Don’t Put Too Much Meaning Into Control Variables

Update: The success of this blog post motivated us to formulate our point in a bit more detail in this paper, which is available on arXiv. Check it out if you need a citable version of the argument below.


I’m currently reading this great paper by Carlos Cinelli and Chad Hazlett: “Making Sense of Sensitivity: Extending Omitted Variable Bias”. They develop a full suite of sensitivity analysis tools for the omitted variable problem in linear regression, which everyone interested in causal inference should have a look at. While kind of a side topic, they make an important point on page 6 (footnote 6): Continue reading Don’t Put Too Much Meaning Into Control Variables