I’ve been meaning to answer here for a while - I use causal inference techniques a lot in my work, although largely those from the Rubin world rather than from the Pearl world.
I’m sorry to say that Julia is light years behind R in particular, but also Stata and Python when it comes to causal inference.
Some packages I’ve used (not necessarily recently or professionally, so not endorsements):
- GitHub - JuliaDiffinDiffs/DiffinDiffs.jl: A suite of Julia packages for difference-in-differences
- GitHub - nignatiadis/RegressionDiscontinuity.jl: Estimation for sharp regression discontinuity designs.
- Home · SynthControl (Disclaimer: I’m the main author of this, help very much wanted)
- GitHub - d2cml-ai/Synthdid.jl: Synthetic difference in differences - Julia implementation of https://synth-inference.github.io/synthdid/
- GitHub - kylebutts/QLD.jl: Quasi-long Differencing Panel Data Estimator
I think Julia is a great language for these estimators, but unfortunately there hasn’t really been any project that really went beyond the single maintainer, narrow focus stage.