Any sort of statistical or econometric estimator is typically published as an R package.
So for example, I recently saw a paper with a quite complex estimator based on dynamic panels and network (or spacial) interdependence that could identify missing network ties.
For that, an R package exists.
If you want to use it in Python, you'd have to replicate a whole estimation infrastructure yourself, starting by extending the basic models in statsmodels.
That example is quite typical in my opinion.
Like I said, really like to code in Python and I don't like R all that much.
But if someone says: "Why would you use R, Python is better", then we can confidently say the person does not know what R is actually used for.
So for example, I recently saw a paper with a quite complex estimator based on dynamic panels and network (or spacial) interdependence that could identify missing network ties. For that, an R package exists.
If you want to use it in Python, you'd have to replicate a whole estimation infrastructure yourself, starting by extending the basic models in statsmodels.
That example is quite typical in my opinion.
Like I said, really like to code in Python and I don't like R all that much. But if someone says: "Why would you use R, Python is better", then we can confidently say the person does not know what R is actually used for.