Offered Fall 2019, Fall 2020, Fall 2021
This is a course in applied econometrics for doctoral and advanced master level students. The course has two primary objectives: (1) to develop skills in linking economic behavioral models and quantitative analysis, in a way that students can use in their own research; (2) to develop students' abilities to understand and evaluate critically other peoples' econometric studies.
The course focuses on developing the theoretical basis and practical application of the most common empirical models used in health policy research. In particular, it pays special attention to a class of models identifying causal effects in observational data, including instrumental variable estimation, simultaneous equations and two-stage-least-squares, quasi-experiments and difference-in-difference method, sample selection, treatment effect models and propensity score methods.
Lectures will be complemented with computer exercises building on public domain data sets commonly used in health research. The statistical package recommended for the exercises is Stata.