# Econometrics

## Objectives

To acquire the theoretical knowledge and practical capabilities necessary for the use of the linear regression model with sectional and time series data.

## General characterization

1306

7.5

##### Responsible teacher

João Valle e Azevedo

##### Hours

Weekly - Available soon

Total - Available soon

English

### Prerequisites

Mandatory Precedence:

- 1303. Linear Algebra

- 1305. Statistics for Economics and Management

### Bibliography

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach, 5th Edition.

Resources

Moddle page containing class slides, econometric software tutorials and past exams. Availability of econometric software in the Computer Lab.

### Teaching method

Theoretical Classes (approx. 72 hours), Practical Classes, including Computer Lab (approx. 36 hours)

### Evaluation method

Final grade will be based on a group assignment (weighted 25%), midterm (weighted 25%) and on the final exam (weighted 50%). In order to pass, students must obtain a grade higher or equal to 8.0 in the final exam.

Regular Exam Period
Continuous assessment elements (and their weights):
Group assignment (weighted 25%), midterm (weighted 25%) and on the final exam (weighted 50%). In order to pass, students must obtain a grade higher or equal to 8.0 in the final exam.

Final exam (and their weighting): 50%

Resit Exam Period
Continuous assessment (and their weights) if different than 100%: NA

Final exam (and its weight): 100%

Continuous assessment (and their weights) if the scanning feature doesn’t count 100%: Group assignment (weighted 25%), midterm (weighted 25%) and final exam (weighted 50%). In order to pass, students must obtain a grade higher or equal to 8.0 in the final exam.
Final exam (and its weight):50% Grade Improvement in Resit Period
Continuous assessment (and their weights) if different than 100%:NA

Final exam (and their weighting): 100%

## Subject matter

Multiple Linear Regression (Estimation and inference), Heteroskedasticity, Serial Correlation and Time Series Models.

## Programs

Programs where the course is taught: