| Code |
16489
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| Year |
3
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| Semester |
S1
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| ECTS Credits |
6
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| Workload |
TP(60H)
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| Scientific area |
Economics
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|
Entry requirements |
- Probabilities and Statistics
- Statistics Applied to Economics
- Spreadsheet basics
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Learning outcomes |
- Familiarize students with the instruments and techniques for the development and interpretation of econometric models.
- Develop knowledge of econometric subjects that are essential for carrying out work of a theoretical and empirical nature.
- To design and develop strategies to adapt the studied methods to real problems.
- To initiate students in the use of widely used programs in the academic and professional field (mainly Eviews and R).
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Syllabus |
1. Introduction: object and methodology of econometrics
2. Data analysis and transformation
3. Linear regression model (LRM)
3.1 Correlation and causality
3.2 Violation of assumptions
3.3 Quality of fit
3.4 Confidence intervals
3.5 Hypothesis tests
4.Model evaluation and diagnostic tests
4.1 F test
4.2 Coefficient of determination
4.3 Test for normality
4.4 Multicollinearity
4.5 Heteroscedasticity
4.6 Structure permanence tests
5.Some extensions of LRM
5.1 Functional form of regression models.
5.2 Binary variables.
5.3 Descriptive models of trend and seasonality.
5.4 Coefficients tests of two regressions.
5.5 Robust least squares method.
5.6 Weighted Least Squares Method.
6.Models with Qualitative Dependent Variable
6.1 Introduction: binary choice models
6.2 Linear Probability Models
6.3 Probit and Logit Models
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Main Bibliography |
Wooldridge, Jeffrey M., Introductory econometrics: a modern approach. 7th ed., South-Western/Cengage Learning, 2019
Asteriou, Dimitrios e Hall, Stephen G., Applied Econometrics, Palgrave Macmilan, 4th Ed., 2021
Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer, Introduction to Econometrics with R, 2024
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Teaching Methodologies and Assessment Criteria |
Assessment is continuous and consists of two tests (30%+70%).
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Language |
Portuguese. Tutorial support is available in English.
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