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Book Review
September 2022

STEM education and regional economic development

The STEM Dilemma: Skills that Matter to Regions. By Fran Stewart. Kalamazoo, MI: W. E. Upjohn Institute for Employment Research, 2017, 222 pp.,

In this book, author Fran Stewart begins by recalling a 2016 controversy stirred by the then-newly-elected governor of Kentucky, who proposed a shift of public resources toward college education that promotes “things people want.” This was the governor’s shorthand for saying “yes” to science, technology, engineering, and mathematics (STEM) education and “no” to liberal arts. This opinion permeates American society, and Stewart uses this anecdote to demonstrate the current cultural dominance of STEM education. Indeed, we often see STEM education as a one-way ticket to personal riches and national economic stability. But Stewart also uses Kentucky’s example as a starting point to question whether this belief is based in reality. Throughout the book, she critically examines the efficacy of STEM education as a sole driver of economic development, the meaning of economic development itself, and the role geographic location plays in informing the choice of public investment in human capital.

To carry out her analysis, Stewart relies on data from the Occupational Information Network, a federal database that contains information on the knowledge, skills, and abilities (KSAs) required for a given occupation. This information is collected through a survey asking respondents to rate the importance of different KSAs in the performance of their jobs. Stewart groups these KSAs into “STEM” and “soft” skill categories and distinguishes between jobs with high- and low-level skill demands. Combining these dimensions, she arrives at four occupational skill sets: High STEM/High Soft, High STEM/Low Soft, Low STEM/High Soft, and Low STEM/Low Soft. These categories are then used to compare economic performance across regions, with the aim of identifying the kinds of jobs that can generate the most economic growth.

Examining regional variations is key to Stewart’s analysis, which looks at metropolitan statistical areas (geographic areas where people live, work, and commute) to compare the economic effects of STEM and liberal arts education. This regional focus has several advantages. First, it avoids the fallacy of one-size-fits-all policies that Stewart claims often beguile our elected officials. Second, by considering geography alongside occupational skill level in discussing education policy, it suggests that no matter the supply of jobs, the demand for certain occupations must be there first. For example, as noted in the book, if more than half of a region’s employment is composed of Low STEM/Low Soft jobs, simply dropping engineers from the sky will not generate economic activity. Finally, discussing regional variations is important because young college graduates in STEM disciplines tend to be more geographically mobile.

In examining regional economic performance, Stewart focuses on the following five measures: median wage, growth in gross regional product (GRP), total factor productivity, per capita income, and the poverty rate. This relatively broad set of metrics reflects the idea that economic well-being goes beyond wages and employment. Stewart finds that regions with a higher concentration of High STEM/High Soft occupations have a higher median wage and total factor productivity, but lower GRP growth. Regions with High STEM/Low Soft occupations have the second-highest median wage, followed by regions with Low STEM/High Soft occupations and regions with Low STEM/Low Soft occupations. Stewart’s results also imply that areas with a high concentration of Low STEM/Low Soft jobs are least economically developed, suggesting that local officials in those areas should devise plans for addressing issues such as negative GRP growth and make efforts to attract jobs with higher STEM- and soft-skill requirements. Occupations in the bottom third of the STEM- and soft-skill continuums account for 34.1 percent of U.S. employment, and Stewart rightly points out that these occupations will not disappear overnight and should be accommodated by long-term regional policy.

Throughout the book, Stewart maintains that STEM education is not the only—or even the most likely—path to economic development. In the United States, more than 50 percent of all workers are employed in jobs in the lower half of the STEM- and soft-skill continuums. For every High STEM job, there are 2.6 Low STEM jobs. Stewart points out that there simply are not enough High STEM jobs, so giving everyone an engineering degree is not the panacea for regional economic problems. Moreover, she finds that the focus on STEM education is too narrow. Regions whose employment is dominated by High Soft jobs have higher median wages and higher productivity, irrespective of the level of STEM skills involved. Overall, Stewart advocates for an education policy model that favors responding to labor demand over what she calls the “blunt, supply-based proxy of educational attainment.”

The STEM Dilemma draws heavily on data to reveal the optimal way to structure education policy. It tells us that, before choosing to rely solely on STEM education as a policy tool, we must ensure that the opportunity cost of doing so is worth it and that there are no other, more efficient ways to increase overall economic activity. It should be noted that Stewart’s book was published in 2017, and its analyses do not capture the effects of the coronavirus pandemic. How would these analyses differ now that working from home has become more common? Would regional differences still matter as much given that people with college education have increased their participation in the work-from-home economy? And have advanced soft skills become more coveted in an age of online meetings? These are long-term questions that will only be answered years removed from the pandemic, but Stewart has laid the groundwork that could guide future research and serve as a baseline for detecting significant change.

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About the Reviewer

Michael Daniel Levinstein

Michael Daniel Levinstein is an economist in the Office of Employment and Unemployment Statistics, U.S. Bureau of Labor Statistics.

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