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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 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
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 (EViews and Stata)
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Main Bibliography |
Principal:
-Asteriou, Dimitrios e Hall, Stephen G., Applied Econometrics, Palgrave Macmilan, 4th Ed., 2021.
- Wooldridge, Jeffrey M., Introductory econometrics: a modern approach. 8th ed., South-Western/Cengage Learning, 2025
- Christoph Hanck, Martin Arnold, Alexander Gerber, and Martin Schmelzer, Introduction to Econometrics with R, 2024 Introduction to Econometrics with R (econometrics-with-r.org)
Recomendada/ Recommended
-Baltagi, Badi H., Econometric Analysis of Panel Data, John Wiley & Sons, 5th edition, 2013.
-Armstrong, J. Scott, Illusions in regression analysis, in International Journal of Forecasting, Vol. 28, No. 3, July–September 2012, pp 689-694.
-Greene, William H., Econometric Analysis, Global Edition Pearson Higher Education, 8th edition, 2020.
-Wooldridge, Jeffrey, Econometric Analysis of Cross Section and Panel Data, The MIT Press, 2nd edition, 2010.
-Wooldridge, J.M. (2015), "Introductory Econometrics: A Modern Approach", 6th Ed., South Western
-Davidson, R. and J.
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