Does anyone have any information on likelihood or proportion of American Economic departments hiring international students as research assistants.
I'm to enter a MSc program in UK this autumn and I'm definitely interested in doing a PhD thereafter but am interested to apply for some of RA jobs (plenty posted on NBERs websit) to gain experience as well as added value to application.
However given that I'm an International student, do you know how many students generally apply, how many get accepted or will they sponsor a visa?
Also, as most of these jobs look like data type work along with editing and managing projects and papers; while I'm extremely proficient in Stata, a lot of them emphasize on some kind of mathematical/finance/macro modelling done in Python or R, for which I'm inexperienced in.
Hence I would appreciate some information on chances of being employed as If more than likely, I would expend a lot of time during the MSc to also train and code in Python/R.
Check here as well for postings: Econ RA Listings (@econ_ra) | Twitter
Generally, you will be limited as not all positions sponsor visas. Postings should mention if they can sponsor; if not you should check before applying.
Others may have different opinions on this (I think @startz and/or @Kaysa often advocates for Python knowledge), but I would probably not pour too much time into worrying about Python/R. The more important thing in applications is to show your general coding skills: can you write clean, efficient code that someone else could understand without too much headache? I think being an expert in one language (like Stata) is the better strategy here compared to being adequate in many. Most recruiters will understand that coding skills are transferrable, and that you can pick up the nomenclature of a new language pretty easily. I would only spend time learning Python/R if it has no marginal impact on your grades in your master's program, and even then I might recommend spending that time reading papers or Mostly Harmless Econometrics instead. Or, learning to use Git (check out the awesome GUI "SourceTree"). Or, reading Shapiro/Gentzkow's "Code and Data for the Social Sciences".
Python/R are certainly useful, I don't mean to discount them entirely. But it seems to me that, while some small portion of RA jobs may really care about knowledge in a specific language, the majority just want RA's who are strong in code generally and in empirical economic research know-how. (Even among those that want experience in a specific language, Stata is still the language of choice for a good chunk.) So while not knowing Python may disqualify you entirely from a small proportion of jobs, improving your general coding skills and empirics will make you that much more competitive for the many remaining openings. It also likely has more value-added for you down the road. This seems an easy tradeoff to make, from my view.
An afterthought: I would also guess that any position so invested in Python/R that they won't give you time to pick it up based on experience in another language is also going to only be after applicants who already have extensive experience with Python/R. As in, your self-study of Python/R would have to be deep in order to be very useful, and still you may well be competing against someone else who has already worked full-time using the language. All around I just don't think it's the most efficient way to spend your time boosting your RA application.
Thanks for all the helpful comments
They'll definitely help me plan what to invest my time in. Shapiro/Gentzkow's "Code and Data for the Social Sciences" seems like a useful read. As for MHE, i used it for a microeconometrics course in my final year. Moreover having done an undergrad dissertation, I'm extremely familiar with painstaking data collecting, cleaning and manipulation, but I mostly used STATA to get it done.
I guess I'll focus on generally improving in stata for the time being and use that as well as my dissertation experiences as well as my econometrics know-how from courses taken when applying. I'll have further research experience after writing the MSc dissertation too.
If you're already well-versed in Stata and MHE, it's not that learning Python/R is useless. I just personally would prioritize it below these other things, including doing well in your MSc program. If you're solid on all the rest and twiddling your thumbs, by all means pick up a new language.
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