Learning outcomes

The aim of this course is to give students advanced practice of how to conduct empirical economic research. After having taken the course, students should have an advanced understanding of causal inference, and be able to compare, implement and interpret different methods used to estimate causal effects.

Content

The course will cover multivariate regression, nonlinear regression, panel data, instrumental variables, regression discontinuity designs, and differences between experimental and quasi-experimental methods. The course will also cover ways to deal with econometric problems which often arise in applied work, such as missing values, multiple outcomes, non-random samples and outliers. The course will also discuss different philosophies and approaches to causal inference, including the potential outcomes framework, reduced form estimation and structural estimation. The course will cover basic to advanced statistical programming.

Assessment

Written exam