Thank you!

Out of curiosity, was there any particular reason for prevalence of women as interviewers?

Nice, thanks! 🙏

Haven’t looked into it yet, but did they release the weights of the pre-trained model? A demo I saw only showed a GUI, so just wondering.

Also really helps us students to simply annotate and focus on listening to the lecture, rather than trying to write everything down!

🙋🏻‍♀️

Yes I think Stata should consider integrating this feature given how much they charge, lol.

Thanks for sharing!It could be a good workaround. My comments were based on two experiences recently where the user-written package kept getting updated and our results would change every time. version didn’t help as Stata version was not the problem. We ultimately decided to not use those packages.

Thank you for the link! The guide seems to be very helpful. Option 1: I thought that’s only for version control of Stata itself, not for controlling multiple package versions/updates? And option 2 still seems less convenient than, say, generating an automatic requirements file using a Python IDE.

Thanks for the recommendation! This was meant to be a general comment where I used examples from the three I use frequently! And I have been meaning to look into Julia.

Haha no this was meant to be a general note, I just used examples from the three I regularly juggle with :) I had to learn some basic MATLAB for some work early this year but don’t use it regularly.

personal experience over the years, so you’re free to disagree! It’s just I’ve been meaning to write this 🧵 for a while and finally found some time.

End.

(n/n)

main point of my rant was that don’t be a hostage of a tool, instead know your preferences, common applications and best use cases of each, and decide what’s best given a task. Knowing a couple of things simultaneously doesn’t hurt!
Also this is purely from an Econ perspective and based on (10/n)

a quick analysis, it’s easier to write a do file for an econ-related task than a Python script.
The only place I’d draw the line is probably analysis using Excel. It’s still useful to know extremely basic excel of course, e.g. tracking field team activities, budgeting and HR stuff.
I guess the (9/n)

versions, and equally dislike there’s no version control system for non-official ones (at least not that I’m aware of.) Their help files are well documented usually, and I don’t have to decide which is the best package for a specific task like R. Many time if you have smaller datasets and need (8/n)

of variable names, and without having to create separate lists or dictionaries. This is particularly important in domains who frequently share their findings to policymakers and non-academic audiences. I also like the fact that their official commands have backward compatibility across (7/n)

Many economists still continue to release packages in Stata, which are of more value within our discipline only perhaps or to the wider social science community.

What I personally like is the fact that I can use produce graphs and tables very easily using the variable labels directly instead (6/n)