Introduction à l'économétrie

1    Covariance and Regression
Introduction to Linear Regression
2    Inference
Introduction to Inference in Linear Regression
3    Multicollinearity
FWL Theorem and VIF
4    Regression Model Assumptions
Gauss-Markov Theorem, Functional Form, and Specification
5    Endogeneity
Instrumental Variables and 2SLS
6    Heteroscedasticity
Inference Correction and Weighted Least Squares (wls)
7    Serial Correlation
Inference Correction and Cochrane-Orcutt Method
8    Maximum Likelihood
LM, LR, and Wald Tests
9    Binary Dependent Variable
Logit and Probit
10    Censoring and Selection
Tobit and Heckman
11    Time Series
Stationarity and Cointegration
12    Panel Data
Fixed Effects and Random Effects

At the end of the course, the students will be able to :

• Use statistical software

• Verify the assumptions in a model

• Use statistical models in daily life

Required and corequired courses

Lectures and exercises (in computer lab)

References, bibliography, and recommended reading

• Dougherty, C. (2007). Introduction to Econometrics, Oxford University Press. (Main reference book). The slides used during the theory course are in French and are largely a translation of the slides that accompany this book.
• Greene, W. (2000), Econometric Analysis, Prentice Hall, London.
• Verbeek, M. (2000), A Guide to Modern Econometrics, Wiley-Interscience, New York.

Campus

Solbosch

Method(s) of evaluation

• Practice work
• written examination
• Other

Practice work

written examination

Other

A quarter of the final mark is based on the completion of homework given during the first semester. Completion of homework is a mandatory step to be able to take the written exam.

The written exam is organized during the January session. The exam consists of a theoretical part and a practical part, without interruption between the two.

The instructor reserves the right to invite any student to an additional oral interview in order to verify their personal mastery of the content of the submitted examination, particularly when inconsistencies identified in the examination prevent the instructor from properly assessing the student’s level of mastery of the knowledge and skills targeted by the course.

Mark calculation method (including weighting of intermediary marks)

5 points: group projects • 2 projects during the year • Groups of 4 students • Analysis of a database using statistical software

15 points: examination • Face-to-face if the health context allows it • With an A4 sheet of handwritten notes

Language(s) of evaluation

• french