECONOMIC ANALYSIS
    Theoretical credits: 1,6
    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