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Did the Post-Recession Recovery Improve Racial Wage Equity?


By Alessia Leibert
September 2023

Among Minnesota workers laid off during the initial months of the Pandemic Recession, how many were able to return to their pre-pandemic wages by the end of 2022? And did claimants of color benefit from the economic recovery?

This study answers these questions by analyzing the earnings of 241,736 people in the Twin Cities Metro who requested UI benefits1 in the initial months of the Pandemic Recession. Given the high rates of inflation post-recession, real earnings (inflation-adjusted) were eroded for workers whose salaries did not keep up with inflation, and these tended to be older workers. Overall, 38% of claimants were unable to return to pre-pandemic wages, suffering wage losses greater than 1% (Figure 1). The share of negatively affected individuals increases with age, penalizing older workers the most.

Figure 1

Shares of claimants suffering losses in real wages and average real wage growth by age

Claimants with lower educational attainment (who are also typically younger) benefited from the extremely tight labor market in those low-wage, low-skill sectors that had to remain closed for longer and could lure workers back to work with high wage offers. As shown in Figure 2, claimants with high school or less posted higher average wage growth than claimants with a bachelor's or higher credential. The most penalized were claimants with a master's degree or higher: 53% of them suffered wage losses greater than 1% of their pre-pandemic wages, not because they switched to lower-paying jobs but because their employer did not adjust their wages enough to offset inflation.

Figure 2

Shares of claimants suffering losses in real wages and average real wage growth by education level

Figure 3 wraps up this introduction by showing strong wage growth among claimants of color. Black claimants and those who identified with more than one race benefited the most, posting an average wage growth of over 16% versus 11% among white claimants.

Figure 3

Shares of claimants suffering losses in real wages and average real wage growth by race/ethnicity

Low-wage workers also benefited. According to this recent report, income for workers in the bottom 25% grew much faster than others even after accounting for inflation.

The Recovery Benefited the Working Poor, but Not Enough to Catch Up

Did higher wage growth for the segments of the workforce who need it the most fix wage inequalities by race, ethnicity and education? This does not seem to be the case. One and a half years of strong wage growth were not enough to offset the large earnings inequalities that pre-dated the pandemic. The next section breaks down earnings by race/ethnicity, age, and education level to examine pre- to post-pandemic wage inequalities. Figure 4 plots median hourly wages from 1st quarter 2020 to 4th quarter 2022, for a total of 12 quarters - or three years - of data. To simplify the display, the graph shows only the four largest race/ethnic groups and ages 20 to 42.

Figure 4

Growth in real wages from pre-pandemic to 4th quarter 2022

The graph shows that:

  • Racial/ethnic disparities in median wages are evident in each age group and follow the same pattern: Black claimants always trail other groups, white claimants always earn more than other groups, and Asians and Latinos fall in-between.
  • The spikes in wages corresponding to 4th, 8th, and 12th quarter are due to seasonality effects (such as end-of-year bonuses in certain job categories) and follow similar patterns by race/ethnicity;
  • Racial/ethnic disparities emerge very early in life. In the youngest age group (20 to 24) Black claimants with a high school education started from a pre-pandemic hourly wage of $16.28, while other race groups started from wages higher than $17 an hour;
  • Wage gaps widen with age. Initial (or pre-pandemic) wages, corresponding to the first data point in each age range, are always higher than initial wages in the preceding age range. This is to be expected because increases in age correspond to increases in work experience. However, increases over time are much more pronounced among white claimants than among other races, even those without postsecondary credentials. Pre-pandemic wages for white claimants jumped from $17.73 in the 20 to 24 age range to $30.01 an hour in the 37 to 42 range, representing a $12.48 difference or 71%. In contrast, Black claimants in the 20 to 24 age range started with wages of $16.28 and those in the 37 to 42 age range started with $21.69, a difference of just $5.41 dollars, or 33%. Such slower earnings progression with age (or experience) indicates slower career advancement, and lower life-long earning potential, relative to white claimants. As a result, the gap in wages between white claimants and other racial groups widens with age.
  • The good news is that wages for Black claimants have grown more than white claimants within each age range except the youngest, where white claimants' wages grew faster. This result is due primarily to the fact that Black claimants in each age range started from the lowest wages.

Figure 5 displays bachelor's degree holders.

Figure 5

Growth in real wage from pre-pandemic to 4th quarter 2022

The graph shows that:

  • Compared to Figure 4, racial wage gaps at the end of the three years are smaller in every age range, suggesting that earning a bachelor's had an equalizing effect relative to lower levels of education;
  • Wage growth is quite strong for bachelor's degree holders until age 37. From age 43, growth turns into a loss for white claimants due to inflation, while claimants of color still experience some growth. However, this faster wage growth during the recovery is not enough for claimants of color to make up for the initial gap. In the 37 to 42 age range Black workers started at $26.32 and ended at $30.03, a much larger boost than others but not enough to fill the huge initial wage differences;
  • As seen in Figure 4, wage progression from one age range to the next is slower for Black claimants. Higher educational attainment helped Black claimants advance in their careers as they aged (as demonstrated by higher wages in each subsequent age range) but the increase was less rapid than other races.

The following dashboard shows results for all education levels.

Figure 5 earnings outcomes by education level dashboard

The results clearly show that higher education leads to higher wages, but racial disparities remain stubborn and grow larger with age. The earnings of white claimants surpass those of other racial groups at every education level except master's and above, where Asian claimants out-earn white claimants.

Multiple Factors Cause Wage Disparities

The evidence discussed so far boils down to two main trends:

  1. Wage growth over time within the same age range (same age cohort) tends to favor workers of color over white claimants, because the economic recovery was relatively more beneficial to the lowest wage earners;
  2. Wage growth across age ranges (cohorts of different ages) tends to favor white claimants, who have higher returns from work experience and, therefore, higher lifelong earnings than other racial groups regardless of education level. This is also the key reason as to why wage gaps are smaller at a younger age and larger at an older age. This structural inequality cannot be fixed with a few quarters of stronger wage growth for workers of color.

Racial and ethnic disparities are caused by multiple factors. One factor is quality of schooling, which can vary according to a person's socio-economic status, both at the K-12 level and at the post-secondary level2, shaping future earnings trajectories. Minnesotans of color are also less likely than white residents to pursue degrees in high-earning fields such as STEM3. Furthermore, large differences were found across race in job quality and other measures of labor market disadvantage and may prevent certain race groups from accumulating valuable work experience over the course of their working lives. Two sources of job-related disadvantage are employment in part-time or short-tenured jobs and having an employment history in high turnover industries where career ladders are rarely available.

Gaps Shrink Within Occupation

Differences in earnings are not only determined by differences in education. An even greater impact on earnings is from an individual's occupation, which reflects both career choices and investments in education and job training4. Figure 6 shows that claimants of color were over-represented in lower-skill, lower-pay occupations such as Food Preparation, Food Processing (mostly employed in Manufacturing), Home Health & Personal Care Aides, Nursing Assistants, as well as Janitors, Cleaners and Maids. While white claimants represented 68% of all claimants in our dataset, they made up much smaller shares of occupations in this list relative to claimants of color. For example, Black claimants made up 66.3% of all claimants in Home & Personal Care Aides despite the fact that they represented only 15.6% of the total dataset5. Black claimants were also over-represented in seasonal and high turnover occupations such as Childcare Workers.

Figure 6

Pandemic Claimants Resident in the Metro employed in high-risk frontline occupations

A second dashboard allows users to drill down into the occupational category that claimants reported at the time of layoff in 2nd quarter 2020. Although it shows occupational groups rather than individual occupations, it sheds light on the role of occupational segregation in racial wage gaps.

Occupational segregation occurs in two main ways: first, when workers of color are less likely to pursue high-earning and growth potential careers and training paths than white workers; second, when workers of color pursue these paths but are prevented from entering the targeted career due to biases in hiring and/or promotional opportunities.

Figure 7 gives a snapshot of dashboard results, comparing two occupations in the Healthcare Support category where white workers were under-represented: Home Health & Personal Care Aides and Nursing Assistants. A question we can ask of this visual is: Do racial wage gaps persist within the same occupational category after holding age and education level constant?

We find much smaller or even reversed racial wage gaps. Among Home Health & Personal Care Aides, wages are flat for all race groups. A 37 to 42-year-old worker can expect the same pay as a 20 to 24-year-old because seniority, or greater experience, does not lead to higher wages in this occupation6. White people in this occupation continue to earn more than other racial/ethnic groups, but not by much. Among Nursing Assistants, both Asian and Black people out-earn white people. The trajectory of Asian workers, in particular, is different from other racial groups, perhaps because many switched occupations after 2020, entering better paid ones. Changes in occupation are likely especially between age 20 and 30, but cannot be measured with our data. In conclusion, if white Minnesotans were represented in these occupations at the same rate as Minnesotans of color (see Figure 6), we would see little or no racial wage gaps. This is why occupational segregation matters.

While controlling for occupation commonly reduces gaps, exceptions exist. In the Construction category, for example (Figure 8), gaps remain stubbornly large even when zooming into detailed occupations and education level. Missing or bumpy lines are due to low sample sizes for claimants of color.

While Latino workers occasionally out-earn white workers, the wage gap between white and Black workers as Carpenters and Electricians is staggering. This stems from the fact that two workers with the same job type can be employed in different industry sectors. For example, white Carpenters and Electricians are more likely to be employed in the Construction industry than their Black counterparts. Over time, this leads to a faster accumulation of skills for white Carpenters and Electricians, eventually resulting in higher wages relative to Black workers. There are also generational differences between the age groupings: young workers who attended college recently might be more marketable than workers who attended college decades earlier, unless they had the opportunity to update their skills through on-the-job training. This factor is linked to the previous one: if white workers have easier access to industries that offer on-the-job training, they are at lower risk of skills obsolescence than non-white workers.

Because of these factors, some of which may be driven by racial biases in hiring and job training, two individuals in the same occupation can end up with very different earnings outcomes depending on different opportunities for skills acquisition.

In conclusion, even in occupations that presumably open up career ladder opportunities, Black claimants' earnings generally trail those of other races except in the youngest age range or at high levels of educational attainment.

Success Stories

Breaking down earnings by occupation reveals some success stories for claimants of color. For example:

  • Latino workers fare extremely well in occupations like Construction and Installation, Maintenance & Repair (all related to the Construction industry), with earnings closely tracking or surpassing those of white workers . Individuals from the Latino community have been very successful at entering the Construction industry and accessing well paid union-jobs not requiring postsecondary education. This is encouraging because these occupations are experiencing severe labor shortages;
  • People from the Latino and Asian communities with no education beyond high school or with some college fare well in Production (especially Food Processing), Transportation & Material Moving, Building & Grounds Cleaning, and Healthcare Support occupations. Unfortunately, these tend to be low-wage occupations, paying less than the overall median;
  • Black workers who pursue careers in healthcare, especially Nursing Assistants, LPNs and RNs, do very well in Minnesota's labor market. Unfortunately, a smaller share of Black workers become employed as RNs – the most financially viable of these careers – relative to white workers7;
  • Black workers with a bachelor's or higher fare extremely well in Education & Training and Community & Social Service occupations, often out-earning white workers. This suggests that they acquired a teaching or counseling license. This is encouraging because these occupations are experiencing severe labor shortages and are looking to diversify. However, obtaining a bachelor's degree or higher credential is unaffordable for many workers of color;
  • Asian workers with a bachelor's or higher credential fare very well in Architecture & Engineering, Computer & Mathematical, and Healthcare Professional & Technical occupations, often out-earning white workers. That's because a relatively high share of Asian Minnesotans pursue graduate studies in high-demand STEM fields and medicine.

These success stories demonstrate that Latino and Asian workers have been more successful in finding their niche in Minnesota's labor market relative to Black workers. Once a niche is created, the perception of acceptance in a field will draw more youth from the community into the same field.8 This evidence also points to a key strategy employers can use to draw new talent and fix labor shortages: recruit from communities of color and make training and career advancement opportunities accessible. This will create recruiting networks to motivate and enable more workers of color to pursue the types of jobs that Minnesota employers are struggling the most to fill and that provide good career opportunities.


This study offers a rare look at the role of age, education, and occupation in producing inequalities in lifetime earnings by race and ethnicity. Here is a summary of findings:

  • The economic recovery post-pandemic has been good for workers of color. Despite inflation, Minnesota saw historically fast wage growth for workers with lower educational attainment and lower wages, including workers of color who were laid off in the initial months of the pandemic. However, one and a half years of strong wage growth are not enough to offset the large earnings inequalities that pre-dated the pandemic;
  • Racial wage gaps generally narrow when education level and occupational category are taken into account. This demonstrates that racial and ethnic wage gaps are partially explained by differences in educational attainment and occupation. However, disparities sometimes persist even when education and occupational category are the same. Black claimants trail other groups, white claimants almost always earn more than others, and Asian and Latino workers fall in-between;
  • We find large generational effects in racial and ethnic wage gaps. Gaps are smallest in the youngest age category (age 20 to 24) and grow larger with age. Slower wage progression over the lifetime for claimants of color relative to white workers at a similar education level suggests that differences in education are not the main reason for the gap. There are other contributing factors, including job segregation by occupation and industry and racial discrimination in hiring, that prevent claimants of color, especially Black workers, from accessing opportunities to train for higher paid careers. Aging always carries the risk of skills obsolescence, but some racial groups appear at higher risk than others. This triggers a vicious cycle: large wealth inequalities, carried over generations, prevent workers of color from investing in postsecondary education, but it is extremely difficult for these workers to accumulate wealth if the time they spend working is less valuable compared to other racial groups. The evidence presented in this and related studies shows how working in short-tenured, low-quality jobs is one of the reasons why certain racial and ethnic groups experience slower growth in wages with work experience relative to their white peers;
  • There are many bright spots, including the fact that Latinos and Asians have established themselves in some high-earning, high demand occupational fields. Black workers, in contrast, were only able to close or narrow the wage gap when they invested in a Nursing license or a bachelor's or higher degree.

Despite the fact that the recovery provided a much-needed wage boost to low-wage workers, the overall findings point to the self-perpetuating and inter-generational nature of racial inequalities and the inextricable relationship between opportunity gaps and skills gaps.

1Since this study is focused on reemployment outcomes, we excluded individuals who were not employed in Minnesota at any time during 2022.

2See Table 2 and Table 3 in

3See Figure 3 in

4Prior research showed how one of the main drivers of racial wage gaps is the racial variation in ability to invest in human capital, of which formal education is just one of many forms. Others are the contributions of time and money that individuals, their parents, their schools and communities (through extra-curricular activities) and their employers make to enhance the individual's skills, including on-the-job training. All of these investments combined help individuals enter and thrive in a specific occupation.

5With the only exception of those claimants who did not report their occupation.

6The 2023 SEIU contract for Personal Care Aides does build in a pay scale based on experience but this does not kick in until 2025.

7This is true not only in our claimants' dataset but in Minnesota as a whole, according to an analysis of postsecondary graduates documented in Figure 3 of this report


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