Causal Inference in Empirical Economics
We, as human beings, tend to attribute cause and effect to observations quite quickly, even if such a causal relationship does not really exist. Causal inference is the science of the study of causal relationships and gives us tools to study rigorously if an intervention, action, or treatment actually casually determines a certain outcome. Causal inference is required to answer questions such as “What is the impact of social distancing on the spread of COVID-19?”, “What is the effect of minimum wages on employment?”, or “To what extent do increases in food prices increase conflict?” In this “Advanced Causal Inference” course five development economists from both Wageningen University (WUR) and Utrecht University (UU), will teach state-of-the-art causal inference methods for both experimental and quasi-experimental designs, and help students to apply these to their own research designs. The course will be taught in hybrid form: each week there will be one physical lecture (either in Wageningen or in Utrecht) and the rest of the meetings will be online. Students that are staying abroad will be allowed to participate online if they participate actively. Of course if restrictions change, we may have to move the course online.
Learning objectives
After successful completion of this course, participants are expected to be able to:
- Use economic theory to design a (quasi) experiment
- Apply and evaluate statistical techniques in terms of valid causal inference
- Appraise various experimental design choices
- Appraise various quasi-experimental methods
- Write a pre-analysis plan including power analysis
Former occurrences of this course
14 Febr – 8 April 2022 | 10 May – 2 July 2021
