Niveau d'étude
BAC +4
ECTS
4,5 crédits
Composante
Sciences économiques, gestion, mathématiques et informatique
Volume horaire
40h
Période de l'année
Enseignement septième semestre
Description
This course provides students with intermediate-level econometrics for micro-level data.
- The first part of the course deals with linear regression models, traditional estimators (OLS and related) and focuses on issues related to statistical inference, endogeneity bias (IV estimators) and sample selection.
- The second part of the course covers discrete and limited dependent variable models and their related maximum-likelihood estimators.
Objectifs
- Understanding the core theory underlying econometric modelling and estimation for cross-sectional data.
- Being able to formulate a question/hypothesis into an econometric problem and identify the key challenges.
- Being able to choose the most appropriate solution among many modelling strategies and estimators.
- Being able to implement the solution using a software.
Évaluation
- Session 1
Formule standard :
Type : Écrit
Durée : 1h30
Contenu : questions de cours et exercices
Formule dérogatoire :
Type : Écrit
Durée : 1h30
Contenu : questions de cours et exercices
- Session 2 :
Type : Écrit
Durée : 1h30
Contenu : questions de cours et exercices
Pré-requis obligatoires
Statistics : descriptive and inference (bachelor level)
Introductory econometrics (bachelor level)
Compétences visées
- Understanding core theory underlying econometric modelling and estimation for cross-sectional data
- Being able to formulate a question/hypothesis into an econometric problem and identify the key challenges
- Being able to choose the most appropriate solution among many modelling strategies and estimators
- Being able to implement the solution using a software
Bibliographie
- Cameron, C. & Trivedi, P. (2005) : Microeconometrics – Methods and Applications, Cambridge University Press
- Wooldridge, J. (2015) : Introductory Econometrics, a Modern Approach, Cengage
- Wooldridge, J. (2010) : Econometric Analysis of Cross-Section and Panel Data, MIT press