• Niveau d'étude

    BAC +4

  • ECTS

    3 crédits

  • Composante

    Sciences économiques, gestion, mathématiques et informatique

  • Volume horaire

    40.0h

  • Période de l'année

    Enseignement septième semestre

Description

The course is organized in chapters of increasing difficulty, over a schedule of 8 sessions of 3 hours each. All chapters present the core theory underlying the different econometric models and estimators, and then propose simple applications on real or simulated data. The course is supplemented by tutorial sessions to practice with paper-and-pencil exercises as well as using the Stata software.

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Objectifs

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. Extensions to panel-data settings are proposed if time permits.

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Évaluation

Session 1 :
Formule standard : La note finale est composée d’une note de contrôle continu (50%) et d’une note d’examen terminal (50%) consistant en épreuve sur table de 2 heures.
Formule dérogatoire : Une épreuve sur table de 2 heures.

Session 2 : Une épreuve sur table de 2 heures.

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Heures d'enseignement

  • MicroeconometricsCM24h
  • MicroeconometricsTD16h

Pré-requis nécessaires

Statistics : descriptive and inference (bachelor level)

Introductory econometrics (bachelor level).

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Compétences visées

The competences acquired are the following
- 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
- 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.

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Bibliographie

  • Cameron, C. & Trivedi, P. (2005) : Microeconometrics – Methods and Applications, Cambridge University Press
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