| Code |
14163
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| Year |
1
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| Semester |
S1
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| ECTS Credits |
7,5
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| Workload |
OT(3H)/TP(30H)
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| Scientific area |
Economics
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Entry requirements |
No exigible or required.
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Learning outcomes |
Aims:
- To develop the skills in, and knowledge of, econometrics necessary for theoretical and empirical work based on cross-sectional, time-series or panel data.
- To learn how to conduct empirical studies in economics and related fields using modern econometric
techniques.
Competences:
- Data analysis and manipulation.
- Reason logically and work analytically.
- Work with abstract concepts and in a context of generality.
- Select and apply appropriate techniques to solve econometric problems.
- Team work, written and oral communication.
- Computing skills and knowledge of econometric software.
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Syllabus |
1. Econometrics: introduction and eevisions
2. Panel data analysis: Fixed and Random Effects in Static Models; Test for the presence of fixed effects; Hausman test; Wald Tests, Heteroscedasticity, Autocorrelation; Robust estimation. Modeling and Estimation with practical applications using Stata
3.. Panel corrected standard errors (PCSE) estimation model. Modeling and estimation with practical applications using Stata
4.Cointegration.Estimation of Pooled Mean Group (PMG), Mean Group (MG), Dynamic Fixed Effect (DFE), Dynamic Ordinary Least Squares (DOLS) and Full Modified Ordinary Least Squares (FMOLS) models.
5. Estimation Generalized Method Of Moments (GMM).
6. Applied Economics Case Study
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Main Bibliography |
Davidson, R., J.G. Mackinnon, (2003), Econometric Theory and Methods, Oxford University Press.
Greene, W. (2018), Econometric Analysis, 8th Edition, Pearson.
Verbeek, M. (2017), A Guide to Modern Econometrics, 5.ª ed., Wiley.
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Teaching Methodologies and Assessment Criteria |
Classes on topics based on theory and practical examples applied to econometrics. On average, students should have approximately 10 hours of work per week outside the classroom. The course schedule and list of bibliographic references will be available on the course page. In the teaching-learning component, the assessment will consist of a research paper with a weighting of 50% in the final grade and a final test with a weighting of 50%.
Final exams to be taken during the regular period and/or resit will have a weighting of 100%.
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Language |
Portuguese. Tutorial support is available in English.
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