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Thread: advice for RA position

  1. #21
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    Re: advice for RA position

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    I am clearly late to the party here but thought I can give colour to the above discussion, involving Kaysa and others (Disclaimer: I was an RA at a highly ranked institution, but was never responsible for evaluating applicants.)

    I think many RA applicants are unaware that RA positions can vary greatly in the way they are managed. Let me give two cases somewhat inspired by reality:

    1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

    2) A junior faculty has a good pipeline of papers making their way through the review process. The professor needs to revise the papers for submission and hires an RA to speed up the process. The RA's work will involve a mix of augmenting the professor's Stata code and running new analyses suggested by referees (say, run a simulation in MATLAB).

    The ideal hedge against the uncertainty is to be a CS whiz and have expertise in all the programming languages used in econ - Stata, R, Matlab, Python, ARCGIS, Fortran etc - but this is not realistic for most candidates, even ones at top schools.

    Now my hunch is that most RA jobs are more like case 1) than case 2). Say you start from scratch. Knowing the above, first you learn Stata, the lingua franca of empirical micro today. Then you invest in languages rising in popularity - Python, GIS, some relational databases. If you still have time, pick up Matlab and R.

    Most importantly, if you say you know a language you need to show you can use it as part of a research pipeline. This is where cold-calling professors for some data work may land you an opportunity - or take a class with a data analysis project at the end.

    ...with all that said, talking about coding so much is looking at the tree and missing the forest. IMO, the largest constituency RA programs service are top-of-class US Liberal Arts College students who need an intermediary to match them to top PhDs. If you are not in that group, take note of the competition.

  2. #22
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    Re: advice for RA position

    Quote Originally Posted by DisraeliShrugg View Post
    I am clearly late to the party here but thought I can give colour to the above discussion, involving Kaysa and others (Disclaimer: I was an RA at a highly ranked institution, but was never responsible for evaluating applicants.)

    I think many RA applicants are unaware that RA positions can vary greatly in the way they are managed. Let me give two cases somewhat inspired by reality:

    1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.

    2) A junior faculty has a good pipeline of papers making their way through the review process. The professor needs to revise the papers for submission and hires an RA to speed up the process. The RA's work will involve a mix of augmenting the professor's Stata code and running new analyses suggested by referees (say, run a simulation in MATLAB).

    The ideal hedge against the uncertainty is to be a CS whiz and have expertise in all the programming languages used in econ - Stata, R, Matlab, Python, ARCGIS, Fortran etc - but this is not realistic for most candidates, even ones at top schools.

    Now my hunch is that most RA jobs are more like case 1) than case 2). Say you start from scratch. Knowing the above, first you learn Stata, the lingua franca of empirical micro today. Then you invest in languages rising in popularity - Python, GIS, some relational databases. If you still have time, pick up Matlab and R.

    Most importantly, if you say you know a language you need to show you can use it as part of a research pipeline. This is where cold-calling professors for some data work may land you an opportunity - or take a class with a data analysis project at the end.

    ...with all that said, talking about coding so much is looking at the tree and missing the forest. IMO, the largest constituency RA programs service are top-of-class US Liberal Arts College students who need an intermediary to match them to top PhDs. If you are not in that group, take note of the competition.
    That's a very helpful summary and you should stick around to help answer applicant questions related to RA work. Many of the frequent posters here (including me) did not have full-time RA experience before grad school.

  3. #23
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    Re: advice for RA position

    Quote Originally Posted by DisraeliShrugg View Post
    1) A junior faculty has obtained access to a "rich" administrative/commercial dataset no one else is using, or has scoped out a way to collect large amounts of data stored on webpages or PDFs. These data have the potential to kickstart a series of papers. With some grant support, the professor hires a RA who will be focused on cleaning, formatting and documenting this dataset.
    I am applying to an RA position in top 10 institution. In the second round, they provided me a data set for ticket price from StubHub with a tricky research question. This data set is unconventional, I don't think many people having access to these kinds of data.

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