Causal Analysis in Theory and Practice

Andrew Gelman posted a new blog on Causal Inference https://statmodeling.stat.columbia.edu/2022/05/14/causal-is-what-we-say-when-we-dont-know-what-were-doing/#comment-2053584 which I have found to be not only strange, but wrong. Among the statements that I find objectionable is the title: “Causal” is like “error term”: it’s what we say when we’re not trying to model the process.

I have posted a couple of comments there, expressing my bewilderment, and summarized them in the following statement:

Andrew,
Re-reading your post, I pause at every line that mentions “causal inference” and I say to myself: This is not my “causal inference,” and if Andrew is right that this is what statisticians mean by “causal inference,” then there are two non intersecting kinds of “causal inference” in the world, one used by statisticians and one by people in my culture whom, for lack of better words, I call “Causal Inference Folks.”

I cannot go over every line, but here is a glaring one: “causal inference is all about the aggregation of individual effects into average effects, and if you have a direct model for individual effects, then you just fit it directly.”

Not in my culture. I actually go from average effects to individual effects. See https://ucla.in/3aZx2eQ and https://ucla.in/33HSkNI. Moreover, I have never seen “a direct model for individual effects” unless it is an SCM. Is that what you had in mind? If so, how does it differ from a “mechanistic model.” What would I be missing if I use SCM and never mention “mechanistic models”?

Bottom line, your post reinforces my explicit distinction between “statisticians” and “causal inference folks” to the point where I can hardly see an overlap. To make it concrete, let me ask a quantitative question: How many “statisticians” do you know who subscribe to the First Law of Causal Inference https://ucla.in/2QXpkYD, or to the Ladder of Causation https://ucla.in/2URVLZW, or to the backdoor criterion or etc? These are foundational notions that we “causal inference folks” consider to be the DNA of our culture, without which we are back in pre-1990 era.

For us, “Causal” is not like “error term”: it’s what we say when we ARE trying to model the process.