This course is intended for PhD candidates planning to conduct econometric analysis or understand the econometric approaches of their peers. The course is designed to allow teams of 2 or 3 students to write their first econometric study. Each team will receive individual advice throughout the process.

The course will first help students to define an appropriate research question in light of the available data and existing literature.

Second, it will give them a concise overview of standard principles, methods and estimation techniques such as the classical linear normal regression model (ordinary least squares (OLS), multicolinearity, heteroscedasticity, serial correlation, normality of the error term, endogeneity), functional forms of regression models, time series (unit roots, cointegration, error correction models), panel data techniques (pooled OLS, fixed and random effects models), qualitative response models (linear probability, logit, probit, Tobit models).

Finally, students will be thought ‘how to get started with Stata’. Put differently, they will learn how to use a state-of-the-art econometric software to handle data and do econometrics.