Sectoral Training Programs at the Intersection of Evidence and Values

TLDR: Given their dual aim of boosting participant earnings while expanding equity, new research demonstrates that sectoral training programs confront an equity-effectiveness tradeoff. The findings serve as a reminder that using evidence in decision-making about policy and practice is never value neutral.

Sectoral training programs prepare job seekers for employment in specific industries with strong labor demand and opportunities for career growth. These programs typically operate locally, working with area employers in targeted sectors – often health care, information technology (IT), and manufacturing - to identify in-demand occupations offering high starting wages and benefits along with opportunities for career advancement.

Sectoral training programs also aim to provide a path to higher-paying jobs specifically for adults who traditionally face barriers to employment, including individuals from low-income backgrounds and without a college degree. In other words, these programs are dually aimed at impacting both employment and equity.

Impacts on employment and earnings

In terms of employment and earnings impacts, a 2022 summary of evidence notes that high-performing sectoral training programs yield some of the largest average effects observed among evaluations of US training and employment services programs. These programs lead to sizeable increases in earnings in the year following training completion, while evaluations that follow participants for longer periods demonstrate that these earnings persist. Sectoral training programs also increase participation in training and career services and attainment of educational credentials and certificates attained, particularly in the targeted sectors.

Impacts on equity

Sectoral training programs also aim to impact equity by expanding opportunity for workers without four-year college degrees and those from low-income and historically underserved backgrounds. In terms of equity impacts, the authors of a new study note that the average effects of sectoral training programs provide an imcomplete picture. Because many of these programs – including the one their research focuses on, Year Up – can serve only a certain number of participants, they screen applicants to identify those most likely to meet the program’s demands and benefit from participation. Thus, average impacts tell us more about program effects for screened-in applicants than about how sectoral training programs are addressing their equity aims.

An equity-effectiveness tradeoff

To better understand how sectoral training programs are advancing equity, the researchers use statistical and machine learning techniques to sort Year Up applicants into five ordered groups (quintiles) based on predicted program impacts on their earnings. Then they examined the characteristics of participants in each quintile.

Applicants in the top quintile of predicted earnings received about three times the earnings boost from Year-Up participation relative to those in the bottom quintile. Applicants in this bottom quintile, who received the smallest predicted earnings, were disproportionately from Black, female, low-income, and lower skilled backgrounds.

In other words, Year Up confronts an equity–effectiveness tradeoff.

This isn’t necessarily surprising. Average impacts across evaluations of education and training programs tend to obscure differential impacts among participants with varying backgrounds. At least some of these programs make (unobserved) tradeoffs between effectiveness and equity. These tradeoffs are simply easier to see with sectoral employment programs because these programs explicitly pursue two objectives simultaneously: raising earnings and expanding opportunity for disadvantaged workers. Yet they must screen applicants due to capacity constraints.

Evidence use and values

The study concludes that because maximizing either effectiveness or equity comes at the other’s expense, the key is adjusting screening criteria so that both are optimized. This assumes that both goals are equally important. Yet concluding that expanding opportunity for those who’ve faced disproportionate disadvantage for generations or even centuries should not come at the expense of overall benefits for everyone is, of course, a value judgment.

I appreciated this study and its engagement with the tradeoffs we make between effectiveness for all and expanding equity for those we have long underserved. What I most appreciate is the reminder that while the idea of using evidence in decision-making about policy and practice sounds value neutral, it is not. And surfacing the values that inform how we interpret and act on evidence can help us better assess the kinds of tradeoffs we may be making, and with what consequences for whom.