To lift the American economy, we need to understand the workers at the bottom of it

When many people and policymakers think of Americans who earn low wages, they may believe these workers are mostly students, or temps, or secondary earners—and thus not be too troubled by their fluid economic situation. In a new Brookings analysis, however, we find the picture is not so simple. More than 53 million people—or 44% of all workers ages 18 to 64 in the United States—can be defined as “low-wage workers,” with median hourly earnings of $10.22. See the methods section of our paper to learn about how we identify low-wage workers.

These low-wage workers are a racially diverse group, and disproportionately female. Fifty-two percent are white, 25% are Latino or Hispanic, 15% are Black, and 5% are Asian American. Females account for 54% of low-wage workers, higher than their total share of the entire workforce (48%).

Fifty-seven percent of low-wage workers work full time year-round, considerably lower than mid/high-wage workers (81%). Among those working less than full time year-round, the data don’t specify if this is voluntary or involuntary, and it is probably a mix.

Two-thirds of low-wage workers are in their prime working years of 25-54, and nearly half of this group (40%) are raising children. Given the links between education and earnings, it is not surprising that low-wage workers have lower levels of education than mid/high-wage workers. Fourteen percent of low-wage workers have a bachelor’s degree, compared to 44% among mid/high-wage workers, and nearly half (49%) have a high school diploma or less, compared to 24% among mid/high-wage workers.

We segment low-wage workers into nine distinct groups

Any group that numbers in the tens of millions includes people in varying circumstances. To show the diversity among low-wage workers and to better inform strategies to help improve their employment prospects, we divide low-wage workers into nine mutually exclusive groups defined by shared characteristics relevant to the labor market. We then create fictionalized personas to illustrate their different circumstances. We use the measures of age, educational attainment, and school enrollment to form the clusters, based on well-established evidence that these factors are important to labor market outcomes, and our judgement that they provide the simplest and most comprehensive assessment of employment prospects.

Age is a fundamental organizing principle for both individuals and society: it shapes people’s activities and roles as well as institutions and policies. A 48-year-old is likely to face and make different labor market choices than a 24-year-old: The older worker is more likely to have family responsibilities, work full time, perhaps face age discrimination, and is less likely to be in school.

Education is a primary sorter of job opportunities. Unemployment rates decrease with additional education, and study after study has found workers with postsecondary degrees earn more than those without.

Lastly, for young adults, school enrollment is an important differentiator, since students have different work patterns than nonstudents, and enrollment in college or training signals future job possibilities. For young people, the higher likelihood of school enrollment points to the need for a balancing act between school and work, as well as strategies to encourage continued school attendance and graduation.

Of course, age, education, and school enrollment are not the only factors that shape a person’s job prospects. Importantly, however, they do apply across demographic groups. Men and women; people who are Black, Latino or Hispanic, white, and Asian American; parents and nonparents; people with and without disabilities—their choices are all informed by their age, education, and enrollment status in ways that are relatively predictable and generalizable.

The largest cluster consists of prime-age adults with a high school diploma or less

The largest cluster, accounting for 15 million people (28% of low-wage workers) consists of workers ages 25 to 50 with no more than a high school diploma. It is one of two clusters that are majority male (54%) and it is the most racially and ethnically diverse of all groups, with the lowest share of white workers (40%) and highest share of Latino or Hispanic workers (39%). Many in this cluster also experience economic hardship, with high shares living below 150% of the federal poverty line (39%), receiving safety net assistance (35%), and relying solely on their wages to support their families (31%). This cluster is also the most likely to have children (44%).

 For more information on the clusters, click on the links below to view a description and personas. For an overview of all of the clusters, please click on this link.

• Cluster 1: Ages 18-24, not in school, no college degree
  • 7.1 million people; 13% of low-wage workers (see full profile)
• Cluster 2: Ages 18-24, in school, no college degree
  • 3.8 million people; 7% of low-wage workers (see full profile)
• Cluster 3: Ages 18-24, with an associate degree or more
  • 2 million people; 4% of low-wage workers. (see full profile)
• Cluster 4: Ages 25-50, with a high school diploma or less
  • 14.8 million people; 28% of low-wage workers (see full profile)
• Cluster 5: Ages 25-50, with some post-secondary education but no degree
  • 7.7 million people; 14% of low-wage workers (see full profile)
• Cluster 6: Ages 25-50, with an associate degree or more  
  • 7.6 million people; 14% of low-wage workers (see full profile)
• Cluster 7: Ages 51-64, with a high school diploma or less
  • 5.6 million people; 10% of low-wage workers (see full profile)
• Cluster 8: Ages 51-64, with some post-secondary education but no degree
  • 2.3 million people; 4% of low-wage workers (see full profile)
• Cluster 9: Ages 51-64, with an associate degree or more
  • 2.4 million people; 5% of low-wage workers (see full profile)

Local and regional leaders in the public, private, and social sectors can use the data in this analysis to better understand their workforce and labor markets. Whether particular clusters or personas are overrepresented or underrepresented should inform economic and employment strategies. In our view, policies and programs to help low-wage workers advance to higher wages and greater financial stability should address both sides of the labor market: the assets and circumstances of workers as well as the number and nature of available jobs. Here are some ways policymakers and programs can do that:

• Improve worker skills.We know a great deal about how to do this, and many successful programs are in place, but at nowhere near the scale required. We should diffuse and scale what works, which will require additional funds, political will for reallocating funding toward evidence-backed programs, a commitment to organizational change on the part of education and training organizations, and greater employer involvement. A related policy question is determining the balance of financial support from the public and private sectors.

• Address discrimination and bias in the labor market. People of color and women are overrepresented in the low-wage workforce, and there is ample evidence that discriminatory practices hurt them in the job market. The federal Equal Employment Opportunity Commission should enforce anti-discrimination laws on the books, while states and localities can also enact and enforce workplace protections. Employers can also review their recruitment, hiring, and promotion practices to determine if they are fully tapping into the available talent pool.

• Promote good jobs through economic and workforce development. The success of any job seeker depends not only upon his or her skills and abilities, but also on the strength of the economy and the number and types of available jobs. We need to rethink our approaches to workforce and economic development by better linking worker skills to firm and regional productivity and focusing more on helping businesses grow and innovate, and less on business attraction and incentives.

The data themselves cannot dictate particular actions, since every locale and region has its own history and institutional capacity. But the findings can shine a light on a segment of the workforce that is often overlooked, and we hope that they inspire people to aim higher and act bigger to improve their communities.