New data map bridges higher education and labour market
The College-to-Jobs Initiative was developed with the support of market data company Lightcast and financial service Capital One. It looked at pre-COVID-19 data for 2014-2019 and noted that the graduate number growth rate between 2014 and 2019 was 14.7% compared to a 4% worker growth rate in a wide range of sectors split into 24 categories.
The data matches graduate number growth with economic mobility in similar regions, in general and, by looking at specific academic disciplines, study areas and degree types, should apply specific filters.
The goal, said Joe Fuller, professor of management practice and co-leader of the Managing the Future of Work Initiative at Harvard Business School, was: “How can we create better pathways for more Americans of all ages and backgrounds to good, paying, household-sustaining jobs?”
Speaking at an online launch seminar for the project, he said: “Social mobility is seen as the golden standard of upwards mobility, but we also see that graduates are under-employed and that there's a considerable scepticism ... about whether or not colleges are a good deal.”
The goal of the data project was to explore whether that was the case, to “investigate the alignment between colleges and the labour market to explore how we could improve those outcomes for more learners”.
Project coordinator David Deming, academic dean and Isabelle and Scott Black Professor of Political Economy at the Harvard Kennedy School, said the college-to-job digital map was a tool to help people ask “the right questions about how we … create better links and pathways between education training institutions and the labour market”.
He suggested users – universities, colleges, employers and policy makers – should dig into the data and see what jobs are highly in demand in any particular area: what employers want; what degrees and certificate programmes are being offered by local institutions; and if there is a mismatch.
If there is, higher education might think about making investments in more career-relevant courses, possibly working with employers and government.
Specific study areas
The freely available database enables users to drill down into a specific study area – and test the local effectiveness of courses, matching graduate growth with economic mobility (comparing student and parent income).
Looking at agriculture studies, for example, the data shows a cluster of high social mobility associated with such courses in California, but weaker social mobility in North Carolina and Tennessee – all strong agricultural regions. For IT and computing studies, there are some impressive nodes of high IT study-associated economic mobility in southern Texas, but some weaker economic mobility around San Francisco, an IT hub.
The labour market side of the database highlights where worker growth outpaces graduate growth – some key mismatches here are in southern Arizona, northern Pennsylvania, and northern Minnesota, for example. By contrast, graduate growth has been seriously outpacing worker growth in much of California, most of Texas (except the far south) and northern Alabama, for example.
Drilling down into occupation types can give more useful guidance to policy makers and educational institutions. Southern Louisiana has a shortage of IT and computing graduates, for example, but New York City and much of New York State does not.
“Is there a mismatch? Is there an opportunity to invest more in healthcare? ... Every town in America has a hospital or medical institution and you often see the education and training institutions are not often in those places ... and it’s a huge growth area in the economy,” said Deming.
Data at your fingertips
“You can have data right at your fingertips,” he said, “It’s a way to compare your areas to others ... It speeds up the research and development process for generating insights about how we can improve economic development in any particular area.”
He said the College-to-Jobs Initiative database will be updated, although in his view it was important not to emphasise real time data, but focus instead on longer run trends, especially if looking to make expensive higher education investment decisions.
“I’d be more confident if there’s a five-year trend,” said Deming.
The potential of the system was hailed during the webinar by Chike Aguh, chief innovation officer at the US Department of Labor, whose own social mobility had been aided by his Nigerian immigrant parents ensuring that their son had a solid US higher education.
He said the education system needed to be “the engine of talent to make sure that we have the workers of today for the technologies of tomorrow”, and that the data might help pinpoint where student and employee recruitment was perhaps less effective for immigrants, non-whites and women.
Education must be used “not simply as a centre of knowledge but also as a critical piece of the economic engine”, offering government and industry tools to ensure people get back to work especially during times of economic disruption, such as the COVID-19 pandemic, said Aguh. We want “to connect higher education more fully and more robustly, more vigorously to the American economy”, he added.
New York University (NYU) School of Professional Studies Dean Angie Kamath said data can help design sophisticated solutions to integrating higher education with workplaces, across society.
“This is a multi-variable problem, and some multivariable solutions are required,” she noted.
The nature of internships could be one focus, she suggested. A student relying on a part-time job to remain solvent during a university course “is not a rational choice”, she said, because the paid job might not be waiting after a work experience gig ended. For such students, a two or three week ‘winternship’ during the college winter break might make a lot more sense, and companies are funding such programmes, she said.
Fuller said he hoped the system will boost “the quality and the accessibility of data ... to do better research” related to designing such opportunities. It would help higher education, employers and government “make more informed decisions and ... ask better or more specific questions about what’s going on in the labour market, where more resources should be employed and what's bottlenecking people’s advancement”.
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