Econometric Methods
Keywords |
Classification |
Keyword |
OFICIAL |
Economics |
Instance: 2022/2023 - 1S
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; EGLS and White);
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. Test Ramsey for detecting specification errors.
Mandatory literature
Damodar N. Gujarati;
Basic econometrics. ISBN: 9780071276252
Manuel José Mendes de Oliveira;
Econometria. ISBN: 978-972-592-550-8
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
“distributed evaluation” 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
Observations
The support materials (slides, exercises and their solutions, data bases) given in each class are made previously available in the
intranet of the Faculty.
All these materials will be taken down within 24 hours previous to any tests or exams. Thus students are advised to save these materials in pens or any other saving devises in due time.