Teaching Assistant in 2019 (Fall) – 18h.
Main themes: Rubin causal model, Ordinary Least Square (identification, estimation, and inference), Instrumental Variable, Panel and repeated cross-section data (Differences in Differences), and Prediction versus Causality.
Teaching Assistant in 2018 and 2019 (Spring) – 18h.
Main themes: Generalized Method of Moments, Panel data methods (First Difference, Within), Limited dependent variable: binary models (probit, logit), multinomial logit, conditional logit, count models, selection and censorship, and duration models.
Teaching Assistant in 2017, 2018, and 2019 (Fall) – 18h.
Main themes: Statistical models (identification, parametric/nonparametric), Estimation (Method of Moments, Maximum of Likelihood, Bayes), Confidence intervals, Parametric tests, Adequation tests, Introduction to density estimation (kernel methods, Nadaraya-Watson), and Computational statistics (Newton-Raphson, EM Algorithm, Gibbs-sampling, Bootstrap).
Statistics (Graduate – crash course)
Course entitled “Mathematical Statistics” at ENSAE (Graduate level – crash course for parallel admission students) taught by Guillaume Lecué in 2018 and 2019 – current course website (in French) – link to course material.
Teaching Assistant in 2018 and 2019 (Fall) – 12h.
Main themes: Statistical models, Plug-in approach, Probability basic tools (LLN, CLT, Delta-method), Z- and M-estimation and asymptotic inference, Comparison of estimators (Cramer-Rao bounds), and Parametric tests (Neyman-Pearson).
Teaching Assistant in 2018 and 2019 (Spring) – 24h.
Main themes: Statistical models (identification, parametric), Estimation (Method of Moments, Maximum of Likelihood), Confidence intervals, Parametric tests, Adequation tests, and Application in R (tutorials).
Mathematics (Undergraduate – oral examiner in preparatory classes)
Oral examiner for Serge Nicolas in the B/L preparatory class at Lycée Henri IV, Paris.
2h weekly in academic years 2014-2015 and 2015-2016.
Main themes: Real and complex analysis, Linear algebra, and Probability.