Black—white wage gaps by education were larger in than in 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 , while Hispanic workers were consistently paid more than black workers Figure P. 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 mids Schmitt, Shierholz, and Mishel The evidence suggests that the demand for college graduates has grown far less in the period since the mids 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 s 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 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. 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 to 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. 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. 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 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.
Both are measured in log changes and shown as annual changes. 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.
It is logged for comparability with the college wage premium. The regression-adjusted college wage premium grew rather quickly between and and then rose at a much slower rate in the s, about an eighth as much. It had already slowed considerably by the mids Bivens et al. The idea that increased employer demand for education is a prime driver of inequality appeared to be a more plausible story then. Therefore, it is highly implausible that the growth of unmet employer needs for college graduates has driven wage inequality over the last 19 years.
The more salient story between and 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 to , the overall 95th-percentile wage grew nearly four times as fast as wages at the median 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 to 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.
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 Even so, the 90th-percentile wage grew nearly twice as fast as the average Between and , the median high school wage grew slowly 1.
The raw gap between median college wages and median high school wages is no wider in than in 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. 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 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.
This divergence has unambiguously risen and constitutes the single largest factor accounting for the overall gap between median hourly pay and economywide productivity growth.
Notes: Data are for all workers. Net productivity is the growth of output of goods and services minus depreciation, per hour worked. 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 In fact, workers in the top fifth are three times as likely to have ESI as workers in the bottom fifth.
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.
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.
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.
And many health plan enrollees cannot rely on other resources to pay for increases in cost-sharing payments Rae, Claxton, and Levitt In Figure E, we demonstrate that median wage growth was slow and uneven between and 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 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.
Our findings of low-wage growth are based on using the CPI. We explore this question by comparing wage growth using the two deflators. Following the example shown in Bernstein , we look first at the cumulative change in the real median hourly wage over the last 40 years Figure V.
The fits and starts of typical wage growth are evident in both lines. Wages grew faster in the late s as well as in the last five years — , with notable flatness again between those periods of faster growth. While it is true that, over the entire period, real wage growth is notably faster using the PCE, typical wage growth only accumulates to The annualized percent change since is in parentheses. Another way to look at the question of slow wage growth for typical workers is to compare growth at different points of the wage distribution, to find out whether changing the deflator tells a different story about inequality.
While growth for all groups is somewhat faster using the PCE, it does not at all change the fact that growth is much faster at the top than at the middle and the bottom of the wage distribution. Between and , growth at the 95th percentile using the PCE was almost three times as fast as growth at the median and over five times as fast as growth at the 10th percentile. The choice of deflator simply does not change the overall story of unequal and uneven wage growth over the last 40 years.
Wages are adjusted using the personal consumption expenditures PCE price index. Wage growth over the last 40 years has been slow, uneven, and unequal. These phenomena are the result of a series of policies that have reduced the leverage of most workers to achieve faster wage growth. Declining union membership has also played a major role in slow and unequal wage growth. To stem inequality and see healthy wage growth for the vast majority of workers, we need to use all the tools in our toolbox to reverse these policy trends.
Macroeconomic policy matters. Rising wages over the last few years have happened during a period of falling unemployment, with unemployment rates dropping to historical lows. This is no coincidence. Full employment is one way that workers gain enough bargaining power to increase their wages; employers have to pay more to attract and retain the workers they need when workers are scarce.
The lever for higher wages that comes from full employment is most important for workers at the bottom of the wage distribution, as well as for workers that have historically faced discrimination in the labor market. For a given fall in the unemployment rate, wage growth rises more for these workers, and in the absence of stronger labor standards, it is often only in the tightest of labor markets that these workers see stronger wage growth Bivens and Zipperer ; Wilson Labor policy matters.
Analysis of the relationship between 10th-percentile wage growth and state-level minimum wages suggests that policy matters. I also want to thank Maria Cancian for inviting me to present in an APPAM Super Session, forcing me to think harder about some of these issues, and Katherine Swartz, who attended the session and offered up useful insights on health insurance costs.
Last, I wish to thank my coworkers at EPI who have helped to get this paper across the finish line. Elise Gould joined the Economic Policy Institute in Her research areas include wages, poverty, inequality, economic mobility, and health care. She has testified before the U. Gould received her Ph. Black—white wage gap Overall Men Women 3. Hispanic—white wage gap Overall Women 8. While the share of the overall workforce living in states that rely on the federal minimum wage has been stable over time We decide on the appropriate percentile to use in the imputation of growth rates for the 95th percentile using data on the share of weekly earnings for the group that is top-coded as well as the share in neighboring wage bins that receive the top code.
Including Connecticut as a changer in this analysis—even though the increase did not occur until October —only serves to mute the effect. Notably, the 10th-percentile wage in Connecticut actually fell between and ; including Connecticut among the state-changers reduces the gap in the 10th-percentile change between those states with and without minimum wage changes in those two years; including Connecticut among the non-changers yields a growth in the 10th percentile in minimum-wage-changing states of 4.
It is important to note that there appears to be no relationship between changes in the median wage and changes in the minimum wage. Between and , the median wage in states with minimum wage changes increased 0. Median wage growth was faster in non-changing states for men 2. These differences are much smaller and they also operate in the opposite direction from the differences at the 10th percentile.
This belies any claims that strong wage growth at the 10th percentile is simply due to strong overall wage growth in those states and that 10th-percentile wages in those states would have risen with or without the minimum wage increases. See, for example, Gould Furthermore, occupational segregation plays a significant role in these gaps, for both black men Hamilton, Austin, and Darity and black women Banks Trends in black—white wage gaps found here are supported by other important research Wilson and Rodgers See Bivens and Mishel for a more thorough description of the decomposition of these factors.
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. This sample is chosen to focus on those with regular employment. Banks, Nina. Economic Policy Institute, February Bernstein, Jared.
Bernstein, Jared, and Dean Baker. Washington, D. Bivens, Josh. Economic Policy Institute, March Economic Policy Institute Briefing Paper no. Bivens, Josh, and Lawrence Mishel. Economic Policy Institute, September Bivens, Josh, and Ben Zipperer.
Economic Policy Institute, August Various years. National Income and Product Accounts. Accessed January Facebook Twitter Instagram. Voter Vitals. The Vitals. Globalization, insufficient economic dynamism, the declining rate of private sector union membership, and other factors have contributed to weak wage growth for many Americans.
Wage growth for typical workers has been weak for decades, but the tightening labor market along with state and local increases to minimum wages have recently boosted wages at the bottom. A closer look. Why are workers at the bottom doing relatively better lately?
What else could explain rising wages at the bottom? But why have wages for the typical worker risen so slowly over the past 40 years? The reasons for weak long-run wage growth include:. What government policies might raise wages? Increased wage transparency would put employers and workers on a more level playing field during wage negotiations. Reduced use of non-compete contracts would give workers more employment opportunities.
Strengthened collective bargaining would boost pay and reduce inequality. Improved antitrust enforcement could diminish labor market monopsony — that is, places and occupations where a small handful of employers dominate — and would limit employer power over workers in some labor markets. But two lessons from the-recent wage data are:. Recent minimum wage increases have likely improved wages at the bottom of the distribution.
A tight labor market coming from sustained economic growth is supporting that wage growth. February 27, November 14, Companies can increase wages for a number of reasons. The most common reason for raising wages is an increase to the minimum wage.
The federal and state governments have the power to increase the minimum wage. Consumer goods companies are also known for making incremental wage increases for their workers. These minimum wage increases are a leading factor for wage push inflation. In consumer goods companies especially, wage push inflation is highly prevalent, and its effect is a function of the percentage increase in wages.
Industry factors also play a part in driving wage increases. If a specific industry is growing rapidly, companies might raise wages to attract talent or provide higher compensation for their workers as an incentive to help business growth.
All such factors have a wage push inflation effect on the goods and services the company provides. Economists track wages closely because of their wage push inflation effects. Additionally, any wage increase that occurs will increase the money supply of consumers. With a higher money supply, consumers have more spending power, so the demand for goods increases.
An increase in demand for goods then increases the price of goods in the broader market. Companies charge more for their goods to pay higher wages, and the higher wages also increase the price of goods in the broader market. As the cost of goods and services rise at the companies paying higher wages and in the broader market overall, the wage increase is not as helpful to employees, since the cost of goods in the market has also risen. If prices remain increased, workers eventually require another wage increase to compensate for the cost of living increase.
The percentage increase of the wages and prices and their overall effect on the market are key factors driving inflation in the economy. But because the goods become more expensive, that raise isn't enough to propel a consumer's purchasing power , and the wage must be raised again, therefore causing an inflationary spiral.
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