Teaching Experience

Since 2022, I have taught Master’s-level courses as a non-tenured teaching and research fellow (ATER) and adjunct faculty member (vacataire) at the Institut d’études du développement de la Sorbonne (IEDES, Paris 1 Panthéon-Sorbonne University) and at the Faculty of Law, Economics and Political Science (UFR DESP, University of Rouen). Courses covered econometrics, impact evaluation, programming, development measurement, data analysis, vulnerability, and risk management. Further details are provided below.

Methodology Courses

Applied Microeconometrics — Lecture (M2, UFR DESP)
2025–2026 · 5 students · 20 hours
Assessment: final exam
Covers causal inference methods from both a theoretical and applied perspective, including randomization, matching, difference-in-differences, and regression discontinuity, with practical sessions in R.

Impact Evaluation — Lecture & Tutorial (M2, IEDES)
2024–2025 · 19 students · 15h lectures + 12h tutorials
Assessment: final exam (60%) + Stata assignment (40%)
Covers advanced causal inference methods including panel data models, difference-in-differences, regression discontinuity, synthetic control, and matching, with practical sessions in Stata. I taught 6 hours of lectures on panel data methods and 6 hours of Stata tutorials.

Data Collection and Analysis — Lecture (M2, IEDES)
2024–2025 · 19 students · 18 hours
Assessment: group project on paper replication in R
Covers data collection and estimation methods beyond standard linear models, including maximum likelihood, generalized linear models, multivariate analysis, and survey methods, with applications in R and Stata. I taught 12 hours on maximum likelihood estimation and generalized linear models.

Quantitative Analysis: Inference, Causality and Rationality — Lecture & Tutorial (M1, IEDES)
2022–2023, 2023-2024 · 22 students · 21 hours
Assessment: final exam
Introduces students in social sciences to quantitative methods, covering probability, descriptive statistics, linear regression, and instrumental variables. Upon completing the course, students are able to describe data numerically and graphically, read and interpret quantitative articles, and use observational data for causal inference.

Tutored Project — Lecture (M1, IEDES)
2022–2023 · 8 students · 18 hours
Assessment: take-home assignment and presentation
Introduces students to the research process in economics, guiding them through the critical reading and methodological replication of academic papers, with hands-on practice in R and Stata.

Thematic Courses

Development Measurement — Tutorial (M1, IEDES)
2022–2023, 2023-2024 · 40 students · 6 hours
Assessment: take-home assignment and presentation
Complements the Development Measurement lecture through graded assignments on poverty, employment, and inequality measurement. Sessions combine critical reading of academic articles, computation and interpretation of indicators, and in-class presentations and discussions.

Inequality, Vulnerability and Risk Management — Lecture (M2, IEDES)
2023–2024 · 25 students · 18 hours
Assessment: group presentation on selected papers
Explores the concept of risk, its sources, and management strategies. Introduces theoretical frameworks including expected utility theory, Pareto optimality, prospect theory, and risk-sharing models.