Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h
Q2
Teacher(s)
Van Bellegem Sébastien;
Language
English
Prerequisites
Mathematics and Statistics for Economists
Main themes
The course must cover the basic most important topics of econometric theory at an advanced level.
These themes concern econometric model formulation, estimation and testing.
Teaching is at an advanced level. Proofs of important results are covered, though not systematically. Applications are also used so that students learn how to carry applications in their own research.
Contents
These themes concern econometric model formulation, estimation and testing.
Teaching is at an advanced level. Proofs of important results are covered, though not systematically. Applications are also used so that students learn how to carry applications in their own research.
Contents
- Linear regression : exact finite sample theory of ordinary and generalized least squares
- Large-sample theory: convergence concepts, stochastic processes (stationarity and ergodicitys, IID and white noise, martingales, martingale difference sequences) and limit theorems for IID and MDS). Application to large sample theory of least-squares estimation.
- GMM and the method of instrumental variables
- The method of maximum likelihood: (estimation and testing) and its application to linear regression and non-linear regression models.
- Empirical applications. Use of an econometric and simulation/computational software.
Aims
At the end of this learning unit, the student is able to : | |
| 1 |
The purpose is that students acquire the basic tools of econometric research which are of general use in more specialized fields of research and which are covered in subsequent courses (Microeconometrics and Econometrics of Time-Series). An example of such a tool is the method of estimation by maximum likelihood. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Evaluation methods
Oral or written exam. A part of the final result is reserved for the evaluation of the exercises assignned during the term.
Other information
Support: A textbook like Hayashi Econometrics
Bibliography
Faculty or entity
ECON
