Job losses have disproportionately affected minorities, women, younger workers, and workers with lower educational attainment or income, according to our analysis of the US Census Current Population Survey (CPS) as of November 2020.
- Black and Hispanic 1 workers faced 1.6 to 2.0 times the unemployment rates of their white counterparts.
- Households with less than $30,000 in annual income faced double the unemployment rates of higher-income households.
- Women have accounted for nearly 56 percent of workforce exits since the start of the pandemic, despite making up just 48 percent of the workforce.
And these effects build on one another—the economic fallout is even greater for individuals who belong to two or more affected segments.
Given the extensive disruption to employment, an inclusive recovery depends on the ability of vulnerable workers to return to work safely, gain new skills where needed, and find stable new jobs where possible. Overarching strategies, such as providing expanded unemployment benefits and front-loading near-term capital projects, may help ease overall unemployment, but interventions must address specific employment barriers for heavily affected segments. For example, workers without a college degree may need additional training and skills-based credentials to transition to new career pathways. These interventions should also consider how the pandemic’s acceleration of existing trends related to the future of work, including the shift to technology-enabled operating models, will affect workers and skill requirements beyond the immediate future.
Public, private, and nonprofit institutions can pursue coordinated action to address these barriers and facilitate the longer-term skill shifts required for a more resilient workforce. A focus on equity throughout recovery can help the US economy and workforce avoid irreversible damage, especially for its hardest-hit workers.
Jobless recovery: More than 40 percent of employment losses remain
After the US economic recessions of 2001 and 2008, the economy was slower to rebuild jobs than in previous recessions, even with targeted intervention. We anticipate the recovery from the current crisis to be similar to these two recessions, in which employment recovery trailed GDP recovery by two to three years.
In keeping with recent historical trends, the current crisis has seen GDP bounce back quickly while a recovery in employment remains muted. In just two quarters, GDP dropped by 11.4 percent before regaining 75 percent of losses in the third quarter. 3 Meanwhile, employment initially suffered a decline of more than 17 percent (25 million jobs), and had regained just 60 percent of losses as of November 2020.
The economy may also take longer to recover from the COVID-19 pandemic because of structural decline in consumer demand across several large industries (for example, travel and hospitality), resulting in long-term employment losses. Given the impact to consumer demand, we anticipate that many larger enterprises have adjusted their operating models and will continue to do so—for example, by implementing technology and automation that displace workers. The acceleration of existing trends will outlast core employment-recovery timelines.
Rising permanent job losses and long-term economic risks
The rapid but partial recovery of top-line employment fails to reflect worsening long-term economic risks. Employment losses early in the pandemic were caused by a decline in workforce participation—8.3 million workers had stopped looking for work by April—and a sharp increase in temporary unemployment (Exhibit 1). As of November, temporary job losses and workforce participation had largely returned to prepandemic levels, but two concerning trends have emerged. First, the decline in temporary unemployment likely includes a shift to the gig economy and other part-time roles, which vary widely in take-home pay and are more likely to lack benefits. Second, permanent unemployment has doubled since March, leaving a growing set of unemployed workers without jobs waiting for them.
As a result, those who have been out of work or in part-time roles for an extended period of time may face challenges finding stable jobs even as employment rebounds. Accelerated automation and hiring in technology roles may leave behind workers who lack much-needed skill sets while also causing hiring challenges for employers. To promote steady employment and avoid talent shortages throughout the recovery, private- and public-sector leaders could focus on developing new training and career pathways for displaced workers—especially in domains where talent is already scarce and where workers are unlikely to find stable jobs linked to their existing skills.
Priority could be given to workers from the hardest-hit industries, such as accommodation and food services; arts, entertainment, and recreation; education; and healthcare. Collectively, these industries have suffered more than five million job losses—nearly 60 percent of net losses—since November 2019. 7 The severe impact to these industries is the result of several contributing factors, including a delayed return to consumer confidence and spending, potential widespread bankruptcies, and closures of small and medium-size businesses. Workers in each of these industries may need to build on their existing skills to pursue new career pathways.
We studied two employment scenarios to explore which industries might provide job growth and new career pathways for displaced workers during the recovery. Both scenarios suggest that, absent concerted action to address inequity, full recovery for vulnerable populations is unlikely until 2023 or 2024. The scenarios also underscore an emerging shift in skill requirements. For example, the information-technology, government, and healthcare industries have the potential to exceed prepandemic employment as early as the end of 2021. While job growth in those industries is unlikely to offset the economy’s net job losses, these sectors could still serve as early targets for training and credentialing efforts.
A slower recovery for the most affected demographic groups
The pandemic’s economic impact has fallen disproportionately on minorities, women, younger workers, and workers with lower educational attainment or income. Critically, vulnerabilities intersect, meaning that members of more than one vulnerable group face an even more challenging road to recovery. While available data do not permit an exploration of all intersectionality, a couple of data points illustrate the compounded challenges. For example, as of November, Black workers without a college degree had an unemployment rate of 12 to 14 percent, nearly double that of white workers with comparable educational attainment (6 to 9 percent). 8 In addition, women with less than high-school attainment had an unemployment rate that was ten percentage points higher than their male counterparts compared with prepandemic levels.
Since some government programs ceased in May, nearly eight million Americans have dropped below the poverty line, causing the largest single-year increase in poverty in six decades. 9 Forward-looking employment scenarios indicate this group is likely to be among the slowest to recover, in part because these eight million people are more heavily represented in the sectors and occupations most affected by the pandemic. To ensure an equitable recovery, these disproportionate effects must inform our collective response.
Racial and ethnic minorities
Employment disparities that existed prepandemic have largely endured. Unemployment rates for Black people and other minorities (Native Americans, Native Alaskans, Hawaiians, and Pacific Islanders) are approximately double those of white workers. Hispanic unemployment rates are more than 1.6 times white unemployment rates.
While recovery for Black, Hispanic, and white workers is likely to lag behind that of Asian workers through 2021, we expect this gap to narrow, with recovery to prepandemic employment by the first quarter of 2024 for all races and ethnicities (Exhibit 2). However, this recovery represents a return to the gap that existed prior to COVID-19, not closure of the gap across racial and ethnic groups.
In the economic recovery after the past two economic downturns, women experienced similar or lower unemployment rates than men. In contrast, the pandemic caused the largest female-to-male gap in unemployment rates since 2000, with unemployment for women 2.5 percentage points higher as of November 2020. This initial disparity has translated into an enduring employment gap. Despite accounting for 48 percent of the workforce, nearly 450,000 more women than men have been displaced from work by the pandemic as of November (Exhibit 3). Further, women account for 56 percent of all workforce exits since the start of the pandemic and 100 percent of net job losses in December.
Many women have had to leave their jobs during the pandemic to take care of young children and supervise online learning for school-age children. Forward-looking scenarios indicate employment recovery for women is likely to take 18 additional months compared with men, creating an employment gap that persists beyond the initial recovery.
Recent high-school and college graduates entered the worst economy in decades. In April, workers aged 18 to 24 faced 27 percent unemployment, with 13 percent of this segment ceasing to look for work. While employment has largely recovered, this segment has exited the workforce at twice the rate of other age groups since the start of the pandemic (Exhibit 4). Whether due to graduation delays or challenges finding work, an extended gap between graduation and job placement is likely to permanently affect the earnings trajectories and professional prospects of younger workers—with a disproportionate impact on lower-income students.
Workers with lower educational attainment were among the most affected early in the pandemic, and there remains a wide gap in employment between those with and without a college degree. Moreover, due to the concentration of job losses in accommodation, entertainment, and hospitality, forward-looking scenarios suggest an 18- to 24-month gap between when education groups recover to prepandemic employment (Exhibit 5).
Despite being the only income group with more workers entering the labor force than exiting, households earning less than $30,000 have had the largest increase in unemployment rates since February, resulting in the largest relative employment losses of any income group.
In parallel, forward-looking scenarios suggest that workers earning less than $25,000 are one of only two demographic segments (the other being workers with less than a high-school education) unlikely to recover until 2025—more than two full years after workers earning more than $75,000. A slow recovery for the lowest-earning families may leave many unable to meet basic needs, consequently reducing their ability to train for new career paths and exacerbating existing financial barriers to opportunity.
Ensuring a more equitable recovery
Public, private, and nonprofit institutions must confront difficult challenges throughout recovery: continuing employment losses, the transition of workers to and from the gig economy or part-time work, and the increased need for support services in some segments. In parallel, the continued shift to technology-enabled operating models, which has played a role in rapid GDP recovery, is likely to exacerbate the recovery gap for the most vulnerable workers.
Stakeholders should consider several factors to ensure a more equitable recovery.
First, progress will require collaboration and integrated services across a range of stakeholders. For example, educational institutions and companies may need to provide classroom-to-apprenticeship opportunities for individuals who have been out of a job since April. Applied-learning experiences that emphasize skills and also satisfy credential requirements could help drive a shift to skills-based hiring, smooth reentry into the workforce, and ensure alignment between training programs and employer needs. Similarly, at-risk small businesses may need support transitioning to more resilient operating models and new revenue streams before they can rehire their full workforce. Several coalitions have launched in US cities to support small-business recovery—including Dallas Forward, Detroit Means Business, and Small Business Strong in Boston—and can serve as models for public, private, and nonprofit leaders looking to launch action-focused partnerships. At a national level, the Rework America Alliance—in which McKinsey is a partner—has brought together community organizations, employers, educators, unions, and others to collaborate in expanding employment opportunities for lower-wage workers based on work experience rather than academic credentials.
Second, since the pandemic has disproportionately affected a few key demographics, an equitable recovery must address disparities and unique barriers to employment across race and ethnicity, gender, age, educational attainment, and income groups. Leaders can tailor support for the most affected demographic groups, make resources accessible through trusted channels, and address the full range of employment barriers. For example, educational institutions and companies may need to provide training for non-college-educated workers in partnership with local community organizations or nonprofits that have unique access to underserved workers. And to aid reentry of parents into the workforce, employers and public-sector leaders may need to partner with K–12 schools to address issues with childcare and remote learning.
Third, public, private, and nonprofit leaders can explore ideas for creating near-term, local jobs to accelerate recovery. For example, front-loading capital projects and investments in local small businesses could generate labor demand. Investing in affordable housing and transportation infrastructure would both create jobs and ease core constraints on economic growth. For private-sector leaders, developing a diverse, local supplier base could support community regrowth and ensure greater supply-chain resilience.
Fourth, leaders need to align on an inclusive set of target outcomes—from supporting workforce reentry to reducing aggregate unemployment to using new jobs as entry points to long-term career pathways.
Last, stakeholders need to acknowledge where the recovery runs up against longer-term trends in the future of work. Near-term interventions might address pandemic-related problems in the labor market (workers’ employment gaps, workforce exits, and atrophy of skills caused by lengthy unemployment), but technology-enabled operating models will continue affecting workers for the foreseeable future. As a result, educational institutions may need to tailor programs to address in-demand digital skills with a five- to ten-year view, rather than focusing squarely on postpandemic recovery. In parallel, private- and public-sector institutions may need to consider mobility and retraining for a meaningful portion of their workforces to avoid talent shortages and displaced workers.
Although the current crisis and resulting economic inequality may seem intractable, the crisis offers a window of opportunity to work toward an equitable recovery. Urgent responses to the pandemic and further technological disruption could help avoid long-term talent gaps, depressed consumer demand, and increased economic tension. Such action can also enable employers to reap the economic benefits of a higher-performing, more diverse workforce. To accomplish these goals, leaders across sectors and geographies will need to prioritize equity and place a strong focus on accelerating the recovery for the hardest hit workers.
About the author(s)
André Dua is a senior partner in McKinsey’s Miami office, Kweilin Ellingrud is a senior partner in the Minneapolis office, Michael Lazar is a partner and Tucker Van Aken is a consultant in the Stamford office, Ryan Luby is an expert in the New York office, and Sanjay Srinivasan is a consultant in the Atlanta office.
The authors wish to thank Michael Pusic, Jose Maria Quiros, Ben Saft, Soyoko Umeno, Kristin Unruh, Maricruz Vargas, Julius Vutz, and Grace Zimmerly for their contributions to this article.