Econometric Methods

Code:

1GE305

Acronym:

MEC

Keywords
Classification	Keyword
OFICIAL	Economics

Instance: 2021/2022 - 1S

Active?	Yes
Responsible unit:	Agrupamento Científico de Economia
Course/CS Responsible:	Bachelor in Business Administration

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
LGES	155	Bologna Syllabus since 2012	3	-	6	42	162

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