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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, 3rd Ed., 2015.
Baltagi, Badi H., Econometric Analysis of Panel Data, John Wiley & Sons, 5th edition, 2013.
Recomendada/ Recommended
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.G. MacKinnon (2003), Econometric Theory and Methods, Oxford University Press.
Greene, W. (2011), Econometric Analysis, Pearson (7th Edition)Publishers.
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