Teaching plan for the course unit

 

 

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General information

 

Course unit name: Econometrics II

Course unit code: 366721

Academic year: 2025-2026

Coordinator: Esther Vaya Valcarce

Department: Department of Econometrics, Statistics and Applied Economics

Credits: 6

Single program: S

 

 

Estimated learning time

Total number of hours 150

 

Face-to-face and/or online activities

60

 

-  Lecture with practical component

Face-to-face

 

45

 

-  Problem-solving class

Face-to-face

 

15

Supervised project

40

Independent learning

50

 

 

Recommendations

 

Econometrics shares close links with economic statistics, mathematical economics, and economic theory. For this reason, students are recommended to have a good grounding in the subjects related to these areas, as covered in the Economics degree program. Furthermore, Econometrics II assumes a certain familiarity with the basic concepts and techniques taught in Econometrics I.

 

 

Competences / Learning outcomes to be gained during study

 

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Commitment to ethical practice (critical and self-critical skills and attitudes consistent with ethical and deontological principles).

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Capacity to apply ICTs to professional activities.

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Ability to use physical and electronic bibliographical resources.

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Ability to apply the knowledge acquired and analytical skills for solving academic and professional problems.

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Capacity to prepare, analyse and interpret economic information.

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Ability to produce critical analyses of economic theories and models.

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Knowledge and understanding of the nature, sources and uses of economic information and of the appropriate software for processing and analysing economic data.

Learning objectives

 

Referring to knowledge

  • Expand upon basic knowledge of econometrics to enable the critical interpretation of econometric results.
  • Acquire the theoretical and practical foundations, including the use of econometrics software, necessary for conducting complex econometric analyses.
  • Understand the implications for ordinary least squares (OLS) estimation (and know how to detect them using the appropriate diagnostic tests) when the basic assumptions of the multiple linear regression model (MLRM) related to the non-sphericity of the disturbance term (non-normality, heteroscedasticity, and autocorrelation) are violated, as well as the most suitable estimation method in these cases: generalized least squares.
  • Understand and know how to apply different validation procedures for econometric models; that is, the full set of tests that must be applied before a model is used for its intended purpose, as well as tools for selecting between alternative models, distinguishing between those appropriate for nested models and those for non-nested models.
  • Understand the specific characteristics of linear regression models that include exogenous qualitative variables and exogenous variables subject to endogeneity.

 

 

Teaching blocks

 

Lesson 1. Treatment of unobserved heterogeneity in panel data

Lesson 2. Estimation using instrumental variables

Lesson 3. Heteroscedasticity

Lesson 4. Models with a binary dependent variable

Lesson 5. Regression with (stationary) time series data

 

 

Teaching methods and general organization

 

Given that the learning objectives require substantial practical work, the general teaching methodology combines theoretical instruction with a strong emphasis on practical application. To this end, the following types of activity are undertaken:

— On-campus learning activities: these are carried out in the classroom with the lecturer. They include theoretical lectures, lectures with a practical component, and problem-solving sessions. A total of 60 hours are devoted to these activities. To facilitate learning, students have access to lecture slides via the Virtual Campus prior to each session.

— Independent learning activities: These include problem-solving exercises, computer sessions, and self-assessment of the knowledge and skills acquired. The practical exercises involve answering a set of questions based on real economic data using an econometric program. Students must interpret the program’s calculations and results by applying the theoretical concepts learned throughout the course. A total of 50 hours are assigned to these activities.

— Tutored or directed activities: These consist of discussion of problems to clarify doubts and provide guidance on students’ independent work. A total of 40 hours are assigned to these activities.

Once students have acquired the theoretical and practical content of the subject, problem-solving activities, independent work, and tutored sessions contribute to the acquisition of such competencies as the ability to produce, analyse and interpret economic information; to critically evaluate theories and models; to identify and use appropriate data sources; and to apply suitable computer tools for data analysis. Independent work also supports the development of ICT skills, which are essential for professional growth.

As part of the Teaching Quality Improvement Project implemented in the Faculty of Economics and Business (promoted by the Research, Innovation and Teaching and Learning Improvement [RIMDA] unit and the Office of the Vice-Rector for Teaching and Academic Planning), the teaching methodology used in some groups may differ slightly from that described above.Details of any such variations will be published on the Virtual Campus at the beginning of the semester.

Whenever possible, a gender perspective is incorporated into the analyses, tools, and practical exercises. The aim is to ensure that the training aligns with the University’s equality plan.

 

 

Official assessment of learning outcomes

 

Continuous assessment consists of two components:

a) Continuous assessment activities. Students complete two activities, representing 40% of the final grade (20% each), which must be completed on-campus on the scheduled dates.

b) Final examination. This is an exam with short-answer questions and limited space for responses, covering both the theoretical and practical components of the subject. Students must demonstrate the knowledge and skills acquired during the course, partially developed through the previous continuous assessment activities. The examination accounts for the remaining 60% of the final grade.

All assessment components completed during the course (continuous assessment activities and final examination) are graded on a scale of 0 to 10, and the percentage weightings specified above are then applied to calculate the final grade.

A student passes the course by achieving a minimum final grade of 5, calculated as the weighted average of all activities. To be eligible for continuous assessment, a minimum mark of 3.5 out of 10 must be obtained on the final examination. Otherwise, the final grade corresponds to that of the mark obtained on the examination mark alone.

Repeat assessment consists of a final examination with the same format as that for the single mode of assessment. Dates for repeat assessment are set in the Faculty’s academic calendar and coincide with the second examination period for undergraduate studies (in July). The date for repeat assessment examinations is established by the Academic Board.

If methodological changes described in the teaching methodology section affect the assessment system, students involved will be informed of how each activity contributes to the final grade.

 

Examination-based assessment

Students who are unable to meet the requirements for continuous assessment are entitled to opt for the single mode of assessment.

To pass the subject, students must demonstrate a sufficient level of achievement of the learning objectives in a single examination, which accounts for 100% of the final grade. This is an exam with short-answer questions and limited space for responses, covering both the theoretical and practical components of the subject. Students must demonstrate the knowledge and skills acquired as outlined in this course plan. The exam is sat on campus on the official date set by the Academic Board.

To pass the subject via this mode of assessment, students must:

a) Submit a written request indicating that they wish to waive their right to continuous assessment by the deadline announced by the Academic Board.
b) Obtain a mark of at least 5 out of 10 on the examination.

Repeat assessment adheres to the same format.

Finally, note that the assessment system for the EUS group is specified in the course programme designed for this group.