Teaching
I have taught courses at the Master's and Bachelor's level at WU, served as a teaching assistant at CEU, and organised two reading groups with various guests at WU. You can find details on some of the courses I've taught below.
Econometrics 2 (WU Bachelor)
This class covers econometric methods with a focus on causal inference, and is supplemented with assignments that involve applied coding and prediction tasks. Topics include an introduction to statistical learning, causality, experiments, directed acyclic graphs, instrumental variables, non-linear models, maximum likelihood estimation, regularization, and other methods for causal inference. View Slides
Applied Econometrics (WU Bachelor)
This class builds on Econometrics 2 and covers econometric methods to deal with panel (longitudinal) and time series data, and has students conduct a first research project. Topics include autoregressive and moving average models, unit roots, stationarity, and cointegration, autoregressive conditional heteroskedasticity and vector autoregressive models, as well as spurious correlations, panel datasets, random and fixed effect specifications, and diff-in-diff methods. Request Slides
Bayesian Macroeconometrics (WU Master)
This class provides an introduction to Bayesian econometrics and a deeper dive into time series models, with a focus on vector autoregressive models and issues in macroeconomics. Topics include Bayesian inference, computation, and regression analysis, estimation with simulation-based methods (MCMC), prior specification, model selection and averaging, as well as vector autoregressive models, model diagnostics, identification and structural forms, as well as the analysis of impulse response functions, forecast error variance and historical decompositions. Request Slides
Spatial Economics (WU Master)
This class provides an introduction to spatial data analysis in economic contexts, with a focus on network foundations, regression analysis, and applied issues in environmental and development economics. Topics include basic graph theory and networks, peer-effect and spatial econometric models as well as their theoretical foundations, identification issues, the analysis of spillover effects and of network structures, as well as the basics of spatial economics. Request Slides