An Updated Analysis of Who Would Benefit from an Increased Overtime Salary Threshold
If salaried employees are paid less than the overtime salary threshold (currently $23,660 in annual salary), they are entitled to overtime pay when they work more than 40 hours in a week. If however, they make more than the salary threshold, they are entitled to overtime pay only if their primary duty is not executive, administrative, or professional.
In a 2014 analysis, former EPI economist Heidi Shierholz estimated the share of salaried workers who were covered by the overtime salary threshold in 1975 and in 2013. She found that, despite an increase in the threshold in 2004, the share of the workforce covered by the threshold declined from 65 percent in 1975 to just 11 percent in 2013. This is because most of the value of the threshold was eliminated between 1975 and today due to inflation. As a result of Shierholz’s findings, EPI recommended that the overtime salary threshold be increased to the 1975 threshold in today’s dollars (in 2013, this was $51,168), which would have covered 47 percent of the workforce.
Because the analysis focused solely on the salary threshold test–i.e., because the analysis focused on just the salary of workers without regard for the duties of their occupation[1]–increasing the threshold to reflect an amount into today’s dollars wouldn’t mean that all of the workers who fell in between $23,660 and $51,168 would gain overtime protections. Many of these workers would already have been entitled to this protection because their primary job duty was not executive, administrative, or professional.
Now, in updating this analysis, we want to be as precise as possible in identifying the workers who will be affected by the updated salary threshold rule. To do this, we narrowed the sample to those workers who are full-time workers (usually work 35 hours or more at their primary job), expanded the age of the population to all workers 18 years or older (previously limited to those 18-64), and removed certain occupations that are automatically exempt from overtime protections (e.g., medical professionals, lawyers, judges, teachers of all levels, and religious workers).
Refugees Deserve Support in America, Not Just a Home
On World Refugee Day, The Hill published a Contributors piece by the libertarian Cato Institute’s immigration policy analyst, Alex Nowrasteh, headlined, “The US should be a home for refugees.” In it, he offers a brief history of refugee policy and flows into the United States over the past century and suggests that the United States “should … allow more to settle here.” That’s a noble sentiment, but the headline is misleading because it leaves out the substance of what Nowrasteh proposes in order to help make this happen. In short, Nowrasteh wants to welcome more refugees to the United States but proposes abandoning them and letting them fend for themselves once they get here…
Time to End the Vicious Cycle of Inequality Begetting Unequal Education
A new EPI study of the academic preparation of kindergartners by social class and race ended up being less about absolute preparation of children at the beginning of school and more about how prepared they are relative to one another. In short, children do not start school as equals. According to Inequalities at the Starting Gate: Cognitive and Noncognitive Skills Gaps between 2010–2011 Kindergarten Classmates, children’s school preparation is highly unequal, and what determines being better or worse off is a student’s social class.
While inequalities in the cognitive abilities of our young people have been documented by previous research (see EPI’s Inequality at the Starting Gate study from 2002 and Robert Putnam’s new book, Our Kids: The American Dream in Crisis), our study uses a dataset that allowed for examining how prepared children are in both cognitive (reading and math) and noncognitive domains (social skills, persistence, and creativity, among others). The data set (the National Center for Education’s Early Childhood Longitudinal Study of the Kindergarten Class of 2010-2011) also offers information on individual and family demographic characteristics and various enrichment activities that parents undertake with their children, enabling assessment of the importance of these variables for children’s preparation. All in all, the data allowed us to understand the broad school readiness of a recent generation of students. These students were born after—and thus presumably benefited from—the spread of prekindergarten education and other advances in school preparedness research and policymaking. But these children were also raised in a context of economic stagnation.
Consistently, results showed that having less money puts children at a relative disadvantage, in terms of the cognitive and noncognitive skills developed by the age of 5, while having more money benefits them, as skill levels increase along with social class. Most gaps are striking in size and appear for all the examined cognitive, noncognitive, and executive function skills. For example, children in the highest socioeconomic group have reading and math scores that are a full standard deviation larger than the scores of their peers in the lowest socioeconomic group. To give a sense of how large this gap is, it would take up to four independent, “substantively important,” education interventions to close the gap, according to a “classification of effects” from the U.S. Department of Education’s What Works Clearinghouse. The social-class-based gaps in other skills such as working memory, persistence in completing tasks, and self-control are 0.7, 0.4, and 0.5 standard deviations, respectively.
Hall of Shame: 13 Democrats Who Voted to End Debate on Fast-Track Trade Legislation
Fast-track trade legislation is the first step in the process of greasing the skids for the proposed Trans-Pacific Partnership (TPP), and any other trade deal proposed by this president or any other for the next six years. Last month, the 13 democrats listed in the table below voted to end debate on fast track (Trade Promotion Authority, or TPA), allowing a final vote to take place. There are strong arguments against the TPP, which will increase inequality and hurt the middle class.
* The low-impact scenario assumes ending currency manipulation would reduce the trade deficit by $200 billion; the high-impact scenario assumes a $500 billion reduction in the trade deficit. The table shows the hypothetical change in 2015 three years after implementation. Source: Author's analysis of Scott 2014a and Scott 2014bTrade and jobs gained and lost in selected states
Net U.S. jobs displaced due to goods trade with China, 2001–2013
Net U.S. jobs created by eliminating currency manipulation
Low-impact scenario*
High-impact scenario*
Senator
State
State employment (in 2011)
Jobs lost
Jobs lost as a share of employment
Jobs gained
Jobs gained as a share of employment
Jobs gained
Jobs gained as a share of employment
Feinstein, Dianne
California
16,426,700
564,200
3.4%
258,400
1.6%
687,100
4.2%
Bennet, Michael
Colorado
2,492,400
59,400
2.4%
38,300
1.5%
95,700
3.8%
Carper, Tom
Delaware
420,400
5,500
1.3%
6,700
1.6%
16,200
3.9%
Coons, Chris
Nelson, Bill
Florida
8,101,900
115,700
1.4%
110,200
1.4%
274,000
3.4%
McCaskill, Claire
Missouri
2,742,100
44,200
1.6%
47,200
1.7%
116,800
4.3%
Shaheen, Jeanne
New Hampshire
684,800
22,700
3.3%
12,700
1.9%
31,300
4.6%
Heitkamp, Heidi
North Dakota
370,800
2,400
0.6%
7,400
2.0%
17,000
4.6%
Wyden, Ron
Oregon
1,710,300
62,700
3.7%
31,300
1.8%
78,600
4.6%
Kaine, Tim
Virginia
3,860,100
63,500
1.6%
52,500
1.4%
131,300
3.4%
Warner, Mark
Cantwell, Maria
Washington
3,118,000
55,900
1.8%
61,300
2.0%
140,300
4.5%
Murray, Pat
Total jobs at risk in these states**
39,927,500
996,200
2.5%
626,000
1.6%
1,588,300
4.0%
These 13 democrats come from 10 states that lost 996,200 jobs due to growing trade deficits with China between 2001 and 2013, nearly one-third of the 3.2 million jobs eliminated by China trade in the United States in that period. States like Oregon, California, and Colorado were among the hardest hit states in the country. But they are also home or host to Nike (Oregon), Lockheed-Martin (Colorado), and Apple, Google, Intel and other Goliaths of Silicon Valley (California). New Hampshire serve as a bedroom community for many electronics industry workers in nearby Massachusetts, and has lost hundreds of thousands of jobs in recent decades in textiles, shoemaking and small machine making.Read more
Top CEO Compensation Soars, and Why We Do Not Look at “Average CEOs”
Our new study shows the average compensation of CEOs in the largest firms was $16.3 million in 2014, up 3.9 percent since 2013 and 54.3 percent since the recovery began in 2009. More impressively, from 1978 to 2014, inflation-adjusted CEO compensation increased 997 percent, a rise almost double stock market growth and substantially greater than the painfully slow 10.9 percent growth in a typical worker’s annual compensation over the same period. Consequently, the CEO-to-worker compensation ratio was 303-to-1 in 2014, lower than the 376-to-1 ratio in 2000 but far higher than the 20-to-1 in 1965 and any time in the 1960s, 1970s, 1980s, or 1990s, as the Figure shows.
CEO-to-worker compensation ratio, 1965–2014
| Year | CEO-to-worker compensation ratio |
|---|---|
| 1965/01/01 | 20.0 |
| 1966/01/01 | 21.2 |
| 1967/01/01 | 22.4 |
| 1968/01/01 | 23.7 |
| 1969/01/01 | 23.4 |
| 1970/01/01 | 23.2 |
| 1971/01/01 | 22.9 |
| 1972/01/01 | 22.6 |
| 1973/01/01 | 22.3 |
| 1974/01/01 | 23.7 |
| 1975/01/01 | 25.1 |
| 1976/01/01 | 26.6 |
| 1977/01/01 | 28.2 |
| 1978/01/01 | 29.9 |
| 1979/01/01 | 31.8 |
| 1980/01/01 | 33.8 |
| 1981/01/01 | 35.9 |
| 1982/01/01 | 38.2 |
| 1983/01/01 | 40.6 |
| 1984/01/01 | 43.2 |
| 1985/01/01 | 45.9 |
| 1986/01/01 | 48.9 |
| 1987/01/01 | 51.9 |
| 1988/01/01 | 55.2 |
| 1989/01/01 | 58.7 |
| 1990/01/01 | 71.2 |
| 1991/01/01 | 86.2 |
| 1992/01/01 | 104.4 |
| 1993/01/01 | 111.8 |
| 1994/01/01 | 87.3 |
| 1995/01/01 | 122.6 |
| 1996/01/01 | 153.8 |
| 1997/01/01 | 233.0 |
| 1998/01/01 | 321.8 |
| 1999/01/01 | 286.7 |
| 2000/01/01 | 376.1 |
| 2001/01/01 | 214.2 |
| 2002/01/01 | 188.5 |
| 2003/01/01 | 227.5 |
| 2004/01/01 | 256.6 |
| 2005/01/01 | 308.0 |
| 2006/01/01 | 341.4 |
| 2007/01/01 | 345.3 |
| 2008/01/01 | 239.3 |
| 2009/01/01 | 195.8 |
| 2010/01/01 | 229.7 |
| 2011/01/01 | 235.5 |
| 2012/01/01 | 285.3 |
| 2013/01/01 | 303.1 |
| 2014/01/01 | 303.4 |
Note: CEO annual compensation is computed using the "options realized" compensation series, which includes salary, bonus, restricted stock grants, options exercised, and long-term incentive payouts for CEOs at the top 350 U.S. firms ranked by sales.
Source: Authors' analysis of data from Compustat's ExecuComp database, Current Employment Statistics program, and the Bureau of Economic Analysis NIPA tables
Our measure of CEO pay covers chief executives of the top 350 U.S. firms and includes the value of stock options exercised in a given year plus salary, bonuses, restricted stock grants, and long-term incentive payouts. (Full methodological details here)
Our analysis, which shows that CEO pay grew far faster than pay of the top 0.1 percent of wage earners (those earning more than 99.9 percent of wage earners), indicates that CEO compensation growth does not simply reflect the increased value of highly paid professionals in a competitive race for skills (the so-called “market for talent”). CEO compensation in 2013 (the latest year for data on top wage earners) was 5.84 times greater than wages of the top 0.1 percent of wage earners, a ratio 2.66 points higher than the 3.18 ratio that prevailed over the 1947–1979 period. The compensation gains of top CEOs were therefore equivalent to the wages of 2.66 very-high-wage earners.
Don’t worry about all this, says American Enterprise Institute scholar Mark Perry, because our sample, and those used by the Associated Press and the Wall Street Journal, is misleading. Looking at the compensation of CEOs in the largest firms, according to Perry, is not “very representative of the average U.S. company or the average U.S. CEO,” because “the samples of 300–350 firms for CEO pay represent only one of about every 21,500 private firms in the U.S., or about 1/200 of 1 percent of the total number of U.S. firms.” Perry notes, “According to both the BLS and the Census Bureau, there are more than 7 million private firms in the U.S.”
Former Labor Secretaries and EPI Board Members F. Ray Marshall and Robert Reich oppose TPA and TPP
In a jointly authored statement, former EPI board members and U.S. Labor Secretaries F. Ray Marshall and Robert Reich called on Congress to reject Trade Promotion Authority and the Trans-Pacific Partnership because that deal will “harm America’s working people.” Despite this statement, the House today approved a truncated version of Fast Track (TPA) that excludes funding for Trade Adjustment Assistance for displaced workers. But passing TPA without TAA is a risky gamble because many Democrats have demanded that the two move simultaneously.
In their letter to Congress, Marshall and Reich conclude that “Trade can work for working Americans, but only when Americans can effectively know about what is in a trade deal, and only when a trade deal is effectively designed to create more good jobs in America. This Fast Track mechanism toward the Trans Pacific Partnership is a bad deal for America.”
Disney Reverses 35 Layoffs, but No Fairytale Ending for Thousands of Others Displaced by H-1B Visa Program
We learned of some welcome news when Computerworld and the New York Times reported that Disney had reversed a decision to replace 35 American information technology (IT) workers with cheaper H-1B guestworkers at its ABC broadcasting offices in New York City and Burbank, CA. The news comes after a significant spotlight was shined on Disney’s recent replacement of 250 technology workers with H-1B guestworkers at Disney’s Theme Parks division. This is good news for the 35 workers who will keep their jobs for now, and at least in the short term, will not have to train their foreign guestworker replacements. However, this decision by Disney executives does nothing for the 250 workers who have already lost their jobs to workers they were forced to train and who will earn roughly $40,000 less for doing the same job. Nor does it help the approximately 225 Northeast Utilities workers, or the 400 at Southern California Edison (SCE), or the 600 at Xerox, or 900 at Cargill, or 100 at Fossil Group, or tens of thousands of workers who likely suffered a similar fate at hundreds of other places that have never been reported.
It appears that the media attention has shamed Disney into reversing its decision to force more of its American workers out in favor of cheaper guestworkers. Clearly, Disney’s own sense of social responsibility wasn’t enough to convince its executives to do the right thing in the first place. While the reversal of Disney’s layoffs is good news, it hardly makes us sanguine about the future of the H-1B visa program. The payoff for replacing American workers with indentured and underpaid H-1B guestworkers is simply too high: as much as a 49 percent wage savings in some cases. Relying solely on the media to shame firms is insufficient. Simply put, the government must immediately make changes to the program.
We would also like to emphasize two important points about the H-1B that have not been highlighted enough in the recent media coverage. First, the temporary foreign workers employed by the firms hired to replace American workers are blameless in all of these situations, as one American IT worker who was recently replaced by an H-1B at SCE attested to in a recent interview. The blame should be placed squarely on the corporate profiteering that leaves Americans out of a job and foreign workers vastly underpaid for the work they are hired to do. The H-1B workers are simply seeking to advance their careers and to make better lives for themselves in the United States, and are often placed in working situations where they are vulnerable and can be easily exploited.
The True Cost of Low Prices is Exploited Workers
This piece was originally published in the New York Times “Room for Debate” section on May 12, 2015.
The true costs of goods and services is a secondary issue to stagnant and exploitative wages: The cost of certain goods might go up, but more people would be able to afford them with better compensation. The current price of low-cost goods and services in the United States is low-income, exploited workers living in poverty. But the country as a whole isn’t broke, only its workers are — while corporations and C.E.O.s are richer than ever.
The value of the federal minimum wage has declined 24 percent since 1968. If we re-established the relationship between the minimum wage and the overall median wage to its 1968 level, we would raise wages for 35 million people, a full quarter of the workforce.
The situation is even worse for those earning tips, such as nail salon workers. Their pay is set at $2.13 an hour by the federal government. If tips don’t supplement these workers’ paycheck to the regular minimum, they have to ask their employers for the difference. (And good luck with that.)
But low and stagnant wages are not the result of benign, abstract economic forces. They reflect conscious policy choices by lawmakers influenced by powerful corporate lobby groups like the Chamber of Commerce and the National Restaurant Association.
Hatch Should Fix H-1B Visa Program Instead of Expand It
Corporate lobbyists have convinced legislators of both parties that America needs more guest workers in high-tech jobs. Leading the charge in Congress to do their bidding is Utah Sen. Orrin Hatch, who has introduced legislation to double or triple the number of non-immigrant tech workers who can be hired annually on H-1B visas. But his proposal won’t fix the H-1B program’s flaws, which allow American and foreign workers alike to be exploited and underpaid.
Continue reading the rest of this op-ed at the Salt Lake Tribune.
National Retail Federation Report Suggests Huge Positive Impact for Labor Department Overtime Rules
The National Retail Federation (NRF), a lobbying organization for department store corporations, sporting goods and grocery chains, and other large retailers, is opposed to the Department of Labor’s update of the rules governing the right of salaried workers to overtime pay. The reasons the NRF gives are somewhat contradictory and are sometimes surprising. But they boil down to this: the retail lobby doesn’t think businesses should have to pay for the overtime hours most of their employees work.
In March 2014, President Obama directed the Secretary of Labor to update the rules intended to exclude high-level employees like executives and professionals from overtime protections. The rules are currently so out of date that they define even workers earning below-poverty salaries as exempt, even though the pay of true executives and professionals like lawyers and CPAs has been soaring for decades. To fix this problem, the Labor Department is reportedly considering raising the threshold for exemption from $23,660 a year to $42,000 or more. Some advocates are calling for a threshold as high as $70,000 a year, which would protect the same share of the salaried workforce as was covered in 1975.
If the threshold is raised to $42,000, the NRF predicts significant changes in retail employment: while some employers will raise salaries for employees near the threshold to guarantee that they continue to be excluded from overtime protection, many salaried employees (some of whom work 60-70 hours a week for no extra pay) will have their hours reduced and as a result, 76,000 new jobs will be created averaging 30 hours per week. Altogether, half of the retail workforce that is currently excluded from coverage will be guaranteed coverage by the law’s overtime protections. That all sounds pretty good to me.
TPP Panic: Playing the China Card
Stung by the sudden derailment in the House of Representatives of their rush to pass the Trans-Pacific Partnership (TPP), the Washington establishment has wasted no time in warning us of the terrifying menace of a rising China, should the trade deal not be put back on track next week.
Echoing previous remarks by the president, House Speaker John Boehner warned “we’re allowing and inviting China to go right on setting the rules of the world economy.” Pro-TPP Democratic Congressman Jim Hines (D-Conn.) said that Friday’s vote, “told the world that we prefer that China set the rules and values that govern trade in the Pacific.”
These remarks are both fatuous and revealing of how weak the case for the TPP is, even among its own promoters.
As a matter of obvious fact, the rules of the world economy within which the Chinese have been taking the United States to the economic cleaners were not set in China. They were set in Washington, DC by our own American policymakers and fixers who in one way or another were, and still are, are in the pay of multinational corporate investors.
Under Ronald Reagan, the two Bushes, Bill Clinton and now Barack Obama the United States government designed and imposed the global model of “free trade” which promoted the shift of investment from the United States to parts of the world where labor is cheap, the environment is unprotected, and the public interest is even more up for sale than it is here.
TiSA: A Secret Trade Agreement That Will Usurp America’s Authority to Make Immigration Policy
Proponents of Trade Promotion Authority (aka fast-track trade negotiating authority), which the House of Representatives will likely vote on soon, have made an unequivocal promise that future trade agreements like the Trans-Pacific Partnership (TPP) and the Transatlantic Trade and Investment Partnership (TTIP) will explicitly exclude any provisions that would require a change to U.S. immigration law, regulations, policy, or practices. Many members of Congress in both parties have expressed concern that trade agreements might limit America’s ability to set immigration policy. Republican congressmen Paul Ryan and Robert Goodlatte have responded by explicitly assuring members of their party that there will be no immigration provisions in any trade bill.
U.S. Trade Representative Michael Froman has stated in an interrogatory with Sen. Chuck Grassley (R-Iowa) and via letter that nothing is being negotiated in the TPP that “would require any modification to U.S. immigration law or policy or any changes to the U.S. visa system.”
Furthermore, just a few weeks ago, the Senate Finance Committee released a statement titled “TPA Drives High-Quality Trade Agreements, Not Immigration Law: The Administration Has No Authority Under TPA or Any Pending Trade Agreement to Unilaterally Change U.S. Immigration Laws,” and the committee’s May 12 report on the Fast Track bill that was eventually passed by the full Senate contained this relevant language:
For many years, Congress has made it abundantly clear that international trade agreements should not change, nor require any change, to U.S. immigration law and practice…
The Committee continues to believe that it is not appropriate to negotiate in a trade agreement any provision that would (1) require changes to U.S. immigration law, regulations, policy, or practice; (2) accord immigration-related benefits to parties to trade agreements; (3) commit the United States to keep unchanged, with respect to nationals of parties to trade agreements, one or more existing provisions of U.S. immigration law, policy, or practice; or (4) expand to additional countries immigration-related commitments already made by the United States in earlier trade agreements.
The Politics of Fast Track: Exports, Imports and Jobs
The House is expected to vote this week on fast track authority to negotiate two massive trade deals, including the proposed Trans-Pacific Partnership (TPP) and the Transatlantic Trade and Investment Partnership (T-TIP). The Wall Street Journal noted on Sunday that “the decade’s old argument that major trade agreements boost both exports and jobs at home is losing its political punch, even in some of the country’s most export-heavy Congressional Districts.” One reason is that counting exports is less than half the story. While it’s true that exports support domestic jobs, imports reduce demand for domestic output and cost jobs.
As I’ve written before, trade is a two-way street, and talking about exports without considering imports is like keeping score in a baseball game by counting only the runs scored by the home team. It might make you feel good, but it won’t tell you who’s winning the game. The Journal story included a table showing the ten congressional districts with the biggest gains in exports since 2006. The authors expressed surprise that only three of the ten members representing these districts have announced support for fast track (trade promotion authority, or TPA).
Looking at jobs supported and displaced by trade in these districts provides a very different picture, which helps explain why supporters of fast track are having trouble rounding up votes in the House. In a recent study, I estimated the number of jobs supported and displaced by China trade between 2001 and 2013. We used the results of this study to examine the impacts of China trade on jobs by congressional district between 2006 and 2013—the period covered in the Wall Street Journal story. The results for the top ten districts identified by the Journal are shown in the following table.
Pension Politics in Pennsylvania
I testified last week in Harrisburg on a 410-page public pension “reform” bill (SB1) that neither I nor my fellow witnesses had read. Normally, we would have been able to rely on actuarial reports, but the actuaries weren’t given enough time to read the bill either. This didn’t stop 28 state senators from passing the bill on a party-line vote without even bothering to hold a hearing (the two I attended—one as a witness—were held by House committees after the Senate vote).
At the first hearing, supporters claimed the bill would help repair Pennsylvania’s credit rating and ensure intergenerational equity. You would never know that the bill actually delays paying down legacy costs. As a result, even the Manhattan Institute’s Richard Dreyfuss (the public pension scourge, not Jaws hero), couldn’t bring himself to support it.
Supporters also claim the bill “preserves current employee retirement benefits,” despite the fact that $13 billion of the projected $16 billion in cost savings comes from changes affecting current employees. At least one of these changes—removing a subsidy for lump sum distributions—might be a good idea in the abstract. But all cuts affecting mid-career workers will inevitably (and probably successfully) be challenged in court, as Dreyfuss pointed out.
Job Openings Rise as the Hires and Quits Rates Remain Stubborn
This morning’s Job Openings and Labor Turnover Survey (JOLTS) report reflects the solid employment situation for April, which is considerably better than the weakness we saw in March. Job openings were up, which, along with a slight drop in the unemployment level, meant that the job-seekers-to-job-openings ratio fell to 1.6 in April. While this reflects an improvement, it fails to include the 3.1 million missing workers in April and is still far above its low-point of 1.1 in 2000. Furthermore, it remains the case that even if we continue moving forward at the pace of average employment over the last six months (236,000 jobs per month), the economy won’t resemble the strength of the pre-recession economy (such as it was) until the end of next year.
The total number of job openings rose to 5.4 million in April while the number of hires was little changed at 5.0 million. While there has been a clear improvement, it is important to remember that a job opening when the labor market is weak often does not mean the same thing as a job opening when the labor market is strong. There is a wide range of “recruitment intensity” a company can put behind a job opening. If a firm is trying hard to fill an opening, it may increase the compensation package and/or scale back the required qualifications. On the other hand, if it is not trying very hard, it might hike up the required qualifications and/or offer a meager compensation package. Perhaps unsurprisingly, research shows that recruitment intensity is cyclical—it tends to be stronger when the labor market is strong, and weaker when the labor market is weak. This means that when a job opening goes unfilled and the labor market is weak, as it is today, companies may very well be holding out for an overly-qualified candidate at a cheap price.
Another indicator of the labor market’s continued weakness is the depressed quits rate. The figure below displays the rate of separations disaggregated into the hires rate, the quits rate, and the layoff rate. Layoffs shot up during the recession but recovered quickly and have been at pre-recession levels for more than three years. The fact that this trend continued in April is a good sign. That said, not only do layoffs need to come down before we see a full recovery in the labor market, but hiring also needs to pick up—the hires rate was down slightly to 3.5 percent in April. It has been generally improving, but it still remains below its pre-recession level.
Young Black High School Grads Face Astonishing Underemployment
Last week, I wrote about how high school graduates will face significant economic challenges when they graduate this spring. High school graduates almost always experience higher levels of unemployment and lower wages than their counterparts with a college degree, and their labor market difficulties were particularly exacerbated by the Great Recession. Despite officially ending in June 2009, the recession left millions unemployed for prolonged spells, with recent workforce entrants such as young high school grads being particularly vulnerable.
Underemployment is one of the major problems that young workers currently face. Approximately 19.5 percent of young high school graduates (those ages 17–20) are unemployed and about 37.0 percent are underemployed. For young college graduates (those ages 21–24) the unemployment rate is 7.2 percent and the underemployment rate is 14.9 percent. Our measure of underemployment is the U-6 measure from the BLS, which includes not only unemployed workers but also those who are part-time for economic reasons and those who are marginally attached to the labor force.
When we look at the underemployment data by race, we often see an even worse situation. As shown in the charts below, 23.0 percent of young black college graduates are currently underemployed, compared with 22.4 percent of young Hispanic college grads and 12.9 percent of white college grads. And as elevated as these rates are, the picture is bleakest for young high school graduates, who are majority of young workers.
Underemployment rate of young college graduates, by race and ethnicity, 2000–2015*
| Date | White | Black |
|---|---|---|
| 2000-01-01 | 7.6% | 17.5% |
| 2000-02-01 | 7.5% | 17.8% |
| 2000-03-01 | 7.8% | 17.8% |
| 2000-04-01 | 7.8% | 17.0% |
| 2000-05-01 | 7.9% | 16.1% |
| 2000-06-01 | 7.8% | 16.6% |
| 2000-07-01 | 7.7% | 15.4% |
| 2000-08-01 | 7.4% | 14.6% |
| 2000-09-01 | 7.3% | 15.1% |
| 2000-10-01 | 7.2% | 15.3% |
| 2000-11-01 | 7.0% | 15.7% |
| 2000-12-01 | 6.9% | 15.4% |
| 2001-01-01 | 6.8% | 14.2% |
| 2001-02-01 | 6.8% | 12.2% |
| 2001-03-01 | 6.9% | 11.6% |
| 2001-04-01 | 7.0% | 11.6% |
| 2001-05-01 | 6.9% | 11.3% |
| 2001-06-01 | 7.1% | 12.0% |
| 2001-07-01 | 7.1% | 12.3% |
| 2001-08-01 | 7.6% | 13.3% |
| 2001-09-01 | 8.1% | 13.3% |
| 2001-10-01 | 8.3% | 14.0% |
| 2001-11-01 | 8.5% | 14.7% |
| 2001-12-01 | 8.6% | 15.9% |
| 2002-01-01 | 8.8% | 16.4% |
| 2002-02-01 | 9.0% | 17.6% |
| 2002-03-01 | 8.9% | 17.6% |
| 2002-04-01 | 8.9% | 18.3% |
| 2002-05-01 | 9.0% | 18.5% |
| 2002-06-01 | 8.8% | 18.2% |
| 2002-07-01 | 8.9% | 18.3% |
| 2002-08-01 | 8.6% | 17.5% |
| 2002-09-01 | 8.6% | 17.5% |
| 2002-10-01 | 8.4% | 17.3% |
| 2002-11-01 | 8.4% | 17.1% |
| 2002-12-01 | 8.7% | 15.7% |
| 2003-01-01 | 9.0% | 15.3% |
| 2003-02-01 | 8.9% | 14.9% |
| 2003-03-01 | 9.2% | 14.8% |
| 2003-04-01 | 9.1% | 14.3% |
| 2003-05-01 | 9.3% | 15.9% |
| 2003-06-01 | 9.6% | 15.2% |
| 2003-07-01 | 10.0% | 15.5% |
| 2003-08-01 | 10.3% | 15.5% |
| 2003-09-01 | 10.2% | 15.4% |
| 2003-10-01 | 10.4% | 15.1% |
| 2003-11-01 | 10.5% | 15.0% |
| 2003-12-01 | 10.4% | 15.1% |
| 2004-01-01 | 10.3% | 15.9% |
| 2004-02-01 | 10.5% | 16.9% |
| 2004-03-01 | 10.5% | 17.5% |
| 2004-04-01 | 10.7% | 17.4% |
| 2004-05-01 | 10.5% | 15.9% |
| 2004-06-01 | 10.6% | 15.4% |
| 2004-07-01 | 10.3% | 15.5% |
| 2004-08-01 | 10.1% | 14.6% |
| 2004-09-01 | 10.0% | 14.5% |
| 2004-10-01 | 9.8% | 15.9% |
| 2004-11-01 | 9.8% | 16.5% |
| 2004-12-01 | 9.8% | 16.7% |
| 2005-01-01 | 9.8% | 16.3% |
| 2005-02-01 | 9.8% | 15.5% |
| 2005-03-01 | 9.7% | 15.7% |
| 2005-04-01 | 9.7% | 15.8% |
| 2005-05-01 | 9.9% | 16.6% |
| 2005-06-01 | 9.6% | 16.5% |
| 2005-07-01 | 9.5% | 16.6% |
| 2005-08-01 | 9.6% | 17.5% |
| 2005-09-01 | 9.7% | 17.6% |
| 2005-10-01 | 9.6% | 16.5% |
| 2005-11-01 | 9.6% | 15.8% |
| 2005-12-01 | 9.5% | 15.5% |
| 2006-01-01 | 9.4% | 15.0% |
| 2006-02-01 | 9.4% | 15.2% |
| 2006-03-01 | 9.3% | 15.2% |
| 2006-04-01 | 9.0% | 14.5% |
| 2006-05-01 | 8.8% | 13.2% |
| 2006-06-01 | 8.9% | 13.8% |
| 2006-07-01 | 8.9% | 14.8% |
| 2006-08-01 | 8.6% | 14.6% |
| 2006-09-01 | 8.5% | 14.3% |
| 2006-10-01 | 8.7% | 13.7% |
| 2006-11-01 | 8.5% | 13.3% |
| 2006-12-01 | 8.7% | 13.2% |
| 2007-01-01 | 8.7% | 13.4% |
| 2007-02-01 | 8.4% | 13.2% |
| 2007-03-01 | 8.2% | 13.4% |
| 2007-04-01 | 8.2% | 14.6% |
| 2007-05-01 | 8.3% | 15.3% |
| 2007-06-01 | 8.4% | 15.2% |
| 2007-07-01 | 8.5% | 14.6% |
| 2007-08-01 | 8.8% | 13.6% |
| 2007-09-01 | 9.1% | 14.5% |
| 2007-10-01 | 9.0% | 15.1% |
| 2007-11-01 | 9.2% | 15.4% |
| 2007-12-01 | 9.0% | 16.2% |
| 2008-01-01 | 8.9% | 16.6% |
| 2008-02-01 | 9.0% | 17.0% |
| 2008-03-01 | 9.1% | 16.1% |
| 2008-04-01 | 9.2% | 15.5% |
| 2008-05-01 | 9.4% | 15.6% |
| 2008-06-01 | 9.8% | 15.6% |
| 2008-07-01 | 9.9% | 15.4% |
| 2008-08-01 | 9.9% | 16.5% |
| 2008-09-01 | 10.0% | 15.8% |
| 2008-10-01 | 10.2% | 14.9% |
| 2008-11-01 | 10.3% | 14.8% |
| 2008-12-01 | 10.6% | 14.7% |
| 2009-01-01 | 11.1% | 14.9% |
| 2009-02-01 | 11.5% | 16.0% |
| 2009-03-01 | 12.2% | 18.0% |
| 2009-04-01 | 12.5% | 19.5% |
| 2009-05-01 | 12.8% | 20.4% |
| 2009-06-01 | 13.3% | 20.7% |
| 2009-07-01 | 13.6% | 22.3% |
| 2009-08-01 | 14.4% | 24.1% |
| 2009-09-01 | 14.8% | 25.9% |
| 2009-10-01 | 15.1% | 26.1% |
| 2009-11-01 | 15.5% | 25.1% |
| 2009-12-01 | 15.8% | 25.9% |
| 2010-01-01 | 16.0% | 26.3% |
| 2010-02-01 | 16.2% | 25.8% |
| 2010-03-01 | 16.1% | 24.6% |
| 2010-04-01 | 16.4% | 25.3% |
| 2010-05-01 | 16.6% | 24.9% |
| 2010-06-01 | 16.6% | 26.6% |
| 2010-07-01 | 16.7% | 28.5% |
| 2010-08-01 | 16.2% | 28.9% |
| 2010-09-01 | 16.5% | 28.7% |
| 2010-10-01 | 16.6% | 29.2% |
| 2010-11-01 | 16.7% | 29.3% |
| 2010-12-01 | 16.7% | 30.0% |
| 2011-01-01 | 17.0% | 30.8% |
| 2011-02-01 | 17.2% | 30.7% |
| 2011-03-01 | 17.5% | 31.0% |
| 2011-04-01 | 17.3% | 28.8% |
| 2011-05-01 | 17.1% | 28.2% |
| 2011-06-01 | 17.1% | 28.4% |
| 2011-07-01 | 17.6% | 26.0% |
| 2011-08-01 | 18.1% | 24.6% |
| 2011-09-01 | 18.0% | 23.7% |
| 2011-10-01 | 17.7% | 23.5% |
| 2011-11-01 | 17.6% | 22.5% |
| 2011-12-01 | 17.3% | 21.3% |
| 2012-01-01 | 17.2% | 20.9% |
| 2012-02-01 | 17.0% | 21.1% |
| 2012-03-01 | 16.7% | 21.4% |
| 2012-04-01 | 16.5% | 22.4% |
| 2012-05-01 | 16.5% | 22.2% |
| 2012-06-01 | 16.4% | 20.3% |
| 2012-07-01 | 16.3% | 19.8% |
| 2012-08-01 | 15.9% | 20.6% |
| 2012-09-01 | 15.8% | 21.2% |
| 2012-10-01 | 15.7% | 20.6% |
| 2012-11-01 | 15.3% | 20.8% |
| 2012-12-01 | 15.5% | 20.8% |
| 2013-01-01 | 15.6% | 21.2% |
| 2013-02-01 | 15.6% | 22.9% |
| 2013-03-01 | 15.6% | 23.5% |
| 2013-04-01 | 15.7% | 23.0% |
| 2013-05-01 | 15.8% | 24.0% |
| 2013-06-01 | 15.7% | 25.2% |
| 2013-07-01 | 15.5% | 25.0% |
| 2013-08-01 | 15.5% | 26.4% |
| 2013-09-01 | 15.7% | 27.5% |
| 2013-10-01 | 16.0% | 28.2% |
| 2013-11-01 | 16.2% | 28.4% |
| 2013-12-01 | 16.1% | 29.0% |
| 2014-01-01 | 16.1% | 29.5% |
| 2014-02-01 | 16.0% | 28.2% |
| 2014-03-01 | 15.8% | 28.1% |
| 2014-04-01 | 15.4% | 27.8% |
| 2014-05-01 | 15.0% | 26.8% |
| 2014-06-01 | 14.9% | 26.2% |
| 2014-07-01 | 14.6% | 27.0% |
| 2014-08-01 | 14.3% | 25.3% |
| 2014-09-01 | 13.9% | 24.0% |
| 2014-10-01 | 13.6% | 23.4% |
| 2014-11-01 | 13.4% | 22.7% |
| 2014-12-01 | 13.4% | 22.2% |
| 2015-01-01 | 13.1% | 21.7% |
| 2015-02-01 | 13.0% | 23.7% |
| 2015-03-01 | 12.9% | 23.0% |
* Data reflect 12-month moving averages; data for 2015 represent 12-month average from April 2014 to March 2015.
Note: Data are for college graduates age 21–24 who are not enrolled in further schooling. Shaded areas denote recessions. Race/ethnicity categories are mutually exclusive (i.e., white non-Hispanic and black non-Hispanic). The Hispanic category is not included due to insufficient sample sizes over part of the series.
Source: EPI analysis of basic monthly Current Population Survey microdata
On Substance, Martin O’Malley Was Right About American Wages: Don’t Let Nitpicks Convince You That There Is Not A Crisis in American Pay
Three separate sources have recently “fact-checked” claims that Martin O’Malley made about American wages in his recent speech announcing his candidacy for the Democratic nomination. The precise O’Malley quote was:
Today in America, 70 percent of us are earning the same or less than we were 12 years ago, and this is the first time that that has happened this side of World War II.
O’Malley has said that our research on wages provided a basis for his claim (examples can be found here and here).
First, let’s be clear on what our claim is and then I’ll talk about the fact checkers’ assessments of O’Malley’s use of the data.
We have data on hourly wages by decile since 1973. Between 2002 and 2014, inflation-adjusted hourly wages for the bottom 7 deciles (i.e., 70 percent of the American workforce) fell. This is a remarkable economic fact and one that O’Malley is clearly right to highlight.
Further, between 1947 and 1973 there is almost certainly no 12-year period when the bottom 70 percent of wage earners saw hourly wage declines. Precise wage data by decile is sketchy over this period, but the circumstantial evidence on this is overwhelming. Just look at this graph, which shows hourly pay for a grouping reflecting the bottom 80 percent of the workforce rising sharply until the early 1970s.
What Can the TPP Offer Canada? Not Much.
When Canada joined the Trans-Pacific Partnership talks in 2012 it did so somewhat reluctantly and, like Mexico, with strings attached. One of them was that Canadian negotiators could not reopen any closed text. So, in this sense, it’s been a bit of a raw deal for the Obama administration’s NAFTA partners from the beginning. Canada’s bigger business lobbies called it a defensive move, to “secure” NAFTA supply chains rather than offering any meaningful market access elsewhere. The Canadian public have almost no idea what’s going on. But as TPP countries appear to be close to the end game, people here are starting to ask the obvious questions: what’s in it for us, and what will we have to give up to get it. The answers are equally obvious if you look past the hype: not much, and quite a lot.
To begin with, Canada already has free trade deals in place with four of the larger TPP countries (Peru, Chile, the United States, and Mexico), and tariffs on trade with the others—representing 3 percent of imports and 5 percent of exports—are very low. Canada has a trade deficit with these non-FTA countries of $5 to $8 billion annually, and 80 percent of Canada’s top exports to these countries are raw or semi-processed goods (e.g., beef, coal, lumber), while 85 percent of imports are of higher value-added goods (e.g., autos, machinery, computer and electrical components). This Canadian trade deficit will likely widen if the TPP is ratified, as the United States found two years into its FTA with South Korea.
Tariff removal through the TPP is therefore likely to worsen the erosion of the Canadian manufacturing sector and jobs that has been taking place since NAFTA—a result, in part, of the limits free trade deals place on performance requirements and production-sharing arrangements. NAFTA-driven restructuring did not even have the promised effect of raising Canadian productivity levels, which languish at 70 percent of U.S. levels twenty years into the agreement. Instead, Canada has experienced greater corporate concentration, a significant decline in investment in new production, and rising inequality.
In short, there is little trade expansion upside for Canada in this negotiation. And yet the Canadian public will eventually be asked to make considerable public policy concessions to see the TPP through. As many U.S. commentators have argued, the trade impacts of TPP are far less important than the serious concerns it raises about excessive intellectual property rights, regulatory harmonization, and the perpetuation of a controversial investor-state dispute settlement (ISDS) regime that has been extremely damaging to democratic governance globally, not to mention quite humiliating for Canada.
Et Tu, Mickey Mouse? Disney Pads Record Profits by Replacing U.S. Workers with Cheaper H-1B Guestworkers
There was a lot to celebrate in the Magic Kingdom this year. The Disney Corporation had its most profitable year ever, with profits of $7.5 billion—up 22 percent from the previous year. Disney’s stock price is up approximately 150 percent over the past three years. These kinds of results have paid off handsomely for its CEO Bob Iger, who took home $46 million in compensation last year.
Disney prides itself on its recipe for “delighting customers,” a recipe it says includes putting employees first. They tout this as a key to their success in creating “a culture where going the extra mile for customers comes naturally” for employees. One method of creating this culture is referring to its employees as “cast members.” In fact, Disney is so proud of its organizational culture that it’s even created an institute to share its magic with other businesses (for a consulting fee, of course).
So, you would expect a firm that puts its employees first to share the vast prosperity that’s been created with the very employees who went above and beyond to help generate those record profits.
Well, how did Mr. Iger repay his workers—sorry, I mean cast members—for creating all this profit? Not with bonuses and a big raises. Instead, as the New York Times just detailed in a major report, he forced hundreds of them to train their own replacements—temporary foreign workers here on H-1B guestworker visas—before he laid them off.
Don’t Pop the Champagne Corks Yet: Putting Year-over-Year Hourly Earnings Growth in Perspective
Average hourly earnings hit $24.96 in May, an increase of 2.3 percent over May 2014. We’ve been tracking nominal wage growth over the recovery and at best we can find reason for only a very modest celebration. 2.3 percent growth is a move in the right direction, but it’s nowhere near the 3.5 to 4.0 percent growth we expect in a healthy labor market.
As shown in the figure below, average hourly wage growth has been teetering around 2.0 percent for the last five years. There has been a slight increase in the annual twelve-month growth trend this past month to 2.3 percent from the trends observed in earlier months this year, which hovered between 2.0 and 2.2 percent. This may be a temporary increase, as we’ve seen 2.3 percent before. Even more important is that a 2.3 percent annual growth in wages is far below target, as the graph shows.
Nominal wage growth has been far below target in the recovery: Year-over-year change in private-sector nominal average hourly earnings, 2007–2015
| All nonfarm employees | Production/nonsupervisory workers | |
|---|---|---|
| Mar-2007 | 3.5910224% | 4.1112455% |
| Apr-2007 | 3.2738095% | 3.8461538% |
| May-2007 | 3.7257824% | 4.1441441% |
| Jun-2007 | 3.8062284% | 4.1267943% |
| Jul-2007 | 3.4482759% | 4.0524434% |
| Aug-2007 | 3.4940945% | 4.0404040% |
| Sep-2007 | 3.2827046% | 4.1493776% |
| Oct-2007 | 3.2778865% | 3.7780401% |
| Nov-2007 | 3.2714844% | 3.8869258% |
| Dec-2007 | 3.1599417% | 3.8123167% |
| Jan-2008 | 3.1067961% | 3.8619075% |
| Feb-2008 | 3.0947776% | 3.7296037% |
| Mar-2008 | 3.0813674% | 3.7746806% |
| Apr-2008 | 2.8818444% | 3.7037037% |
| May-2008 | 3.0172414% | 3.6908881% |
| Jun-2008 | 2.6666667% | 3.6186100% |
| Jul-2008 | 3.0000000% | 3.7227950% |
| Aug-2008 | 3.3285782% | 3.8263849% |
| Sep-2008 | 3.2258065% | 3.6425726% |
| Oct-2008 | 3.3159640% | 3.9249147% |
| Nov-2008 | 3.6406619% | 3.8548753% |
| Dec-2008 | 3.5815269% | 3.8418079% |
| Jan-2009 | 3.5781544% | 3.7183099% |
| Feb-2009 | 3.2363977% | 3.6516854% |
| Mar-2009 | 3.1293788% | 3.5254617% |
| Apr-2009 | 3.2212885% | 3.2924107% |
| May-2009 | 2.8358903% | 3.0589544% |
| Jun-2009 | 2.7829314% | 2.9379157% |
| Jul-2009 | 2.5889968% | 2.7056875% |
| Aug-2009 | 2.3930051% | 2.6402640% |
| Sep-2009 | 2.3437500% | 2.7457441% |
| Oct-2009 | 2.3383769% | 2.6272578% |
| Nov-2009 | 2.0529197% | 2.6746725% |
| Dec-2009 | 1.8198362% | 2.5027203% |
| Jan-2010 | 1.9545455% | 2.6072787% |
| Feb-2010 | 1.9990913% | 2.4932249% |
| Mar-2010 | 1.7663043% | 2.2702703% |
| Apr-2010 | 1.8091361% | 2.4311183% |
| May-2010 | 1.9439421% | 2.5903940% |
| Jun-2010 | 1.7148014% | 2.5309639% |
| Jul-2010 | 1.8476791% | 2.4731183% |
| Aug-2010 | 1.7528090% | 2.4115756% |
| Sep-2010 | 1.8410418% | 2.2982362% |
| Oct-2010 | 1.8817204% | 2.5066667% |
| Nov-2010 | 1.6540009% | 2.2328549% |
| Dec-2010 | 1.7426273% | 2.0700637% |
| Jan-2011 | 1.9170753% | 2.1704606% |
| Feb-2011 | 1.8708241% | 2.1152829% |
| Mar-2011 | 1.8691589% | 2.0613108% |
| Apr-2011 | 1.9102621% | 2.1097046% |
| May-2011 | 1.9955654% | 2.1567596% |
| Jun-2011 | 2.1295475% | 1.9957983% |
| Jul-2011 | 2.2566372% | 2.3084995% |
| Aug-2011 | 1.8992933% | 1.9884877% |
| Sep-2011 | 1.9400353% | 1.9331243% |
| Oct-2011 | 2.1108179% | 1.7689906% |
| Nov-2011 | 2.0228672% | 1.7680707% |
| Dec-2011 | 1.9762846% | 1.7680707% |
| Jan-2012 | 1.7497813% | 1.3989637% |
| Feb-2012 | 1.8801924% | 1.4500259% |
| Mar-2012 | 2.0969856% | 1.7607457% |
| Apr-2012 | 2.0052310% | 1.7561983% |
| May-2012 | 1.8260870% | 1.3903193% |
| Jun-2012 | 1.9548219% | 1.5447992% |
| Jul-2012 | 1.7741238% | 1.3333333% |
| Aug-2012 | 1.8205462% | 1.3340174% |
| Sep-2012 | 1.9896194% | 1.4351615% |
| Oct-2012 | 1.5073213% | 1.2781186% |
| Nov-2012 | 1.8965517% | 1.4307614% |
| Dec-2012 | 2.1963824% | 1.7373531% |
| Jan-2013 | 2.1496131% | 1.8906490% |
| Feb-2013 | 2.1030043% | 2.0418581% |
| Mar-2013 | 1.9255456% | 1.8829517% |
| Apr-2013 | 2.0085470% | 1.7258883% |
| May-2013 | 2.0068318% | 1.8791265% |
| Jun-2013 | 2.1303792% | 2.0283976% |
| Jul-2013 | 1.9132653% | 1.9230769% |
| Aug-2013 | 2.2562793% | 2.1772152% |
| Sep-2013 | 2.0356234% | 2.1728146% |
| Oct-2013 | 2.2486211% | 2.2715800% |
| Nov-2013 | 2.2419628% | 2.3173804% |
| Dec-2013 | 1.8963338% | 2.1597187% |
| Jan-2014 | 1.9360269% | 2.3069208% |
| Feb-2014 | 2.1437579% | 2.4512256% |
| Mar-2014 | 2.1830395% | 2.3976024% |
| Apr-2014 | 1.9689987% | 2.3952096% |
| May-2014 | 2.1347844% | 2.4426720% |
| Jun-2014 | 2.0442219% | 2.3359841% |
| Jul-2014 | 2.0859408% | 2.4329692% |
| Aug-2014 | 2.2064946% | 2.4777007% |
| Sep-2014 | 2.0365752% | 2.2749753% |
| Oct-2014 | 2.0331950% | 2.2704837% |
| Nov-2014 | 2.1100538% | 2.2648941% |
| Dec-2014 | 1.8196857% | 1.8682399% |
| Jan-2015 | 2.2295623% | 2.0098039% |
| Feb-2015 | 1.975309% | 1.6601563% |
| Mar-2015 | 2.095316% | 1.853659% |
| Apr-2015 | 2.21857% | 1.900585% |
| May-2015 | 2.295082% | 2.043796% |
* Nominal wage growth consistent with the Federal Reserve Board's 2 percent inflation target, 1.5 percent productivity growth, and a stable labor share of income.
Source: EPI analysis of Bureau of Labor Statistics Current Employment Statistics public data series
More Hope about the Labor Market Can Lead to a Higher Unemployment Rate
That’s what happened in May. We saw solid job growth in payroll employment (+280,000 jobs). At the same time, we saw a solid increase in the civilian labor force—nearly 400,000 more people in the labor force in May. It’s not surprising then that the unemployment rate (by definition, the number of unemployed people divided by the labor force) increased slightly (though not significantly, statistically speaking). Regardless, this “rise” is actually a positive sign.
The weak labor market has sidelined millions of “missing workers,” or potential workers who, because of weak job opportunities, are neither employed nor actively seeking a job. In other words, these are people who would be either working or looking for work if job opportunities were significantly stronger. An increase in optimism about the labor market leads to more people actively seeking employment. As expected, a rise in the labor force in May corresponded with a decline in the estimated number of missing workers.
* Potential workers who, due to weak job opportunities, are neither employed nor actively seeking work Note: Volatility in the number of missing workers in 2006–2008, including cases of negative numbers of missing workers, is simply the result of month-to-month variability in the sample. The Great Recession–induced pool of missing workers began to form and grow starting in late 2008. Source: EPI analysis of Current Population Survey public data seriesMillions of potential workers sidelined: Missing workers,* January 2006–May 2015
Date
Missing workers
2006-01-01
610,000
2006-02-01
160,000
2006-03-01
190,000
2006-04-01
300,000
2006-05-01
170,000
2006-06-01
110,000
2006-07-01
60,000
2006-08-01
-140,000
2006-09-01
90,000
2006-10-01
-130,000
2006-11-01
-380,000
2006-12-01
-650,000
2007-01-01
-670,000
2007-02-01
-480,000
2007-03-01
-420,000
2007-04-01
340,000
2007-05-01
200,000
2007-06-01
80,000
2007-07-01
90,000
2007-08-01
560,000
2007-09-01
150,000
2007-10-01
480,000
2007-11-01
-140,000
2007-12-01
-250,000
2008-01-01
-790,000
2008-02-01
-330,000
2008-03-01
-480,000
2008-04-01
-260,000
2008-05-01
-730,000
2008-06-01
-610,000
2008-07-01
-640,000
2008-08-01
-650,000
2008-09-01
-350,000
2008-10-01
-550,000
2008-11-01
-300,000
2008-12-01
-300,000
2009-01-01
-100,000
2009-02-01
-230,000
2009-03-01
210,000
2009-04-01
-130,000
2009-05-01
-200,000
2009-06-01
-260,000
2009-07-01
120,000
2009-08-01
410,000
2009-09-01
1,220,000
2009-10-01
1,350,000
2009-11-01
1,400,000
2009-12-01
2,100,000
2010-01-01
1,660,000
2010-02-01
1,540,000
2010-03-01
1,320,000
2010-04-01
770,000
2010-05-01
1,330,000
2010-06-01
1,710,000
2010-07-01
1,880,000
2010-08-01
1,490,000
2010-09-01
1,850,000
2010-10-01
2,320,000
2010-11-01
1,960,000
2010-12-01
2,390,000
2011-01-01
2,460,000
2011-02-01
2,630,000
2011-03-01
2,430,000
2011-04-01
2,500,000
2011-05-01
2,590,000
2011-06-01
2,670,000
2011-07-01
3,110,000
2011-08-01
2,520,000
2011-09-01
2,510,000
2011-10-01
2,540,000
2011-11-01
2,510,000
2011-12-01
2,470,000
2012-01-01
2,780,000
2012-02-01
2,540,000
2012-03-01
2,530,000
2012-04-01
2,890,000
2012-05-01
2,480,000
2012-06-01
2,240,000
2012-07-01
2,770,000
2012-08-01
2,830,000
2012-09-01
2,690,000
2012-10-01
2,130,000
2012-11-01
2,480,000
2012-12-01
2,060,000
2013-01-01
2,340,000
2013-02-01
2,690,000
2013-03-01
3,130,000
2013-04-01
2,880,000
2013-05-01
2,740,000
2013-06-01
2,580,000
2013-07-01
2,860,000
2013-08-01
3,010,000
2013-09-01
3,130,000
2013-10-01
3,810,000
2013-11-01
3,360,000
2013-12-01
3,550,000
2014-01-01
3,420,000
2014-02-01
3,200,000
2014-03-01
2,840,000
2014-04-01
3,670,000
2014-05-01
3,410,000
2014-06-01
3,320,000
2014-07-01
3,170,000
2014-08-01
3,260,000
2014-09-01
3,580,000
2014-10-01
3,060,000
2014-11-01
3,030,000
2014-12-01
3,230,000
2015-01-01
2,860,000
2015-02-01
3,110,000
2015-03-01
3,330,000
2015-04-01
3,140,000
2015-05-01
2,830,000
Yes, the Employment Report Was Decent. But No, The Labor Market Isn’t Strong.
Yes, this morning’s jobs report had some welcome news. Payroll employment was up 280,000 jobs, slightly above the trend of the previous six months. But the recovery is far from complete: there is still a three million job shortfall in the economy today.
The recent trends in job growth predict a slow march back to full recovery. If we continued to add 280,000 jobs a month into the future, we wouldn’t fill the jobs gap until August 2016—more than a year away. Over the last six months, average job growth was 236,000. If we continued to add jobs at that pace, the gap wouldn’t close until the end of 2016. The three month average of 207,000 jobs (much slower because of the poor March report) moves full recovery even farther into the future—at that pace, we wouldn’t return to pre-recession labor market health until April 2017.
Furthermore, it’s important to remember that the 2007 labor market is still a low bar and that recovery is not just about jobs. Nominal wage growth continues to be far below target. Yes, 2.3 percent wage growth is an improvement, but it’s nowhere near strong enough to call for rate hikes. The Fed should not feel comfortable raising rates in September—in fact, they shouldn’t even begin to think about having a conversation about raising rates until 2016.
Don’t Forget about High School Grads
Last week, we released The Class of 2015, our annual report examining the job and wage prospects for newly-minted high school and college graduates. When we release this study, the media tend to focus on the chances college graduates have for snagging a job. But I want to submit a humble plea: don’t forget about the high school grads. After all, they make up the majority of young people.
Only 9.7 percent of young people between the ages of 17 and 24 have a college degree or more. 52.7 percent, meanwhile, have a high school degree or less (as shown in Table 1), and another 37.6 percent have only some college experience. And this trend isn’t unique to young people—even when you look at workers who are a little bit older, college graduates are still a minority. A significant share of workers age 24–29 have only a high school degree (26.4 percent) or some college experience (30.7 percent) and only 34.1 percent have a bachelor’s or advanced degree.
* Data reflect 12-month moving average as of March 2015. Note: Race/ethnicity categories are mutually exclusive (i.e., white non-Hispanic, black non-Hispanic, and Hispanic any race). Source: EPI analysis of basic monthly Current Population Survey microdataHighest degree earned, by age and demographic, 2015*
Age 17–24
Age 24–29
All
Men
Women
White
Black
Hispanic
All
Men
Women
White
Black
Hispanic
Less than high school
24.8%
26.1%
23.5%
22.5%
26.6%
30.9%
8.9%
9.7%
8.0%
4.6%
9.2%
21.6%
High school
27.9%
30.1%
25.7%
26.1%
32.2%
32.1%
26.4%
29.9%
22.9%
23.8%
33.0%
32.5%
Some college
37.6%
35.8%
39.5%
39.2%
35.9%
32.9%
30.7%
29.4%
32.0%
30.4%
36.7%
29.9%
Bachelor’s degree
9.0%
7.5%
10.5%
11.5%
4.9%
3.8%
26.6%
24.6%
28.5%
32.5%
17.2%
13.3%
Advanced degree
0.7%
0.6%
0.9%
0.8%
0.5%
0.3%
7.5%
6.4%
8.5%
8.6%
4.0%
2.8%
When you look at the wages that young people with a high school degree are making, they are far less than what college grads can expect. The average young high school graduate who does not enroll in further schooling makes $10.40 an hour, which has declined 5.5 percent from the $11.01 they were making in 2000. $10.40 an hour translates to an average full-time, full-year worker salary of just $21,632 for high school graduates. To put that in perspective, that is less than is needed to lift a four-person family above the poverty line and less than the amount needed for a one adult, one child family to get by in every area in the United States.
What to Watch on Jobs Day: What’s at Stake at the Upcoming FOMC Meeting and the Outlook for Young Workers
In tomorrow’s release of the Employment Report, I’m primarily looking for evidence confirming that the Federal Reserve should continue to stay the course through its June (and most likely September) meetings. I’ll also be looking more closely at the labor market for young people: specifically, youth entering the labor market in the summer and prospects for recent high school grads.
When the Federal Open Market Committee meets in two weeks, they will almost surely continue their current agenda and resist pressure to raise interest rates. Raising interest rates prematurely would slow the recovery, which is still in much need of oxygen. Job growth sputtered in March, but picked up again in April. If the economy continues to grow at an average of 191,000 jobs a month (as it has for the past three months), it will return to pre-Great Recession labor market health by August 2017. If you want to downplay the very weak March data, then the average job growth over the past six months (255,000 jobs per month) moving forward gets us back to prerecession health by October 2016.
All measures point to a slowly recovering economy, but an economy that is still far from the health of 2007, let alone the health of the far-stronger economy of 2000. The employment-to-population ratio remains seriously depressed, and there are still over 3 million potential workers sidelined by the weak labor market. Further, wage growth has continued to fall flat—nominal hourly wage growth has remained at around 2 percent over the last five years, far below any reasonable target.
Now that the college graduating class of 2015 has begun to try their luck in the labor market, it’s time to consider how 2015’s high school graduates are expected to do as they graduate this month. Extensive details on the specifics of the high school graduates—including underemployment and wages—are available here. Below is a chart of the unemployment rates of everyone in the labor force versus those under 25 years old and the youngest potential workers, those between 16 and 19 years old. While the unemployment rates for all groups have declined precipitously during the recovery, two other facts are readily apparent. First, the unemployment rates for any of them have not fully recovered (and it’s important to remember that this measure of unemployment fails to include those working part-time that want full time jobs or those who may have just recently given up looking for work). Second, the younger the potential labor mark entrant, the higher the unemployment rate—and the farther those younger cohorts are from a healthy unemployment rate. Unfortunately, this does not bode well for young workers looking for summer employment or their first job out of high school or college.
Note: Shaded areas denote recessions. Data are seasonally adjusted. Source: Economic Policy Institute analysis of Bureau of Labor Statistics Current Population Survey public data seriesUnemployment rate of workers by age group, 1969–2015
Date
All
16–24
16–19
1969-01-01
3.4%
8.2%
12.0%
1969-02-01
3.4%
8.1%
11.9%
1969-03-01
3.4%
8.3%
12.3%
1969-04-01
3.4%
8.2%
12.0%
1969-05-01
3.4%
8.3%
12.4%
1969-06-01
3.5%
8.3%
12.2%
1969-07-01
3.5%
8.7%
12.8%
1969-08-01
3.5%
8.2%
12.2%
1969-09-01
3.7%
8.9%
12.6%
1969-10-01
3.7%
8.8%
12.6%
1969-11-01
3.5%
8.2%
11.6%
1969-12-01
3.5%
8.4%
11.8%
1970-01-01
3.9%
9.3%
13.5%
1970-02-01
4.2%
9.8%
13.3%
1970-03-01
4.4%
9.6%
13.4%
1970-04-01
4.6%
10.4%
14.7%
1970-05-01
4.8%
10.4%
14.2%
1970-06-01
4.9%
11.2%
16.3%
1970-07-01
5.0%
11.0%
14.7%
1970-08-01
5.1%
11.4%
15.7%
1970-09-01
5.4%
12.1%
16.2%
1970-10-01
5.5%
12.2%
16.7%
1970-11-01
5.9%
12.9%
17.4%
1970-12-01
6.1%
12.8%
17.1%
1971-01-01
5.9%
12.6%
16.8%
1971-02-01
5.9%
12.5%
16.3%
1971-03-01
6.0%
12.8%
16.9%
1971-04-01
5.9%
12.5%
16.3%
1971-05-01
5.9%
13.0%
16.8%
1971-06-01
5.9%
13.2%
17.7%
1971-07-01
6.0%
12.9%
17.7%
1971-08-01
6.1%
12.8%
16.8%
1971-09-01
6.0%
12.4%
16.7%
1971-10-01
5.8%
12.4%
16.9%
1971-11-01
6.0%
13.0%
16.9%
1971-12-01
6.0%
12.7%
16.9%
1972-01-01
5.8%
12.7%
16.9%
1972-02-01
5.7%
12.8%
18.0%
1972-03-01
5.8%
12.8%
17.2%
1972-04-01
5.7%
12.4%
16.5%
1972-05-01
5.7%
11.8%
15.3%
1972-06-01
5.7%
11.8%
15.9%
1972-07-01
5.6%
12.0%
15.6%
1972-08-01
5.6%
12.1%
16.5%
1972-09-01
5.5%
12.0%
16.3%
1972-10-01
5.6%
12.0%
15.8%
1972-11-01
5.3%
11.5%
15.7%
1972-12-01
5.2%
11.3%
15.6%
1973-01-01
4.9%
10.2%
13.7%
1973-02-01
5.0%
10.9%
15.3%
1973-03-01
4.9%
10.4%
14.3%
1973-04-01
5.0%
11.0%
15.5%
1973-05-01
4.9%
10.7%
14.9%
1973-06-01
4.9%
10.4%
13.8%
1973-07-01
4.8%
10.6%
14.3%
1973-08-01
4.8%
10.3%
14.0%
1973-09-01
4.8%
10.7%
14.7%
1973-10-01
4.6%
10.0%
14.4%
1973-11-01
4.8%
10.4%
15.0%
1973-12-01
4.9%
10.5%
14.6%
1974-01-01
5.1%
10.8%
14.6%
1974-02-01
5.2%
11.0%
14.9%
1974-03-01
5.1%
10.7%
14.9%
1974-04-01
5.1%
10.5%
14.3%
1974-05-01
5.1%
11.3%
15.4%
1974-06-01
5.4%
11.8%
16.3%
1974-07-01
5.5%
12.1%
16.8%
1974-08-01
5.5%
11.7%
14.9%
1974-09-01
5.9%
12.6%
17.0%
1974-10-01
6.0%
12.5%
17.2%
1974-11-01
6.6%
13.4%
17.8%
1974-12-01
7.2%
14.2%
18.2%
1975-01-01
8.1%
15.1%
19.5%
1975-02-01
8.1%
15.6%
19.4%
1975-03-01
8.6%
16.2%
19.9%
1975-04-01
8.8%
16.5%
19.9%
1975-05-01
9.0%
16.9%
20.4%
1975-06-01
8.8%
16.3%
20.9%
1975-07-01
8.6%
16.6%
20.7%
1975-08-01
8.4%
16.3%
20.7%
1975-09-01
8.4%
16.1%
19.5%
1975-10-01
8.4%
16.1%
19.8%
1975-11-01
8.3%
15.7%
19.0%
1975-12-01
8.2%
15.6%
19.8%
1976-01-01
7.9%
15.4%
19.6%
1976-02-01
7.7%
14.7%
19.0%
1976-03-01
7.6%
14.6%
18.9%
1976-04-01
7.7%
14.9%
19.5%
1976-05-01
7.4%
14.3%
18.6%
1976-06-01
7.6%
14.5%
18.5%
1976-07-01
7.8%
14.2%
18.3%
1976-08-01
7.8%
15.0%
19.6%
1976-09-01
7.6%
14.4%
18.6%
1976-10-01
7.7%
14.9%
19.0%
1976-11-01
7.8%
14.9%
19.2%
1976-12-01
7.8%
14.8%
19.1%
1977-01-01
7.5%
14.3%
18.9%
1977-02-01
7.6%
14.5%
18.4%
1977-03-01
7.4%
14.2%
18.6%
1977-04-01
7.2%
13.7%
18.0%
1977-05-01
7.0%
13.7%
17.8%
1977-06-01
7.2%
14.0%
18.8%
1977-07-01
6.9%
13.3%
17.5%
1977-08-01
7.0%
13.7%
17.4%
1977-09-01
6.8%
13.5%
18.0%
1977-10-01
6.8%
13.0%
17.2%
1977-11-01
6.8%
13.1%
17.2%
1977-12-01
6.4%
12.2%
15.5%
1978-01-01
6.4%
12.9%
16.7%
1978-02-01
6.3%
13.0%
17.2%
1978-03-01
6.3%
13.0%
17.3%
1978-04-01
6.1%
12.6%
16.6%
1978-05-01
6.0%
11.8%
16.0%
1978-06-01
5.9%
11.7%
15.4%
1978-07-01
6.2%
12.5%
16.5%
1978-08-01
5.9%
11.7%
15.7%
1978-09-01
6.0%
12.1%
16.4%
1978-10-01
5.8%
11.5%
16.1%
1978-11-01
5.9%
11.9%
16.3%
1978-12-01
6.0%
12.1%
16.7%
1979-01-01
5.9%
11.6%
16.1%
1979-02-01
5.9%
11.7%
16.1%
1979-03-01
5.8%
11.6%
15.9%
1979-04-01
5.8%
11.6%
16.3%
1979-05-01
5.6%
11.6%
16.1%
1979-06-01
5.7%
11.5%
15.7%
1979-07-01
5.7%
11.6%
15.6%
1979-08-01
6.0%
12.2%
16.5%
1979-09-01
5.9%
12.1%
16.5%
1979-10-01
6.0%
12.1%
16.5%
1979-11-01
5.9%
11.6%
15.9%
1979-12-01
6.0%
12.4%
16.2%
1980-01-01
6.3%
12.6%
16.5%
1980-02-01
6.3%
12.5%
16.6%
1980-03-01
6.3%
12.3%
16.3%
1980-04-01
6.9%
13.1%
16.2%
1980-05-01
7.5%
14.7%
18.6%
1980-06-01
7.6%
14.7%
18.9%
1980-07-01
7.8%
14.9%
19.1%
1980-08-01
7.7%
14.7%
18.9%
1980-09-01
7.5%
14.3%
18.0%
1980-10-01
7.5%
14.5%
18.4%
1980-11-01
7.5%
14.4%
18.5%
1980-12-01
7.2%
13.7%
17.6%
1981-01-01
7.5%
14.5%
19.1%
1981-02-01
7.4%
14.6%
19.3%
1981-03-01
7.4%
14.5%
19.2%
1981-04-01
7.2%
14.5%
18.8%
1981-05-01
7.5%
15.1%
19.1%
1981-06-01
7.5%
14.9%
19.8%
1981-07-01
7.2%
14.1%
18.6%
1981-08-01
7.4%
14.5%
18.8%
1981-09-01
7.6%
14.9%
19.7%
1981-10-01
7.9%
15.3%
20.3%
1981-11-01
8.3%
15.9%
21.3%
1981-12-01
8.5%
16.1%
21.1%
1982-01-01
8.6%
16.5%
22.0%
1982-02-01
8.9%
17.0%
22.6%
1982-03-01
9.0%
16.9%
21.8%
1982-04-01
9.3%
17.4%
22.8%
1982-05-01
9.4%
17.3%
22.8%
1982-06-01
9.6%
17.5%
22.9%
1982-07-01
9.8%
18.0%
24.0%
1982-08-01
9.8%
18.1%
23.7%
1982-09-01
10.1%
18.2%
23.6%
1982-10-01
10.4%
18.5%
23.7%
1982-11-01
10.8%
19.0%
24.1%
1982-12-01
10.8%
18.9%
24.1%
1983-01-01
10.4%
18.5%
23.1%
1983-02-01
10.4%
18.4%
22.8%
1983-03-01
10.3%
18.2%
23.5%
1983-04-01
10.2%
18.0%
23.4%
1983-05-01
10.1%
17.7%
22.8%
1983-06-01
10.1%
17.8%
24.0%
1983-07-01
9.4%
16.8%
22.8%
1983-08-01
9.5%
17.3%
22.9%
1983-09-01
9.2%
16.4%
21.7%
1983-10-01
8.8%
16.2%
21.4%
1983-11-01
8.5%
15.4%
20.2%
1983-12-01
8.3%
14.9%
19.9%
1984-01-01
8.0%
14.8%
19.5%
1984-02-01
7.8%
14.3%
19.4%
1984-03-01
7.8%
14.4%
19.8%
1984-04-01
7.7%
14.5%
19.2%
1984-05-01
7.4%
13.6%
18.7%
1984-06-01
7.2%
13.2%
18.2%
1984-07-01
7.5%
13.7%
18.8%
1984-08-01
7.5%
14.1%
18.7%
1984-09-01
7.3%
14.0%
19.2%
1984-10-01
7.4%
13.6%
18.6%
1984-11-01
7.2%
13.2%
17.7%
1984-12-01
7.3%
13.7%
18.8%
1985-01-01
7.3%
13.6%
18.8%
1985-02-01
7.2%
13.6%
18.3%
1985-03-01
7.2%
13.6%
18.2%
1985-04-01
7.3%
13.2%
17.5%
1985-05-01
7.2%
13.6%
18.5%
1985-06-01
7.4%
13.5%
18.5%
1985-07-01
7.4%
14.2%
20.2%
1985-08-01
7.1%
13.3%
17.9%
1985-09-01
7.1%
13.3%
17.9%
1985-10-01
7.1%
14.1%
20.0%
1985-11-01
7.0%
13.5%
18.3%
1985-12-01
7.0%
13.5%
19.1%
1986-01-01
6.7%
13.0%
18.1%
1986-02-01
7.2%
13.6%
18.8%
1986-03-01
7.2%
13.2%
18.2%
1986-04-01
7.1%
13.7%
19.2%
1986-05-01
7.2%
13.7%
18.6%
1986-06-01
7.2%
13.5%
19.2%
1986-07-01
7.0%
13.3%
18.4%
1986-08-01
6.9%
13.1%
18.0%
1986-09-01
7.0%
13.6%
18.4%
1986-10-01
7.0%
13.0%
17.7%
1986-11-01
6.9%
12.8%
18.1%
1986-12-01
6.6%
13.0%
17.5%
1987-01-01
6.6%
13.0%
17.7%
1987-02-01
6.6%
13.1%
18.0%
1987-03-01
6.6%
12.8%
17.9%
1987-04-01
6.3%
12.6%
17.3%
1987-05-01
6.3%
12.5%
17.4%
1987-06-01
6.2%
12.3%
16.5%
1987-07-01
6.1%
11.8%
15.8%
1987-08-01
6.0%
11.7%
15.9%
1987-09-01
5.9%
11.8%
16.2%
1987-10-01
6.0%
11.8%
17.3%
1987-11-01
5.8%
11.5%
16.6%
1987-12-01
5.7%
11.2%
16.0%
1988-01-01
5.7%
11.5%
16.1%
1988-02-01
5.7%
11.3%
15.6%
1988-03-01
5.7%
11.8%
16.6%
1988-04-01
5.4%
11.2%
16.0%
1988-05-01
5.6%
11.3%
15.3%
1988-06-01
5.4%
10.5%
14.2%
1988-07-01
5.4%
10.8%
14.8%
1988-08-01
5.6%
11.0%
15.4%
1988-09-01
5.4%
10.8%
15.5%
1988-10-01
5.4%
10.8%
15.1%
1988-11-01
5.3%
10.5%
13.9%
1988-12-01
5.3%
10.8%
14.8%
1989-01-01
5.4%
11.8%
16.4%
1989-02-01
5.2%
10.6%
15.0%
1989-03-01
5.0%
10.1%
13.9%
1989-04-01
5.2%
10.6%
14.6%
1989-05-01
5.2%
10.4%
14.8%
1989-06-01
5.3%
11.2%
15.7%
1989-07-01
5.2%
10.6%
14.2%
1989-08-01
5.2%
10.9%
14.6%
1989-09-01
5.3%
11.1%
15.2%
1989-10-01
5.3%
11.0%
15.0%
1989-11-01
5.4%
11.3%
15.5%
1989-12-01
5.4%
11.2%
15.3%
1990-01-01
5.4%
10.8%
14.8%
1990-02-01
5.3%
10.7%
15.0%
1990-03-01
5.2%
10.6%
14.3%
1990-04-01
5.4%
11.1%
14.7%
1990-05-01
5.4%
10.8%
15.0%
1990-06-01
5.2%
10.4%
14.3%
1990-07-01
5.5%
10.7%
15.0%
1990-08-01
5.7%
11.5%
16.3%
1990-09-01
5.9%
11.7%
16.4%
1990-10-01
5.9%
11.8%
16.5%
1990-11-01
6.2%
12.0%
17.1%
1990-12-01
6.3%
12.0%
17.4%
1991-01-01
6.4%
12.6%
18.6%
1991-02-01
6.6%
12.8%
17.4%
1991-03-01
6.8%
13.1%
18.3%
1991-04-01
6.7%
12.7%
17.8%
1991-05-01
6.9%
13.6%
18.8%
1991-06-01
6.9%
13.6%
18.5%
1991-07-01
6.8%
13.8%
19.4%
1991-08-01
6.9%
13.5%
18.9%
1991-09-01
6.9%
13.4%
18.8%
1991-10-01
7.0%
13.9%
19.1%
1991-11-01
7.0%
13.8%
19.0%
1991-12-01
7.3%
14.6%
20.3%
1992-01-01
7.3%
13.9%
19.2%
1992-02-01
7.4%
14.2%
20.1%
1992-03-01
7.4%
14.1%
20.3%
1992-04-01
7.4%
13.6%
18.5%
1992-05-01
7.6%
14.4%
20.1%
1992-06-01
7.8%
15.2%
23.0%
1992-07-01
7.7%
14.5%
20.8%
1992-08-01
7.6%
14.2%
19.9%
1992-09-01
7.6%
14.5%
21.0%
1992-10-01
7.3%
13.5%
18.3%
1992-11-01
7.4%
14.3%
20.5%
1992-12-01
7.4%
14.2%
19.8%
1993-01-01
7.3%
14.0%
19.9%
1993-02-01
7.1%
14.1%
19.7%
1993-03-01
7.0%
13.6%
19.7%
1993-04-01
7.1%
13.8%
19.5%
1993-05-01
7.1%
14.2%
19.8%
1993-06-01
7.0%
13.7%
19.9%
1993-07-01
6.9%
13.1%
18.4%
1993-08-01
6.8%
13.0%
18.4%
1993-09-01
6.7%
12.6%
18.2%
1993-10-01
6.8%
13.0%
18.7%
1993-11-01
6.6%
12.9%
18.5%
1993-12-01
6.5%
12.5%
17.9%
1994-01-01
6.6%
13.4%
18.3%
1994-02-01
6.6%
12.9%
18.0%
1994-03-01
6.5%
13.1%
18.0%
1994-04-01
6.4%
13.3%
19.1%
1994-05-01
6.1%
12.5%
18.0%
1994-06-01
6.1%
12.4%
17.6%
1994-07-01
6.1%
12.4%
17.6%
1994-08-01
6.0%
12.5%
17.3%
1994-09-01
5.9%
12.1%
17.5%
1994-10-01
5.8%
12.0%
17.5%
1994-11-01
5.6%
11.4%
15.6%
1994-12-01
5.5%
11.5%
17.0%
1995-01-01
5.6%
11.4%
16.5%
1995-02-01
5.4%
11.7%
17.4%
1995-03-01
5.4%
11.6%
16.1%
1995-04-01
5.8%
12.0%
17.5%
1995-05-01
5.6%
11.9%
17.5%
1995-06-01
5.6%
12.0%
17.1%
1995-07-01
5.7%
12.5%
18.2%
1995-08-01
5.7%
12.5%
17.3%
1995-09-01
5.6%
12.7%
17.6%
1995-10-01
5.5%
12.4%
17.4%
1995-11-01
5.6%
12.0%
17.5%
1995-12-01
5.6%
12.4%
18.0%
1996-01-01
5.6%
12.8%
17.7%
1996-02-01
5.5%
12.2%
16.8%
1996-03-01
5.5%
12.2%
17.1%
1996-04-01
5.6%
12.0%
17.1%
1996-05-01
5.6%
12.2%
16.8%
1996-06-01
5.3%
11.8%
16.2%
1996-07-01
5.5%
12.4%
17.1%
1996-08-01
5.1%
11.6%
16.8%
1996-09-01
5.2%
11.4%
15.6%
1996-10-01
5.2%
11.6%
16.3%
1996-11-01
5.4%
11.9%
16.8%
1996-12-01
5.4%
11.8%
16.6%
1997-01-01
5.3%
12.2%
16.8%
1997-02-01
5.2%
11.8%
17.1%
1997-03-01
5.2%
11.7%
16.4%
1997-04-01
5.1%
11.6%
15.9%
1997-05-01
4.9%
11.1%
16.0%
1997-06-01
5.0%
11.4%
16.8%
1997-07-01
4.9%
11.2%
17.1%
1997-08-01
4.8%
11.1%
16.1%
1997-09-01
4.9%
11.2%
16.1%
1997-10-01
4.7%
11.0%
15.1%
1997-11-01
4.6%
10.8%
14.8%
1997-12-01
4.7%
10.5%
14.0%
1998-01-01
4.6%
10.9%
13.9%
1998-02-01
4.6%
10.6%
14.5%
1998-03-01
4.7%
10.5%
14.8%
1998-04-01
4.3%
9.7%
13.5%
1998-05-01
4.4%
10.3%
14.8%
1998-06-01
4.5%
10.6%
14.9%
1998-07-01
4.5%
10.6%
14.6%
1998-08-01
4.5%
10.8%
14.7%
1998-09-01
4.6%
11.0%
15.0%
1998-10-01
4.5%
10.5%
15.7%
1998-11-01
4.4%
9.8%
14.7%
1998-12-01
4.4%
9.6%
13.5%
1999-01-01
4.3%
10.2%
15.2%
1999-02-01
4.4%
10.1%
13.9%
1999-03-01
4.2%
9.9%
14.2%
1999-04-01
4.3%
10.0%
14.2%
1999-05-01
4.2%
9.6%
13.3%
1999-06-01
4.3%
10.0%
13.9%
1999-07-01
4.3%
9.9%
13.4%
1999-08-01
4.2%
9.6%
13.3%
1999-09-01
4.2%
10.2%
14.8%
1999-10-01
4.1%
10.0%
13.8%
1999-11-01
4.1%
9.9%
13.9%
1999-12-01
4.0%
9.6%
13.4%
2000-01-01
4.0%
9.4%
12.7%
2000-02-01
4.1%
9.9%
13.8%
2000-03-01
4.0%
9.6%
13.3%
2000-04-01
3.8%
9.2%
12.6%
2000-05-01
4.0%
9.8%
12.8%
2000-06-01
4.0%
9.3%
12.3%
2000-07-01
4.0%
9.3%
13.4%
2000-08-01
4.1%
9.3%
14.0%
2000-09-01
3.9%
8.9%
13.0%
2000-10-01
3.9%
8.9%
12.8%
2000-11-01
3.9%
9.1%
13.0%
2000-12-01
3.9%
9.2%
13.2%
2001-01-01
4.2%
9.6%
13.8%
2001-02-01
4.2%
9.6%
13.7%
2001-03-01
4.3%
9.8%
13.8%
2001-04-01
4.4%
10.2%
13.9%
2001-05-01
4.3%
9.9%
13.4%
2001-06-01
4.5%
10.4%
14.2%
2001-07-01
4.6%
10.2%
14.4%
2001-08-01
4.9%
11.2%
15.6%
2001-09-01
5.0%
10.8%
15.2%
2001-10-01
5.3%
11.5%
16.0%
2001-11-01
5.5%
11.6%
15.9%
2001-12-01
5.7%
12.2%
17.0%
2002-01-01
5.7%
12.1%
16.5%
2002-02-01
5.7%
11.8%
16.0%
2002-03-01
5.7%
12.5%
16.6%
2002-04-01
5.9%
12.3%
16.7%
2002-05-01
5.8%
11.6%
16.6%
2002-06-01
5.8%
11.8%
16.7%
2002-07-01
5.8%
12.1%
16.8%
2002-08-01
5.7%
12.0%
17.0%
2002-09-01
5.7%
11.7%
16.3%
2002-10-01
5.7%
11.8%
15.1%
2002-11-01
5.9%
12.1%
17.1%
2002-12-01
6.0%
12.1%
16.9%
2003-01-01
5.8%
12.0%
17.2%
2003-02-01
5.9%
12.1%
17.2%
2003-03-01
5.9%
12.0%
17.8%
2003-04-01
6.0%
12.6%
17.7%
2003-05-01
6.1%
12.9%
17.9%
2003-06-01
6.3%
13.2%
19.0%
2003-07-01
6.2%
13.0%
18.2%
2003-08-01
6.1%
12.3%
16.6%
2003-09-01
6.1%
12.8%
17.6%
2003-10-01
6.0%
12.2%
17.2%
2003-11-01
5.8%
12.1%
15.7%
2003-12-01
5.7%
11.7%
16.2%
2004-01-01
5.7%
12.0%
17.0%
2004-02-01
5.6%
11.7%
16.5%
2004-03-01
5.8%
12.0%
16.8%
2004-04-01
5.6%
11.6%
16.6%
2004-05-01
5.6%
12.1%
17.1%
2004-06-01
5.6%
12.0%
17.0%
2004-07-01
5.5%
12.1%
17.8%
2004-08-01
5.4%
11.5%
16.7%
2004-09-01
5.4%
11.7%
16.6%
2004-10-01
5.5%
12.1%
17.4%
2004-11-01
5.4%
11.5%
16.4%
2004-12-01
5.4%
11.7%
17.6%
2005-01-01
5.3%
11.6%
16.2%
2005-02-01
5.4%
12.4%
17.5%
2005-03-01
5.2%
11.8%
17.1%
2005-04-01
5.2%
11.8%
17.8%
2005-05-01
5.1%
11.7%
17.8%
2005-06-01
5.0%
11.1%
16.3%
2005-07-01
5.0%
10.7%
16.1%
2005-08-01
4.9%
11.1%
16.1%
2005-09-01
5.0%
10.8%
15.5%
2005-10-01
5.0%
10.8%
16.1%
2005-11-01
5.0%
11.1%
17.0%
2005-12-01
4.9%
10.5%
14.9%
2006-01-01
4.7%
10.4%
15.1%
2006-02-01
4.8%
10.8%
15.3%
2006-03-01
4.7%
10.5%
16.1%
2006-04-01
4.7%
10.3%
14.6%
2006-05-01
4.6%
10.0%
14.0%
2006-06-01
4.6%
10.4%
15.8%
2006-07-01
4.7%
10.9%
15.9%
2006-08-01
4.7%
10.7%
16.0%
2006-09-01
4.5%
10.6%
16.3%
2006-10-01
4.4%
10.6%
15.2%
2006-11-01
4.5%
10.6%
14.8%
2006-12-01
4.4%
10.0%
14.6%
2007-01-01
4.6%
10.3%
14.8%
2007-02-01
4.5%
9.9%
14.9%
2007-03-01
4.4%
10.0%
14.9%
2007-04-01
4.5%
10.3%
15.9%
2007-05-01
4.4%
9.9%
15.9%
2007-06-01
4.6%
10.6%
16.3%
2007-07-01
4.7%
10.5%
15.3%
2007-08-01
4.6%
10.7%
15.9%
2007-09-01
4.7%
11.2%
15.9%
2007-10-01
4.7%
10.7%
15.4%
2007-11-01
4.7%
10.8%
16.2%
2007-12-01
5.0%
11.7%
16.8%
2008-01-01
5.0%
11.7%
17.8%
2008-02-01
4.9%
11.4%
16.6%
2008-03-01
5.1%
11.4%
16.1%
2008-04-01
5.0%
11.0%
15.9%
2008-05-01
5.4%
13.0%
19.0%
2008-06-01
5.6%
12.9%
19.2%
2008-07-01
5.8%
13.5%
20.7%
2008-08-01
6.1%
13.1%
18.6%
2008-09-01
6.1%
13.5%
19.1%
2008-10-01
6.5%
13.6%
20.0%
2008-11-01
6.8%
14.0%
20.3%
2008-12-01
7.3%
14.8%
20.5%
2009-01-01
7.8%
15.0%
20.7%
2009-02-01
8.3%
16.0%
22.3%
2009-03-01
8.7%
16.5%
22.2%
2009-04-01
9.0%
16.7%
22.2%
2009-05-01
9.4%
17.6%
23.4%
2009-06-01
9.5%
18.0%
24.7%
2009-07-01
9.5%
17.9%
24.3%
2009-08-01
9.6%
18.1%
25.0%
2009-09-01
9.8%
18.4%
25.9%
2009-10-01
10.0%
19.1%
27.2%
2009-11-01
9.9%
19.2%
26.9%
2009-12-01
9.9%
18.8%
26.7%
2010-01-01
9.8%
18.8%
26.1%
2010-02-01
9.8%
18.7%
25.6%
2010-03-01
9.9%
18.8%
26.2%
2010-04-01
9.9%
19.5%
25.4%
2010-05-01
9.6%
18.1%
26.5%
2010-06-01
9.4%
18.2%
25.9%
2010-07-01
9.4%
18.4%
25.9%
2010-08-01
9.5%
17.7%
25.5%
2010-09-01
9.5%
17.9%
25.8%
2010-10-01
9.4%
18.7%
27.2%
2010-11-01
9.8%
18.5%
24.8%
2010-12-01
9.3%
17.9%
25.3%
2011-01-01
9.2%
18.1%
25.7%
2011-02-01
9.0%
17.7%
24.1%
2011-03-01
9.0%
17.6%
24.4%
2011-04-01
9.1%
17.6%
24.6%
2011-05-01
9.0%
17.3%
23.9%
2011-06-01
9.1%
17.1%
24.6%
2011-07-11
9.0%
17.3%
24.7%
2011-08-20
9.0%
17.4%
25.0%
2011-09-01
9.0%
17.3%
24.4%
2011-10-11
8.8%
16.7%
24.2%
2011-11-20
8.6%
17.1%
24.2%
2011-12-30
8.5%
16.7%
23.3%
2012-01-12
8.3%
16.1%
23.7%
2012-02-12
8.3%
16.5%
23.8%
2012-03-12
8.2%
16.3%
25.0%
2012-04-12
8.2%
16.5%
24.8%
2012-05-12
8.2%
16.1%
24.3%
2012-06-12
8.2%
16.3%
23.4%
2012-07-12
8.2%
16.3%
23.6%
2012-08-12
8.0%
16.7%
24.3%
2012-09-12
7.8%
15.4%
23.7%
2012-10-12
7.8%
16.1%
23.9%
2012-11-12
7.7%
15.9%
24.0%
2012-12-12
7.9%
16.6%
24.1%
2013-01-12
8.0%
16.8%
23.9%
2013-02-12
7.7%
16.2%
25.2%
2013-03-12
7.5%
16.1%
24.1%
2013-04-12
7.6%
16.1%
24.1%
2013-05-12
7.5%
16.2%
24.2%
2013-06-12
7.5%
16.1%
23.3%
2013-07-12
7.3%
15.5%
23.2%
2013-08-12
7.2%
15.5%
22.5%
2013-09-12
7.2%
15.0%
21.1%
2013-10-12
7.2%
15.0%
22.2%
2013-11-12
7.0%
14.2%
20.9%
2013-12-12
6.7%
13.5%
20.4%
2014-01-12
6.6%
14.3%
20.8%
2014-02-12
6.7%
14.3%
21.3%
2014-03-12
6.6%
14.5%
20.9%
2014-04-12
6.2%
12.8%
19.1%
2014-05-12
6.3%
13.2%
19.2%
2014-06-12
6.1%
13.3%
20.7%
2014-07-12
6.2%
13.6%
20.0%
2014-08-12
6.1%
13.0%
19.4%
2014-09-12
5.9%
13.7%
19.8%
2014-10-12
5.7%
12.7%
18.7%
2014-11-12
5.8%
12.7%
17.5%
2014-12-12
5.6%
12.4%
16.8%
2015-01-12
5.7%
12.2%
18.8%
2015-02-12
5.5%
11.9%
17.1%
2015-03-12
5.5%
12.3%
17.5%
2015-04-12
5.4%
11.6%
17.1%
New Research Does Not Provide Any Reason to Doubt that CEO Pay Fueled Top 1% Income Growth
A new paper, Firming up Inequality, has been receiving substantial attention in the media for its claim that wage inequality is not occurring within firms but only occurs between firms. The authors claim that their results disprove the claim made by me and others, such as Thomas Piketty and Emmanuel Saez, that the growth of top 1 percent incomes was driven by the pay of executives and those in the financial sector. Though the authors present valuable new data, which offers the possibility of great insights, their current analysis does not disprove that executive pay has fueled top 1 percent income growth. In fact, the study neither examines nor rebuts claims about executive pay.
The authors also offer a “we live in the best possible world” interpretation of their findings—inequality is due to high productivity growth of “superfirms.” This is pure speculation and is completely disconnected from their actual empirical work. A similar study examined productivity trends and contradicts their narrative about superfirms.
Last, there are reasons to be skeptical of their findings because they imply huge wage disparities have opened up between median workers across firms within an industry that are implausible.
1. The paper neither examines nor rebuts the claim that executive pay was a major factor in the doubling of the income share of the top 1 percent.
The paper characterizes itself as a critique of the findings that executive pay (and financial sector pay) has fueled the growth of top 1 percent incomes, citing my work with Natalie Sabadish, as well as Piketty’s:
In the absence of comprehensive evidence on wages paid by firms, it is frequently asserted that inequality within the firm is a driving force leading to an increase in overall inequality. For example, according to Mishel and Sabadish (2014), “a key driver of wage inequality is the growth of chief executive officer earnings and compensation.” Piketty (2013) (p. 315) agrees, noting that “the primary reason for increased income inequality in recent decades is the rise of the supermanager.”
Strong Wage Growth Would Complement the Safety Net in Reducing Poverty
Last week, we published Broad-Based Wage Growth Is a Key Tool in the Fight Against Poverty, which argued that our fight against poverty over the last few decades has been missing a key element: strong wage growth for the majority of workers. To substantiate this claim, we simulated the impacts on poverty rates in a few scenarios in which wages grew across the board according to different benchmarks (e.g., average wage growth, productivity, and productivity and full employment).
Judging by a recent blog post, Matt Bruenig seems unimpressed. He spends a large part of the first part of his post suggesting that efforts to boost market incomes (i.e., wages) will necessarily fall short because the majority of those who are in poverty (namely, the elderly, children, the disabled, and caregivers) do not work. He ends by assessing the result of our simulation as uninspiring largely because the “employable” poor make up only a minority of those in poverty. Given the alleged ineffectiveness of wage-growth, he calls for increased transfers to fight poverty.
We think Bruenig overlooks two key aspects of the role of wages in reducing overall poverty. First, we believe he ignores the extent to which children would benefit from the spillover of increased wages for their parents. Second, he ignores the fact that people move in and out of poverty—by raising the income floor for many families, broad-based wage growth plays an important role in preventing more of them from falling under the poverty line.
Yes, Trade Deficits Do Indeed Matter for Jobs
The issue of currency management by U.S. trading partners that increases U.S. trade deficits has become a front-burner issue in debates over the proposed Trans-Pacific Partnership (TPP). The discussion about whether or not trade deficits can really affect U.S. employment, however, occasionally gets very muddled. Here’s a quick attempt to un-muddle a couple different issues.
Trade deficits and overall employment
Trade deficits occurring when the U.S. economy is stuck below full employment and at the zero lower bound (ZLB) on short-term interest rates are a drag on economic growth and overall employment, period. And this describes the U.S. economy today, so a reduction in the trade deficit in the next couple of years spurred by a reversal of trading partners’ currency management would boost growth and jobs.
The logic is simple—exports boost demand for U.S. output while imports reduce demand for U.S. output. When net exports (exports minus imports) fall, then aggregate demand is reduced. Trade deficits are the mirror image of capital inflows into the U.S. economy, and there are times when these capital inflows can reduce domestic interest rates and boost economic activity, providing an offset to the demand-drag caused by trade flows. Today is not one of those times—further downward pressure on already rock-bottom interest rates (particularly since most of these inflows go into U.S. Treasuries) do very little to boost domestic investment to counteract the demand drag from trade flows.
Millennials Aren’t Lazy: Millennials Aren’t Working Because the Economy Isn’t Either
‘Tis the season to be a graduate and members of the class of 2015 may be wondering: what are my chances in this job market?
The class of 2015 is entering an economy still in recovery from the Great Recession. Job prospects for the class of 2015 are better than for the several classes that graduated before them, but young graduates today still face many economic challenges, including stagnant wages and high levels of unemployment and underemployment. The class of 2015 joins the six classes before it in graduating into an acutely weak labor market and competing with more experienced workers for a limited amount of job opportunities.
Although unemployment rates of young graduates have come down in recent years after skyrocketing during the Great Recession, they still remain elevated compared to where they were before the recession began. Underemployment rates for the class of 2015 also remain high. This means that many young graduates either want a job but have recently given up looking for work, or have a job that does not provide the hours they need.
Among young college graduates who are employed, many are working in a job that does not require a college degree at all. This is another sign of continued slack in the labor market, and a sign that young graduates’ high unemployment is not because they lack the right skills, but because of a continued lack of economy-wide demand for workers.
Head Start’s 50th Anniversary
This week marks the 50th anniversary of Head Start, a Great Society program that despite spotty funding has brightened the lives of millions of preschoolers. My daughter is one of them.
Like three-quarters of the public schools here in Washington DC, my daughter’s school is a Title I school, where 40 percent or more of the students are from low-income families. Her pre-K program is funded in part by Head Start, even though my daughter and some of her classmates don’t qualify as low income. As it happens, my daughter’s school, HD Cooke Elementary, helped pioneer the Head Start program in 1965 (see cute picture below).
DC has a cutting-edge universal pre-K program and also participates in a pilot program where all kids eat free thanks to a U.S. Department of Agriculture grant. So my daughter not only started attending a great public school at age 3, but eats two nutritious meals a day with her buddies, starting with a meet-and-greet breakfast, the social highlight of her day (and often mine).
DC is somewhat atypical in that there has been an influx of upper-income taxpayers, yet the school system still serves a heavily low-income student body. DC public schools were “majority-minority” before this was true for the United States as a whole.
The growing tax base helped pay to retrofit my daughter’s school to add more natural lighting, a beautiful library and gym, and great playgrounds. In 2010, the school, built in 1909 with an extension dating to 1960, became the first school in DC and one of the oldest in the country to be certified green. Projects like these show how infrastructure and human capital investment can combine with job creation and energy efficiency—a win-win-win unless your name is Koch.
Don’t Blame the Poor for the Faults of Our Economy
When assigning blame for our nation’s persistent poverty problem, many policymakers tend to focus on underlying demographics or behavior of the poor—factors like racial background or the rise of single parent households, instead of the stark economic reality the poorest Americans have to contend with. While demographics and individual behavior have a place in the policy discussion, growing inequality is the primary reason the poverty rate has remained elevated over the last several decades.
The chart below breaks down the poverty rate and shows how demographic and economic factors affected the poverty rate between 1979 and 2013. Since 1979, increasing inequality has been the largest poverty-boosting factor, outweighing racial identity and family structure and completely eclipsing the effects of overall economic growth and educational attainment in driving down the poverty rate. Despite our growing economy and the fact that poor workers are now more educated than ever, rising inequality has worked to keep low-income people in poverty. This increase in inequality was driven by stagnating wages for low- and middle-income households (for example, 10th percentile real wages were actually lower in 2013 than they were in 1979).
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement microdata based on Danziger and Gottschalk (1995)Impact on poverty rate of economic, demographic, and education changes, 1979–2013
Factor
Effect
Inequality
7.1
Growth
-3.4
Education
-2.9
Family structure
1.6
Race
1.1
Interaction
-0.5
