Econometric Methods
Keywords |
Classification |
Keyword |
OFICIAL |
Economics |
Instance: 2021/2022 - 1S ![Requerida a integração com o Moodle Ícone do Moodle](/fep/pt/imagens/MoodleIcon)
Cycles of Study/Courses
Teaching language
Portuguese and english
Objectives
To supply the students with knowledge about basic econometrics tools that allow students to develop empirical work autonomously with particular emphasis on applications of management, finances and marketing.
Learning outcomes and competences
By the end of the semester, students are expected to be able to apply standard econometric techniques to empirical data
Working method
Presencial
Program
1. Introduction - method to specify, estimate and evaluate econometric models; types of data.
2. The simple linear classic model (SLCM)
2.1. Estimation - OLS (assumptions, estimators, goodness of fit);
2.2. Economic Interpretation of the SLCM;
2.4. Alternative functional forms of the SLRM and interpretation of coefficients.
2.3. Inference: Hypothesis t tests for individual coefficients
3. Multiple linear regression model (MLCM)
3.1. OLS (estimation and properties);
3.2. Economic Interpretation of the MLCM;
3.3. Inference: Hypothesis tests for sets of coefficients (the F test of the overall significance and Wald tests);
4. Intercept and slope dummy variables: use of and interpretation of their oefficients’
5. Relaxing the assumptions of the classical model
5.1. Specification: structural stability (Chow test vs. test with dummy variables);
5.3. Heteroscedasticity (detection - White teste; estimation - GLS);
5.4. Autocorrelation (detection - Durbin-Watson and Breusch-Godfrey tests; estimation - GLS, EGLS, Newey-West);
5.2. Multicollinearity: what to do when present.
5.5. Tests for detecting specification errors.
Mandatory literature
Manuel Mendes Oliveira, Natércia Fortuna, Luís Delfim Santos; Econometria, Escolar Editora, 2011. ISBN: 9789725923269
Wooldridge, Jeffrey; Introductory Econometrics: a modern approach, CENGAGE Learning Custom Publishing, 2018. ISBN: 9781337558860
Damodar Gujarati and Dawn Porter; Basic Econometrics, MacGraw Hill, 2008. ISBN: 9780073375779
Teaching methods and learning activities
Theory lectures complemented with computer lab sessions with software EViews.
Software
EViews
Evaluation Type
Distributed evaluation without final exam
Assessment Components
Designation |
Weight (%) |
Teste |
100,00 |
Total: |
100,00 |
Amount of time allocated to each course unit
Designation |
Time (hours) |
Estudo autónomo |
120,00 |
Frequência das aulas |
42,00 |
Total: |
162,00 |
Eligibility for exams
The successful student has to obtain at least 9.5/20 marks for the weighted average of two tests and, in none of them, a mark smaller than 6/20 values. The first test takes place in November and the second one in the day of the exam, in January.
The successful student can also choose to just attend the January exam and obtain there, at least, 9.5/20 marks.
Not being able to do so, the student can still pass the discipline by attending the resit exam (also in January) and obtaining, at least, 9.5/20 marks.
Calculation formula of final grade
“avaliação distribuída” with two tests (T1, T2)
Final score = 0.5*T1+0.5*T2.
Examinations or Special Assignments
N.A.
Internship work/project
N.A.
Special assessment (TE, DA, ...)
General regulations apply
Classification improvement
General regulations apply