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Econometrics II

Code 12114
Year 3
Semester S2
ECTS Credits 6
Workload TP(60H)
Scientific area Economics
Entry requirements Knowledge base of the spreadsheet (Excel) and statistics.
Mode of delivery Face-to-face
Work placements Not applicable
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 financial, related fields using modern econometric techniques.
- Develop strategies to adapt the analysed methods to specific problems in empirical applications, such as missing data, data with noise, endogeneity problems and spurious correlations

- 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 (EViews and Stata)
Syllabus 1. Autocorrelation
1.1. Nature of the problem
1.2. The 1st order auto-regressive process
1.3. Detection tests: from Durbin-Watson, from Breusch-Godfrey
1.4. Estimation methods
2. Models with lagged variables
2.1. Distributed lag models
2..2. Koyck transformation
2..3. Partial adjustment models
2.4. Adaptive expectations models
2.5. Estimation of autoregressive models
3. Univariate stationary and non-stationary models
3.1. Stationary and Unit Root Tests
3.2. ARMA / ARIMA models
4. Models of conditioned heteroscedasticity and volatility: ARCH / GARCH
5. Stationary and non-stationary multivariate models
5.1. Multivariate models - VAR (Vector auto-regression)
5.2. Granger Causality and Cointegration,
5.3. VECM (vector error correction models) and Johansen Method models; Applications and case studies
Main Bibliography Dimitriuos Asteriou and Stephen Hall . (2012), Applied Econometrics . Second Edition . Palgrave Macmillan.

Wooldridge, Jeffrey M., Introductory econometrics: a modern approach. 6th ed., South-Western/Cengage Learning, 2016.
Aljandali, Abdulkader e·Tatahi, Motasam, Economic and Financial Modelling with EViews: A Guide for Students and Professionals, Springer, 2018.
Franses, P.H. and van Dijk, D. (2000). Non-Linear Time Series Models in Empirical Finance. Hamilton, J.D. (1994). Time Series Analysis, PUP.
William H. Greene; Econometric Analysis, 7th ed., Pearson Education, Inc., 2012. ISBN: 0-13-139538-6
Language Portuguese. Tutorial support is available in English.
Last updated on: 2021-06-15

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