Econometrics II (advanced level)
- Provide students with analytic and quantitative framework to implement causal inference
- Understand potential outcome and directed acyclic graph approaches
- Know the fundamental problem of causal inference
- Understand the deference between causal identification and estimation
- Understand the role of randomization
- Conduct estimation and inference for average treatment effects in RCT
- Understand the role of covariate adjustment in causal inference
- Learn how to apply instrumental variable design in research
- Understand the role of fixed effects in causal inference
- Learn how to apply difference-in-difference design in research
- Learn how to apply regression discontinuity design in research
- Translating concepts between academia and industry (e.g. A/B testing). Practical challenges in designing and implementing causal inference at scale
- Experimental ideal
- Causal inference with linear regression
- Instrumental variables
- Fixed effects
- Regression discontinuity design
- Causal Inference in Industry
- Group projectsThe task is for groups of 5-6 people.
- QuizzesShort quizzes in class. They will take from 10 to 15 minutes, depending on the complexity.
- TestThe test is carried out in the classroom (remotely in case of switching to online learning), in writing, 80 minutes. The test is a closed book, closed notes. Using course materials is not allowed.
- Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics : An Empiricist’s Companion. Princeton: Princeton University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=329761
- Causality tests in econometrics : choice of causal variables, Sreenivasulu, B., 2013