teaching

During my PhD, I have worked as a Teaching Assistant for several introductory econometrics courses. I enjoy teaching the foundations of statistics and econometrics because, while our work often delves into complex theoretical details, it’s sometimes fun to get challenged on the very basic bridges between data and theory. Courses I taught so far:

🔹 Quantitative Methods for Public Policy

  • Course Code: PP402
  • Level: Graduate
  • Department: School of Public Policy
  • Description: The course introduces several econometric approaches that are widely used for quantitative and empirical evaluation which can be applied to policy-making. We will develop the basic methodology and assumptions underlying each approach, which is essential to understand when each tool can be applied, and when not. The emphasis is on the practical application of these skills and tools to real-life situations and policy-making interventions. Topics covered include regression analysis, hypothesis testing, randomised control experiments, difference-in-differences regressions, instrumental variables, and regression discontinuity design.
  • Years taught: 2024/25
  • Course Website

🔹 Econometrics I

  • Course Code: EC2C3
  • Level: Undergraduate (2nd year)
  • Department: Economics
  • Description: This course is an applied introduction to econometrics. The focus is on regression-based techniques and interpreting results in applied settings. The course will centre on how statistical tools can be used to answer causal “what-if” questions (e.g., “What is the effect of years of education on income?”). You will work with statistical software to analyse actual data sets and will learn basic programming in Stata through dedicated workshops. Topics include: randomised experiments, programme evaluation, matching, simple and multiple regression analysis, inference, omitted variable bias, functional form specification, measurement error, missing data, reverse causality, and instrumental variables.
  • Years taught: 2022/23, 2023/24
  • Course Website

🔹 Econometrics II

  • Course Code: EC2C4
  • Level: Undergraduate (2nd year)
  • Department: Economics
  • Description: This course builds on the material learned in EC2C3. The focus of the course is the underlying theory of empirical research in economics: estimation methods, properties of estimators (unbiasedness, standard error formula, sampling distribution, consistency) and hypothesis testing. Topics include: Bivariate and multiple regression (estimation, inference, asymptotic property); heteroskedasticity; endogeneity (omitted variables and simultaneity); instrumental variables and two-stage least squares; binary choice models; and time series analysis.
  • Years taught: 2022/23, 2023/24
  • Course Website