Module Code: EC7004
- ECTS Credit: 10
- Mandatory/Optional: Mandatory
- Module Coordinator: Professor Gaia Narciso and Professor Agustin Benetrix
Aims of Module
The aim of this module is to provide students with the skills required to undertake independent applied research using modern econometric methods. The course builds on the fundamental concepts developed in Module I and aims to extend students’ understanding of the subject to a more advanced level. The course attempts to provide a balance between theory and applied research.
The module will be delivered through a combination of lectures (18 hours) dealing primarily with theoretical issues and workshops (18 hours) involving smaller group work focussing on applying the theoretical concepts explored in lectures to real data.
Students attending this module will deepen their theoretical knowledge of a range of topics in econometrics and develop the necessary practical skills to estimate their own macroeconomic models. The workshops accompanying lectures will instruct students in the use of econometrics software necessary for applied work.
- Stationary time series
- Unit roots and cointegration
- Simultaneous equations models
- Panel VAR models
N.B.: Additional readings will be suggested in the lectures.
There will be a two-hour workshop held in each week of term to instruct students in the use of Stata and to assist students in the preparation of their term project.
ReadingThe core texts for this course are:
- Baum, C. F. (2006), An Introduction to Modern Econometrics using Stata. Stata Press
- Davidson, R. D. and MacKinnon J. G. (2004), Econometric Theory and Methods, Oxford University Press.
- Enders, W. (2014), Applied Econometric Time Series, Wiley.
- Greene, W. (2008), Econometrics Analysis, Pearson.
- Harvey, A. C. (1993), Time Series Models, Pearson Education.
- Pevalin, D. and Robson, K. (2009), The Stata Survival Manual. McGraw Hill.
- Verbeek M. (2004), A Guide to Modern Econometrics, 2nd Edition. Wiley.
- Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel Data, 2nd edition, MIT Press.
- Hayashi, F. (2000), Econometrics, Princeton University Press.
- Lütkepohl H. (2005), New Introduction to Multiple Time Series Analysis, Springer.
- Hamilton, J.D. (1994), Time Series Analysis, Princeton University Press.
Assessment for the module consists of a final exam accounting for 60% of the grade. For the remaining 40%, students will have to complete 4 homework exercises (5% each), and to undertake one individual project making worth 20%.