| Code |
16279
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| Year |
1
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| Semester |
S1
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| ECTS Credits |
6
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| Workload |
TP(30H)
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| Scientific area |
Economics
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Entry requirements |
Basic concepts of statistics and introduction to econometrics.
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Learning outcomes |
At the end of the course unit, students should be able to:
• Carry out theoretical and empirical work, whether based on cross-sectional, time series or panel data.
• Apply the latest econometric techniques in the analysis of various economic problems.
• Design and develop strategies that allow the methods studied to be adapted to specific problems that are always encountered in practical applications, such as lack of data, noisy data, endogeneity problems, and spurious correlations.
• Use econometric software to estimate models.
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Syllabus |
1. Linear Regression Model: Cross-sectional Data: Specification, Estimation and Inference; Endogenous Explanatory Variables
2. Cross-sectional Data: Specification; Endogenous Explanatory Variables and Exogenous Explanatory Variables. Violation of Assumptions, Quality of Fit, Hypothesis Testing
3. Diagnosis of Normality, Multicollinearity and Heteroscedasticity.
4. Fixed Effects and Random Effects Models in Static Models; Hausman Test; Wald Tests, Heteroscedasticity, Autocorrelation.
5. Panel corrected standard errors (PCSE) estimation model Post-estimation tests
6. Models for Dynamic Panel Data: Fixed Effects and Random Effects Models: with bias correction.
7. Estimation of Dynamic Models: Inconsistency of Static estimators. Instrumental variable estimators.
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Main Bibliography |
Croissant, Y., & Millo, G. (2018). Panel Data Econometrics with R. Wiley.
Pesaran, M. H. (2015). Time Series and Panel Data Econometrics. OUP Catalogue.
Verbeek, M. (2017). A guide to modern econometrics. John Wiley & Sons.
Wooldridge, J.M. (2019), "Introductory Econometrics: A Modern Approach", 7th Ed., South Western Publishers.Franses
Artigos científicos selecionados.
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Teaching Methodologies and Assessment Criteria |
Students should attend classes every week to understand and to learn to use the main econometric tools for cross-sectional, time series and panel data, the theoretical arguments used to obtain the main results and to be familiar with the interpreting results for selected pratical examples.
Lessons are based on theoretical-practical classes, with a limited number of students (30). After theoretical and practical subjects are taught, students will solve practical problems that help them understand the contents and implement this knowledge in their work. When solving the exercises, priority is given to using real data with the support of appropriate econometric software.
Assessment consists of an individual written test (50%) and an individual practical assignment per student, weighted at 50% (15% in the intermediate presentation in the last lesson of November and 35% in the final report.
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Language |
Portuguese. Tutorial support is available in English.
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