[joker3]

That matters, but I don't think that's happening until all of the big graduate-level metrics textbooks get R versions. And even then, at least a few papers are going to run into trouble with older reviewers who are used to seeing work done in Stata and don't trust anything else.

[alexhutcheson]

Yes, and it's also non-trivial to write R code that matches your textbook's answer if your textbook used Stata. You have to do things like look up which specific variant of the sandwich estimator Stata uses for robust standard errors, so you can tell R to match that.

In Stata's defense: It helps that Stata is actually really good for the "running regressions" part. In particular, it gets robust standard errors right without much extra work in complex cases that would require a lot of additional code in Python or R.

R wins easily for data visualization and scripting, though. It's also much better as a skill you can "take with you". If you end up working in industry, you may not be able to expense a Stata license, but you'll almost certainly be able to use R (although maybe not RStudio).

[mruts]

You don't even want to expense a Stata license. Stata is the worst thing I've ever had to use. Maybe as a person who can't program it makes sense, but as a professional developer almost everything about Stata is non-intuitive, confusing, and stupid. Also the only thing to go on is their stupid pdf manual. Finding real people on the internet who actually use it is almost impossible.