Courses Bachelor Display 2017-2018
|Course Description||To PDF|
|Course title||Econometric Methods II|
Denis de Crombrugghe
For more information: email@example.com
|Language of instruction||English|
(1) Thorough understanding of standard econometric models and methods for the analysis of independent data; independent data are typically cross-sectional, as opposed to time series which are sequential and generally serially dependent.
(2) Additionally, some practical experience with the application of the methods, the interpretation of the models, and the evaluation of inferences.
(3) In particular, providing background and warming up for students about to write a Bachelor thesis on an empirical topic.
In order to satisfy the Econometrics & OR curriculum, you have to choose two of the
courses EBC2091, EBC2120, EBC2121, EBC2122 in period 4.
"ECONOMETRIC METHODS II" IS THE NEW TITLE FOR THE COURSE PREVIOUSLY LABELLED "DYNAMIC MODELLING".
The course is designed as a follow-up to the second-year course Econometric Methods 1 (EBC2111), reviewing known methods somewhat more formally before introducing the new ones. The intended main topics are
(1) a quick review of linear models, (2) Instrumental Variable methods (IV), (3) Maximum Likelihood methods (MLE), (4) Generalised Methods of Moments (GMM), (5) nonlinear models for choices, counts, corner solutions etc., (6) linear models for panel data.
These topics will be treated at a fairly advanced level, starting from abstract assumptions about a multivariate world described in terms of vectors and matrices.
Wooldridge J.M. (2010): Econometric Analysis of Cross-Section and Panel Data, Second Edition, MIT Press, Cambridge, MA. (First half).
Davidson R. & J.G. MacKinnon (2004): Econometric Theory and Methods, Oxford University Press.
Cameron A.C. & P.K. Trivedi (2005): Microeconometrics, Cambridge University Press. (First half).
Greene W.H. (2008): Econometric Analysis, Sixth (or Seventh) Edition, Pearson Prentice Hall.
Linear algebra, mathematical statistics (EBC2107), Econometric Methods I (EBC2111) or the equivalent.
Familiarity with statistical software like Stata and Gauss, Matlab or R.
|Teaching methods||PBL / Presentation / Lecture / Assignment / Groupwork|
|Assessment methods||Final Paper / Participation / Written Exam|
|Evaluation in previous academic year||For the complete evaluation of this course please click "here"|
|This course belongs to the following programmes / specialisations||