How important is the apprenticeship model to entering a research career?

Those of us working in research careers can invariably share stories about working as a research assistant, cleaning datasets, coding, running models, doing literature reviews, and many of the other less-glamorous tasks that make up the research process. That was a key aspect of our apprenticeship into the world of research, and a gateway into a research career. But how important really is research assistance as an entry point into a research career?

That is the question addressed in this 2025 NBER Working Paper (ungated version here) by Ina Ganguli (University of Massachusetts, Amherst) and Raviv Murciano-Goroff (Boston University). They look at the impact of working in a university lab (an important subset of research assistance work) on subsequently pursuing a scientific career. Interestingly, Ganguli and Murciano-Goroff use changes in the local minimum wage as an exogenous source of variation in lab employment, so this paper also indirectly contributes to the literature on the employment effects of the minimum wage, in a context (research labs) that is not often the focus of that literature.

Their data comes from UMETRICS, which collates data on research grants across universities, and their dataset covers 32 universities over the period from 2000 to 2019 (although the dataset has coverage up to 2022, including those additional years would mean having to account for the COVID-19 pandemic).

First, using a dataset collated at the lab level, Ganguli and Murciano-Goroff use a staggered difference-in-differences approach to look at the impact of minimum wage changes on employment of undergraduates in the labs. This analysis essentially compares the change in undergraduate employment between the time before and the time after an increase in the minimum wage, between university labs that were affected by the minimum wage increase and those that were not. In that analysis, they find that:

...following minimum wage increases, labs decrease the employment of undergraduates by 7.4% on average...

So, not dissimilar to the literature on minimum wage effects on employment, when focused on young people in exposed occupations. Ganguli and Murciano-Goroff then use the minimum wage change as an instrument for students' exposure to laboratory research as an undergraduate. The key assumption is that minimum wages while an undergraduate affect later scientific careers only through their effect on lab employment opportunities.

Using a dataset of over 28,000 undergraduates and their subsequent career paths, Ganguli and Murciano-Goroff find that:

...decreased exposure to scientific work translates into significantly lower rates of undergraduate research assistants pursuing doctoral degrees or working in the life sciences sector after graduation. We find that working one fewer quarter in a lab during an undergrad student’s college years translates into between a 7.0 and 10.3 percentage point decrease in the rate of enrolling in a doctoral-level program. Given our sample of 28,283 students, this implies that if all students had experienced a minimum wage increase, roughly 500 fewer undergraduates in our sample would have pursued these advanced degrees.

So, the results imply that one fewer quarter of lab experience as an undergraduate reduces enrolment in a doctoral programme by 7.0 to 10.3 percentage points. That is a fairly large effect and should make graduate research programmes take notice of the importance of undergraduate research assistance opportunities for the pipeline into graduate research.

So, working in a lab as an undergraduate is a key pathway towards a career in the life sciences, and when those opportunities are restricted, students are less likely to embark on such a career. These results won't be too surprising to those of us who have been through an apprenticeship as a researcher. It is likely that I would be doing something very different right now if I hadn't been pulled into a lot of research projects towards the end of my undergraduate studies. I almost certainly wouldn't have pursued a PhD, or become an academic. Research assistant jobs are more than just jobs. They provide mentoring, information, skills, networks, references, and a chance to try out being a researcher in a safe setting.

These results also highlight two other things for me. First, they suggest that minimum wage increases may have a negative impact on the career pipeline into science. I'm unsure that this negative impact of the minimum wage has been identified before. However, we should be cautious because Ganguli and Murciano-Goroff are primarily interested in using minimum wage changes to identify the effect of undergraduate research experience on later careers, rather than estimating the overall long-run consequences of minimum wage increases for the scientific workforce. Nevertheless, their results suggest that this may be an important unintended consequence of higher minimum wages, and one that would be worth further research.

Second, given that research assistants do a lot of the 'drudge work' in research, if generative AI is also able to do a lot of that work, that further suggests a negative impact on the career pipeline into science through the rise of generative AI. I know others have written on this before (see here), so the challenge here is not a new idea.

On the plus side, that suggests another method that could be used to further test for the impacts of undergraduate (and graduate) research assistance on future academic careers, beyond focusing on life sciences (as Ganguli and Murciano-Goroff do). By comparing academic fields that are more (or less) exposed to generative AI (especially in the early days of generative AI), we might be able to tease out how important research assistance is to future academic careers across many fields.

Research apprenticeship is important, and these results give us a clear indication of how important it can be. Cleaning data, running models, searching the literature, and doing all the other seemingly mundane tasks of a research assistant are not just cheap ways for senior researchers to get research done. They are also how the next generation of researchers learns what research is, discovers whether they enjoy doing it, and gets started on a research career. If these opportunities are reduced, whether through higher minimum wages or through substitution by generative AI, we may save on some of the drudge work today, but at the cost of having fewer researchers tomorrow.

[HT: Marginal Revolution]

This week in research #138

Here's what caught my eye in research over the past week:

• Akter et al. argue that New Zealand’s low-risk drinking advice is outdated and now overdue for review
• Jones (open access) outlines two scenarios for the impact of artificial intelligence on the economy, providing some guidance about the potential future consequences of AI
• Lee and Porter (open access) provide a simple introduction to the 'weak instruments' problem, including some practical do’s and don’ts implied by the findings of the weak instruments research literature
• Poterba and Werning (open access) summarise the work of last year's John Bates Clark medal winner, Stefanie Stantcheva

Book review: Humble Pi

Alongside my professional interest in popular economics books, I'm a sucker for popular mathematics books like Jordan Ellenberg's How Not to Be Wrong (which I reviewed here). And I particularly like these books if they are fun. So, I was really looking forward to reading Humble Pi, by Matt Parker.

And I wasn't disappointed. Humble Pi is equal parts sombre (after all, there are plenty of maths errors that have led to tragic outcomes, such as the Challenger space shuttle) and amusing (such as Sun Microsystems employee Steve Null, whose details kept disappearing from their database because his last name was NULL). Parker says that the book:

...is a collection of my favourite mathematical mistakes of all time. Mistakes aren't just amusing... they're revealing.

And he's right. There is a lot to learn from this book, while at the same time being amused by (at least some) of the mistakes. Who knew that there was a word 'frigorific'? (a frigorific mixture is a combination of chemicals that always stabilises to the same temperature). And Parker writes in both an engaging and funny style. Consider this:

Do biologists use Excel to process their data? Is the phosphoglycan C-terminal? Yes! (Well, I think it is. It was that or 'Do BP1FB1 genes secrete in the woods?!' but I wasn't confident about that one either. I'm way beyond my limit of biological knowledge trying to look up even obvious microbiology things.) Look: the point is yes. Cell biologists use Excel a lot.

I laughed, until I stopped. And then I laughed again. And there was lots of that while I read this book. Parker also has some pet peeves that come through in the book, such as a strong aversion to stars shining through the shadowed part of a crescent moon. On that point he even takes aim at the Sesame Street classic, I Don't Want to Live on the Moon.

I'll let him off for the anti-Sesame-Street rant, as the rest of the book is a lot of fun to read. I even found the page numbers starting high and counting down to zero to be quite endearing (actually, if I'm honest, I wish more books numbered their pages that way). If you're looking for a good diversion or a change of pace, and don't mind learning a thing or two about maths along the way, this might be a good book for you. Recommended!

Can a simple email nudge students to seek study help?

Students don't always access the help that they need. Often, it's because they don't realise what support is available to them. I'm interested in any way that we can make it easier for students to access support that enhances their learning and helps them to succeed. So, I was really interested to read this 2020 article by Rita Balaban and Patrick Conway (both University of North Carolina at Chapel Hill), published in the AEA Papers and Proceedings (ungated earlier version here).

Balaban and Conway evaluate the impact of emails (passive nudges) reminding students about two economics support programmes that were available on the UNC Chapel Hill campus. The two programmes were the 'EconAid Center', which provided walk-in peer tutoring during weekdays and early evenings, and a series of five hour-long learning strategy seminars run by the co-authors. Students were randomly assigned to one of two email groups, one of which received weekly reminders about the EconAid Center, while the other received reminders before each learning strategy seminar. The evaluation focuses on the 199 students who consented to participate.

Those emails represent a very light-touch intervention. But did they work? The nudges did get students to engage with the programmes, but only for female students and first-year students, who were more likely to engage with the EconAid Center if they received the email nudges. Female students and students of colour were actually less likely to attend the learning strategy seminars if they received the email nudges. So, at best a mixed result.

Turning to whether the two programmes worked to improve grades:

The coefficients corresponding to the effects of the support programs on performance are positive but insignificantly different from zero.

Now, the small sample of 199 students (and the much smaller samples for subgroups) may simply have been too small to estimate the effects precisely. Participation in the programmes was also relatively low. A larger study might therefore do a better job of telling us whether the programmes actually had an effect or not.

So, file this study away under possibilities for the future. Light-touch nudges may help some students take the first step towards seeking support. A natural extension today would be to test whether similar nudges can steer students towards effective human or AI-assisted study support.