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Econometric Methods

Code 15437
Year 1
Semester S2
ECTS Credits 6
Workload OT(15H)/TP(45H)
Scientific area Economics and Management
Entry requirements not applicable
Learning outcomes Aims:
- To develop the skills in, and knowledge of, econometrics necessary for theoretical and empirical work based on time-series and forecasting techniques;
- To learn how to conduct empirical studies in economics and financial to related fields using parametric and non-parametric econometric techniques;
- To learn the importance of forecasting economic magnitudes or variables;
- To learn some of the more important techniques of forecasting economic and financial variables, either in the short,medium, long and very long terms.

- Data analysis and manipulation;
- Select and apply appropriate techniques to solve econometric problems;
- Team work, written and oral communication;
- Computing skills and knowledge of econometric software.
Syllabus 1. Descriptive analysis of time series: chronogram and identification of the components of a time series (trend, cycle, seasonality, residual component).
2. Smoothing methods: moving averages, single, double and triple exponential smoothing.
3. Multivariate models: VAR, VECM, Threshold-AR, Markov-Switching
5. Forecasting time series with autoregressive neural networks
6. Difference-in-differences modelling
7. Propensity Score Matching
8. Machine learning topics applied to econometrics
Main Bibliography M. Hashem Pesaran (2015), Time Series and Panel Data Econometrics, Oxford
Verbeek, M. (2018), A Guide to Modern Econometrics, 5th Ed., Wiley.
Gertler, Paul J., et al.(2016) Impact Evaluation in Practice, World Bank Group
Charles S. Reichart (2019) Quasi-Experimentation: A Guide to Design and Analysis (Methodology in the Social Sciences), The Guilford Press
Roth, Jonathan, et al (2022); What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature, Cornell University
Teaching Methodologies and Assessment Criteria Small group classes where theoretical contents are supplemented by exercise lectures and computer exercises. Real economic data is employed on solving the computer exercises using adequate software.

Evaluation: written examination 17th May (60%) + one empirical project 7th June (40%)
Language Portuguese. Tutorial support is available in English.
Last updated on: 2024-03-14

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