“Pearlian causality” is sort of like “Hawkingian physics.” (Not to dismiss the amazing contributions of both Pearl and Hawking to their respective fields).
I am not sure what cool or insightful is for you. What seems cool to me is that proper analysis of causality and/or missing data (these two are related) in observational data in epidemiology is now more or less routine. The use of instrumental variables for getting causal effects is also routine in econometrics.
The very fact that people think about a causal effect as a formal mathematical thing, and then use proper techniques to get it in applied/data analysis settings seems very neat to me. This is what success of analytic philosophy ought to look like!
What you mention in your last paragraph is roughly what I had in mind when asking for examples. So I take it that IVs are a method inspired by causal graphs (or at least causal maths)? If so you’ve answered my question.
IVs were first derived by either Sewall Wright or his dad (there is some disagreement on this point). I don’t think they formally understood interventions in general back in 1928, but they understood causality very well in the linear model special case.
IVs can be used in more general models than linear, and the reason they work in such settings needed formal causal math to work out, yes. IVs recover interventionist causal effects.
“Pearlian causality” is sort of like “Hawkingian physics.” (Not to dismiss the amazing contributions of both Pearl and Hawking to their respective fields).
I am not sure what cool or insightful is for you. What seems cool to me is that proper analysis of causality and/or missing data (these two are related) in observational data in epidemiology is now more or less routine. The use of instrumental variables for getting causal effects is also routine in econometrics.
The very fact that people think about a causal effect as a formal mathematical thing, and then use proper techniques to get it in applied/data analysis settings seems very neat to me. This is what success of analytic philosophy ought to look like!
What you mention in your last paragraph is roughly what I had in mind when asking for examples. So I take it that IVs are a method inspired by causal graphs (or at least causal maths)? If so you’ve answered my question.
IVs were first derived by either Sewall Wright or his dad (there is some disagreement on this point). I don’t think they formally understood interventions in general back in 1928, but they understood causality very well in the linear model special case.
IVs can be used in more general models than linear, and the reason they work in such settings needed formal causal math to work out, yes. IVs recover interventionist causal effects.