How to find us

Econometrics 2017/2018

  • 5 ECTS
  • Taught in Portuguese
  • Both continuous and final Assessment


The objective is to give the students the necessary theoretical and practical (Software) knowledge for them to be able to create and analyse a linear regression model. The students should be able to: i) When in the presence of typical Economics and Management problems, applying linear regression models correctly; ii) in the presence of a linear regression model, to verify if the underlying assumptions are verified, so that the results are valid: iii) interpret and conclude the results of a linear regression model as an Economist; iv) to Estimate and analyse econometric models using an adequate software, such as SPSS:

Recommended Prerequisites

Mathematics, Statistics, Macroeconomics, Microeconomics

Teaching Metodology

Demonstrative Methodology: The classes are essentially theoretical, complemented with exercises and exemples in which the importance of Econometrics to Economics is demonstrated.
Guided Practice Methodology: The practical component of the course requires the SPSS and the students will have some preparation on how to estimate and interpret the models taught in the course with this software.
There will be a group work as part of the evaluation, where students can find by themselves what is the best way to apply the knowledge acquired in the course.

Body of Work

1. Introduction to Econometrics
2. Two-Variable Linear Regression Models
3. Multiple Linear Regression Models
4. Heteroskedasticity
5. Autocorrelation
6. Models with binary dependent variables: Logit and Probit.

Recommended Bibliography

Gujarati, D. e Porter, D. (2009). Basic econometrics (5th ed.). Boston: McGraw Hill.

Complementary Bibliography

Maddala, G. (2001). Introduction to Econometrics (3th ed.). New York: John Wiley and Sons.

Weekly Planning

1. Introduction to Econometrics
2. Two-Variable Linear Regression Models
3. Two-Variable Linear Regression Models
4. Two-Variable Linear Regression Models
5. Multiple Linear Regression Models
6. Multiple Linear Regression Models
7. Multiple Linear Regression Models
8. Multiple Linear Regression Models
9. Heteroskedasticity
10. Heteroskedasticity
11. Autocorrelation
12. Autocorrelation
13. Models with binary dependent variables: Logit and Probit
14. Models with binary dependent variables: Logit and Probit
15. Presentation of Group Work Essays

Demonstration of the syllabus coherence with the curricular unit's objectives

The contents allow the student to obtain basic knowledge of Econometrics, which is crucial for the estimation and interpretation/analysis of the models that may be necessary on their professional and/or academic career. The students will be given the theoretical baggage to attain the proposed objectives for this course. The sequence in which the topics are presented has the objective to introduce logicly and progressively the contents.

Demonstration of the teaching methodologies coherence with the curricular unit's objectives

The theoretical nature of these classes allow the students to understand the contents of the course. The practical approach complements and fortifies the knowledge of the students, their curiosity on the topics and allows the understanding of the importance of Econometrics to the Economics Field. The methodology therefore leads the students on attaining the proposed objectives of the Course.

relevant generic skillimproved?assessed?
Achieving practical application of theoretical knowledgeYesYes
Analytical and synthetic skillsYesYes
Commitment to effectivenessYesYes
Commitment to qualityYesYes
Event organization, planning and managementYesYes
IT and technology proficiencyYesYes
Problem Analysis and AssessmentYesYes
Research skillsYesYes
This website uses cookies to provide better functionality and for performance measurements (European Union Directive 2009/136/EC)