From 2016 I will teach a short course in August at the LSE on Health Econometrics. If you are interested you can apply here for a place:
Participants should have some professional experience working in careers that involve health economics, health policy or management. Alternatively this course is also suitable for high level students who are studying in one of the above areas.
This course provides a practical overview of the most common econometric techniques used in health economics and health policy. We begin by providing a foundation of basic statistics which allows us to highlight the ‘evaluation problem’. The remainder of the course focuses on the main approaches available to solve this problem and allow for causal inference: lab experiments, field experiments, natural experiments, linear regression techniques, instrumental variables, regression discontinuity design, propensity score matching, difference-in-differences design and panel data approaches. For each approach, we will discuss the basic intuition, underlying assumptions and relative advantages and disadvantages. We will critically discuss literature that uses each method. The course is ‘hands on’ so participants can expect to get practical experience with Stata using real world data and carefully interpret statistical output.
After successful completion of this course participants will:
1. Acquire a competency in econometrics as it is applied to health economics.
2. Have a working knowledge of Stata.
3. Be able to interpret statistical output and critically assess research design.
4. Be able to clearly distinguish between association and causality in an econometric framework and see the value of both.
5. Have the tools to distinguish between high quality and low quality research that use the introduced techniques