Modélisation et exploration des données multivariées - Applied Econometrics

Enseignants

Draye Xavier; Gaspart Frédéric; Govaerts Bernadette;

Langue
d'enseignement

Français

Préalables

General skills for a bio-engineering bachelor, probability theory, matrix algebra, statistical inference (hypothesis tests, confidence interval, general introduction to estimation)

Thèmes abordés

For the various types of non-experimental data (cross-sections, time series, panel data), the course outlines the main problems that are expected in linear regression models, some typical ways of identifying them with the help of theory or of statistical tests, and their most usual solutions. The main focus is, respectively, endogeneity for cross-sectional data, nonstationarity for time series and correlated random effects for panel data.

Contenu

1. Introduction to the different data types (cross-sections, time series, panel data) and to the small-sample and large-sample justifications of the OLS estimators
2. Cross-sections : typical exceptions to the Gauss-Markov assumptions, sources of endogeneity, IV estimators
3. Time series : the problem of non-stationarity, unit root tests, a few typical econometric specification for time series (Koyck, ECM,...)
4. Panel data : fixed effect model vs random effect model, the unifying Mundlak approach

Méthodes d'enseignement

Classes and homeworks

Modes d'évaluation
des acquis des étudiants

Homeworks in groups

Autres infos

Langue d'enseignement : anglais

Ressources
en ligne

Teams, Moodle

Faculté ou entité
en charge

AGRO