What is the state of U.S. wages? Slow wage growth persists: Consistent positive wage growth has occurred in only 10 of the last 40 years.

Inequality continues: The highest earners (95th percentile) continue to pull away from middle- and low-wage workers.

Policy matters: Wage growth at the bottom was strongest in states with minimum wage increases in 2019.

Black–white wage gaps persist: In 2019, black wages exceeded their 2000 and 2007 levels across the wage distribution for the first time in this recovery. Even so, black–white wage gaps are significantly wider now than in 2000.

Gender gaps defy educational attainment: Women with an advanced degree are paid, on average, less than men with a college degree.

College graduates are losing ground: Wages for the bottom 50% of college graduates are lower today than they were in 2000.

Rising wage inequality and slow and uneven hourly wage growth for the vast majority of workers have been defining features of the U.S. labor market for the last four decades, despite steady (if too slow) productivity growth. In only 10 of the last 40 years did most workers see any consistent positive wage growth: in the tight labor market of the late 1990s and in the last five years (2014–2019), when the unemployment rate hit its lowest point in 50 years. Despite these gains, wage inequality continues to climb and workers at the middle and bottom of the wage scale are just making up lost ground and continue to struggle to make ends meet rather than get ahead. The median hourly wage—the wage at which half the workforce is paid more and half the workforce is paid less—stands at $19.33 per hour. For a full-time, full-year worker, this would translate into about $40,000 per year.

This report begins with a look back at 40 years of wage data, highlighting the continued divergence of productivity and pay and the unequal and uneven wage growth for most workers. This report then takes a deeper look at the most up-to-date hourly wage trends, through 2019, across the wage distribution and across education categories, highlighting important differences by race, ethnicity, and gender. By looking at real (i.e., inflation-adjusted) hourly wages by percentile, we can compare what is happening over time for the lowest-wage workers (those at the 10th and 20th percentiles) and for middle-wage workers (those at or near the 50th percentile) with wage trends for the highest-wage workers (those at the 90th and 95th percentiles).

The median wage in 2019 is $19.33 per hour, which translates into about $40,000 per year for a full-time, full-year worker.

The data show not only rising inequality through the 2000s, but also the persistence—and in some cases worsening—of wage gaps by gender and race. What also stands out in this last year of data is that, while wages are growing for most workers, wage growth continues to be slower than would be expected in an economy with historically low unemployment.

Finally, we dispel some rather pervasive but uninformed myths about why wage growth has been so slow for most workers over the last 40 years. Slow wage growth cannot be explained away by positing education shortages, by including benefits and looking at total compensation, or by changing the price deflator (changing the way wages are adjusted for inflation). To the contrary, the potential for wage growth has been squandered on the very few at the top, leaving the vast majority of the U.S. workforce without economic power and the means to achieve a decent standard of living.

Slow and unequal wage growth is the result of a series of policy decisions that have reduced the leverage of most workers to achieve faster wage growth. At the conclusion of this report, we discuss an array of solutions to reverse these trends.

Summary of key findings

Below is a summary of the key findings of this report. These findings are outlined in greater detail in subsequent sections of the report.

Slow wage growth and rising inequality is the norm. Over the last 40 years, wages for the vast majority of the U.S. workforce have grown slower than their potential and much slower than for those at the top.

Without the wage growth spurred by exceptionally low unemployment in the late 1990s and the last five years, wages for most workers would be lower today (in real terms) than they were 40 years ago.

Even with recent wage growth, the median wage—the wage at the center of the wage distribution—is only $19.33 an hour, which translates into about $40,000 for a full-time, full-year worker.

Wage inequality. From 2000 to 2019, wage growth was strongest for the highest-wage workers, continuing the trend in rising wage inequality since 1979.

Since 2007, the labor market peak before the Great Recession, the strongest wage growth has continued to be within the top 10% of the wage distribution.

From 2018 to 2019, the fastest growth continued at the top (4.5% at the 95th percentile), while median wages grew 1.0% over the year and wages at the bottom fell (-0.7% at the 10th percentile).

Wage inequality by gender. While wage inequality has generally been on the rise for both men and women, wage inequality is higher and growing more among men than among women.

In recent years, it has become increasingly difficult to accurately assess 95th-percentile hourly wages for men. This is because the CPS does not provide data for weekly earnings above $2,884.61 (i.e., earnings are “top-coded”) and an increasing share of men have earnings above this amount. (See “What is top-coding and how does it affect data reliability?” below.) We use an imputation procedure (described in Gould 2019) to estimate men’s wage growth at the 95th percentile.

We find that men at the 95th percentile saw the largest wage gains since 2000 (37.1%), almost twice the gains at the 90th percentile (19.9%), while the median wage rose only 3.4% over the entire 19-year period. Low-wage men fared better than those at the middle, rising 11.9% and 10.2% at the 10th and 20th percentiles, respectively. Between 2018 and 2019, low-wage male workers saw the largest increases in earnings.

Since 2000, wage inequality has grown slower among women compared with men. Women have experienced more equal wage growth, ranging from 10.1% at the 40th percentile to 30.0% at the 95th percentile. Between 2018 and 2019, the median woman’s wage grew 3.5% while the 95th-percentile wage grew 3.1% and the 10th-percentile wage grew 2.0%.

Gender wage gap. The “gender wage gap” refers to the historically persistent difference between what men and women are paid in the workplace. While significant gender wage gaps remained across the wage distribution, the gender wage gap at the median continued to shrink over the last year, with a typical woman paid 85 cents on the typical man’s dollar in 2019 (or, facing a 15% wage gap).

The gender wage gap at the 10th percentile remained the smallest across the wage distribution, at 9.2%, though it is about where it was in 2000.

As inequality among men has continued to increase, it is not surprising that the gender wage gap at the top grew significantly and that 95th-percentile women were paid 29.2% less in 2019 than 95th-percentile men.

The regression-adjusted average gender wage gap narrowed slightly from 2000 to 2019, to 22.6%. This measure accounts for differences in educational attainment, age, and other potentially relevant characteristics for wages, and reports the gender wage gap remaining after these statistical controls are used.

Wage growth in states with minimum wage increases. From 2018 to 2019, wages of the lowest-wage workers grew more in states that increased their minimum wage than in those that did not.

On average, in the 27 states without minimum wage increases in 2019, the 10th-percentile wage rose 0.9%; in states with minimum wage increases in 2019 (including the District of Columbia), the average 10th-percentile wage rose by 4.1%.

The differential is larger when looking across recent years with many minimum wage increases: Between 2013 and 2019, when 26 states and D.C. experienced at least one minimum wage increase, the 10th-percentile wage grew much faster in those states (and in D.C.) than in states without any increase (17.6% vs. 9.3%).

In both comparison periods, men and women at their respective 10th percentiles saw greater wage growth in states with minimum wage changes versus those without.

Wage growth by race and ethnicity. At every decile, wage growth since 2000 was faster for white and Hispanic workers than for black workers.

In this analysis, workers are grouped into three mutually exclusive categories: Hispanic, black non-Hispanic, and white non-Hispanic. Sample sizes make it difficult to conduct reliable data analysis for any other race or ethnic group.

After suffering declines in the aftermath of the Great Recession, in 2019, for the first time, wages at all deciles of the black wage distribution exceeded their 2000 and 2007 levels.

Because wages of 95th-percentile white workers exceed the top-coding threshold, their wages have to be imputed (as described in Gould 2019). Regardless of measurement, between 2018 and 2019, the strongest wage growth among white workers was at the top and bottom of the wage distribution.

Over the entire period from 2000 to 2019, Hispanic workers experienced more broadly based wage growth, with strong growth at the top as well as at the median and at the bottom. Over the last year, Hispanic workers’ wage growth was strongest among moderate-wage workers while the 10th percentile lost ground.

Black–white and Hispanic–white wage gaps. Wage gaps by race and ethnicity describe how much less African American and Hispanic workers are paid relative to white workers. Throughout the wage distribution, black–white wage gaps were larger in 2019 than in 2000; conversely, Hispanic workers have been slowly closing the gap with white workers in the bottom 70% of the wage distribution.

After widening for most years since 2000, the regression-adjusted black–white wage gap (controlling for education, age, gender, and region) has narrowed over the last year.

While the Hispanic–white wage gap has narrowed slightly over the last 19 years (12.3% in 2000 compared with 10.8% in 2019), the black–white gap was significantly larger in 2019 (14.9%) than it was in 2000 (10.2%). In 2000, the regression-adjusted Hispanic–white wage gap was larger than the regression-adjusted black–white wage gap. By 2019, the reverse was true.

Wage growth by education. From 2000 to 2019, the strongest wage growth occurred among those with advanced degrees, those with college degrees, and those with less than a high school diploma.

In this report, education attainment is reported in five mutually exclusive categories: less than high school, high school diploma, some college (two-year degree or part of a two- or four-year degree), college (four-year) degree, and advanced degree.

For the first time in this recovery, workers with some college in 2019 just exceeded the 2007 “some college” wage level.

Over the last year, the strongest wage growth occurred among those with some college and those with college degrees.

The wages of those with a college degree rose faster than the wages of those with a high school diploma over the last year, widening the gap between college and high school wages, after it had widened from 2016 to 2018. As a result, the college wage premium—the regression-adjusted log-wage difference between the wages of college-educated and high-school-educated workers—rose to 49.5% in 2019, though it remained below where it was in 2016 (50.6%).

Between 2000 and 2019, the college wage premium rose slightly, from 47.0% to 49.5% over that whole period. The growth in the college wage premium was nowhere near fast enough to explain the total rise in wage inequality over that time.

Wage growth by education and gender. Since 2000, wage growth for those with a college or advanced degree has been faster for men than for women, while wage growth for those with some college, a high school diploma, or less than high school has been faster for women than for men.

In general, the women’s wage distribution by educational attainment is more compressed; that is, the wage differences between workers at different education levels are not quite as large for women as they are for men.

For the first time in this recovery, wages of men with some college have finally reached their 2000 levels.

While there has been a slow narrowing of gender wage gaps since 2000 for those with less than high school, a high school diploma, or some college, gender wage gaps are wider than in 2000 among those with college or advanced degrees.

At every education level, women are paid consistently less than their male counterparts, and the average wage for a man with a college degree is higher than the average wage for a woman with an advanced degree.

Wage growth by education and race and ethnicity. From 2000 to 2019, wage growth for white and black workers was faster for those with a college or advanced degree than for those with lower levels of educational attainment.

Average wages grew faster among white and Hispanic workers than among black workers for all education groups from 2000 to 2019.

In 2019, black workers with some college still had lower wages than in 2000.

From 2018 to 2019, Hispanic workers were the only group that had positive wage growth across all levels of educational attainment.

Black–white wage gaps by education were larger in 2019 than in 2000 for all education groups, while Hispanic–white wage gaps were narrower for workers at any level of educational attainment except those with some college. At nearly every education level, Hispanic and black workers were paid consistently less than their white counterparts.

Some convenient but misguided explanations of slow wage growth. Assorted explanations have been put forth for why wage growth continues to be slow; some even claim that wage growth is not slow. In this report, we examine those arguments closely and find that:

Slow wage growth cannot be explained away by education shortages because the rise in wage inequality has been far larger than the rise in returns to education, with inequality rising sharply within educational categories.

Slow wage growth cannot be explained away by including health insurance costs because average health benefits didn’t grow fast enough to crowd out wage growth, and because many low- and middle-wage workers do not have access to employer-sponsored health insurance, hence growth in its costs is irrelevant to their measured wage trends.

Changing the price deflator used to adjust wages for inflation can boost measured wage growth. But wage growth would still lag far behind growth in economywide productivity, and changing price deflators does not affect measured inequality at all.

1979–2019: Slow wage growth and rising inequality has been the norm over the last 40 years

Wages for the vast majority have grown slower than their potential and much slower than for those at the top.

Since 1979, “real” (inflation-adjusted) hourly pay for the vast majority of American workers has diverged from economywide productivity, and this divergence is at the root of numerous American economic challenges. Figure A displays productivity and hourly compensation from 1947 to 2018. After tracking rather closely in the three decades following World War II, growing productivity and typical worker compensation diverged. From 1979 to 2018, productivity grew 69.6%, while hourly compensation of production and nonsupervisory workers grew just 11.6%. Productivity thus grew six times as fast as typical worker compensation.

Figure A The gap between productivity and a typical worker’s compensation has increased dramatically since 1979 : Productivity growth and hourly compensation growth, 1948–2018 Year Hourly compensation Net productivity 1948 0.00% 0.00% 1949 6.24% 1.55% 1950 10.46% 9.34% 1951 11.74% 12.24% 1952 15.02% 15.49% 1953 20.82% 19.41% 1954 23.48% 21.44% 1955 28.70% 26.38% 1956 33.89% 26.59% 1957 37.08% 30.04% 1958 38.08% 32.72% 1959 42.46% 37.63% 1960 45.38% 40.06% 1961 47.84% 44.37% 1962 52.32% 49.80% 1963 54.86% 55.03% 1964 58.32% 59.94% 1965 62.27% 64.92% 1966 64.70% 69.95% 1967 66.68% 71.98% 1968 71.05% 77.13% 1969 74.39% 77.85% 1970 76.81% 80.35% 1971 81.66% 87.10% 1972 91.34% 92.20% 1973 90.96% 96.96% 1974 87.05% 93.83% 1975 86.86% 98.11% 1976 89.35% 103.59% 1977 92.82% 106.05% 1978 95.66% 108.27% 1979 93.25% 108.11% 1980 88.05% 106.77% 1981 87.36% 110.50% 1982 87.70% 108.37% 1983 88.49% 114.51% 1984 87.03% 120.21% 1985 86.18% 123.65% 1986 87.25% 128.28% 1987 84.67% 128.80% 1988 84.02% 132.01% 1989 83.93% 134.12% 1990 82.37% 136.95% 1991 82.02% 138.50% 1992 83.20% 147.48% 1993 83.46% 148.51% 1994 83.89% 150.54% 1995 82.76% 151.59% 1996 82.87% 156.24% 1997 84.87% 160.72% 1998 89.27% 166.21% 1999 91.98% 173.46% 2000 92.96% 179.47% 2001 95.60% 183.71% 2002 99.49% 191.50% 2003 101.58% 201.22% 2004 100.56% 209.29% 2005 99.73% 215.29% 2006 99.88% 217.61% 2007 101.45% 219.78% 2008 101.39% 221.39% 2009 109.30% 228.75% 2010 111.00% 238.23% 2011 108.47% 238.21% 2012 106.50% 239.57% 2013 108.40% 240.96% 2014 109.08% 242.91% 2015 112.41% 245.75% 2016 114.39% 246.34% 2017 114.67% 249.78% 2018 115.62% 252.90% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Data are for compensation (wages and benefits) of production/nonsupervisory workers in the private sector and for net productivity of the total economy. “Net productivity” is the growth of output of goods and services less depreciation per hour worked. Sources: EPI analysis of unpublished Total Economy Productivity data from the Bureau of Labor Statistics (BLS) Labor Productivity and Costs program and EPI analysis of wage data from BLS Current Employment Statistics, BLS Employment Cost Trends, BLS Consumer Price Index, and Bureau of Economic Analysis National Income and Product Accounts Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

A natural question that arises from these data is just where did the “excess” productivity go? A significant portion of it went to higher corporate profits and increased income accruing to capital and business owners (Bivens et al. 2014). But much of it went to those at the very top of the wage distribution (Mishel and Kassa 2019). As shown in Figure B, the top 1% of earners saw cumulative gains in annual wages of 157.8% between 1979 and 2018—far in excess of economywide productivity growth and over six times as fast as average growth for the bottom 90% (23.9%). Over the same period, top 0.1% earnings grew 340.7%.

While the Current Population Survey Outgoing Rotation Group (CPS)—the primary data set used in this report (EPI 2020a)—is not conducive to disaggregation within the top 5% of the earnings distribution (both because of top-coding and insufficient sample sizes), it is still instructive for measuring the growth in wage inequality over the last 40 years. Figure C illustrates that for all but the highest earners, hourly wage growth has been weak. Median hourly wages (wages at the exact middle of the wage distribution) rose 15.1% between 1979 and 2019, compared with an increase of 3.3% for the 10th-percentile worker (i.e., the worker who earns more than only 10% of workers and less than 90% of workers). Over the same period, the 95th-percentile worker saw wage growth of 63.2%.

Figure C The 95th percentile continues to pull away from middle- and low-wage workers : Cumulative change in real hourly wages of workers, by wage percentile, 1979–2019 Year 10th 50th 95th 1979 0.0% 0.0% 0.0% 1980 -6.7% -0.6% -1.8% 1981 -8.1% -1.7% -1.5% 1982 -11.8% -2.1% 0.5% 1983 -14.7% -1.9% 3.5% 1984 -16.4% -1.4% 3.9% 1985 -17.5% 0.1% 6.1% 1986 -17.2% 0.8% 8.6% 1987 -17.3% 1.9% 11.6% 1988 -16.5% 0.5% 14.3% 1989 -17.1% 0.3% 7.7% 1990 -16.5% 0.2% 9.1% 1991 -15.1% -0.6% 10.6% 1992 -14.4% 0.4% 8.8% 1993 -13.1% 1.9% 6.6% 1994 -13.8% 0.8% 12.4% 1995 -14.7% -0.6% 12.7% 1996 -15.7% -2.3% 13.4% 1997 -13.2% -0.3% 14.8% 1998 -7.8% 3.3% 18.3% 1999 -6.1% 5.9% 21.5% 2000 -6.7% 6.5% 24.9% 2001 -3.8% 8.2% 27.0% 2002 -0.8% 9.8% 31.6% 2003 -1.2% 9.9% 30.5% 2004 -3.0% 11.1% 31.7% 2005 -5.3% 9.5% 32.0% 2006 -5.9% 9.9% 33.2% 2007 -4.3% 10.1% 35.5% 2008 -3.2% 9.3% 36.3% 2009 -2.4% 11.7% 39.4% 2010 -3.2% 11.0% 38.6% 2011 -5.7% 8.2% 37.3% 2012 -7.3% 6.9% 39.0% 2013 -6.7% 7.4% 41.4% 2014 -5.9% 7.5% 39.4% 2015 -1.4% 9.3% 48.3% 2016 -0.6% 11.2% 49.8% 2017 3.5% 12.2% 52.0% 2018 4.1% 14.0% 56.1% 2019 3.3% 15.1% 63.2% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Shaded areas denote recessions. The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

What is top-coding and how does it affect data reliability? The CPS is one of the best measures of hourly pay because it allows researchers to analyze differences across the wage distribution and by demographic characteristics. However, for confidentiality reasons, the CPS “top-codes” weekly earnings: All workers who report weekly earnings above $2,884.61 (annual earnings for full-year workers above $150,000) are recorded as having weekly earnings of exactly $2,884.61, to preserve the anonymity of respondents. This top-code amount of $2,884.61 hasn’t changed or been updated for inflation since 1998 and, as a result, a growing share of workers are assigned this weekly earnings value rather than having their actual wages reported. Because these workers’ actual wages are masked by the top code, it has become harder to uncover the extent of top-end wage levels and growth. (For further discussion of top-coding and its implications, see Ingraham 2019.) Other data, such as data from the Social Security Administration, illustrates that wage growth is far more concentrated at the top than can be illustrated using the CPS, with growth at and within the top 1% exhibiting growth orders of magnitude faster than at the 95th percentile. In the most recent year of data, the top code is assigned to more than 5% of weekly earnings for male workers, white workers, and college-educated workers in the CPS; with no adjustment, this would compromise our 95th-percentile hourly wage estimates. For the purposes of this report, we use what we think is an acceptable proxy for wage growth at this percentile, as described in Gould 2019 (“Methodological considerations” section).

To put this growth in inequality in perspective, consider that the 10th-percentile wage grew from $9.75 to $10.07. Over this 40-year period, wages for this group increased only $0.32 in real (inflation-adjusted) terms. The median wage grew from $16.79 to $19.33, an increase of $2.54. At the top, the 95th-percentile wage grew from $41.15 to $67.14, an increase of $25.99. What’s obvious from these comparisons is that there was a modest increase in the ratio of the middle wage to the lowest wage (the 50/10 wage ratio), but by far most of the increase in inequality occurred between the top and everyone else. During the same period, the 95/10 wage ratio—which describes 95th-percentile earnings relative to 10th-percentile earnings—increased from 4.2 to 6.7, which means that top earners were paid 4.2 times as much as low-paid workers in 1979 and now top earners are paid 6.7 times as much as low-paid workers.

The gap between the top and the middle has also increased significantly. As of 2019, the 95th-percentile wage was 3.5 times as high as the median wage. Recall that the median wage–the wage at which half the workforce is paid more and half the workforce is paid less—in 2019 is $19.33 per hour. For a full-time, full-year worker, this translates into about $40,000 per year.

Except for the wage gains spurred by exceptionally low unemployment in the late 1990s and the last five years, wage growth would have been zero over the last four decades.

Figure A illustrates that typical worker compensation between 1947 and the mid-1970s was not only stronger, but also steadier, than in subsequent years. Since the late 1970s, growth has been slow and uneven, occurring only in fits and starts. Figure D zooms in on average real earnings of the bottom 90%—shown previously as the bottom line in Figure B. There were long periods of stagnant wage growth since 1979, shown in red as well as illustrated by annualized percent changes in the accompanying bar graph. Only in the tightest of labor markets did average wages for the bottom 90% rise in any meaningful way.

Figure E provides a slightly more extreme version of this story, analyzing the median wage from the CPS, shown previously in Figure C. There was consistent positive wage growth in only 10 of the last 40 years. If it hadn’t been for a period of strong across-the-board wage growth in the late 1990s and the last five years, median wages would have fallen outright.

Figure E Consistent positive wage growth has occurred in only 10 of the last 40 years : Cumulative change in real median wages, 1979–2019, and annualized change over specified periods 50th percentile 50th percentile 50th percentile 50th percentile 1979 0.00% 1980 -0.60% 1981 -1.70% 1982 -2.10% 1983 -1.90% 1984 -1.40% 1985 0.10% 1986 0.80% 1987 1.90% 1988 0.50% 1989 0.30% 1990 0.20% 1991 -0.60% 1992 0.40% 1993 1.90% 1994 0.80% 1995 -0.60% 1996 -2.30% -2.30% 1997 -0.30% 1998 3.30% 1999 5.90% 2000 6.50% 2001 8.20% 8.20% 2002 9.80% 2003 9.90% 2004 11.10% 2005 9.50% 2006 9.90% 2007 10.10% 2008 9.30% 2009 11.70% 2010 11.00% 2011 8.20% 2012 6.90% 2013 7.40% 2014 7.50% 7.50% 2015 9.30% 2016 11.20% 2017 12.20% 2018 14.0% 2019 15.1% Chart Data The data underlying the figure. Years Real median hourly wage growth 1979-1996 -0.1% 1996-2001 2.0% 2001-2014 0.0% 2014-2019 1.4% Chart Data The data underlying the figure. Notes: Shaded areas denote recessions. The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

2000–2019: Hourly wages have continued to grow slowly and unequally since 2000

Wage growth since the turn of the century has continued to follow this trend: slower growth for most compared with faster growth for those at the top. Table 1 shows hourly wages by wage decile (and at the 95th percentile) and includes data from 2000 (the previous business cycle peak), 2007 (the most recent business cycle peak), and the two most recent years of data (2018 and 2019).

Table 1 Hourly wages of all workers, by wage percentile, selected years, 2000–2019 (2019$) Wage by percentile Wage ratio Year/range 10th 20th 30th 40th 50th 60th 70th 80th 90th 95th 50th/10th 95th/50th 95th/10th 2000 $9.09 $11.13 $13.25 $15.05 $17.89 $21.01 $25.18 $30.51 $40.17 $51.37 1.97 2.87 5.65 2007 $9.33 $11.24 $13.26 $15.57 $18.48 $21.68 $25.92 $32.08 $43.18 $55.75 1.98 3.02 5.97 2018 $10.15 $12.12 $14.16 $16.22 $19.14 $22.42 $27.25 $34.41 $48.34 $64.25 1.89 3.36 6.33 2019 $10.07 $12.31 $14.64 $16.71 $19.33 $22.95 $27.94 $34.98 $48.08 $67.14 1.92 3.47 6.66 Annualized percent changes Wage ratio change 2000–2019 0.5% 0.5% 0.5% 0.6% 0.4% 0.5% 0.5% 0.7% 1.0% 1.4% 0.0 0.6 1.0 2000–2007 0.4% 0.1% 0.0% 0.5% 0.5% 0.4% 0.4% 0.7% 1.0% 1.2% 0.0 0.1 0.3 2007–2019 0.6% 0.8% 0.8% 0.6% 0.4% 0.5% 0.6% 0.7% 0.9% 1.6% -0.1 0.5 0.7 2018–2019 -0.7% 1.5% 3.4% 3.0% 1.0% 2.4% 2.5% 1.7% -0.5% 4.5% 0.0 0.1 0.3 Note: The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

While the CPS remains one of the best data sets to analyze hourly wage growth across and within demographic groups, some caution should be exercised in interpreting data, because of top-coding and volatility issues. First, top-coding of weekly earnings is catching an increasing number and share of workers as inequality continues to climb, making it increasingly difficult to obtain reliable measures of 95th-percentile wages, particularly for male workers and white workers. Therefore, we make an adjustment when examining recent wage levels and trends for these workers. Second, because the CPS exhibits a fair amount of year-to-year volatility, one-year changes in wages by decile or by demographic group in the CPS—while providing new and valuable information—should be taken with a grain of salt. For a more in-depth examination of these considerations, see Gould 2019. For a full discussion of EPI’s use of the CPS-ORG data, see EPI’s Methodology for Measuring Wages and Benefits (EPI 2019).

In the full business cycle from 2000 to 2007, growth was relatively slow overall and relatively unequal; the gains at the 90th and 95th percentiles were higher than at the middle or bottom of the wage distribution. After growing at about the same rate from 2000 to 2007, wages for the bottom grew significantly faster than wages for the middle from 2007 to 2019, slightly decreasing the 50/10 wage ratio, or the ratio of wages at the middle to wages at the bottom. However, because of the large and disproportionate gains at the top, both the 95/50 ratio (the ratio of 95th-percentile wages to median wages) and the 95/10 ratio (the ratio of 95th-percentile wages to 10th-percentile wages) grew substantially from 2007 to 2019.

With the caveat that, as discussed above, we need to be careful not to assign too much meaning to one-year changes given concerns about data volatility, we note the following trends over the past year: The one-year change in the median wage from 2018 to 2019 was 1.0%, compared with 1.5% at the 20th percentile and a loss of 0.7% at the 10th percentile. The strongest growth in the overall wage distribution occurred at the 95th percentile, at 4.5%.

On the whole, the trends between 2018 and 2019 suggest a continuation of growing wage inequality, with the top in particular pulling away from the middle and bottom. The loss for low-wage workers is somewhat surprising given that the labor market continues to tighten, and tighter labor markets have historically provided disproportionate benefit to wage growth at the bottom. However, the composition of the low-wage workforce may play a role as more previously sidelined workers (re)enter the labor force and find jobs. At this point in the business cycle, these (re)entering workers are less likely to be attached to the labor force in general and wield little bargaining power to garner higher wages; this group might include, for example, workers with lower levels of educational attainment. Further, the bottom 10% of the overall U.S. workforce is increasingly found in states with a minimum wage no higher than the federal minimum of $7.25 per hour, meaning they were less likely to be affected by state-level minimum wage increases across the country (EPI 2020b). For more on the relationship between state-level minimum wages and wage growth for low-wage workers, see the section “Wage growth at the bottom was faster in states that increased their minimum wage in 2019” later in this report.

Figure F illustrates the trends in wages for selected deciles (and the 95th percentile), showing the cumulative percent change in real hourly wages from 2000 to 2019. The overall story of inequality is clear. The lines demonstrate that those with the highest wages have had the fastest wage growth in recent years. From 2000 to 2019, the 95th-percentile wage grew nearly four times as fast as wages at the median (30.7% vs. 8.0%). By 2019, the 95/10 ratio had grown to 6.7 from 6.0 in 2007 and 5.6 in 2000 (see Table 1). This means that on an hourly basis the 95th-percentile wage earner was paid 6.7 times what the 10th-percentile wage earner was paid ($67.14 per hour vs. $10.07 per hour). Similar trends are found in the 95/50 wage ratio, with those at the top pulling away from those in the middle. In 2019, the 95th-percentile wage earner was paid 3.5 times as much as the median worker ($67.14 vs. $19.33), compared with 3.0 times as much in 2007 and 2.9 times as much in 2000.

Figure F High-wage earners have continued to pull away from everyone else since 2000 : Cumulative percent change in real hourly wages, by wage percentile, 2000–2019 year 10th 50th 90th 95th 2000 0.0% 0.0% 0.0% 0.0% 2001 3.1% 1.5% 3.4% 1.7% 2002 6.3% 3.1% 4.5% 5.4% 2003 5.9% 3.1% 4.5% 4.5% 2004 4.0% 4.3% 5.6% 5.5% 2005 1.5% 2.7% 4.9% 5.7% 2006 0.9% 3.1% 6.8% 6.7% 2007 2.6% 3.3% 7.5% 8.5% 2008 3.8% 2.5% 7.4% 9.1% 2009 4.7% 4.8% 10.9% 11.6% 2010 3.8% 4.2% 11.4% 11.0% 2011 1.1% 1.6% 9.1% 10.0% 2012 -0.6% 0.3% 9.8% 11.3% 2013 0.0% 0.8% 10.7% 13.2% 2014 0.9% 0.9% 9.5% 11.6% 2015 5.7% 2.5% 14.0% 18.8% 2016 6.6% 4.4% 16.1% 20.0% 2017 11.0% 5.3% 18.6% 21.7% 2018 11.6% 7.0% 20.3% 25.1% 2019 10.8% 8% 19.7% 30.7% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Note: The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

The gender wage gap continues to shrink but remains significant; wage inequality is higher and growing more among men than among women.

Analyzing wages at different points in the wage distribution over time can mask different outcomes for men compared with women as well as changes in the gender composition of the workforce. Table 2 replicates the analysis of wage deciles for men and women separately, with a comparison of gender wage disparities over 2000–2019. Figures G and H accompany this table, illustrating the cumulative percent change over 2000–2019 in real hourly wages of men and women at selected wage percentiles.

It is important to keep in mind that the top-coding issue in the CPS disproportionately impacts analysis of men’s wages more than analysis of women’s wages because men’s wages are higher and, at the high-end of the wage distribution, wage growth has been much faster for men than for women over the last 20 years. Because more than 5% of men’s weekly earnings were top-coded in the CPS in 2016, 2017, 2018, and 2019, growth in the 95th-percentile men’s wage is estimated using a slightly lower point in the male wage distribution. Depending on the share that is top-coded, we alternatively apply the growth rate of the 93rd or 94th percentile for each of those years to the 95th percentile in 2015.

Table 2 Hourly wages of men and women, by wage percentile, selected years, 2000–2019 (2019$) Wage by percentile Wage ratio 10th 20th 30th 40th 50th 60th 70th 80th 90th 95th 50th/10th 95th/50th 95th/10th Men 2000 $9.77 $12.01 $14.78 $17.23 $20.30 $23.80 $28.43 $34.22 $45.27 $57.36 2.08 2.83 5.87 2007 $9.88 $12.31 $14.76 $17.37 $20.33 $23.94 $28.54 $35.53 $47.62 $61.73 2.06 3.04 6.25 2018 $10.34 $12.70 $15.25 $17.73 $20.47 $24.56 $29.98 $38.15 $53.03 $77.01 1.98 3.76 7.44 2019 $10.93 $13.23 $15.27 $18.01 $21.00 $25.02 $30.16 $38.55 $54.28 $78.64 1.92 3.74 7.19 Annualized percent changes Wage ratio change 2000–2019 0.6% 0.5% 0.2% 0.2% 0.2% 0.3% 0.3% 0.6% 1.0% 1.7% -0.16 0.92 1.32 2000–2007 0.2% 0.4% 0.0% 0.1% 0.0% 0.1% 0.1% 0.5% 0.7% 1.1% -0.02 0.21 0.38 2007–2019 0.8% 0.6% 0.3% 0.3% 0.3% 0.4% 0.5% 0.7% 1.1% 2.0% -0.14 0.71 0.95 2018–2019 5.7% 4.2% 0.2% 1.5% 2.6% 1.9% 0.6% 1.0% 2.4% 2.1% -0.06 -0.02 -0.25 Women 2000 $8.84 $10.41 $11.96 $13.72 $15.75 $18.30 $21.73 $26.52 $34.67 $42.85 1.78 2.72 4.85 2007 $8.89 $10.52 $12.33 $14.28 $16.55 $19.28 $23.27 $28.46 $37.73 $47.58 1.86 2.87 5.35 2018 $9.73 $11.24 $13.02 $15.17 $17.24 $20.33 $24.46 $30.56 $42.00 $54.03 1.77 3.13 5.55 2019 $9.92 $11.91 $13.47 $15.11 $17.84 $20.54 $24.96 $31.24 $42.95 $55.71 1.80 3.12 5.61 Annualized percent changes Wage ratio change 2000–2019 0.6% 0.7% 0.6% 0.5% 0.7% 0.6% 0.7% 0.9% 1.1% 1.4% 0.02 0.40 0.76 2000–2007 0.1% 0.2% 0.4% 0.6% 0.7% 0.7% 1.0% 1.0% 1.2% 1.5% 0.08 0.15 0.50 2007–2019 0.9% 1.0% 0.7% 0.5% 0.6% 0.5% 0.6% 0.8% 1.1% 1.3% -0.06 0.25 0.26 2018–2019 2.0% 6.0% 3.5% -0.3% 3.5% 1.0% 2.0% 2.2% 2.3% 3.1% 0.03 -0.01 0.06 Wage disparities (women’s wages as a share of men’s) 2000 90.4% 86.7% 80.9% 79.6% 77.6% 76.9% 76.4% 77.5% 76.6% 74.7% 2007 90.0% 85.5% 83.5% 82.3% 81.4% 80.5% 81.6% 80.1% 79.2% 77.1% 2018 94.1% 88.5% 85.4% 85.5% 84.2% 82.8% 81.6% 80.1% 79.2% 70.2% 2019 90.8% 90.0% 88.2% 83.9% 85.0% 82.1% 82.7% 81.0% 79.1% 70.8% Note: The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Even using the potentially slightly slower growth rate in recent years at the 93rd and 94th percentiles as a proxy, long-term trends suggest that low- and middle-wage men have fared comparatively poorly and that wage ratios between the top and the middle (the 95/50 ratio) and the top and the bottom (the 95/10 ratio) have increased more for men than for women. Men’s wages at the 95th percentile grew 37.1% from 2000 to 2019, almost twice as fast as at the 90th percentile (19.9%), while at the median, men’s wages barely rose, increasing only 3.4% over the entire 19-year period. Wage growth for lower-wage working men (at the 10th and 20th percentiles) was considerably stronger than for those at or near the middle of the wage distribution, increasing 11.9% and 10.2%, respectively (EPI 2020c).

After seeing their wages fall between 2017 and 2018 (Gould 2019), men at the middle and bottom of the wage distribution saw their wages rise in 2019: a 2.6% increase at the 50th percentile and a striking 5.7% increase at the 10th percentile, along with a 4.2% increase at the 20th percentile. Table 2 shows that our imputed 95th-percentile men’s wage grew 2.1% between 2018 and 2019, on par with its growth since 2007.

Figure G Disproportionate wage growth since 2000 for those at the top has contributed to widening inequality among men in the workforce : Cumulative percent change in real hourly wages of men, by wage percentile, 2000–2019 Year 10th 50th 90th 95th 2000 0.0% 0.0% 0.0% 0.0% 2001 3.1% 0.7% 2.2% 2.2% 2002 2.8% 2.1% 4.6% 4.4% 2003 2.0% 2.4% 4.3% 5.1% 2004 2.5% 0.6% 5.4% 7.5% 2005 0.5% -1.6% 4.3% 6.0% 2006 1.1% -0.3% 5.2% 6.3% 2007 1.1% 0.1% 5.2% 7.6% 2008 -0.2% 0.0% 6.3% 8.8% 2009 0.9% 2.8% 9.7% 14.8% 2010 0.6% 0.4% 9.5% 13.8% 2011 -1.8% -2.1% 7.6% 11.0% 2012 -2.4% -1.6% 8.6% 16.5% 2013 -2.0% -2.6% 9.8% 15.1% 2014 -0.9% -3.5% 7.6% 13.1% 2015 0.5% -0.2% 14.2% 23.2% 2016 7.1% 0.9% 13.1% 29.9% 2017 6.7% 2.3% 15.2% 27.3% 2018 5.9% 0.8% 17.1% 34.2% 2019 11.9% 3.4% 19.9% 37.1% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: The xth-percentile wage is the wage at which x% of wage earners earn less and (100–x)% earn more. The 95th-percentile men’s wage is imputed using the growth rates of the 93rd and 94th percentiles from recent years as needed, since the weekly earnings top code continues to capture a large and growing share of the men’s wage distribution, making it difficult to accurately measure top-level wages. For more information on this issue, see Gould’s State of Working America Wages 2018 (2019). Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Figure H Women’s wages are more compressed than men’s wages, but inequality among women has increased since 2000 : Cumulative percent change in real hourly wages of women, by wage percentile, 2000–2019 Year 10th 50th 90th 95th 2000 0.0% 0.0% 0.0% 0.0% 2001 0.4% 2.1% 1.8% 2.8% 2002 2.8% 5.1% 3.1% 6.1% 2003 2.6% 6.1% 5.7% 7.5% 2004 2.1% 4.7% 6.1% 7.4% 2005 0.9% 4.1% 7.4% 8.6% 2006 0.2% 4.8% 6.9% 9.6% 2007 0.7% 5.1% 8.8% 11.0% 2008 1.1% 6.1% 9.5% 11.3% 2009 4.0% 8.6% 11.4% 13.4% 2010 5.0% 8.1% 14.0% 15.6% 2011 2.4% 7.3% 11.4% 14.7% 2012 0.4% 5.5% 11.2% 14.8% 2013 0.0% 4.7% 11.9% 16.2% 2014 -0.7% 3.4% 12.4% 17.9% 2015 3.7% 5.8% 16.8% 20.9% 2016 7.5% 7.9% 18.5% 24.0% 2017 7.4% 9.3% 20.0% 23.9% 2018 10.2% 9.5% 21.1% 26.1% 2019 12.3% 13.3% 23.9% 30.0% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Note: The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Women also experienced a growth in wage inequality from 2000 to 2019, with the 95th percentile continuing to pull away from the middle and bottom of the wage distribution. Wages at the 90th and 95th percentiles grew about twice as fast as for middle- and low-wage earners over the 19-year period. However, wage inequality among women in 2019 was not as high as it was among men: A 95th-percentile woman was paid 5.6 times as much as a 10th-percentile woman, while the 95/10 ratio for men was 7.2. While inequality has grown modestly among women, the growth in women’s wages is more broadly shared across the wage distribution than the growth in men’s wages. Across wage deciles, women’s wages grew between 10.1% (at the 40th percentile) and 30.0% (at the 95th percentile), while men’s wage growth spanned 3.3% (at the 30th percentile) to 37.1% (at the 95th percentile) between 2000 and 2019.

Median wages for women grew 3.5% between 2018 and 2019 compared with 2.0% at the bottom (10th percentile) and 3.1% at the top (95th percentile). (Again, we do not recommend drawing conclusions about economic trends based on a single year of data; long-term trends give a more reliable picture of what’s going on in the economy.) The largest growth over the year was found at the 20th percentile, where wages grew 6.0%. It is intriguing that faster wage growth for men was at the 10th percentile (with a wage of $10.93 in 2019) while the fastest wage growth for women was at the 20th percentile (with a wage of $11.91 in 2019). A discussion of the role of not only tight labor markets, but also state-level minimum wages for faster wage growth at the bottom of the wage distribution, follows this section.

The “gender wage gap” refers to historically persistent differences between what men and women are paid in the workplace. While significant gender wage gaps remain across the wage distribution, the gender wage gap at the median continued to shrink, with the typical woman earning 85 cents for every dollar a man earned in 2019 (that is, women faced a 15% wage gap). Unfortunately, the narrowing of the gender wage gap at the median between 2000 and 2019 was due in part to particularly slow wage growth in the median men’s wage, which rose only 3.4% over the 19-year period (or 0.2% annually), rather than tremendously fast growth for women (which rose 0.7% on an annual basis—well below economywide productivity growth). If we can stem the tide of rising inequality and claw back the disproportionate gains going to those at the top of the overall wage distribution—which led to wage growth that was about 10 times as fast at the top as at the middle for men (see Figure G)—it would be economically feasible to see both men’s and women’s median wages rise while simultaneously closing the gender wage gap (Davis and Gould 2015). The gender wage gap at the bottom of the wage distribution, while considerably narrower than at the top, has reversed recent years’ gains, and is now back to near where it was in 2000, with women’s 10th-percentile wage 9.2% less than men’s. The largest gender wage gap occurs among the highest-paid workers, with higher-earning women facing a 29.2% pay penalty.

The regression-adjusted average gender wage gap (controlling for education, age, race, and region) showed a small narrowing between 2000 and 2019, from 23.9% to 22.6% (Appendix Table 1), while much greater progress was made between 1979 and 2000; the regression-adjusted gender wage gap was 37.7% in 1979 (EPI 2020c).

Wage growth at the bottom was faster in states that increased their minimum wage in 2019.

In 2019, the minimum wage was increased in 16 states and the District of Columbia through legislation or referendum and in eight states because the minimum wage is indexed to inflation in those states. One state, New Jersey, is double-counted in this tally, as it had both a legislated and an indexed increase in 2019. Most of the minimum wage increases occurred at the start of the year, though some occurred later in the year. For this analysis, we rely on average changes in the minimum wage from 2018 to 2019; therefore, we also include any minimum wage changes that happened during the second half of 2018 without an actual change in 2019, which would imply an increase in the average minimum wage workers faced in 2019 versus 2018; this occurred only in Maryland, where the minimum wage increased from $9.25 to $10.10 in July 2018. Connecticut has the latest minimum wage change in the two-year period, occurring in October 2019, and is still counted among the minimum wage changers for this analysis.

Figure I shows in green the states with minimum wage increases that occurred through legislation or referendum in 2019; states in blue had automatic increases resulting from indexing the minimum wage to inflation. Workers in states that increased their minimum wage between 2018 and 2019 account for about 55% of the U.S. workforce. Comparing the average minimum wage in each state across 2018 with the average across 2019, the amounts of the nominal minimum wage increases, legislated or indexed, ranged from $0.05 (0.5%) in Alaska to $1.00 (9.1%−10.0%) in California, Massachusetts, and Maine.

Figure I The minimum wage increased in 23 states and the District of Columbia in 2019 : States with minimum wage increases in 2019, by type of increase This interactive feature is not supported in this browser. Please use a modern browser such as Chrome or Firefox to view the map. Click here to download Google Chrome.

Click here to download Firefox. Click here to view a limited version of the map. State Abbreviation Category Alaska AK Indexed Alabama AL No change Arkansas AR Legislated or ballot measure Arizona AZ Legislated or ballot measure California CA Legislated or ballot measure Colorado CO Legislated or ballot measure Connecticut CT Legislated or ballot measure District of Columbia DC Legislated or ballot measure Delaware DE Legislated or ballot measure Florida FL Indexed Georgia GA No change Hawaii HI No change Iowa IA No change Idaho ID No change Illinois IL No change Indiana IN No change Kansas KS No change Kentucky KY No change Louisiana LA No change Massachusetts MA Legislated or ballot measure Maryland MD Legislated or ballot measure Maine ME Legislated or ballot measure Michigan MI Legislated or ballot measure Minnesota MN Indexed Missouri MO Legislated or ballot measure Mississippi MS No change Montana MT Indexed North Carolina NC No change North Dakota ND No change Nebraska NE No change New Hampshire NH No change New Jersey NJ Legislated or ballot measure New Mexico NM No change Nevada NV No change New York NY Legislated or ballot measure Ohio OH Indexed Oklahoma OK No change Oregon OR Legislated or ballot measure Pennsylvania PA No change Rhode Island RI Legislated or ballot measure South Carolina SC No change South Dakota SD Indexed Tennessee TN No change Texas TX No change Utah UT No change Virginia VA No change Vermont VT Indexed Washington WA Legislated or ballot measure Wisconsin WI No change West Virginia WV No change Wyoming WY No change Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Minimum wage increases passed through either legislation or ballot measure took effect on January 1, 2019, in Arkansas, Arizona, California, Colorado, Delaware, Maine, Massachusetts, Michigan, Missouri, New York, Rhode Island, and Washington. Alaska, Florida, Minnesota, Montana, New Jersey, Ohio, South Dakota, and Vermont increased their minimum wages in 2019 because of indexing to inflation. New Jersey, Oregon, and Washington, D.C., legislated minimum wage increases that took effect on July 1, 2019. Note that Connecticut legislated a minimum wage increase that took effect on October 1, 2019. This sample considers all changes after January 2018 and before December 2019; therefore, Maryland is included even though the legislated minimum wage increase for Maryland took effect on July 1, 2018. Note that after indexing to inflation on January 1, 2019, New Jersey legislated a minimum wage increase on July 1, 2019; therefore, New Jersey appears twice in these lists. Source: EPI analysis of state minimum wage laws. See EPI’s minimum wage tracker for the most current state-level minimum wage information. Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

When we compare 10th-percentile wage growth among states that are grouped by whether they had any minimum wage increase or not, the comparison yields highly suggestive results. As shown in Figure J, when looking at 10th-percentile wages, growth in states without minimum wage increases was much slower (0.9%) than in states with any kind of minimum wage increase (4.1%). This result holds true for both men and women at the 10th percentile. The 10th-percentile men’s wage grew 3.6% in states with minimum wage increases, compared with 0.7% growth in states without any minimum wage increases, while women’s 10th-percentile wages grew 2.8% in states with minimum wage increases and 1.4% in states without.

Figure J Wage growth at the bottom was strongest in states with minimum wage increases in 2019 : 10th-percentile wage growth, by presence of 2019 state minimum wage increase and by gender, 2018–2019 States with minimum wage increases States without minimum wage increases Overall 4.1% 0.9% Men 3.6% 0.7% Women 2.8% 1.4% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Minimum wage increases passed through either legislation or ballot measure took effect on January 1, 2019, in Arkansas, Arizona, California, Colorado, Delaware, Maine, Massachusetts, Michigan, Missouri, New York, Rhode Island, and Washington. Alaska, Florida, Minnesota, Montana, New Jersey, Ohio, South Dakota, and Vermont increased their minimum wages in 2019 because of indexing to inflation. New Jersey, Oregon, and Washington, D.C., legislated minimum wage increases that took effect on July 1, 2019. Note that Connecticut legislated a minimum wage increase that took effect on October 1, 2019. This sample considers all changes after January 2018 and before December 2019; therefore, Maryland is included even though the legislated minimum wage increase for Maryland took effect on July 1, 2018. Note that after indexing to inflation on January 1, 2019, New Jersey legislated a minimum wage increase on July 1, 2019; therefore, New Jersey appears twice in these lists. Sources: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org, and EPI analysis of state minimum wage laws. See EPI’s minimum wage tracker for the most current state-level minimum wage information. Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

It is not surprising that these differences are smaller than what has been seen in earlier years because as the economy gets closer to full employment, we would expect tighter labor markets to boost the 10th-percentile wage across all states regardless of changes in the minimum wage. Furthermore, 2019 changes in state minimum wages came on the heels of other recent changes to minimum wages in many of the same states in recent years. In fact, when we compare states that have had any minimum wage change since 2013—26 states plus D.C.—with states that did not have a minimum wage change during that time, the pattern is even more pronounced.

As shown in Figure K, wage growth at the 10th percentile in states with at least one minimum wage increase from 2013 to 2019 was almost 90% faster than in states without any minimum wage increases (17.6% vs. 9.3%). As expected, given women’s lower wages in general, this result is even stronger for women (16.1% vs. 7.6%), though men also experienced much faster 10th-percentile wage growth in states with minimum wage increases than in those without (16.0% vs. 9.3%).

Figure K Wage growth at the bottom was strongest in states with minimum wage increases between 2013 and 2019 : 10th-percentile wage growth from 2013 to 2019, by presence of state minimum wage increase between 2013 and 2019 and by gender States with minimum wage increases between 2013 and 2019 States with no minimum wage increases between 2013 and 2019 Overall 17.6% 9.3% Men 16.0% 9.3% Women 16.1% 7.6% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Note: Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, the District of Columbia, Florida, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Montana, New Jersey, New York, Ohio, Oregon, Rhode Island, South Dakota, Vermont, and Washington increased their minimum wages at some point between 2013 and 2019. Sources: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org, and EPI analysis of state minimum wage laws. See EPI’s minimum wage tracker for the most current state-level minimum wage information. Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

From 2000 to 2019, within-group wage inequality grew for white, black, and Hispanic workers.

Table 3 examines wage deciles (and the 95th-percentile wage) for white non-Hispanic, black non-Hispanic, and Hispanic workers from 2000 to 2019. From 2000 to 2019, the strongest growth among white, black, and Hispanic workers occurred at the top of the wage distribution, a sign that wage inequality is growing within each of these groups as well as among workers overall. At every decile, wage growth since 2000 has been faster for white and Hispanic workers than for black workers. After suffering declines in the aftermath of the Great Recession, 2019 is the first time wages at all deciles of the black wage distribution have exceeded their 2000 and 2007 levels.

Table 3 Hourly wages by race/ethnicity and wage percentile, selected years, 2000–2019 (2019$) Wage by percentile 10th 20th 30th 40th 50th 60th 70th 80th 90th 95th White 2000 $9.52 $11.83 $14.11 $16.43 $19.28 $22.46 $26.88 $32.68 $42.75 $53.73 2007 $9.75 $12.23 $14.53 $17.19 $19.91 $23.70 $28.05 $34.47 $45.98 $59.25 2018 $10.26 $12.70 $15.27 $17.98 $20.94 $25.02 $30.06 $37.37 $50.95 $71.61 2019 $10.56 $13.05 $15.45 $18.12 $21.32 $25.07 $30.31 $38.39 $52.04 $73.38 Annualized percent changes 2000–2019 0.5% 0.5% 0.5% 0.5% 0.5% 0.6% 0.6% 0.9% 1.0% 1.7% 2000–2007 0.3% 0.5% 0.4% 0.7% 0.5% 0.8% 0.6% 0.8% 1.0% 1.4% 2007–2019 0.7% 0.5% 0.5% 0.4% 0.6% 0.5% 0.6% 0.9% 1.0% 1.8% 2018–2019 2.9% 2.8% 1.2% 0.8% 1.8% 0.2% 0.8% 2.7% 2.1% 2.5% Black 2000 $8.94 $10.46 $11.96 $13.57 $15.28 $17.82 $20.87 $25.15 $31.95 $38.68 2007 $8.90 $10.57 $12.26 $13.70 $15.46 $17.98 $21.01 $25.09 $34.04 $42.50 2018 $9.32 $10.62 $12.21 $13.90 $15.35 $17.72 $20.80 $26.39 $36.02 $48.83 2019 $9.61 $11.10 $12.93 $14.88 $16.12 $18.56 $21.76 $26.92 $36.03 $47.94 Annualized percent changes 2000–2019 0.4% 0.3% 0.4% 0.5% 0.3% 0.2% 0.2% 0.4% 0.6% 1.1% 2000–2007 -0.1% 0.1% 0.4% 0.1% 0.2% 0.1% 0.1% 0.0% 0.9% 1.4% 2007–2019 0.6% 0.4% 0.4% 0.7% 0.3% 0.3% 0.3% 0.6% 0.5% 1.0% 2018–2019 3.1% 4.5% 5.9% 7.0% 5.0% 4.7% 4.6% 2.0% 0.0% -1.8% Hispanic 2000 $8.59 $9.60 $10.61 $11.94 $13.44 $15.03 $17.90 $21.85 $28.82 $37.07 2007 $8.80 $9.90 $11.15 $12.41 $14.32 $16.20 $18.76 $23.58 $31.01 $40.72 2018 $9.97 $11.15 $12.25 $13.76 $15.31 $17.40 $20.34 $25.07 $34.26 $45.04 2019 $9.94 $11.84 $12.90 $14.43 $15.89 $17.96 $20.47 $25.06 $34.93 $46.33 Annualized percent changes 2000–2019 0.8% 1.1% 1.0% 1.0% 0.9% 0.9% 0.7% 0.7% 1.0% 1.2% 2000–2007 0.3% 0.5% 0.7% 0.6% 0.9% 1.1% 0.7% 1.1% 1.1% 1.4% 2007–2019 1.0% 1.5% 1.2% 1.3% 0.9% 0.9% 0.7% 0.5% 1.0% 1.1% 2018–2019 -0.3% 6.2% 5.3% 4.9% 3.8% 3.2% 0.7% 0.0% 1.9% 2.9% Wage disparities Black as a share of white 2000 93.8% 88.4% 84.8% 82.6% 79.2% 79.3% 77.6% 76.9% 74.7% 72.0% 2007 91.3% 86.4% 84.4% 79.7% 77.7% 75.8% 74.9% 72.8% 74.0% 71.7% 2018 90.8% 83.7% 80.0% 77.3% 73.3% 70.8% 69.2% 70.6% 70.7% 68.2% 2019 91.0% 85.0% 83.7% 82.1% 75.6% 74.0% 71.8% 70.1% 69.2% 65.3% Hispanic as a share of white 2000 90.2% 81.1% 75.2% 72.7% 69.7% 66.9% 66.6% 66.9% 67.4% 69.0% 2007 90.2% 81.0% 76.8% 72.2% 71.9% 68.4% 66.9% 68.4% 67.5% 68.7% 2018 97.2% 87.8% 80.2% 76.5% 73.1% 69.5% 67.6% 67.1% 67.2% 62.9% 2019 94.1% 90.7% 83.5% 79.6% 74.6% 71.6% 67.5% 65.3% 67.1% 63.1% Notes: The xth-percentile wage is the wage at which x% of wage earners earn less and (100−x)% earn more. Race/ethnicity categories are mutually exclusive (i.e., white non-Hispanic, black non-Hispanic, and Hispanic any race). The 95th-percentile white wage is imputed using the growth rates of the 94th percentile from recent years, as needed, since the weekly earnings top code continues to capture a large and growing share of the white wage distribution, making it difficult to accurately measure top-level wages. For more information on this issue, see Gould’s State of Working America Wages 2018 (2019). Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

White workers. We estimate that the strongest wage growth among white workers from 2000 to 2019 was at the 95th percentile. To estimate wage growth for the past year only, from 2018 to 2019, we impute the growth rate for the 95th percentile using the 94th-percentile growth rate from 2018 to 2019. We do this to account for the fact that 5.5% of white workers had weekly earnings at or above the top code. Using our imputation method, we find that wage growth for white workers was much faster over the last year among the highest and lowest wage earners, with a notable 2.9% wage increase at the 10th percentile. In addition to top-coding issues, smaller sample sizes within demographic groups mean wage changes tend to be volatile from year to year, so these changes should be taken with a grain of salt. Since 2000, however, wages have grown three times as fast for white workers at the 95th percentile as for white workers at the middle or bottom of the wage distribution.

Hispanic workers. Over the entire period from 2000 to 2019, Hispanic workers experienced more broadly based wage growth, with wages increasing across their wage distribution: There was strong growth at the top (25.0%) as well as at the median (18.2%) and the bottom (15.7%). Over the last year (2018 to 2019), Hispanic workers’ wage growth was strongest among moderate-wage workers—in the 20th to 40th percentiles—while the 10th percentile lost ground.

Black workers. Between 2018 and 2019, the vast majority of black workers had stronger wage growth than in any other year since 2000; however, black wages at the top have not seen improvement since 2018, while 95th-percentile wages for Hispanic and white workers have risen 2.9% and 2.5%, respectively, since 2018. (Again, when looking at all of these numbers, we need to keep in mind that the CPS data is subject to a certain amount of volatility from year to year; for data on black wages, that volatility is likely to be even more pronounced because of the smaller data sample represented by the black population.) Before 2019, what was particularly striking about black wages was slow wage growth since 2000, nearly across the board. In 2019, the tide turned and all deciles have finally exceeded their 2000 and 2007 levels. Even so, white and Hispanic workers had much faster growth across the board since 2000 than black workers, while black workers have just been making up for lost ground as opposed to actually getting ahead.

From 2000 to 2019, the overall black–white wage gap grew, while the overall Hispanic–white wage gap narrowed slightly.

The bottom section of Table 3 displays wage gaps by race/ethnicity. Wage gaps by race/ethnicity track how much less African American and Hispanic workers are paid relative to white workers; here, black and Hispanic wages are shown as a share of white wages at each decile of their respective wage distributions. Compared with white workers, black workers have been losing ground since 2000, with larger black–white wage gaps across the entire distribution. In 2000, black wages at the median were 79.2% of white wages. By 2019, they were only 75.6% of white wages, representing an increase in the wage gap from 20.8% to 24.4%. Conversely, Hispanic workers have been slowly closing the gap with white workers at the bottom 70% of the wage distribution. In 2000, median Hispanic wages were 69.7% of white wages and, by 2019, they were 74.6% of white wages, representing a narrowing of the gap from 30.3% to 25.4%. The 95th-percentile Hispanic–white wage gap still remains significantly wider than its 2000 level.

The regression-adjusted black–white and Hispanic–white wage gaps (controlling for education, age, gender, and region) both narrowed over the last year (Appendix Table 1). While the regression-adjusted Hispanic–white wage gap narrowed a bit, from 12.3% in 2000 to 10.8% in 2019, the regression-adjusted black–white gap was much larger in 2019 (14.9%) than it was in 2000 (10.2%). In 2000, the Hispanic–white wage gap was larger than the black–white wage gap. In 2019, the reverse was true.

Appendix Table 1 also shows the black–white and Hispanic–white wage gaps for men and women separately. It’s worth noting that these wage gaps are much wider for men than for women, reflecting, in part, the sizeable gender wage penalty experience by white women. Further, between 2000 and 2019, the regression-adjusted black–white wage gap widened significantly for both men (+4.4 percentage points) and women (+4.8 percentage points), while the regression-adjusted Hispanic–white wage gap narrowed for men (−2.3 percentage points) and remained about the same for women (-0.1 percentage points).

Wage growth has generally been faster among the more educated, particularly among men, since 2000.

Table 4 presents the most recent data on average hourly wages by education for all workers and by gender, and Figure L displays the cumulative percent change in real average hourly wages by education. (The discussion throughout identifies each group as mutually exclusive such that those identified as having a college degree have no more than a bachelor’s degree.)

Table 4 Average hourly wages by gender and education, selected years, 2000–2019 (2019$) Wage by education Less than high school High school Some college College Advanced degree All 2000 $12.82 $18.18 $20.69 $31.84 $40.18 2007 $13.27 $18.39 $20.83 $32.53 $41.34 2018 $13.93 $18.79 $20.70 $33.96 $44.59 2019 $14.08 $18.91 $20.97 $34.63 $45.07 Annualized percent changes 2000–2019 0.5% 0.2% 0.1% 0.4% 0.6% 2000–2007 0.5% 0.2% 0.1% 0.3% 0.4% 2007–2019 0.5% 0.2% 0.1% 0.5% 0.7% 2018–2019 1.1% 0.6% 1.3% 2.0% 1.1% Men 2000 $14.09 $20.52 $23.40 $36.19 $44.98 2007 $14.50 $20.44 $23.30 $37.18 $46.84 2018 $15.47 $20.72 $23.25 $39.29 $52.18 2019 $15.33 $20.96 $23.58 $39.99 $52.38 Annualized percent changes 2000–2019 0.4% 0.1% 0.0% 0.5% 0.8% 2000–2007 0.4% -0.1% -0.1% 0.4% 0.6% 2007–2019 0.5% 0.2% 0.1% 0.6% 0.9% 2018–2019 -0.9% 1.1% 1.4% 1.8% 0.4% Women 2000 $10.94 $15.34 $17.82 $26.77 $33.78 2007 $11.32 $15.67 $18.24 $27.43 $34.91 2018 $11.67 $15.71 $17.88 $28.33 $36.68 2019 $12.20 $16.15 $18.44 $29.55 $38.64 Annualized percent changes 2000–2019 0.6% 0.3% 0.2% 0.5% 0.7% 2000–2007 0.5% 0.3% 0.3% 0.3% 0.5% 2007–2019 0.6% 0.3% 0.1% 0.6% 0.8% 2018–2019 4.5% 2.8% 3.2% 4.3% 5.3% Wage disparities (women’s wages as a share of men’s) 2000 77.7% 76.1% 77.5% 75.3% 76.5% 2007 78.1% 78.0% 79.7% 75.1% 75.9% 2018 75.5% 77.9% 78.6% 73.4% 72.3% 2019 79.6% 77.1% 78.2% 73.9% 73.8% Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

The U.S. workforce is split roughly into thirds by educational attainment (EPI 2020c). One-third (34.1%) of U.S. workers have a high school diploma or did not complete high school. A little less than one-third (27.7%) of workers have some college, meaning they may have an associate degree or have completed part of a two- or four-year college degree. The remaining 38.1% have a bachelor’s or advanced degree. It is important to keep in mind when analyzing the labor market or discussing economic policy that 61.9% of the workforce do not have a four-year college degree. If the economy is going to deliver decent wages for most U.S. workers, it needs to deliver for the six in 10 workers who do not have a four-year college degree.

Figure L For workers with some college education, wages have finally surpassed their 2000 level : Cumulative percent change in real average hourly wages, by education, 2000–2019 year Less than high school High school Some college College Advanced degree 2000 0.0% 0.0% 0.0% 0.0% 0.0% 2001 1.5% 1.4% 1.6% 1.7% 0.5% 2002 3.5% 2.8% 2.4% 2.2% 3.0% 2003 4.1% 3.4% 2.1% 1.9% 1.7% 2004 3.1% 2.5% 1.8% 0.9% 3.3% 2005 2.0% 1.3% 0.3% 1.3% 2.4% 2006 1.6% 1.8% 0.1% 1.5% 2.7% 2007 3.5% 1.2% 0.7% 2.2% 2.9% 2008 2.8% 0.6% -0.7% 1.6% 3.4% 2009 5.0% 3.0% 0.6% 2.4% 6.8% 2010 2.6% 1.3% -0.5% 2.7% 6.1% 2011 2.0% -0.7% -3.3% 0.0% 3.4% 2012 0.9% -1.4% -4.7% 0.9% 5.4% 2013 -0.3% -2.3% -5.0% 1.6% 5.5% 2014 -0.1% -2.2% -5.1% 0.1% 2.8% 2015 3.9% 0.0% -2.2% 4.2% 5.3% 2016 5.3% 0.9% -1.4% 6.3% 7.9% 2017 8.5% 2.2% -1.6% 6.1% 7.4% 2018 8.7% 3.4% 0.1% 6.7% 11.0% 2019 9.8% pointoptions showlabel labelcolor=”#4383a3″ labely=+6] 4.0% 1.4% 8.8% 12.2% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

From 2000 to 2019, the strongest wage growth occurred among those with advanced degrees (12.2%), those with college degrees (8.8%), and those with less than a high school diploma (9.8%). Given that those with less than a high school diploma are often the lowest-wage workers in general, it is likely that some of their recent gains can be attributed to state-level increases in the minimum wage. Also, these workers represent a small and shrinking share of the overall workforce, only 8.0% of workers in 2019 (EPI 2020c). The average wage for workers with some college has finally exceeded its 2007 level before the Great Recession began and is now 1.4% higher than it was in 2000, with wages for this group rising just shy of 0.1% per year over the last 19 years.

Over the last year, average wages of those with a college degree and those with some college rose the fastest, 2.0% and 1.3% respectively. After narrowing between 2016 and 2018, the gap between wages of those with a college degree and those with a high school diploma widened (EPI 2020c). However, this unadjusted college/high school wage gap remains narrower than in 2016. Similarly, the college wage premium—the regression-adjusted log-wage difference between the wages of college-educated and high school–educated workers—rose slightly from 48.4% to 49.5% between 2018 and 2019, but remains lower than in 2016 (50.6%) (EPI 2020c).

If the economy is going to deliver decent wages for most U.S. workers, it needs to deliver for the six in 10 workers who do not have a four-year college degree.

Over the entire period from 2000 to 2019, wage growth among those with a college degree rose faster than among those with a high school diploma (8.8% vs. 4.0%). Because of the faster gains for those with more credentials, the regression-adjusted college wage premium grew from 47.0% to 49.5% between 2000 and 2019. For a more thorough discussion of the college wage premium and wage inequality, see the section “Slow wage growth cannot be explained away by education shortages” later in this report.

Figures M and N display the cumulative percent change in real hourly wages by education for men and women, respectively. Since 2000, wage growth for those with a college or advanced degree was faster for men than for women, while wage growth for those with some college, a high school diploma, or less than high school was faster for women than for men. In general, the women’s wage distribution by educational attainment is more compressed; that is, the wage differences between workers at different levels of education are not quite as large for women as they are for men.

For both men and women, the largest gains since 2000 were among those with an advanced degree as well as those with a college degree or less than high school. Wages of both men and women with some college have grown the slowest among all levels of educational attainment. For the first time in this recovery, wages of men with some college have finally reached their 2000 levels.

Figure M Wages grew more quickly for men with college or advanced degrees, and wages for men with some college finally reached their 2000 level : Cumulative percent change in real average hourly wages of men, by education, 2000–2019 year Less than high school High school Some college College Advanced degree 2000 0.0% 0.0% 0.0% 0.0% 0.0% 2001 0.6% 0.8% 1.3% 1.7% 0.1% 2002 3.5% 1.8% 1.2% 2.3% 3.3% 2003 4.1% 1.7% 1.0% 1.9% 2.0% 2004 3.3% 1.1% 0.9% 0.8% 4.7% 2005 2.0% -0.6% -1.1% 1.3% 3.5% 2006 1.1% 0.3% -1.5% 1.3% 3.9% 2007 2.9% -0.4% -0.4% 2.8% 4.1% 2008 2.7% -0.8% -1.7% 2.2% 5.0% 2009 4.8% 1.1% -0.1% 3.9% 9.4% 2010 1.2% -0.9% -2.0% 3.1% 8.5% 2011 0.2% -2.9% -5.4% 0.0% 5.2% 2012 0.1% -3.6% -6.5% 2.0% 9.3% 2013 -1.7% -5.1% -6.4% 2.2% 9.4% 2014 -1.1% -4.6% -6.8% -0.7% 6.1% 2015 3.1% -2.4% -2.9% 5.0% 9.4% 2016 5.1% -2.0% -3.0% 8.6% 12.1% 2017 9.3% -0.1% -3.3% 7.5% 10.3% 2018 9.8% 1.0% -0.6% 8.6% 16.0% 2019 8.8% 2.1% 0.8% 10.5% 16.4% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Figure N Average wages were higher in 2019 than in 2000 for women at all levels of educational attainment : Cumulative percent change in real average hourly wages of women, by education, 2000–2019 year Less than high school High school Some college College Advanced degree 2000 0.0% 0.0% 0.0% 0.0% 0.0% 2001 3.0% 2.3% 2.0% 1.7% 1.5% 2002 3.2% 4.0% 4.0% 2.6% 3.0% 2003 3.6% 5.5% 4.0% 2.6% 2.6% 2004 1.9% 4.0% 3.3% 1.5% 2.4% 2005 0.9% 3.0% 2.4% 2.0% 2.6% 2006 1.5% 2.5% 2.2% 2.9% 2.8% 2007 3.4% 2.2% 2.3% 2.5% 3.3% 2008 2.2% 1.2% 1.1% 2.1% 3.9% 2009 4.9% 4.6% 2.2% 2.1% 6.2% 2010 4.4% 3.1% 1.9% 3.7% 6.0% 2011 4.4% 0.8% -0.6% 1.4% 4.6% 2012 1.6% -0.3% -2.4% 0.8% 3.7% 2013 0.8% -0.2% -3.1% 1.9% 4.2% 2014 0.6% -0.9% -3.0% 2.5% 2.5% 2015 4.5% 1.0% -1.1% 4.3% 4.6% 2016 4.6% 2.5% 0.6% 4.7% 7.1% 2017 6.9% 2.4% 0.3% 5.8% 8.6% 2018 6.7% 3.4% 0.7% 5.9% 9.7% 2019 11.5% 3.4% 1.6% 8.4% 12.3% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

While there has been a slow narrowing of gender wage gaps for those with less than high school, a high school diploma, and those with some college since 2000, gender wage gaps are wider among those with college or advanced degrees. As Figure O illustrates, women are paid consistently less than their male counterparts at every education level.

Figure O On average, men are paid more than women at every education level : Average hourly wages by gender and education, 2019 Men Women Less than high school $15.33 $12.20 High school $20.96 $16.15 Some college $23.58 $18.44 College $39.99 $29.55 Advanced degree $52.38 $38.64 Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata from the U.S. Census Bureau Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Educational attainment has grown faster for women than for men between 2000 and 2019, and now women are nearly 6 percentage points more likely than men to have a college or advanced degree (EPI 2020c). Unfortunately, increasing educational attainment has not insulated women from large gender wage gaps: The average wage for a man with a college degree was higher in 2019 than the average wage for a woman with an advanced degree (by 3.5%).

From 2000 to 2019, wage growth for white and black workers was faster for those with a college or advanced degree than for those with lower levels of educational attainment.

Table 5 presents the most recent data on average hourly wages by education for white non-Hispanic, black non-Hispanic, and Hispanic workers. From 2000 to 2019, average wages grew faster among white and Hispanic workers than among black workers for all education groups (which is not surprising given that the same was true at all deciles of the wage distribution). Black workers with some college had lower wages in 2019 than in 2000.

Table 5 Average hourly wages by race/ethnicity and education, selected years, 2000–2019 (2019$) Wage by education Less than high school High school Some college College Advanced degree White 2000 $13.04 $18.93 $21.36 $32.73 $40.69 2007 $13.42 $19.31 $21.58 $33.48 $42.03 2018 $14.02 $20.11 $21.98 $35.38 $45.26 2019 $13.88 $20.04 $22.26 $35.90 $45.29 Annualized percent changes 2000–2019 0.3% 0.3% 0.2% 0.5% 0.6% 2000–2007 0.4% 0.3% 0.1% 0.3% 0.5% 2007–2019 0.3% 0.3% 0.3% 0.6% 0.6% 2018–2019 -1.0% -0.3% 1.3% 1.5% 0.1% Black 2000 $12.32 $16.04 $18.34 $27.09 $35.61 2007 $12.44 $15.95 $18.49 $27.04 $35.00 2018 $11.63 $15.85 $17.46 $27.96 $36.89 2019 $12.40 $16.37 $17.86 $27.81 $37.33 Annualized percent changes 2000–2019 0.0% 0.1% -0.1% 0.1% 0.2% 2000–2007 0.1% -0.1% 0.1% 0.0% -0.2% 2007–2019 0.0% 0.2% -0.3% 0.2% 0.5% 2018–2019 6.6% 3.3% 2.3% -0.5% 1.2% Hispanic 2000 $12.71 $16.17 $18.85 $27.11 $36.19 2007 $13.37 $16.78 $19.16 $28.88 $39.10 2018 $14.36 $17.59 $19.00 $29.00 $39.17 2019 $14.60 $17.88 $19.23 $30.35 $40.80 Annualized percent changes 2000–2019 0.7% 0.5% 0.1% 0.6% 0.6% 2000–2007 0.7% 0.5% 0.2% 0.9% 1.1% 2007–2019 0.7% 0.5% 0.0% 0.4% 0.4% 2018–2019 1.6% 1.7% 1.2% 4.6% 4.2% Wage disparities Black as a share of white 2000 94.5% 84.7% 85.9% 82.8% 87.5% 2007 92.7% 82.6% 85.7% 80.8% 83.3% 2018 82.9% 78.8% 79.5% 79.0% 81.5% 2019 89.3% 81.7% 80.2% 77.5% 82.4% Hispanic as a share of white 2000 97.5% 85.4% 88.3% 82.8% 89.0% 2007 99.6% 86.9% 88.8% 86.2% 93.0% 2018 102.4% 87.5% 86.4% 82.0% 86.5% 2019 105.1% 89.2% 86.4% 84.5% 90.1% Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Over the last year, Hispanic workers were the only group that had positive wage growth across all levels of educational attainment. (Again, we must keep in mind that year-to-year changes are subject to volatility, particularly for smaller population cuts.) Between 2018 and 2019, Hispanic workers with the highest levels of educational attainment experienced the strongest wage growth. Black workers with less than high school experienced the strongest growth, while black workers with a college degree experienced wage losses. White workers with a college degree saw faster wage growth than any other education group, while those with a high school diploma or less than high school experienced losses.

Black–white wage gaps by education were larger in 2019 than in 2000 for all education groups, while Hispanic–white wage gaps were narrower for workers at any level of educational attainment except those with some college. At nearly every education level, black and Hispanic workers were paid less than their white counterparts in 2019, while Hispanic workers were consistently paid more than black workers (Figure P).

Figure P On average, white workers are paid more than black and Hispanic workers at nearly every education level : Average hourly wages, by race/ethnicity and education, 2019 White Hispanic Black Less than high school $13.88 $14.60 $12.40 High school $20.04 $17.88 $16.37 Some college $22.26 $19.23 $17.86 College $35.90 $30.35 $27.81 Advanced degree $45.29 $40.80 $37.33 Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Some convenient but misguided explanations of slow wage growth

Slow wage growth cannot be explained away by education shortages.

Some argue that wage inequality is a simple consequence of growing employer demand for—and a limited supply of—college-educated workers. This demand is often thought to be driven by advances in technology and corresponding technology-driven increases in required credentials. According to this explanation, because there is a shortage of college-educated workers, the wage gap between those with and without college degrees is widening as employers are forced to pay higher wages in the competition for college-degreed workers while those without college degrees are increasingly falling behind.

Despite its intuitive appeal, this story about recent wage trends being driven more and more by a higher demand for college-educated workers does not fit the facts well, especially since the mid-1990s (Schmitt, Shierholz, and Mishel 2013). The evidence suggests that the demand for college graduates has grown far less in the period since the mid-1990s than it did before then. This is difficult to square with contentions that automation or changes in the types of skills employers require have been more rapid in the 2000s than in earlier decades. Rather, automation has been slower in the recent period than in earlier decades, as seen in the pace of productivity, capital, information equipment, and software investment—and in the speed of changes in occupational employment patterns (Mishel and Bivens 2017).

Further, our research shows that the increase in the pay gap between high earners and most workers has been far larger than what can be explained by rising returns to education. The typical U.S. worker’s experience and education have increased significantly over the last 40 years, as seen in Figure Q, while median wage growth has been persistently slow and uneven over that time (recall Figure E). Figure Q plots the growing share of workers who have at least a college degree; it also plots the average age of workers in the middle fifth of the wage distribution from 1979 to 2019. Age is a proxy for experience, which, along with education, should imply higher productivity. While age is not a perfect proxy for experience, the increase in average age by about 5.5 years implies an increase in the experience—and the likely productivity—of the typical worker. And the near doubling of educational attainment should—given most interpretations of the relationship between education and productivity—lead to much faster wage growth than the typical worker has actually experienced.

Figure Q Middle-wage workers have more experience and education than they did four decades ago : Average age and share of workers with a college degree or more in the middle fifth of the wage distribution, 1979–2019 Year % with college or more Average age (years) 1979 16.10% 36.27 1980 16.91% 36.04 1981 16.19% 36.18 1982 17.92% 36.62 1983 18.21% 36.61 1984 18.02% 36.47 1985 17.39% 36.45 1986 17.83% 36.47 1987 17.78% 36.67 1988 17.32% 36.52 1989 17.18% 36.92 1990 17.91% 36.90 1991 17.82% 37.17 1992 17.29% 37.34 1993 18.01% 37.76 1994 17.96% 37.91 1995 19.10% 38.04 1996 18.91% 38.22 1997 19.68% 38.53 1998 20.19% 38.50 1999 19.54% 38.32 2000 19.82% 38.92 2001 20.15% 39.14 2002 21.56% 39.80 2003 21.71% 39.99 2004 21.70% 40.16 2005 21.70% 40.11 2006 23.45% 40.47 2007 23.86% 40.65 2008 24.73% 40.78 2009 25.76% 41.55 2010 26.52% 41.88 2011 26.53% 41.90 2012 26.72% 42.12 2013 28.61% 42.25 2014 29.81% 41.97 2015 30.00% 42.07 2016 29.31% 42.02 2017 31.02% 41.87 2018 31.32% 41.83 2019 32.04% 41.91 Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata from the U.S. Census Bureau Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Further, the growing inequality of note is that between the top (or very top) and everyone else. The pulling away of the very top cannot be explained by differences in educational attainment, but rather is attributable to the escalation of executive and financial-sector pay, among other factors (Mishel and Wolfe 2019).

This becomes more clear when we juxtapose the college wage premium with the 95/50 wage ratio. Figure R compares the change in the college wage premium over 1979–2000 and 2000–2019 with the change in the log 95/50 wage ratio. The college wage premium is the percent by which average hourly wages of four-year college graduates exceed those of otherwise equivalent high school graduates, controlling for gender, race and ethnicity, age, and geographic division. The 95/50 wage ratio is a representation of the level of inequality within the hourly wage distribution, comparing how much the 95th-percentile worker is paid relative to the 50th-percentile worker. Both are measured in log changes and shown as annual changes.

Figure R The college wage premium cannot explain growing wage inequality since 2000 : Average annual percentage-point changes in wage gaps, 1979–2000 and 2000–2019 Log 95/50 ratio College wage premium 1979–2000 0.76 1.00 2000–2019 1.00 0.13 Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: The college wage premium is the percent by which hourly wages of four-year college graduates exceed those of otherwise equivalent high school graduates. This regression-based gap is based on average wages and controls for gender, race and ethnicity, education, age, and geographic division; the log of the hourly wage is the dependent variable. The 95/50 wage ratio is a representation of the level of inequality within the hourly wage distribution. It is logged for comparability with the college wage premium. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

The regression-adjusted college wage premium grew rather quickly between 1979 and 2000 and then rose at a much slower rate in the 2000s, about an eighth as much. It had already slowed considerably by the mid-1990s (Bivens et al. 2014). In contrast, the 95/50 wage ratio grew somewhat faster in the more recent period. When we compare the relative size of the changes in each from 2000 to 2019, it is clear that the very modest gains in the college wage premium in recent years have not been large enough to plausibly drive the continued steady growth of the 95/50 wage ratio. In fact, the log 95/50 wage ratio grew more than seven times as fast as the college premium over this period.

There are plenty of good reasons to provide widespread access to college education, but expanding college enrollment and graduation is not an answer to escalating wage inequality.

Between 1979 and 2000, the log 95/50 wage ratio and the regression-adjusted college wage premium grew at roughly the same pace. The idea that increased employer demand for education is a prime driver of inequality appeared to be a more plausible story then. But it is clear that in the latter period, from 2000 to 2019, gains in the college wage premium have been very modest and far less than the continued steady growth of the 95/50 wage ratio. Therefore, it is highly implausible that the growth of unmet employer needs for college graduates has driven wage inequality over the last 19 years. Given this, the correspondence in the earlier period also shouldn’t be over-interpreted as differences in education levels driving the 95/50 wage ratio.

The more salient story between 2000 and 2019 is not one of a growing differential of wages between college and high school graduates, but one of growing wage inequality between the top (and the tippy top) and the vast majority of workers. Wage inequality is driven by changes within education groups (among workers with the same education) and not between education groups. From 2000 to 2019, the overall 95th-percentile wage grew nearly four times as fast as wages at the median (30.7% vs. 8.0%). Among college graduates only, there has also been a significant pulling away at the very top of the wage distribution, with many college-degreed workers being left behind.

Figure S displays the change in college wages from 2000 to 2019 for the average wage as well as at selected deciles of the college wage distribution. As shown previously in Figure L, average wages for college graduates grew 8.8% between 2000 and 2019. Here, it’s clear that this average masks important differences at different points on the college wage distribution. The highest percentile we show here is the 90th, because the 95th wage percentile for college graduates is fraught with top-coding issues to a greater degree than for white and male workers, making it even more difficult to obtain reliable measures of high-end wages and wage growth (as discussed in more detail in Gould 2019). Even so, the 90th-percentile wage grew nearly twice as fast as the average (15.1% vs. 8.8%) while the 50th-percentile (median) wage was actually lower in 2019 than in 2000 (-0.4%): Half of all college-degreed workers have not experienced any wage growth at all since 2000.

Figure S Wages of the bottom 50% of college graduates are lower today than they were in 2000 : Cumulative percent change in real hourly wages of workers with a college degree for the average, median, and 90th-percentile wages, 2000–2019 Year 50th 90th Average 2000 0.0% 0.0% 0.0% 2001 2.3% 3.6% 1.7% 2002 1.5% 2.4% 2.2% 2003 1.3% 3.3% 1.9% 2004 0.1% 2.8% 0.9% 2005 -1.4% 5.5% 1.3% 2006 -1.0% 4.5% 1.5% 2007 -0.3% 6.4% 2.2% 2008 -1.1% 5.9% 1.6% 2009 -0.6% 6.6% 2.4% 2010 -1.3% 5.3% 2.7% 2011 -3.1% 2.0% 0.0% 2012 -4.5% 3.9% 0.9% 2013 -2.9% 4.7% 1.6% 2014 -4.5% 3.9% 0.1% 2015 -3.1% 8.2% 4.2% 2016 -1.7% 14.5% 6.3% 2017 -3.2% 12.2% 6.1% 2018 -2.4% 9.8% 6.7% 2019 -0.4% 15.1% 8.8% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Note: Education groups are mutually exclusive, so “college” here refers to those with only a four-year college degree. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Between 2000 and 2019, the median high school wage grew slowly (1.7%), while the 95th-percentile high school wage grew much faster (7.5%) (EPI 2020a). The (raw) gap between median college wages and median high school wages is no wider in 2019 than in 2000. In fact, the gap actually narrowed over this period. Increases in inequality over the last 19 years clearly cannot be explained away by claims that employers face a growing shortage of college graduates and that, correspondingly, wage inequality is some unfortunate side effect of the positive gains from technological change that we neither can nor would want to alter. There are plenty of good reasons to provide widespread access to college education, but expanding college enrollment and graduation is not an answer to escalating wage inequality.

Slow wage growth cannot be explained away by including benefits or looking at total compensation.

Some have argued that to best measure pay, one should use total compensation and not simply wages. This argument is based on the theory that benefits—health benefits, in particular—have crowded out wage growth in recent years. But this argument is not borne out in the data.

Recall Figure A, which shows the divergence between productivity and pay over the last 40 years. The pay measure used in that figure includes benefits. Figure T separates out wages and measured compensation in that iconic figure, starting in 1979. The line labeled “hourly compensation,” which represents wages plus benefits, rose only slightly faster than wage growth on its own (14.9% vs. 14.0%) and therefore doesn’t do a whole lot to explain the gap between the potential for wage growth and actual wage growth. The other lines on the chart demonstrate that most of the divergence between productivity and pay over the last 40 years is due to growing inequality—both inequality in how wage income is distributed among workers and how a growing share of income accrues to (already richer) owners of capital rather than to workers.

Inequality in workers’ hourly pay can be measured by examining the divergence between average pay and median pay. This divergence has unambiguously risen and constitutes the single largest factor accounting for the overall gap between median hourly pay and economywide productivity growth. The loss in labor’s share of income represents the overall shift in how much of the income in the economy is received by workers in wages and benefits. As labor’s share falls, this means that a growing share of productivity gains are going to owners of capital. Both growing compensation inequality and changes in labor’s share of income represent growing income inequality over this period, and their combined influence explains the large majority of the overall gap between pay and productivity.

Figure T Growing inequality dominates the story of slow wage growth : Growth of productivity, real average compensation (consumer and producer), real median compensation, and real median hourly wage, 1979–2018 Year Real median hourly wage Real median hourly compensation Real consumer average hourly compensation Real producer average hourly compensation Net productivity 1979 0.0% 0.0% 0.0% 0.0% 0.0% 1980 -0.7% -0.4% -0.8% 1.3% -0.6% 1981 -1.7% -1.0% -0.5% 1.6% 1.1% 1982 -2.1% -1.0% 1.2% 3.1% 0.1% 1983 -1.9% -0.5% 1.5% 3.3% 3.1% 1984 -1.4% -0.1% 2.1% 4.2% 5.8% 1985 0.1% 1.6% 3.8% 5.9% 7.5% 1986 0.8% 2.4% 7.5% 9.4% 9.7% 1987 1.9% 3.0% 8.1% 10.9% 9.9% 1988 0.5% 1.7% 10.0% 12.8% 11.5% 1989 0.3% 1.8% 9.1% 12.2% 12.5% 1990 0.2% 1.7% 10.4% 14.4% 13.9% 1991 -0.7% 1.3% 11.6% 15.7% 14.6% 1992 0.4% 3.0% 15.4% 19.6% 18.9% 1993 1.9% 4.7% 14.8% 18.9% 19.4% 1994 0.8% 3.2% 14.0% 17.9% 20.4% 1995 -0.7% 0.8% 14.0% 18.4% 20.9% 1996 -2.2% -1.4% 14.8% 19.9% 23.1% 1997 -0.2% 0.0% 16.7% 22.0% 25.3% 1998 3.3% 3.3% 21.1% 26.7% 27.9% 1999 5.9% 5.8% 24.0% 30.4% 31.4% 2000 6.5% 6.4% 27.5% 35.5% 34.3% 2001 8.1% 8.6% 29.4% 38.1% 36.3% 2002 9.8% 11.1% 30.9% 39.4% 40.1% 2003 9.9% 11.8% 33.6% 42.4% 44.7% 2004 11.1% 13.2% 36.1% 45.0% 48.6% 2005 9.5% 11.7% 36.3% 45.9% 51.5% 2006 9.9% 11.5% 37.1% 47.1% 52.6% 2007 10.1% 11.3% 39.0% 49.2% 53.7% 2008 9.3% 10.6% 38.0% 50.8% 54.4% 2009 11.6% 13.6% 40.9% 51.6% 58.0% 2010 11.0% 13.0% 41.4% 52.5% 62.5% 2011 8.2% 10.1% 39.8% 52.2% 62.5% 2012 6.9% 8.3% 40.2% 52.7% 63.2% 2013 7.4% 9.3% 40.4% 52.4% 63.8% 2014 7.5% 9.0% 41.7% 53.7% 64.8% 2015 9.2% 10.5% 45.3% 56.2% 66.1% 2016 11.2% 12.2% 45.4% 56.4% 66.4% 2017 12.1% 13.1% 46.7% 58.2% 68.1% 2018 14.0% 14.9% 47.4% 59.0% 69.6% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Data are for all workers. Net productivity is the growth of output of goods and services minus depreciation, per hour worked. “Compensation” refers to total compensation, including wages and benefits. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org; unpublished Total Economy Productivity data from the Bureau of Labor Statistics (BLS) Labor Productivity and Costs program; and Bureau of Economic Analysis National Income and Product Accounts. For more detailed information, see the appendix of Bivens and Mishel, Understanding the Historic Divergence Between Productivity and a Typical Worker’s Pay (2015). Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Further, many forms of compensation are not found equally across the wage distribution. Therefore average benefits—like average wages—tend to overstate typical worker compensation or wage growth. This is certainly true with regard to employer-sponsored health insurance (ESI). Figure U shows the incidence of ESI since 1979. Not only has the incidence of ESI obtained through one’s own job fallen precipitously across the board, but the share of workers with ESI obtained through their own job is far less at the bottom of the wage distribution than at the top. In fact, workers in the top fifth are three times as likely to have ESI as workers in the bottom fifth. And only 59% of middle-wage workers have health insurance on the job. Health insurance costs certainly can’t be blamed for crowding out wage growth for the millions of workers who don’t have health insurance coverage at work.

Figure U High-wage workers are more likely to have employer-sponsored health insurance than low- and middle-wage workers, and all groups have experienced significant declines in coverage since 1979 : Employer-sponsored health insurance coverage rates, by wage fifth, 1979 and 2017 Date 1979 2017 Bottom fifth 37.90% 24.7% Second fifth 60.50% 45.8% Middle fifth 74.70% 59.0% Fourth fifth 83.50% 67.3% Top fifth 89.50% 74.2% Chart Data Download data The data below can be saved or copied directly into Excel. The data underlying the figure. Notes: Health insurance coverage data are for private-sector wage and salary workers ages 18–64 who worked at least 20 hours per week and 26 weeks per year. Coverage is defined as workers who received health insurance from their own job for which their employer paid at least some of the premium. Source: Author’s analysis of EPI Current Population Survey Extracts, Version 1.0 (2020), https://microdata.epi.org Share on Facebook Tweet this chart Embed Copy the code below to embed this chart on your website. Download image

Furthermore, research has shown that workers in firms with more low-wage workers have health insurance plans with cheaper premiums overall, but these workers actually contribute more dollars to their premiums because they are required to pay a higher share of the total cost of coverage when compared with workers in firms with fewer lower-wage workers (Claxton, Rae, et al. 2018). Not only are coverage rates lower in firms with more low-wage workers (33%) versus those in firms with fewer low-wage workers (64%), but, over the last several years, more and more workers are in plans with deductibles and those deductibles have increased (Claxton, Rae, et al. 2018). Because workers have seen slow wage growth—wage growth that is slower than health care cost growth—their ability to pay for premiums as well as out-of-pocket costs has been hampered (Claxton, Levitt, et al. 2018). And many health plan enrollees cannot rely on other resources to pay for increases in cost-sharing payments (Rae, Claxton, and Levitt 2017).

While health insurance costs are certainly squeezing workers, there is little evidence that changes in employer-sponsored health insurance premiums (or any other benefit cost) can explain more than a small portion of trends in workers’ wages.

Slow and unequal wage growth is not a statistical quirk that can be explained away by changing the price deflator.

In Figure E, we demonstrate that median wage growth was slow and uneven between 1979 and 2019. But on average over that time period median wages grew faster than zero percent per year, raising the question of just what benchmark we should use to define “slow” or “fast” wage growth. In Figure A, we show that wage growth for typical workers grew far slower than its potential—defined as economywide productivity growth—and, in Figures B and C, we show that much of that potential for wage growth went to the top or the very top of the wage distribution.

However, some analysts take issue with the argument that wage growth has been slow for most workers (see CEA 2018 for one example). In particular, they posit that wage growth is often measured using the wrong price deflator.

The price deflator is used to measure wages in constant dollars so that growth in wages can be assessed against growth in inflation or changes in the ability of wages to meet economic needs or standard of living. Two commonly used deflators are the CPI (Consumer Price Index) and the PCE (personal consumption expenditures) price index. Our findings of low-wage growth are based on using the CPI. The Census Bureau also uses the CPI for measuring real changes in incomes and earnings as it relates to changes in individuals’ and families’ standard of living. However, detractors argue that the CPI “overstates price increases and understates real wage growth” relative to the PCE price index (CEA 2018, 9).

We explore this question by comparing wage growth using the two deflators. Following the example shown in Bernstein 2018, we look first at the cumulative change in the real median hourly wage over the last 40 years (Figure V). The lighter blue line in Figure V plots wage growth based on the CPI, while the darker line calculates real wages using the PCE deflator. The 