Average wage growth continues to flatline in 2018, while low-wage workers and those with relatively lower levels of educational attainment see stronger gains

Real (inflation-adjusted) average hourly wages from the Current Employment Statistics (CES) survey did not grow at all between June 2017 and June 2018. This is not only troubling, but mildly surprising given the historically low unemployment rate of 4.0 percent. Some of this real wage stagnation can be explained by an uptick in energy prices, but even the underlying pace of nominal wage growth has yet to pick up in the way it historically has as labor markets tightened. It’s likely that the unemployment rate is overstating the strength of the economy given still soft labor force participation and the prime-age employment-to-population ratio. Even so, a steadily improving economy should eventually translate into stronger wage growth. And, if there were any thoughts that those tax cuts were going to lead to faster wage growth, which was doubtful in the first place, zero wage growth certainly isn’t a compelling case.

But the CES is only one measure of wage growth. Its large sample size and benchmarking make it one of the most reliable measures, but it only provides information on average wages for very large groups of workers (all workers or the 82 percent who are non-supervisory). The Current Population Survey-Outgoing Rotation Group (CPS-ORG) allows us to see what’s happening at different parts of the wage distribution and for workers with varying levels of educational attainment. Because of the volatility in the CPS-ORG, we’ve constructed annual averages for the year ending in June of each year, combining first half data in the stated year with second half data in the prior year. All wages are in first half 2018 dollars. Using this metric, real average hourly wages in the CPS-ORG grew 1.2 percent between 2017 and 2018. Table 1 below shows real wages by wage percentile for 2000, 2007, 2017, and 2018, with annualized changes between each set of years shown at the bottom of the table.

Table 1

Hourly wages by wage percentile, 2000–2018 (FH2018 dollars)

Wage by percentile
Year  10th  20th  30th  40th  50th  60th  70th  80th  90th  95th
2000 $9.09 $11.20 $13.11 $15.10 $17.89 $20.97 $24.80 $30.05 $39.23 $50.07
2007 $9.30 $11.36 $13.27 $15.61 $18.20 $21.54 $25.41 $31.12 $41.87 $53.82
2017 $9.85 $11.44 $13.47 $15.60 $18.63 $21.96 $26.45 $33.41 $46.19 $60.95
2018 $10.06 $11.90 $13.89 $15.95 $18.72 $22.00 $26.56 $33.62 $46.49 $62.26
Annualized percent change
2000–2007 0.3% 0.2% 0.2% 0.5% 0.2% 0.4% 0.3% 0.5% 0.9% 1.0%
2007–2018 0.7% 0.4% 0.4% 0.2% 0.3% 0.2% 0.4% 0.7% 1.0% 1.3%
2017–2018 2.2% 4.0% 3.1% 2.3% 0.5% 0.2% 0.4% 0.6% 0.7% 2.2%
2000–2018 0.6% 0.3% 0.3% 0.3% 0.3% 0.3% 0.4% 0.6% 0.9% 1.2%

Note: The xth-percentile wage is the wage at which x% of wage earners earn less and (100-x)% earn more.

Sample based on all workers ages 18–64. Each year represents annual data, calculated using the first-half data in the listed year combined with the second-half data for the prior year.

Source: EPI analysis of Current Population Survey microdata

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Real hourly wage growth over the last year is relatively polarized, with the strongest growth among the bottom 40 percent of workers along with those at the 95th percentile. More broad based growth, with particularly strength at the bottom of the wage distribution, is expected as we continue to move toward full employment. When the unemployment rate falls, even as more workers are drawn into the labor market, available workers of all types become scarcer and employers have to increase wages to attract and retain the workers they want. Lower unemployment has, in the past, benefited low-wage workers more than middle-wage workers and middle-wage more than higher-wage workers. In addition, in the last three to four decades of growing inequality, high-wage workers have had more leverage to bid up their wages faster than others. That trend has continued through the 2000s.Read more

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What to Watch on Jobs Day: Public sector jobs are threatened by austerity and attacks on collective bargaining

Last week, the U.S. Supreme Court ruled on Janus v. AFSCME Council 31. The Court’s 5-4 decision bars unions from requiring state and local government workers who benefit from union representation to pay their fair share of that representation. As a result, public sector unions will be up against a classic free rider problem, in which all the workers in a bargaining unit will be legally entitled to union representation, even if they don’t pay a penny for the benefits and services the union provides. This decision will have profound implications for all state and local government workers throughout the country, not just the share covered by a union contract.

To get a sense of the number of workers directly affected by this decision, let’s take a look at state and local government employment. According to the Current Employment Statistics survey, there are nearly 20 million state and local workers in the economy today. This represents about 13 percent of the overall workforce. The majority of these state and local workers are in the education sector. State and local education workers top 10 million, representing 53 percent of all state and local government workers.

At the same time as attacks on public sector collective bargaining erode compensation and job quality, austerity has held back employment and wage growth. State and local workers—such as the teachers in West Virginia and Oklahoma who were recently protesting not just their low wages but lack of funding in the classroom—have already been hammered by years of austerity policy at all levels of government. In states like Wisconsin, tax cuts for the most well off in the early 2010s were financed by the layoffs and cuts to public employees’ wage and benefits. As of the beginning of this school year, local public education employment was still lower than it was before the Great Recession, and much lower than where it could be if employment had kept up with the growth in school enrollment. This means, in this past school year, we experienced a shortfall of over 300,000 public educators.

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Social Security data confirm same old pattern: Self-employment headcount has risen but economic impact remains small

One indication of the growth of self-employment activity has been the rise in the number of people filing Schedule C income and self-employment earnings in their annual tax filings. This growth has been cited to illustrate the escalation of self-employment and to suggest that Bureau of Labor Statistics (BLS) measures of self-employment are missing an important phenomenon. Tracking headcounts of tax filings, however, does not adequately reflect trends in the economic impact of self-employment since, as this analysis shows, most of the growth is activity for supplementary incomes.

Our analysis of self-employment earnings data from the Social Security Administration (SSA) through 2015 (the latest data) confirms previous general findings regarding Uber drivers, independent work, all online demand platform work, nonemployer establishments, and independent contractors more generally. These previous findings are:

  1. The number of people involved in these types of work activity has increased;
  2. The increase is primarily among people who are doing so to earn supplementary income and for a short amount of hours. The increase in the various self-employment activities has not occurred in people’s “main job” or as their main source of income; and
  3. The economic scale of these activities has not changed much when measured as a share of economy-wide total hours worked, earnings, or compensation. While headcount measures of self-employment activity do show a large increase, the overall economic impact of this activity is relatively small in scale and growth.

The following table summarizes SSA data through 2015, the most recent year available, by “type of earnings”, meaning it distinguishes between those with regular W-2 earnings and those with self-employment earnings: the data show the number of individuals with each type of income and the amount of earnings from each type of earnings. Note that in any given year or at any particular point in time, workers can have income both from regular W-2 employment and from self-employment. One indication of this is that the sum of W-2 filers and the self-employed exceeds the total number of workers, indicating that about 40 percent of self-employed also filed a W-2.Read more

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Janus decision is not about union finances—it’s about working people’s finances

Today, the Supreme Court issued its final opinions from October Term 2017. This ends a particularly devastating term for working people—and for our democracy. One of the most troubling elements of the decisions impacting workers is the court’s repeated undermining of workers’ ability to act collectively in addressing workplace issues. This can be seen in the both Epic Systems Corp. and Janus. Corporate interests have long fought to erode the right of workers’ to join together. The Supreme Court certainly advanced this attack this term.

It is likely that the small group of foundations with ties to the largest and most powerful corporate lobbies that are behind the Janus case feel validated by today’s opinion that shamefully safeguards their interests by contorting the First Amendment. However, this victory will be short lived. Working people in this country know that the economy is not working for them. Today’s decision is likely to make that more true, but at the same time, it has already made workers’ right to a union and collective bargaining a topic covered by cable news and in newspapers throughout the country—a feat in and of itself. As was seen in the reaction to the teachers’ strikes in West Virginia, Oklahoma, and beyond, when issues of economic justice and workers’ rights are put front and center, the interests of the wealthy few rarely prevail.

Much will be said of Janus and its impact on unions—particularly union finances. But today’s decision is really about working people’s finances—our wages and our benefits. Unions provide a means for working people to come together and ensure that we are paid fairly and treated with dignity on the job. Unions are fundamental to a fair economy. Union membership cuts not just across political party affiliation, but also across race, gender, and ethnicity, ensuring that often marginalized voices are represented. Unions also provide an effective, organized voice for working people in our political process—helping to win minimum wage increases and civil rights protections for all working people. Today, millions of men and women in this country are union members, and millions more view unions favorably. Over half of all Americans say that the decline in union representation has been bad for working people in the United States. The Supreme Court today focused on fair share fees, but the focus going forward must be on a fair economy for working people and unions are clearly a critical part of that fight.

Workers of color are far more likely to be paid poverty-level wages than white workers

Marking the 50th anniversary of the 1968 Poor People’s Campaign, EPI has described the potential to reduce poverty through work, provided there are jobs with decent wages and adequate hours available to everyone who can and wants to work. Unfortunately, even when jobs are available, workers are often paid so little that they can still be left in poverty. Today, one in nine U.S. workers are paid wages that would leave them in poverty for their family size if they are the sole earner in their family—even with a full-time, year-round schedule.

Although the share of workers earning poverty wages has declined over the past three decades, there are still large racial and ethnic differences in the shares of workers being paid at adequate wage levels. As shown in the first figure below, workers of color are far more likely to be paid poverty-level wages than white workers. In 2017, 8.6 percent of white workers were paid poverty wages—i.e., hourly wages that would leave them below the federal poverty guideline for their family size if they are the sole earner in the family, even if they work full-time, year-round. In contrast, 19.2 percent—nearly one in five—Hispanic workers were paid poverty wages, and 14.3 percent—roughly one in seven—black workers were paid poverty wages. Asian or Pacific Islander workers also had higher poverty-wage rates than white workers, at 10.9 percent.

Workers of color are far more likely to be paid poverty-level wages than white workers: Share of workers earning poverty-level wages, by race/ethnicity, 1986–2017

Year  White Black Hispanic Asian/P.I.
1986 15.4% 23.5% 28.3% 
1987 14.6% 22.5% 27.7%
1988 14.4% 21.8% 26.9%
1989 13.5% 21.0% 26.6% 16.8%
1990 14.5% 22.7% 30.2% 18.3%
1991 14.4% 22.7% 30.7% 18.7%
1992 14.6% 22.4% 30.9% 19.2%
1993 14.4% 22.1% 31.2% 18.6%
1994 14.8% 22.3% 33.1% 19.3%
1995 14.8% 21.8% 34.2%  20.0%
1996 13.9% 22.0% 32.2% 19.9%
1997 13.9% 21.8%  33.5% 20.4%
1998 12.6% 18.7% 30.8% 18.3%
1999 12.0% 18.2% 29.6% 17.1%
2000 10.8% 16.2% 28.1% 15.4%
2001 10.4% 16.0% 27.1% 13.4%
2002 10.3% 15.3% 26.5% 14.2%
2003 10.0% 14.6% 24.7% 12.8%
2004 10.7% 15.0% 26.0% 14.1%
2005 10.2% 15.5% 25.6% 13.7%
2006 9.8%  14.1%  24.3% 12.2% 
2007 9.9% 14.7% 23.9% 12.5%
2008 10.1% 15.1% 23.0% 13.0%
2009 11.1% 15.2% 25.6% 12.5%
2010 10.5% 14.7% 26.0% 13.1%
2011 10.6% 14.9% 25.3% 13.1%
2012 11.2% 16.6% 26.6% 14.4%
2013 11.0% 16.4% 26.1% 14.0%
2014 11.1% 17.8% 24.6% 13.1%
2015 10.7% 16.8% 24.9% 14.0%
2016 9.6% 15.4% 21.0% 11.8%
2017 8.6% 14.3% 19.2% 10.9%
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The data below can be saved or copied directly into Excel.

Notes: A “poverty-level wage” is a wage that would leave a full-time, year-round worker below the federal poverty guideline for their family size if they are the sole earner in the family. Poverty wage thresholds are specific to each family size, and family sizes are calculated using the total number of people in each family or subfamily within the CPS data. The "Asian or Pacific Islander" race category is only available beginning in 1989.

Source: EPI analysis of Current Population Survey Outgoing Rotation Group microdata

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Among workers of all races and ethnicities, the shares being paid poverty wages have declined from highs reached in either the mid-1980s or the mid-1990s. However, the share of black workers earning poverty wages in 2017 (14.3 percent) was still slightly above where it was in 2006 (14.1 percent.) Black workers are the only group for whom the share receiving poverty wages is not at its lowest level on record.

Notably, racial gaps have been remarkably consistent—if not gotten worse—over time. The share of black workers earning poverty-level wages has consistently been 1.5 times that of white workers for the entirety of the series. The ratio of the Hispanic poverty-wage rate to the white poverty-wage rate has actually grown since the 1980s. In 1986, the share of Hispanic workers earning poverty-level wages was 1.8 times that of white workers; in 2017, it was 2.2 times the share of white workers.Read more

Nonemployer establishments grew in 2016 but their real revenues were stable: This confirms other data on self-employment showing more activity, but little economic impact

Last week’s release of the new Bureau of Labor Statistics (BLS) Contingent Worker Survey (CWS) has renewed public interest in tracking the number of self-employed or independent contractors. Today’s release of the U.S. Census nonemployer establishment data for 2016 provides another useful data point about the trends in self-employment.

Our analysis of these new nonemployer establishment data affirm the pattern seen through 2015. As we wrote yesterday: these data confirm previous general findings regarding Uber drivers, all online demand platform work, and independent contractors more generally. These previous findings are:

  1. There is an increase in the amount of people involved in self-employment or online platform types of work activity;
  2. The increase is primarily among people who are doing so to earn supplementary income and for a short amount of hours. The increase in the various self-employment activities has not occurred in people’s “main job” or as their main source of income; and
  3. The economic scale of these activities has not increased greatly when measured as a share of hours worked or compensation earned. While “headcount” measures do show a large increase, the overall economic impact is relatively small.

As we show, there has been a significant increase in the headcount of nonemployer establishments. However, the economic impact, as measured by the share of nonemployer establishment revenues in total revenues, has not increased in roughly 20 years. Nonemployer establishments grew by 2.0 percent from 2015 to 2016 but their real revenues grew by just 0.2 percent, evidence of a very small economic impact. In fact, over the medium term there has been a slight decline in the nonemployer establishment share of all revenue between 2007 and 2016, from 3.3 to 3.1 percent of all revenue. This indicates that the growth of nonemployer establishments seems to reflect the growth of self-employed individuals operating unincorporated businesses that generate very little revenue, including the period since 2011 when Uber, Lyft, and other online platform work expanded rapidly.Read more

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Has self-employment surged? Data on nonemployer establishments confirm other data showing more activity, but not much economic impact

Update: Read the analysis of 2016 nonemployer establishment data.

Last week’s release of the new Bureau of Labor Statistics (BLS) Contingent Worker Survey (CWS) has renewed public interest in tracking the number of self-employed or independent contractors. The upcoming release of the U.S. Census nonemployer establishment data for 2016 this Thursday will provide another useful data point about the trends in self-employment.

Our analysis of nonemployer establishment data through 2015 indicates that these data confirm previous general findings regarding Uber drivers, all online demand platform work, and independent contractors more generally. These previous findings are:

  1. There is an increase in the amount of people involved in these types of work activity;
  2. The increase is primarily among people who are doing so to earn supplementary income and for a short amount of hours. The increase in the various self-employment activities has not occurred in people’s “main job” or as their main source of income; and
  3. The economic scale of these activities has not increased greatly when measured as a share of hours worked or compensation earned. While “headcount” measures do show a large increase, the overall economic impact is relatively small.

As we will show, there has been a significant increase in the headcount of nonemployer establishments. However, the economic impact, as measured by the share of nonemployer establishment revenues in total revenues, has not increased in roughly 20 years. This indicates that the growth of nonemployer establishments seems to reflect the growth of self-employed individuals operating unincorporated businesses that generate very little revenue.

Background on CWS and nonemployer data

The CWS is based on a household survey and showed that in 2017, the share of independent contractors in total employment was 6.9 percent, comparable to what was reported in all of the other CWS surveys back to 1995. This has elicited surprise by many observers, especially those that have touted the explosion of gig work or freelancing.

The release of new Census data on nonemployer establishments for 2016 this month provides another opportunity to track these trends. These Census data capture the phenomenon of self-employment by examining business establishment/firm data rather than asking individual workers or households about employment. Census describes the data as:

“data for businesses that have no paid employees and are subject to federal income tax. Most nonemployers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner’s principal source of income.”

Various analysts have used these data to track the rise of self-employment with many arguing that the rapid rise of nonemployer establishments reflect a surge of self-employment and gig work. Abraham et al. (2017) note that the growth of nonemployer establishments was faster than self-employment in the Current Population Survey (CPS). They cite this evidence (along with tax records) as being consistent with the argument that the CPS is missing some of the growth of in self-employment, pointing out that nonemployer establishments “have trended upwards as a percent of the number of earners.” Steve King of Emergent Research, a leading analyst of gig and “independent worker” trends, has also said that nonemployer data are “a useful general indicator of U.S. self-employment.”

All of the analyses we have seen of these data solely focus on headcount measures, tracking the number of nonemployer establishments, and do not examine the economic impact, as we do in our analysis by examining the revenues of nonemployer establishments.

This may be surprising since the Census used to (but now does not) warn data users of the following:

“The majority of all business establishments in the United States are nonemployers, yet these firms average less than 4 percent of all sales and receipts nationally. Due to their small economic impact, these firms are excluded from most other Census Bureau business statistics.”Read more

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How big is AI-related employment? Not that big at all—despite what Stanford’s AI Index Annual Report tries to claim

There is much discussion about the potential for artificial intelligence (AI) to transform our workplaces, possibly leading to fewer overall jobs and greater economic inequality in the future. This discussion has always made me wonder to what extent AI is already being used to produce goods and services. So, I was excited to learn about the AI Index from reading the recent Furman and Seamans paper on “AI and the Economy.” Furman and Seamans write: “The AI index, a non-profit project designed to track activity and progress in AI, provides a number of interesting facts designed to track the scientific progress in and impact of artificial intelligence and robotics.” I was even more excited to see the AI index reporting on “the growth of the share of US jobs requiring AI skills.” However, my excitement soon ended when I realized that the information they offered completely obscured the (lack of) importance of the underlying data, and I have to reluctantly conclude that the AI index offers extremely misleading hype on AI jobs rather than useful information. I am getting tired of overhyped phenomena, so this blog post is to alert the public.

The AI Index highlights the fact that “the share of jobs requiring AI skills in the US has grown 4.5x since 2013” (see the graph below). That sounds like a huge explosion of jobs related to AI, right? But exactly how many jobs are they talking about being AI-related now compared with in the past? One cannot tell from their information, because while it shows the growth in the share of AI jobs, it provides no information of the level of these shares (either now or in the past). I am always careful to not present data showing the percent changes of percentages, because this is often misleading. For example, when a share rises from 1 percentage point to 2 percentage points, it has risen 100 percent. If a share rises from 20 percentage points to 22 percentage points, it has only risen by 10 percent. Yet in the latter example the change in the level of the share is twice as large (2 percentage points, compared to 1). So what does it tell us about the share of AI jobs in the economy today to tell us that this share has grown 350 percent, without telling us the initial level of the share? Absolutely nothing.

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CEO pay: Still not related to performance

This post originally appeared on the CEPR blog.

Earlier this year we did an analysis of CEO compensation in the health insurance industry to see if it was affected by the cap on deductibility imposed by the Affordable Care Act (ACA). One of the provisions of the ACA limited the amount of CEO pay that health insurers could deduct on their taxes to $500,000, beginning in 2013.

This provision effectively raised the cost of CEO pay to insurers by more than 50 percent. Prior to 2013, the deduction in effect meant that the government was picking up 35 cents of every dollar of CEO pay, while the companies were paying just 65 cents. 1 With the new provision in place, insurers are now paying 100 cents of every dollar of CEO pay in excess of $500,000.

If the pay reflects the value of the CEO to the company, we should expect this change to reduce the pay of CEOs in the insurance industry. For example, if a CEO gets paid $20 million a year, this should mean that she delivers roughly $20 million in additional value to shareholders.

When the CEO’s pay was fully deductible, the $20 million paid to the CEO actually only cost the company $13 million. This would presumably be the number that matters to shareholders since they care about how much money comes out of their pockets, not the number on the CEO’s paycheck.

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Why is wealthy Westport trying to gut police pensions?

Police in Westport, Connecticut are resisting an attempt to slash their pension and partially replace it with a 401(k)-style plan. Such a move would mess with a tried-and-true system that promotes secure and orderly retirement, in favor of an inefficient one that harms workers with no benefit to taxpayers.

Westport is a latecomer to a trend that appears to have nearly run its course. A few years ago, the Wall Street Journal praised San Jose Mayor Chuck Reed for taking an axe to police and other public employee pensions. Along with Rhode Island Treasurer (later Governor) Gina Raimondo, Reed had become a public face of the pension gutting movement, leading a statewide initiative backed by hedge fund billionaires. Reed and Raimondo, both Democrats, were lauded by conservative think tanks and the Journal for taking on public-sector unions, ignoring the fact that they were courting more powerful interests—the financial industry and wealthy donors.

Similar initiatives followed in Dallas, Memphis, and Palm Beach, among other places. But as the Journal reported last year, in an apparent change of heart, cities that slashed police pensions were later forced to restore benefits or spend millions on retention bonuses in efforts to stem outflows of experienced officers. In Palm Beach, for example, 24 mid-career police officers left in the four-year period after the city cut police and firefighter pensions and partly replaced them with 401(k)-style plans, compared with just one mid-career officer in the previous four years. The exodus of police and firefighters to neighboring jurisdictions caused the city to incur millions in additional training and overtime costs. Five years later, the city reversed course, restoring pension benefits and dropping the 401(k)-style plans.

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