Top five Valentine’s Day gifts ideas for U.S. workers: Nothing spells ‘romance’ like a fair wage and quality jobs

That’s why we decided to sum up what we think are the top five Valentine’s Day gifts ideas for working people across the country.

Power through collective action!

Our economy is out of balance. Corporations and CEOs hold too much power and wealth, and working people know it. Workers are mobilizing, organizing, protesting, and striking at a level not seen in decades, and they are winning pay raises and other real change by using their collective voices.

But, the fact is, it is still too difficult for working people to form a union at their workplace when they want to. The law gives employers too much power and puts too many roadblocks in the way of workers trying to organize a union. The Protecting the Right to Organize (PRO) Act will go a long way toward restoring workers’ right to join together to bargain for better wages and working conditions by streamlining the process when workers form a union, ensuring that they are successful in negotiating a first agreement, and holding employers accountable when they violate labor law. The U.S. Senate should join the House of Representatives and pass the PRO Act in order to restore power to working people.

Affording bread…and roses

The real (inflation-adjusted) minimum wage is now roughly 30 percent lower than it was in 1968, and it has been more than 10 years since congress raised the minimum wage—the longest stretch in history. To end this shameful streak, it is incumbent upon the Senate to take up and pass the Raise the Wage Act immediately. Raising the federal minimum wage to $15 by 2025 would lift wages for 33.5 million workers across the country—more than one-fifth of the wage-earning workforce. The increase would boost total annual wages for these low-wage workers by $92.5 billion, lifting annual earnings for the average affected year-round worker by $2,800. Recent survey data have shown that 74% of U.S. workers live paycheck to paycheck. Policymakers should give working people the ability to make ends meet—but also the ability to treat themselves occasionally.

Failure to raise the federal minimum wage has taken thousands of dollars out of the pockets of minimum wage workers: The real value of the minimum wage (adjusted for inflation) is 17% less than 10 years ago and 31% less than in 1968

Failure to raise the federal minimum wage has taken thousands of dollars out of the pockets of minimum wage workers: The real value of the minimum wage (adjusted for inflation) is 17% less than 10 years ago and 31% less than in 1968

Note: All values are in June 2019 dollars, adjusted using the CPI-U-RS.

Source: Adapted from Figure C in David Cooper, Elise Gould, and Ben Zipperer, Low-Wage Workers Are Suffering from a Decline in the Real Value of the Federal Minimum Wage, Economic Policy Institute, August 2019).

Source: Adapted from Figure C in David Cooper, Elise Gould, and Ben Zipperer, Low-Wage Workers Are Suffering from a Decline in the Real Value of the Federal Minimum Wage, Economic Policy Institute, August 2019). The figure reflects EPI analysis of historical minimum wage data in the Fair Labor Standards Act and amendments.

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Pay workers for their hours worked, or give them their time back

The U.S. Department of Labor announced in September its final overtime rule, which will set the salary threshold under which salaried workers are automatically entitled to overtime pay to $35,568 a year. The rule leaves behind millions of workers who would have received overtime protections under the much stronger rule, published in 2016, that Trump administration chose to abandon. A stronger overtime protection would pay more workers for working more than 40 hours a week, or allow them extra time with their families.

Seven states have already taken steps to raise the overtime threshold, but without further action, it’s estimated that 8.2 million workers who would have benefited from the 2016 rule will be left behind by the Trump administration’s rule, including 3.2 million workers who would have gotten new overtime protections under the 2016 rule and 5.0 million who would have gotten strengthened overtime protections under the 2016 rule. States should follow suit and extend the overtime protections so workers don’t continue to lose out on their hard-earned wages.

Let your workers move on

At least 36 million workers—27.8% of the private-sector workforce—are required to enter noncompete agreements. Noncompete agreements are employment provisions that ban workers at one company from going to work for, or starting, a competing business within a certain period of time after leaving a job. Establishments with high pay or high levels of education among workers are more likely to use noncompetes, but noncompetes agreements are also common in workplaces with low pay and low levels of education. More than a quarter (29.0%) of private-sector workers with an average hourly wage below $13.00 require noncompetes for all their workers. Noncompetes are part of a disturbing trend of employers requiring workers to sign away their rights. Noncompetes may be contributing to weak wage growth, given that changing jobs is how workers often get a raise. And given that noncompetes limit the ability of individuals to start businesses or take other jobs, it also is not difficult to see that noncompetes may be contributing to the declines in dynamism in the U.S. labor market. Congress should pass the bipartisan legislationthe Workforce Mobility Act of 2019to prohibit noncompete agreements.

Labor protections for Uber drivers shuttling around Valentine’s couples

The General Counsel of the National Labor Relations Board recently released a memo claiming that Uber drivers are independent contractors, not employees of Uber. The reality is that these drivers have very little entrepreneurial freedom: Drivers can’t raise revenues because they can’t control prices or expand their customer base through marketing. Unlike a typical enterprise, Uber drivers do not build earnings as they get more experience. Uber drivers are not able to choose their customers—drivers are penalized for rejecting or not accepting trips. And after accounting for Uber’s commissions and fees and vehicle expenses, and taking into account the cost of a modest package of health insurance and other benefits equivalent to those earned by W-2 workers, Uber drivers earn the equivalent of $9.21 in hourly wages—less than what is earned by 90% of all other wage and salary earners, and below the minimum wage in 13 of the 20 major urban markets where Uber operates.

Recently, AB5 went into effect in California, a set of protections aimed at combatting the misclassification of workers as independent contractors, helping ensure that California’s employees have access to basic labor and employment protections denied to independent contractors including: minimum wage and overtime protections, paid sick days and family leave, workers’ compensation benefits, and unemployment insurance benefits. Policymakers across the country should take notice and provide similar protections to workers in their states.

 

AAPI women face a double pay penalty for race and gender

Asian American/Pacific Islander (AAPI) Equal Pay Day is February 11. It marks the number of days into 2020 that AAPI women have to work to make the same amount as their white male counterparts were paid in 2019. Put another way, the average AAPI woman needs to work almost an extra month and a half to make up for the shortfall in annual earnings relative to the average non-Hispanic white man.

The infographic below takes a closer look at the data to debunk commonly held myths about the AAPI women’s pay gap. Specifically, all AAPI women do not face a relatively small pay gap—Asian American women are paid 93 cents on the dollar, while Hawaiian/Pacific Islander women are paid only 68 cents.

Further, Asian American women can’t just educate their way out of the pay gap. Asian American women have higher levels of education than white men, and when comparing wages of workers with the same level of education, the disparities are much larger. Asian American women with a bachelor’s degree only are paid 22% less than their white male counterparts and those with an advanced degree are paid 14% less.

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Declining trade balances disguise continued growth in the non-oil trade deficit

The overall goods and services trade deficit declined 1.7% ($10.9 billion) in 2019, while the total deficit in goods trade fell 2.4% ($21.4 billion). However, the U.S. trade deficit in non-oil goods, which is dominated by trade in manufactured products, increased 1.8% in 2019. Aside from petroleum, trade was a net drag on the economy in 2019 and on manufacturing, in particular.

The small decline in overall U.S. trade deficits follows an 18.3% increase in the goods trade deficit in the first two years of the Trump administration. Taken altogether, the U.S. goods trade deficit increased $116.2 billion (15.5%) in the first three years of the Trump Administration. It has proven neither quick nor easy to reduce the growing U.S. goods trade deficit.

The petroleum products deficit decreased 72.6% in 2019, masking the 1.8% increase in the non-oil goods trade deficit within the overall 2.4% decline in the U.S. goods trade balance. The fracking revolution has resulted in a significant reduction in oil imports (13.9%) and a small increase in petroleum exports (2.8%).

Recent changes in petroleum trade yield this shocking factoid: The United States became a net exporter of petroleum products for the last four months of 2019. This reflects a key element of Trump’s trade “strategy” to export liquefied natural gas (LNG) to the rest of the world, which comes at a steep cost. This will drive up U.S. prices for natural gas and oil, despite the fact that low energy prices were a key element of the mini-recovery in US manufacturing exports. Increased LNG exports will hurt U.S. consumers by increasing fuel costs, heightening risks of transport and catastrophic port explosions, and exacerbating global warming and air pollution levels in the country as a whole.

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What to watch on jobs day: Large downward revisions in employment expected

On Friday, the Bureau of Labor Statistics (BLS) will revise nonfarm payroll employment, hours, and earnings data to reflect the annual benchmark process in the establishment survey. Each year, the BLS benchmarks total nonfarm payroll employment to state unemployment insurance tax records. In August 2019, BLS released preliminary benchmark revisions to payroll employment for April 2018 through March 2019, but revisions don’t get officially incorporated into the historical numbers until the final revisions are released. While revisions in most years tend to be relatively small, this year’s preliminary revisions came in much higher. The preliminary estimate of the benchmark revision indicates a downward adjustment to March 2019 total nonfarm employment of -501,000. This means that between April 2018 and March of 2019, there were a half million fewer jobs created than initially reported. Over the last ten years, preliminary revisions averaged about -92,000, so -501,000 is very large in comparison. And, usually the difference between the preliminary revisions and the final revisions is plus or minus 40,000. Therefore, it’s likely tomorrow’s final revisions will also be around 500,000 fewer jobs in that period.

The revisions will also provide details on changes in the initial payroll employment estimates by sector. For instance, in the preliminary release, the revisions were located primarily in “leisure and hospitality”, “professional and business services”, and “retail trade” with downward revisions of -175,000, -163,000, and -146,400, respectively. On Friday, the historical data will reflect the final benchmarks overall and by sector.

Tracking trends in nominal wage growth

Turning to nominal wage growth, the most important economic indicator to watch in 2020, last month there was a large drop for production/nonsupervisory workers. The figure below charts year-over-year changes in private-sector nominal average hourly earnings for “all nonfarm employees” as well as “production/nonsupervisory workers.” After remaining consistently higher than “all nonfarm” for nearly a year and at or above 3.4% for much of that time, it fell to 3.0% in December, its lowest point since September 2018. This begs the question of whether this is simply a blip and production/nonsupervisory workers will continue to pull away or if the separation in growth rates between the two over the last year was mostly statistical noise.

At this point in the recovery—with unemployment at or below 4.0% for 22 months—wage growth remains lower than expected. As employment growth consistently remains higher than working-age population growth, more and more workers are pulled into the labor force and finding jobs. As this slack gets absorbed, workers should be getting scarcer and scarcer. Therefore, employers would typically have to pay more to attract and retain the workers they want. After increasing in 2018, wage growth for all nonfarm employees has slowed for much of 2019 and remains below target levels.

Nominal Wage Tracker

Nominal wage growth has been far below target in the recovery: Year-over-year change in private-sector nominal average hourly earnings, 2007–2019

Date All nonfarm employees Production/nonsupervisory workers
Mar-2007 3.44% 4.11%
Apr-2007 3.08% 3.79%
May-2007 3.48% 4.14%
Jun-2007 3.56% 4.19%
Jul-2007 3.25% 4.05%
Aug-2007 3.35% 3.98%
Sep-2007 3.14% 4.09%
Oct-2007 3.08% 3.78%
Nov-2007 3.07% 3.83%
Dec-2007 2.97% 3.81%
Jan-2008 2.91% 3.80%
Feb-2008 2.80% 3.79%
Mar-2008 3.04% 3.83%
Apr-2008 2.84% 3.76%
May-2008 3.07% 3.69%
Jun-2008 2.77% 3.56%
Jul-2008 3.05% 3.67%
Aug-2008 3.33% 3.89%
Sep-2008 3.23% 3.64%
Oct-2008 3.27% 3.81%
Nov-2008 3.60% 3.91%
Dec-2008 3.59% 3.90%
Jan-2009 3.63% 3.72%
Feb-2009 3.43% 3.65%
Mar-2009 3.28% 3.47%
Apr-2009 3.42% 3.35%
May-2009 2.93% 3.06%
Jun-2009 2.83% 2.88%
Jul-2009 2.69% 2.71%
Aug-2009 2.44% 2.70%
Sep-2009 2.44% 2.75%
Oct-2009 2.53% 2.68%
Nov-2009 2.19% 2.67%
Dec-2009 1.91% 2.50%
Jan-2010 2.05% 2.66%
Feb-2010 2.09% 2.55%
Mar-2010 1.81% 2.27%
Apr-2010 1.76% 2.38%
May-2010 1.90% 2.59%
Jun-2010 1.76% 2.53%
Jul-2010 1.85% 2.42%
Aug-2010 1.75% 2.36%
Sep-2010 1.84% 2.19%
Oct-2010 1.93% 2.45%
Nov-2010 1.65% 2.13%
Dec-2010 1.79% 2.02%
Jan-2011 1.92% 2.28%
Feb-2011 1.87% 2.06%
Mar-2011 1.87% 2.06%
Apr-2011 1.91% 2.16%
May-2011 2.04% 2.10%
Jun-2011 2.13% 2.05%
Jul-2011 2.30% 2.26%
Aug-2011 1.99% 1.94%
Sep-2011 1.94% 1.99%
Oct-2011 2.07% 1.88%
Nov-2011 2.02% 1.82%
Dec-2011 1.98% 1.77%
Jan-2012 1.71% 1.35%
Feb-2012 1.79% 1.45%
Mar-2012 2.10% 1.76%
Apr-2012 2.09% 1.65%
May-2012 1.78% 1.39%
Jun-2012 2.00% 1.54%
Jul-2012 1.77% 1.44%
Aug-2012 1.86% 1.33%
Sep-2012 2.03% 1.54%
Oct-2012 1.51% 1.18%
Nov-2012 1.90% 1.43%
Dec-2012 2.24% 1.69%
Jan-2013 2.24% 1.84%
Feb-2013 2.15% 2.04%
Mar-2013 1.93% 1.88%
Apr-2013 2.05% 1.83%
May-2013 2.14% 1.93%
Jun-2013 2.13% 2.03%
Jul-2013 2.00% 1.97%
Aug-2013 2.26% 2.23%
Sep-2013 2.04% 2.22%
Oct-2013 2.25% 2.32%
Nov-2013 2.24% 2.37%
Dec-2013 1.85% 2.21%
Jan-2014 1.89% 2.31%
Feb-2014 2.27% 2.55%
Mar-2014 2.10% 2.30%
Apr-2014 1.93% 2.29%
May-2014 2.09% 2.44%
Jun-2014 1.96% 2.24%
Jul-2014 2.04% 2.33%
Aug-2014 2.16% 2.43%
Sep-2014 2.08% 2.22%
Oct-2014 2.03% 2.27%
Nov-2014 2.03% 2.22%
Dec-2014 1.99% 1.92%
Jan-2015 2.19% 2.01%
Feb-2015 1.93% 1.66%
Mar-2015 2.22% 1.95%
Apr-2015 2.26% 2.00%
May-2015 2.34% 2.14%
Jun-2015 2.25% 2.14%
Jul-2015 2.17% 2.04%
Aug-2015 2.20% 1.98%
Sep-2015 2.28% 2.08%
Oct-2015 2.52% 2.37%
Nov-2015 2.43% 2.12%
Dec-2015 2.47% 2.51%
Jan-2016 2.55% 2.40%
Feb-2016 2.42% 2.50%
Mar-2016 2.45% 2.49%
Apr-2016 2.61% 2.58%
May-2016 2.40% 2.33%
Jun-2016 2.60% 2.48%
Jul-2016 2.76% 2.62%
Aug-2016 2.55% 2.51%
Sep-2016 2.63% 2.46%
Oct-2016 2.66% 2.41%
Nov-2016 2.61% 2.50%
Dec-2016 2.65% 2.50%
Jan-2017 2.40% 2.39%
Feb-2017 2.72% 2.34%
Mar-2017 2.55% 2.29%
Apr-2017 2.47% 2.24%
May-2017 2.54% 2.33%
Jun-2017 2.50% 2.32%
Jul-2017 2.57% 2.32%
Aug-2017 2.57% 2.31%
Sep-2017 2.83% 2.59%
Oct-2017 2.32% 2.16%
Nov-2017 2.47% 2.35%
Dec-2017 2.74% 2.48%
Jan-2018 2.81% 2.47%
Feb-2018 2.57% 2.47%
Mar-2018 2.80% 2.74%
Apr-2018 2.79% 2.78%
May-2018 2.94% 2.91%
Jun-2018 2.93% 2.91%
Jul-2018 2.85% 2.85%
Aug-2018 3.18% 3.12%
Sep-2018 2.98% 3.02%
Oct-2018 3.32% 3.25%
Nov-2018 3.31% 3.37%
Dec-2018 3.34% 3.50%
Jan-2019 3.18% 3.35%
Feb-2019 3.40% 3.44%
Mar-2019 3.24% 3.38%
Apr-2019 3.16% 3.33%
May-2019 3.08% 3.36%
Jun-2019 3.18% 3.35%
Jul-2019 3.25% 3.52%
Aug-2019 3.23% 3.51%
Sep-2019 3.00% 3.54%
Oct-2019 3.11% 3.62%
Nov-2019 3.14% 3.39%
Dec-2019 2.87% 3.03%
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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

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On Friday, the BLS will also be employing new population controls in the Current Population Survey (CPS) starting in January 2020. Unlike the establishment survey, these changes to the CPS are not updated historically so caution should be exercised when making comparisons with data for December 2019 or earlier periods. The BLS is also making some changes to their methodology in terms of providing new seasonally adjusted series for measures of labor market underutilization as well as beginning to include both those in opposite-sex and same-sex marriages in estimates of married persons.

The new benchmarks to the establishment survey as well as revisions to the household survey will provide much fodder for thought on Friday morning. And, wage growth continues to be the most important indicator to watch as it lags behind overall improvements in the labor market.

Trump’s ‘blue-collar boom’ is likely a dud

In his State of the Union address tonight, President Trump plans to extol the “blue-collar boom” in the economy along with his purported “great American comeback.” He’ll claim this based on two recent signature trade deals—the United States-Mexico-Canada Agreement (USMCA) and a “phase one” deal with China. Unfortunately, both agreements will likely to lead to more outsourcing and job loss for U.S. workers, and the facts just don’t support Trump’s claims about the broader economy.

Trump comes from a world that has ardently championed globalization, like many of his predecessors. However, that approach has decimated U.S. manufacturing over the past 20 years, eliminating nearly 5 million good factory jobs as shown in Figure A, below. Nearly 90,000 U.S. factories have been lost as well.

Figure A

U.S. manufacturing employment, January 1970–December 2019 (millions of jobs)

Date Manufacturing employment (millions of jobs)
1970-01-01 18.424
1970-02-01 18.361
1970-03-01 18.36
1970-04-01 18.207
1970-05-01 18.029
1970-06-01 17.93
1970-07-01 17.877
1970-08-01 17.779
1970-09-01 17.692
1970-10-01 17.173
1970-11-01 17.024
1970-12-01 17.309
1971-01-01 17.28
1971-02-01 17.216
1971-03-01 17.154
1971-04-01 17.149
1971-05-01 17.225
1971-06-01 17.139
1971-07-01 17.126
1971-08-01 17.115
1971-09-01 17.154
1971-10-01 17.126
1971-11-01 17.166
1971-12-01 17.202
1972-01-01 17.283
1972-02-01 17.361
1972-03-01 17.447
1972-04-01 17.508
1972-05-01 17.602
1972-06-01 17.641
1972-07-01 17.556
1972-08-01 17.741
1972-09-01 17.774
1972-10-01 17.893
1972-11-01 18.005
1972-12-01 18.158
1973-01-01 18.276
1973-02-01 18.41
1973-03-01 18.493
1973-04-01 18.53
1973-05-01 18.564
1973-06-01 18.606
1973-07-01 18.598
1973-08-01 18.629
1973-09-01 18.609
1973-10-01 18.702
1973-11-01 18.773
1973-12-01 18.82
1974-01-01 18.788
1974-02-01 18.727
1974-03-01 18.7
1974-04-01 18.702
1974-05-01 18.688
1974-06-01 18.69
1974-07-01 18.656
1974-08-01 18.57
1974-09-01 18.492
1974-10-01 18.364
1974-11-01 18.077
1974-12-01 17.693
1975-01-01 17.344
1975-02-01 17.004
1975-03-01 16.853
1975-04-01 16.759
1975-05-01 16.746
1975-06-01 16.69
1975-07-01 16.678
1975-08-01 16.824
1975-09-01 16.904
1975-10-01 16.984
1975-11-01 17.025
1975-12-01 17.14
1976-01-01 17.287
1976-02-01 17.384
1976-03-01 17.47
1976-04-01 17.541
1976-05-01 17.513
1976-06-01 17.521
1976-07-01 17.524
1976-08-01 17.596
1976-09-01 17.665
1976-10-01 17.548
1976-11-01 17.682
1976-12-01 17.719
1977-01-01 17.803
1977-02-01 17.843
1977-03-01 17.941
1977-04-01 18.024
1977-05-01 18.107
1977-06-01 18.192
1977-07-01 18.259
1977-08-01 18.276
1977-09-01 18.334
1977-10-01 18.356
1977-11-01 18.419
1977-12-01 18.531
1978-01-01 18.593
1978-02-01 18.639
1978-03-01 18.699
1978-04-01 18.772
1978-05-01 18.848
1978-06-01 18.919
1978-07-01 18.951
1978-08-01 19.006
1978-09-01 19.068
1978-10-01 19.142
1978-11-01 19.257
1978-12-01 19.334
1979-01-01 19.388
1979-02-01 19.409
1979-03-01 19.453
1979-04-01 19.45
1979-05-01 19.509
1979-06-01 19.553
1979-07-01 19.531
1979-08-01 19.406
1979-09-01 19.442
1979-10-01 19.39
1979-11-01 19.299
1979-12-01 19.301
1980-01-01 19.282
1980-02-01 19.219
1980-03-01 19.217
1980-04-01 18.973
1980-05-01 18.726
1980-06-01 18.49
1980-07-01 18.276
1980-08-01 18.414
1980-09-01 18.445
1980-10-01 18.506
1980-11-01 18.601
1980-12-01 18.64
1981-01-01 18.639
1981-02-01 18.613
1981-03-01 18.647
1981-04-01 18.711
1981-05-01 18.766
1981-06-01 18.789
1981-07-01 18.785
1981-08-01 18.748
1981-09-01 18.712
1981-10-01 18.566
1981-11-01 18.409
1981-12-01 18.223
1982-01-01 18.047
1982-02-01 17.981
1982-03-01 17.857
1982-04-01 17.683
1982-05-01 17.588
1982-06-01 17.43
1982-07-01 17.278
1982-08-01 17.16
1982-09-01 17.074
1982-10-01 16.853
1982-11-01 16.722
1982-12-01 16.69
1983-01-01 16.705
1983-02-01 16.706
1983-03-01 16.711
1983-04-01 16.794
1983-05-01 16.885
1983-06-01 16.96
1983-07-01 17.059
1983-08-01 17.118
1983-09-01 17.255
1983-10-01 17.367
1983-11-01 17.479
1983-12-01 17.551
1984-01-01 17.63
1984-02-01 17.728
1984-03-01 17.806
1984-04-01 17.872
1984-05-01 17.916
1984-06-01 17.967
1984-07-01 18.013
1984-08-01 18.034
1984-09-01 18.019
1984-10-01 18.024
1984-11-01 18.016
1984-12-01 18.023
1985-01-01 18.009
1985-02-01 17.966
1985-03-01 17.939
1985-04-01 17.886
1985-05-01 17.855
1985-06-01 17.819
1985-07-01 17.776
1985-08-01 17.756
1985-09-01 17.718
1985-10-01 17.708
1985-11-01 17.697
1985-12-01 17.693
1986-01-01 17.686
1986-02-01 17.663
1986-03-01 17.624
1986-04-01 17.616
1986-05-01 17.593
1986-06-01 17.53
1986-07-01 17.497
1986-08-01 17.489
1986-09-01 17.498
1986-10-01 17.477
1986-11-01 17.472
1986-12-01 17.478
1987-01-01 17.465
1987-02-01 17.499
1987-03-01 17.507
1987-04-01 17.525
1987-05-01 17.542
1987-06-01 17.537
1987-07-01 17.593
1987-08-01 17.63
1987-09-01 17.691
1987-10-01 17.729
1987-11-01 17.775
1987-12-01 17.809
1988-01-01 17.79
1988-02-01 17.823
1988-03-01 17.844
1988-04-01 17.874
1988-05-01 17.892
1988-06-01 17.916
1988-07-01 17.926
1988-08-01 17.891
1988-09-01 17.914
1988-10-01 17.966
1988-11-01 18.003
1988-12-01 18.025
1989-01-01 18.057
1989-02-01 18.055
1989-03-01 18.06
1989-04-01 18.055
1989-05-01 18.04
1989-06-01 18.013
1989-07-01 17.98
1989-08-01 17.964
1989-09-01 17.922
1989-10-01 17.895
1989-11-01 17.886
1989-12-01 17.881
1990-01-01 17.797
1990-02-01 17.893
1990-03-01 17.868
1990-04-01 17.845
1990-05-01 17.797
1990-06-01 17.776
1990-07-01 17.704
1990-08-01 17.649
1990-09-01 17.609
1990-10-01 17.577
1990-11-01 17.428
1990-12-01 17.395
1991-01-01 17.33
1991-02-01 17.211
1991-03-01 17.14
1991-04-01 17.093
1991-05-01 17.07
1991-06-01 17.044
1991-07-01 17.015
1991-08-01 17.025
1991-09-01 17.01
1991-10-01 16.999
1991-11-01 16.961
1991-12-01 16.916
1992-01-01 16.839
1992-02-01 16.829
1992-03-01 16.805
1992-04-01 16.831
1992-05-01 16.835
1992-06-01 16.826
1992-07-01 16.819
1992-08-01 16.783
1992-09-01 16.761
1992-10-01 16.751
1992-11-01 16.758
1992-12-01 16.769
1993-01-01 16.791
1993-02-01 16.805
1993-03-01 16.795
1993-04-01 16.772
1993-05-01 16.766
1993-06-01 16.742
1993-07-01 16.739
1993-08-01 16.741
1993-09-01 16.769
1993-10-01 16.778
1993-11-01 16.8
1993-12-01 16.815
1994-01-01 16.855
1994-02-01 16.862
1994-03-01 16.897
1994-04-01 16.933
1994-05-01 16.962
1994-06-01 17.01
1994-07-01 17.026
1994-08-01 17.081
1994-09-01 17.115
1994-10-01 17.144
1994-11-01 17.186
1994-12-01 17.217
1995-01-01 17.262
1995-02-01 17.265
1995-03-01 17.263
1995-04-01 17.278
1995-05-01 17.259
1995-06-01 17.247
1995-07-01 17.218
1995-08-01 17.24
1995-09-01 17.247
1995-10-01 17.216
1995-11-01 17.209
1995-12-01 17.231
1996-01-01 17.208
1996-02-01 17.229
1996-03-01 17.193
1996-04-01 17.204
1996-05-01 17.222
1996-06-01 17.226
1996-07-01 17.223
1996-08-01 17.255
1996-09-01 17.252
1996-10-01 17.268
1996-11-01 17.277
1996-12-01 17.284
1997-01-01 17.297
1997-02-01 17.316
1997-03-01 17.34
1997-04-01 17.349
1997-05-01 17.362
1997-06-01 17.387
1997-07-01 17.389
1997-08-01 17.452
1997-09-01 17.465
1997-10-01 17.513
1997-11-01 17.556
1997-12-01 17.588  
1998-01-01 17.619
1998-02-01 17.627
1998-03-01 17.637
1998-04-01 17.637
1998-05-01 17.624
1998-06-01 17.608
1998-07-01 17.422
1998-08-01 17.563
1998-09-01 17.557
1998-10-01 17.512
1998-11-01 17.465
1998-12-01 17.449
1999-01-01 17.427
1999-02-01 17.395
1999-03-01 17.368
1999-04-01 17.344
1999-05-01 17.333
1999-06-01 17.295
1999-07-01 17.308
1999-08-01 17.287
1999-09-01 17.281
1999-10-01 17.272
1999-11-01 17.282
1999-12-01 17.28
2000-01-01 17.284
2000-02-01 17.285
2000-03-01 17.302
2000-04-01 17.298
2000-05-01 17.279
2000-06-01 17.296
2000-07-01 17.322
2000-08-01 17.287
2000-09-01 17.23
2000-10-01 17.217
2000-11-01 17.202
2000-12-01 17.181
2001-01-01 17.104
2001-02-01 17.028
2001-03-01 16.938
2001-04-01 16.802
2001-05-01 16.661
2001-06-01 16.515
2001-07-01 16.382
2001-08-01 16.232
2001-09-01 16.117
2001-10-01 15.972
2001-11-01 15.825
2001-12-01 15.711
2002-01-01 15.587
2002-02-01 15.515
2002-03-01 15.443
2002-04-01 15.392
2002-05-01 15.337
2002-06-01 15.298
2002-07-01 15.256
2002-08-01 15.171
2002-09-01 15.119
2002-10-01 15.06
2002-11-01 14.992
2002-12-01 14.912
2003-01-01 14.866
2003-02-01 14.781
2003-03-01 14.721
2003-04-01 14.609
2003-05-01 14.557
2003-06-01 14.493
2003-07-01 14.402
2003-08-01 14.376
2003-09-01 14.347
2003-10-01 14.334
2003-11-01 14.316
2003-12-01 14.3
2004-01-01 14.29
2004-02-01 14.279
2004-03-01 14.287
2004-04-01 14.315
2004-05-01 14.342
2004-06-01 14.332
2004-07-01 14.33
2004-08-01 14.345
2004-09-01 14.331
2004-10-01 14.332
2004-11-01 14.307
2004-12-01 14.287
2005-01-01 14.257
2005-02-01 14.273
2005-03-01 14.269
2005-04-01 14.25
2005-05-01 14.256
2005-06-01 14.227
2005-07-01 14.226
2005-08-01 14.203
2005-09-01 14.175
2005-10-01 14.192
2005-11-01 14.187
2005-12-01 14.193
2006-01-01 14.21
2006-02-01 14.209
2006-03-01 14.214
2006-04-01 14.226
2006-05-01 14.203
2006-06-01 14.213
2006-07-01 14.188
2006-08-01 14.159
2006-09-01 14.125
2006-10-01 14.075
2006-11-01 14.041
2006-12-01 14.015
2007-01-01 14.008
2007-02-01 13.997
2007-03-01 13.97
2007-04-01 13.945
2007-05-01 13.929
2007-06-01 13.911
2007-07-01 13.889
2007-08-01 13.828
2007-09-01 13.79
2007-10-01 13.764
2007-11-01 13.757
2007-12-01 13.746
2008-01-01 13.725
2008-02-01 13.696
2008-03-01 13.659
2008-04-01 13.599
2008-05-01 13.564
2008-06-01 13.504
2008-07-01 13.43
2008-08-01 13.358
2008-09-01 13.275
2008-10-01 13.147
2008-11-01 13.034
2008-12-01 12.85
2009-01-01 12.561
2009-02-01 12.38
2009-03-01 12.208
2009-04-01 12.03
2009-05-01 11.862
2009-06-01 11.726
2009-07-01 11.668
2009-08-01 11.626
2009-09-01 11.591
2009-10-01 11.538
2009-11-01 11.509
2009-12-01 11.475
2010-01-01 11.46
2010-02-01 11.453
2010-03-01 11.453
2010-04-01 11.489
2010-05-01 11.525
2010-06-01 11.545
2010-07-01 11.561
2010-08-01 11.553
2010-09-01 11.563
2010-10-01 11.562
2010-11-01 11.585
2010-12-01 11.595
2011-01-01 11.618
2011-02-01 11.653
2011-03-01 11.67
2011-04-01 11.7
2011-05-01 11.712
2011-06-01 11.724
2011-07-01 11.742
2011-08-01 11.766
2011-09-01 11.771
2011-10-01 11.776
2011-11-01 11.774
2011-12-01 11.799
2012-01-01 11.834
2012-02-01 11.857
2012-03-01 11.899
2012-04-01 11.916
2012-05-01 11.93
2012-06-01 11.941
2012-07-01 11.965
2012-08-01 11.961
2012-09-01 11.948
2012-10-01 11.951
2012-11-01 11.947
2012-12-01 11.961
2013-01-01 11.98
2013-02-01 12.002
2013-03-01 12.006
2013-04-01 12.006
2013-05-01 12.007
2013-06-01 12.005
2013-07-01 11.983
2013-08-01 12.011
2013-09-01 12.022
2013-10-01 12.04
2013-11-01 12.072
2013-12-01 12.086
2014-01-01 12.102
2014-02-01 12.122
2014-03-01 12.131
2014-04-01 12.142
2014-05-01 12.154
2014-06-01 12.177
2014-07-01 12.191
2014-08-01 12.205
2014-09-01 12.214
2014-10-01 12.237
2014-11-01 12.282
2014-12-01 12.301
2015-01-01 12.295
2015-02-01 12.303
2015-03-01 12.311
2015-04-01 12.317
2015-05-01 12.334
2015-06-01 12.338
2015-07-01 12.357
2015-08-01 12.343
2015-09-01 12.35
2015-10-01 12.361
2015-11-01 12.357
2015-12-01 12.362
2016-01-01 12.384
2016-02-01 12.369
2016-03-01 12.344
2016-04-01 12.351
2016-05-01 12.333
2016-06-01 12.353
2016-07-01 12.37
2016-08-01 12.347
2016-09-01 12.344
2016-10-01 12.341
2016-11-01 12.341
2016-12-01 12.355
2017-01-01 12.368
2017-02-01 12.386
2017-03-01 12.395
2017-04-01 12.403
2017-05-01 12.405
2017-06-01 12.42
2017-07-01 12.417
2017-08-01 12.459
2017-09-01 12.467
2017-10-01 12.487
2017-11-01 12.517
2017-12-01 12.545
2018-01-01 12.561
2018-02-01 12.592
2018-03-01 12.612
2018-04-01 12.634
2018-05-01 12.655
2018-06-01 12.687
2018-07-01 12.707
2018-08-01 12.715
2018-09-01 12.733
2018-10-01 12.762
2018-11-01 12.789
2018-12-01 12.809
2019-01-01 12.826
2019-02-01 12.834
2019-03-01 12.831
2019-04-01 12.834
2019-05-01 12.836
2019-06-01 12.846
2019-07-01 12.85
2019-08-01 12.852
2019-09-01 12.854
2019-10-01 12.809
2019-11-01 12.867
2019-12-01 12.855
ChartData Download data

The data below can be saved or copied directly into Excel.

Source: EPI analysis of Bureau of Labor Statistics 2020 Manufacturing Employment data series [CES3000000001].

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Trump has not brought these jobs back, nor will his present policies change the status quo. Globalization, and China trade in particular, have also hurt countless communities throughout the country, especially in the upper Midwest, mid-Atlantic, and Northeast regions. The nation has lost a generation of skilled manufacturing workers, many of whom have dropped out of the labor force and never returned. All of this globalized trade has reduced the wages of roughly 100 million Americans, all non-college educated workers, by roughly $2,000 per year.

In addition, more than half of the U.S. manufacturing jobs lost in the past two decades were due to the growing trade deficit with China, which eliminated 3.7 million U.S. jobs, including 2.8 million manufacturing jobs, between 2001 and 2018. In fact, the United States lost 700,000 jobs to China in the first two years of the Trump administration, as shown in our recent report. The phase one trade deal will not bring those jobs back, either.

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As investment continues to decline, the Trump tax cuts remain nothing but a handout to the rich

President Trump is likely to tout the benefits of the 2017 Tax Cuts and Jobs Act (TCJA) during his annual State of the Union Address. The centerpiece of the TCJA was a corporate rate cut that proponents claimed would eventually trickle down to workers’ wages—boosting the average American household’s wages by $4,000. We pointed out at the time that there was a lot wrong about this economic theory in practice. Even so, key to the theory is that investment would surge after the tax cuts were enacted. And without a substantial uptick in investment, the typical worker has no chance of benefiting from the TCJA’s corporate rate cuts. Instead, investment has cratered since the TCJA passed. In fact, last week’s GDP data showed that for the first time since the Great Recession, investment has declined for three straight quarters. Given that boosting business investment was the primary stated goal of the TCJA, this seems like an unambiguous policy failure for working people, benefiting only the rich and corporations.

Figure A

No evidence the TCJA is working as advertised: Year-over-year change in real, nonresidential fixed investment, 2003Q1–2019Q4

Quarter Real, nonresidential fixed investment
2003Q1 -2.3%
2003Q2 1.6%
2003Q3 4.0%
2003Q4 6.8%
2004Q1 5.2%
2004Q2 4.9%
2004Q3 5.7%
2004Q4 6.5%
2005Q1 9.2%
2005Q2 8.2%
2005Q3 7.4%
2005Q4 6.1%
2006Q1 8.0%
2006Q2 8.2%
2006Q3 7.8%
2006Q4 8.1%
2007Q1 6.5%
2007Q2 7.0%
2007Q3 6.8%
2007Q4 7.3%
2008Q1 5.8%
2008Q2 3.8%
2008Q3 0.2%
2008Q4 -7.0%
2009Q1 -14.4%
2009Q2 -17.1%
2009Q3 -16.1%
2009Q4 -10.3%
2010Q1 -2.3%
2010Q2 4.1%
2010Q3 7.5%
2010Q4 8.9%
2011Q1 8.0%
2011Q2 7.3%
2011Q3 9.3%
2011Q4 10.0%
2012Q1 12.9%
2012Q2 12.6%
2012Q3 7.2%
2012Q4 5.6%
2013Q1 4.3%
2013Q2 2.3%
2013Q3 4.4%
2013Q4 5.4%
2014Q1 5.5%
2014Q2  8.1%
2014Q3 8.4%
2014Q4 6.9%
2015Q1 5.0%
2015Q2 2.5%
2015Q3 0.8%
2015Q4 -0.9%
2016Q1 -0.7%
2016Q2 0.0%
2016Q3 1.1%
2016Q4 2.4%
2017Q1 4.2%
2017Q2 4.3%
2017Q3 3.5%
2017Q4  5.4%
2018Q1 6.0%
2018Q2 6.9%
2018Q3 6.8%
2018Q4 5.9%
2019Q1 4.8%
2019Q2 2.6%
2019Q3 1.4%
2019Q4 -0.1%
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Source: EPI analysis of data from table 1.1.6 from the National Income and Product Accounts (NIPA) from the Bureau of Economic Analysis (BEA).

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The state of the union for black workers: Myths and facts

As President Trump prepares to deliver his State of the Union address, here are three charts that show why the economy is still not “working great” for all black workers in America.


Myth: The black unemployment rate is at an all-time low, and that means the economy is “working great” for all black workers.

Reality: Too many black workers are still out of work—black workers are twice as likely to be unemployed as white workers.


Even with a historically low average annual black unemployment rate of 6.1% in 2019, black workers are twice as likely to be unemployed as white workers overall and are more likely to be unemployed than white workers at every education level. Only black workers with some college or more education have an unemployment rate lower than the overall unemployment rate of white workers.

Black workers are more likely to be unemployed than white workers at every education level: Unemployment rates by race and education, 2019

Education Black White, non-Hispanic
All 6.1% 3.0%
Less than high school 14.7% 8.3% 
High school 8.3% 3.9% 
Some college 4.9% 2.9% 
College 3.4% 2.2% 
Advanced 2.3% 1.7%
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The data below can be saved or copied directly into Excel.

Updated with Jan.–Dec. 2019 data, from Black Workers Endure Persistent Racial Disparities in Employment Outcomes, Economic Policy Institute, 2019.

Source: EPI analysis of U.S. Census Bureau data

Estimates are based on a 12-month average (January 2019–December 2019). “Black” includes blacks of Hispanic ethnicity. Whites are non-Hispanic.

Source: EPI analysis of Current Population Survey basic monthly microdata from the U.S. Census Bureau. Updated from Figure A in Jhacova Williams and Valerie Wilson, Black Workers Endure Persistent Racial Disparities in Employment Outcomes, Economic Policy Institute, August 2019.

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Myth: If black workers had better skills, they would have better employment outcomes.

Reality: Having a college degree doesn’t guarantee a college-level job, especially for black workers.


It is true that workers with higher levels of education have better employment outcomes. But in today’s economy getting a college degree doesn’t provide the universal boost that it used to. We have a high underemployment rate—a high share of college graduates who are working in jobs that do not require a college degree. And as the chart shows, black college graduates are more likely than white college graduates to be employed in occupations that do not require a college degree.

Black college graduates are more likely than white college graduates to be underemployed when it comes to their skills: Share of workers with a college degree who are not employed in a college occupation, by race, 2019

Race/ethnicity Rate
Black 39.4%
White non-Hispanic 30.9%
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Adapted from Black Workers Endure Persistent Racial Disparities in Employment Outcomes, Economic Policy Institute, 2019.

Source: EPI analysis of U.S. Census Bureau data

Estimates are based on a 12-month average (July 2018–June 2019). “Black” includes blacks of Hispanic ethnicity. Whites are non-Hispanic. College graduates include those with a bachelor’s degree or more education. For how "college occupation" is defined, see the methodology in Jhacova Williams and Valerie Wilson, Black Workers Endure Persistent Racial Disparities in Employment Outcomes, Economic Policy Institute, August 2019

Source: EPI analysis of Current Population Survey basic monthly microdata from the U.S. Census Bureau. Adapted from Figures B and C in Jhacova Williams and Valerie Wilson, Black Workers Endure Persistent Racial Disparities in Employment Outcomes, Economic Policy Institute, August 2019.

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Myth: The strong economy and historically low unemployment must mean historically strong wage growth among black workers, and especially among highly educated black workers.

Reality: Wages for black college graduates have actually fallen in the current recovery.


In a recovery, as the unemployment rates falls, you expect wages to grow. But in that respect this current recovery significantly lags the recovery of the late 1990s. Both recoveries have had similar declines in the unemployment rate, but wages today have not grown nearly as fast or as evenly across race and gender as they did during the late 1990s. Today, workers with bachelor’s degrees are not seeing nearly the level of wage growth that this group saw in the late 1990s. In fact, wages fell for black college graduates between 2015 and 2019, even as unemployment rates were falling significantly.

Wage growth was stronger among workers with bachelor’s degrees in the late 1990s than during the current expansion: Real average wage growth, workers with bachelor’s degrees, 1996–2000 and 2015–2019

Demographic 1996–2000 2015–2019
Men 10.9% 7.8%
Women 9.8% 3.0%
White 10.6% 6.6%
Black 11.5% -0.3%

 

ChartData Download data

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Adapted from Wage Growth Is Weak for a Tight Labor Market—and the Pace of Wage Growth Is Uneven Across Race and Gender, Economic Policy Institute, 2019.

Source: EPI analysis of U.S. Census Bureau data

 

In order to include data from the first half of 2019, all years refer to the 12-month period ending in June. Sample includes workers with a bachelor’s degree only.

Source: EPI analysis of Current Population Survey basic monthly microdata from the U.S. Census Bureau. Adapted from Figure B in Elise Gould and Valerie Wilson, Wage Growth is Weak for a Tight Labor Market—and the Pace of Wage Growth is Uneven Across Race and Gender, Economic Policy Institute, August 2019.

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Primer—The state of the union for working people

In preparation for President Trump’s State of the Union speech, the Economic Policy Institute has assembled research from the last year that examines the real state of the union for working people on wages, manufacturing and trade, taxes, labor standards, housing, and immigration.

Wages and employment

  • 2019 had solid job growth, but wage growth slowed. Average monthly job creation has held remarkably steady for the past nine years, but it did soften in the last year, from 223,000 in 2018 to 176,000 in 2019. Wage growth slowed for much of the year, providing further evidence that we are not yet at genuine full employment. After hitting a recent high point of 3.4% year-over-year wage growth, the growth rate has measurably decelerated and wage growth closed out the year at only 2.9% in December.
  • Wage growth for low-wage workers has been strongest in states with minimum wage increases
  • More on longer wage trends in our Nominal Wage Tracker.

Manufacturing and trade

Taxes

Read more

The signal the unemployment rate provides can change a lot over time: EPI Macroeconomics Newsletter

In 2019 the unemployment rate was below 4% for the second straight year, the first time this has happened since 1968 and 1969. Despite the current stretch of low unemployment, by many other measures the labor market does not seem particularly tight. Most obviously, wage growth has been accelerating a bit, but is still disappointing relative to what wage growth we would expect at this level of unemployment.

Productivity growth has firmed up slightly in recent years, but employers still aren’t acting like labor costs are something they’re particularly worried about containing through investments in capital equipment or better processes.

The late 1990s is an obvious reference for highlighting how unresponsive wage and productivity growth have been to low unemployment in recent years. In these years, low unemployment coincided with notable accelerations in both wage and productivity growth. In this newsletter, we highlight some reasons why the headline unemployment rate measured in the late 1990s does not provide quite the expected apples-to-apples comparison with the unemployment rate of today. Key findings are:

  • The unemployment rate that signifies labor market tightness falls as the workforce gets older and becomes better educated. All else equal, a workforce that is growing older and more educated should steadily, over time, reduce the unemployment rate that is consistent with a given wage target. These compositional changes in the workforce have occurred and have reduced unemployment by roughly 0.3 percentage points since 2000, meaning that an unemployment rate of 3.7% today is equivalent in its effect on wage growth to a 4.0% unemployment rate in 2000.
  • Today’s measured unemployment rate captures fewer jobless workers than it used to. Growing nonresponse in the survey used to calculate the unemployment rate has reduced the unemployment rate consistent with a given wage target over time by another 0.3 percentage points since 2000. Growing evidence shows that nonresponse to this survey is not random: rather it is jobless workers who are less likely to respond to the survey that is used to calculate unemployment. This biases the measured unemployment rate downward.
  • There may be a bigger pool of workers competing for jobs than the unemployment rate suggests. Adults not in the labor force today seem substantially more substitutable with adults officially classified as “unemployed” than was the case in the late 1990s recovery. For example, the share of newly employed workers who enter employment from out of the labor force is substantially higher in recent years than in past periods of low unemployment, and the downward pressure that adults not participating in job searches put on wages is higher now than in the late 1990s. In short, many potential workers today are not being classified as unemployed, and hence may be missed by focusing only on the unemployment rate as a measure of labor slack.

The rest of this brief highlights evidence on these three points.

A lower unemployment rate is needed to signify labor market tightness with an older and better-educated workforce

All else equal, workers with more experience and education credentials have lower rates of unemployment. The economic intuition for this is that more experienced and more educated workers have skills that are in greater demand by employers at any given level of economy-wide slack. This demand premium for more experienced workers holds in the aggregate despite the fact that age discrimination afflicts many workers, i.e., the unemployment/age gradient is clearly downward sloping.

Lower unemployment among more experienced and educated workers means that a given unemployment rate (say 4%) achieved in two different years can signify different things about the labor market if the composition of the workforce has changed. An unemployment rate of 4% might signal a moderate degree of slack for a highly educated and more experienced workforce, but may signal a very tight labor market for a workforce that is younger and with fewer credentials. Figure A shows the actual unemployment rate and the composition-adjusted unemployment rate for two time periods: 1997–2000 and 2016–2019. Both periods saw unemployment below 5%. In the first period, the difference between actual and composition-adjusted unemployment is trivial (essentially by construction—we fix the demographic composition of the workforce at its 1995 level, as described in the note to the figure). By the 2016–2019 period, the composition-adjusted unemployment rate is nearly 0.3 percentage points higher. In essence, after controlling for age and education, the unemployment rate today has to be roughly 0.3 percentage points lower to signify the same level of labor market slack as it did during the late 1990s recovery. We also adjusted unemployment by race, ethnicity, and gender (not shown in the figure), but this changed the composition-adjusted unemployment rates only trivially compared with the effects of age and experience.

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On EITC Awareness Day, remember that the EITC and minimum wage work together to raise incomes

Today is Earned Income Tax Credit (EITC) Awareness Day, an effort to make low-income taxpayers aware of the tax credit that provides an important boost to low- and moderate-income families. It also provides the opportunity to address a common misconception around the EITC.

Policy discussions sometimes describe EITC expansions and minimum wage increases as alternative, competing policies for helping low-income workers. But, as economist Jesse Rothstein and I explain in a new report, this framing is incorrect. The two policies are actually complementary. A minimum wage increase and EITC expansion are more effective together than either is on its own.

Federal, state, and local increases in minimum wages have raised the incomes of low-wage workers and their families. The best published scholarship estimates that a $12 an hour minimum wage in 2017—very similar in real terms to current proposals for a gradual increase to a $15 an hour federal minimum wage—would have lowered the number of individuals living in poverty by six million, with disproportionately large effects for people of color.

In contrast, the EITC is a refundable tax credit available to low-income families who have positive earned income: Eligible households receive a net tax refund that supplements their earnings. In 2018, over 22 million working families and individuals received an average credit of nearly $3,200. Like the minimum wage, a large body of research indicates that the EITC reduces poverty, and the tax credit also improves health and educational outcomes. In addition, the EITC can also raise total incomes above the low floor guaranteed by the minimum wage in many parts of the country. The current EITC refund adds 39%—or about $5,800—to the pretax earnings of a single parent with two children working full-time at the federal minimum wage.

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Wilbur Ross’s comments and Trump administration trade policies offer few answers for growing, job-destroying China trade deficit

This morning, Commerce Secretary Wilbur Ross claimed that the coronavirus outbreak in China “will help accelerate the return of jobs to North America.” This comment is not only cruel and inhumane, but it’s also a testament to just how little the Trump administration understands about America’s trade problems and how to solve them. Even the administration’s less off-the-cuff plans for rebuilding U.S. manufacturing have little chance of working. For example, as I noted previously, President Trump’s “phase one” trade deal with China is unlikely to significantly reduce the massive U.S. job losses that have resulted from growing U.S. trade deficits with China.

A new EPI analysis shows that growing trade deficits with China cost 3.7 million U.S. jobs between 2001 and 2018, including 700,000 jobs lost in the first two years of the Trump administration. Job losses occurred in all 50 states, every congressional district, and every industry. Manufacturing was hit the hardest, with 2.8 million jobs lost. Given this toll and the Trump administration’s rhetoric, you’d think they’d look for real solutions. Instead, Trump appears desperate to sign his deal, any deal, so that he can claim progress on reducing trade deficits. But he is shortsighted on trade because his arrangement with Beijing ignores at least two key problems. First, it assumes that China will suddenly obey trade rules and commitments it has never previously respected. And second, it limits Washington’s ability to respond to the currency misalignment currently hampering U.S. exporters.

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Weakened labor movement leads to rising economic inequality

The basic facts about inequality in the United States—that for most of the last 40 years, pay has stagnated for all but the highest paid workers and inequality has risen dramatically—are widely understood. What is less well-known is the role the decline of unionization has played in those trends. The share of workers covered by a collective bargaining agreement dropped from 27 percent to 11.6 percent between 1979 and 2019, meaning the union coverage rate is now less than half where it was 40 years ago.

Research shows that this de-unionization accounts for a sizable share of the growth in inequality over that period—around 13–20 percent for women and 33–37 percent for men. Applying these shares to annual earnings data reveals that working people are now losing on the order of $200 billion per year as a result of the erosion of union coverage over the last four decades—with that money being redistributed upward, to the rich.

The good news is that restoring union coverage—and strengthening workers’ abilities to join together to improve their wages and working conditions in other ways—is therefore likely to put at least $200 billion per year into the pockets of working people. These changes could happen through organizing and policy reform. Policymakers have introduced legislation, the Protecting the Right to Organize (PRO) Act, that would significantly reform current labor law. Building on the reforms in the PRO Act, the Clean Slate for Worker Power Project proposes further transformation of labor law, with innovative ideas to create balance in our economy. Read more

The Trump administration’s new housing rules will worsen segregation

In “The Neighborhoods We Will Not Share,” an article published online at The New York Times, I describe how the Trump administration has proposed a rule that will make it virtually impossible to challenge many policies that reinforce residential racial segregation.

This is no small matter. Segregation underlies many of our most serious social problems. Educators can’t seem to make significant progress in their efforts to close the racial gap in academic achievement that persists in large part because we enroll the most socially and economically disadvantaged children in poorly resourced schools, located in poorly resourced neighborhoods. Health disparities by race stem, in part, from so many African Americans consigned to areas where they have less access to healthy air and healthy foods, and are more subject to stressful conditions. Black men’s high and unjustifiable rates of incarceration depend significantly on their concentration in segregated neighborhoods without good employment opportunities in the formal economy or the transportation to access good jobs. And segregation prevents us from overcoming our very dangerous and frightening political polarization, highly correlated with race. How can we ever develop the common national identity essential to the preservation of our democracy if so many African Americans and whites live so far from each other that we have no ability to understand and empathize with each other’s life experiences?

In my book The Color of Law, I described how 20th century federal, state, and local policies—explicitly racial—created, reinforced, and sustained racial boundaries in every metropolitan area in the United States. These unconstitutional government activities still predict today’s segregated landscape. For example, the explicit exclusion of black working class families from single-family homes, for which white working class family purchases were subsidized, bears substantial responsibility for the black-white wealth gap—while black family incomes are about about 60% of white family incomes, the median black household wealth is less than 10%of white household wealth, an enormous disparity that was propelled by the equity appreciation of white property while African Americans were consigned to neighborhoods where no similar appreciation occurred. The wealth gap predicts much of our contemporary racial inequality.Read more

Yes, David Brooks, there really is a class war

New York Times columnist David Brooks, in an article sub-titled “No, Virginia, there is no class war,” recently trotted out an old argument about why wage growth has been so sluggish for so many U.S. workers for so long: they’re just not very good workers. Specifically, he argues that “wages are still mostly determined by skills and productivity.” Ergo, if there is growing inequality in wages, it must be driven by inequality in workers’ own productivity.

But the evidence he cites is totally unconvincing on this.

First, he notes that wages for lower-wage workers have recently grown more rapidly than for middle-wage workers. But it’s been shown again and again that this is driven in large-part by those states that have raised their minimum wages. It’s also been shown that tighter labor markets disproportionately benefit the lowest-paid workers. The argument that changes in relative bargaining power and economic leverage have been the prime mover of wage trends in recent decades is not an argument that wages can never rise, period. When policies change—like minimum wages increase and the Fed allows labor markets to tighten without slamming on the interest rate brakes—good things happen. We just need to change a lot more policies.

Second, he cites a study that looks at wage and productivity growth in high-skill and low-skill industries between 1989 and 2017. The first odd bit of this evidence is that the wage growth he reports the study claims for high and low-skill industries is essentially identical: 26 percent versus 24 percent. The second odd bit is that this means even high-skill industries only gave average annual wage increases of 0.8 percent over that time, even as aggregate productivity grew by almost twice as fast over that time (about 1.4 percent annually). Finally, and most important, using industry-level productivity growth to infer anything about the productivity of individuals working in these industries cannot be done. To put it most simply, productivity growth within an industry can occur because each input used in production gets more productive, or, there is a shift in the mix of inputs. This might sound wonky but I’ll explain a bit more in the next paragraph:Read more

This MLK Day, remember Emmett Till and voter suppression

“We can never be satisfied as long as the Negro is the victim of the unspeakable horrors of police brutality…We cannot be satisfied as long as the Negro in Mississippi cannot vote and the Negro in New York believes he has nothing for which to vote.” —Martin Luther King Jr.

Two historic events occurred in American history in different years on August 28. In 1955, Emmett Till was lynched in Mississippi—and in 1963, Martin Luther King Jr. addressed the nation from Washington, D.C., with his I Have a Dream” speech. While both events have been ingrained in many Americans’ memories, few are aware that they share a common link between brutality and voter suppression.

The prevailing belief of the circumstances surrounding 14-year-old Emmett Till’s killing is that he was accused of whistling at a white woman. Yet, the truth is he was lynched as an act of voter intimidation. After being acquitted by an all-white jury, one of Emmett Till’s killers confessed to the lynching and gave voting as the first reason he killed Emmett.

“But I just decided it was time a few people got put on notice. As long as I live and can do anything about it, [racial slur] are gonna stay in their place. [Racial slur] ain’t gonna vote where I live. If they did, they’d control the government.”—J.W. “Big Milam”

Although Emmett Till was brutally lynched 65 years ago, historical events like his killing continue to suppress the political participation of black Americans. Using data on historical lynchings and present-day voter registration of blacks in southern states, Figure A shows that blacks who live in counties that experienced more lynchings in the past are less likely to register to vote today.Read more

China trade deal will not restore 3.7 million U.S. jobs lost since China entered the WTO in 2001

The White House has announced plans for a ceremony to sign a “phase one” trade deal with China on Wednesday, although details of the agreement have yet to be announced. As one analyst noted, this deal may not amount to more than a hill of soybeans. It is unlikely to significantly reduce massive U.S. job losses due to growing U.S. trade deficits—the difference between imports and exports—which are dominated by trade deficits in manufactured goods. As shown in a forthcoming EPI report to be released later this month, growing U.S. trade deficits with China eliminated 3.7 million U.S. jobs between 2001 and 2018 alone (see Figure A), including 2.8 million jobs in manufacturing (details will be provided in the forthcoming report).

Figure A

U.S. jobs displaced by the growing goods trade deficit with China since 2001 (in thousands of jobs)

Year  Jobs displaced (thousands)
2001 0.0 
2002 218.1
2003 445.7
2004 852.1
2005 1,306.1
2006 1,651.5
2007 1,964.5
2008 2,030.4
2009 1,686.2
2010 2,295.0
2011 2,616.8
2012 2,764.6
2013 2,812.3
2014 2,993.2
2015 3,197.9
2016 2,965.2
2017 3,339.8
2018 3,704.7
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Source: Authors’ analysis of U.S. Census Bureau American Community Survey data, Bureau of Labor Statistics Employment Projections program data, and U.S. International Trade Commission Interactive Tariff and Trade DataWeb database. Adapted from Rob Scott and Zane Mokhiber, Growing China Trade Deficits Cost 3.7 Million American Jobs between 2001 and 2018, Economic Policy Institute, forthcoming.

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Trade deficits and jobs losses with China continued to grow during the first two years of the Trump administration—despite the administration’s heated rhetoric and imposition of tariffs. The U.S. trade deficit with China rose from $347 billion in 2016 to $420 billion in 2018, an increase of 21.0%. U.S. jobs displaced by those China trade deficits increased from nearly 3.0 million jobs lost in 2016 to 3.7 million jobs lost in 2018, an increase of more than 700,000 jobs lost or displaced in the first two years of the Trump administration.

Although the bilateral trade deficit with China has declined in 2019 (through November), the overall U.S. trade deficit in non-oil goods, which is dominated by trade in manufactured and farm products, has continued to increase, suggesting that trade diversion has grown in importance. These are important topics for future research.

While growing exports support some American jobs, growing imports eliminate existing jobs and prevent new job creation—as imports displace goods that otherwise would have been made in the United States by domestic workers. As a result, growing trade deficits result in increasing U.S. job losses. The top half of Table 1 shows just how much the trade deficit has grown: The U.S. trade deficit with China increased from $83.0 billion in 2001 to $420 billion in 2018. While U.S. exports to China increased in this period, growing exports were overwhelmed by the massive growth of imports from China, which increased by $437 billion in this period. Read more

The labor market continues to improve in 2019 as women surpass men in payroll employment, but wage growth slows

Today’s Bureau of Labor Statistics (BLS) jobs report provides the opportunity to look at 2019 as a whole and in comparison with previous years. As the recovery has strengthened over the last several years, we’ve generally seen improvements in most measures of the labor market: employment, unemployment, and wage growth. These measures tell a consistent story—an economy on its way to full employment, but not there yet. Wage growth continues to be the lagging indicator, which is not as strong as would be expected given the health of the labor market and actually slowed through much of 2019.

Payroll employment growth in December was 145,000, bringing average job growth in 2019 to 176,000. This is a bit softer than the 223,000 average for 2018, but still more than enough to keep up with growth in the working-age population and pull in thousands of workers off the sidelines every month.

Figure A

Average monthly total nonfarm employment growth, 2006–2019

Year Average monthly total nonfarm employment growth
2006 175
2007 95
2008 -296
2009 -421
2010 86
2011 173
2012 181
2013 192
2014 251
2015 227
2016 193
2017 179
2018 223
2019 176
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Source: Data are from the Current Employment Statistics (CES) series of the Bureau of Labor Statistics and are subject to occasional revisions. This chart was based on data accessed in January 2020.

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For the first time in nearly 10 years, women’s share of payroll employment has just surpassed that of men’s. The figure below shows payroll employment for both men and women since 2000. From 2000 to 2007, men’s share of total employment was about 1–2% higher than women’s. In the recession, employment fell markedly in male-dominated professions—notably manufacturing and construction—and women’s share of employment rose in kind. Since 2010, women’s and men’s employment have both increased, with men’s growing faster than women’s initially. In the last couple of years, women’s payroll employment has grown just a bit faster than men’s.

We can turn again to a sector approach as one explanation for why women’s employment has now just surpassed men’s in December. Men make up 77% of employment in construction and manufacturing combined. Coincidentally, women make up 77% of employment in education and health services. Between 2018 and 2019, construction and manufacturing together increased by 356,000, but education and health services employment increased much more—by 603,000. Furthermore, manufacturing employment has faltered late in the year, helping women’s employment eke ahead of men’s in December.

It is important to note that in absolute terms the shares of men’s and women’s employment haven’t changed that dramatically. But, it holds true that women’s payroll employment is now 50.04% of the total, the first time it has been a majority since the depths of the (construction and manufacturing-led) Great Recession.

Figure B

Women’s share of payroll employment ekes ahead of men’s in December 2019: Payroll employment, men and women, 2000 to 2019

Date Payroll employment, women Payroll employment, men
Jan-2000 62861 68159
Feb-2000 62936 68200
Mar-2000 63087 68522
Apr-2000 63294 68606
May-2000 63499 68619
Jun-2000 63457 68622
Jul-2000 63444 68803
Aug-2000 63521 68719
Sep-2000 63635 68729
Oct-2000 63624 68741
Nov-2000 63755 68815
Dec-2000 63791 68931
Jan-2001 63863 68849
Feb-2001 63922 68882
Mar-2001 63894 68867
Apr-2001 63964 68511
May-2001 63995 68431
Jun-2001 63951 68361
Jul-2001 64022 68165
Aug-2001 63979 68064
Sep-2001 63958 67833
Oct-2001 63790 67678
Nov-2001 63676 67482
Dec-2001 63619 67378
Jan-2002 63645 67223
Feb-2002 63622 67130
Mar-2002 63627 67105
Apr-2002 63593 67043
May-2002 63569 67078
Jun-2002 63582 67113
Jul-2002 63572 67032
Aug-2002 63621 66982
Sep-2002 63573 66951
Oct-2002 63600 67043
Nov-2002 63630 67002
Dec-2002 63574 66914
Jan-2003 63592 67004
Feb-2003 63604 66857
Mar-2003 63489 66757
Apr-2003 63501 66693
May-2003 63472 66738
Jun-2003 63429 66780
Jul-2003 63421 66786
Aug-2003 63308 66859
Sep-2003 63460 66819
Oct-2003 63523 66950
Nov-2003 63551 66939
Dec-2003 63604 67001
Jan-2004 63645 67142
Feb-2004 63666 67178
Mar-2004 63773 67383
Apr-2004 63873 67553
May-2004 63996 67714
Jun-2004 64036 67771
Jul-2004 64037 67827
Aug-2004 64007 67948
Sep-2004 64135 67977
Oct-2004 64287 68179
Nov-2004 64327 68194
Dec-2004 64397 68247
Jan-2005 64512 68279
Feb-2005 64611 68439
Mar-2005 64662 68510
Apr-2005 64823 68713
May-2005 64895 68811
Jun-2005 65025 68932
Jul-2005 65121 69193
Aug-2005 65171 69346
Sep-2005 65276 69307
Oct-2005 65214 69459
Nov-2005 65321 69691
Dec-2005 65327 69841
Jan-2006 65394 70052
Feb-2006 65466 70287
Mar-2006 65552 70511
Apr-2006 65587 70634
May-2006 65546 70715
Jun-2006 65577 70765
Jul-2006 65811 70727
Aug-2006 65938 70775
Sep-2006 66064 70796
Oct-2006 66180 70690
Nov-2006 66317 70765
Dec-2006 66468 70800
Jan-2007 66585 70908
Feb-2007 66733 70840
Mar-2007 66835 70975
Apr-2007 66916 70944
May-2007 67058 70954
Jun-2007 67135 70953
Jul-2007 67174 70881
Aug-2007 67273 70759
Sep-2007 67352 70762
Oct-2007 67417 70773
Nov-2007 67484 70815
Dec-2007 67623 70786
Jan-2008 67630 70792
Feb-2008 67662 70678
Mar-2008 67703 70589
Apr-2008 67683 70373
May-2008 67671 70201
Jun-2008 67627 70079
Jul-2008 67628 69880
Aug-2008 67480 69749
Sep-2008 67349 69420
Oct-2008 67166 69122
Nov-2008 67018 68543
Dec-2008 66805 68052
Jan-2009 66554 67520
Feb-2009 66317 67015
Mar-2009 66068 66461
Apr-2009 65822 66013
May-2009 65704 65787
Jun-2009 65550 65476
Jul-2009 65423 65262
Aug-2009 65348 65153
Sep-2009 65239 65020
Oct-2009 65173 64888
Nov-2009 65128 64945
Dec-2009 65063 64741
Jan-2010 65082 64725
Feb-2010 65006 64709
Mar-2010 65072 64823
Apr-2010 65076 65056
May-2010 65296 65370
Jun-2010 65168 65362
Jul-2010 65080 65362
Aug-2010 65026 65411
Sep-2010 64956 65417
Oct-2010 65047 65595
Nov-2010 65085 65680
Dec-2010 65106 65733
Jan-2011 65115 65744
Feb-2011 65157 65915
Mar-2011 65237 66067
Apr-2011 65391 66234
May-2011 65364 66356
Jun-2011 65443 66512
Jul-2011 65466 66550
Aug-2011 65484 66654
Sep-2011 65558 66816
Oct-2011 65654 66924
Nov-2011 65712 66998
Dec-2011 65777 67137
Jan-2012 65952 67317
Feb-2012 66061 67470
Mar-2012 66147 67622
Apr-2012 66187 67665
May-2012 66289 67662
Jun-2012 66316 67707
Jul-2012 66402 67774
Aug-2012 66463 67883
Sep-2012 66543 67992
Oct-2012 66617 68076
Nov-2012 66704 68147
Dec-2012 66791 68297
Jan-2013 66876 68407
Feb-2013 66956 68606
Mar-2013 67067 68631
Apr-2013 67189 68701
May-2013 67265 68849
Jun-2013 67332 68963
Jul-2013 67449 68951
Aug-2013 67593 69049
Sep-2013 67688 69143
Oct-2013 67767 69289
Nov-2013 67920 69403
Dec-2013 67967 69423
Jan-2014 67977 69590
Feb-2014 68054 69681
Mar-2014 68156 69829
Apr-2014 68309 70003
May-2014 68395 70138
Jun-2014 68491 70366
Jul-2014 68567 70517
Aug-2014 68657 70615
Sep-2014 68833 70750
Oct-2014 68964 70877
Nov-2014 69097 71030
Dec-2014 69246 71150
Jan-2015 69327 71282
Feb-2015 69478 71379
Mar-2015 69538 71396
Apr-2015 69660 71574
May-2015 69831 71722
Jun-2015 69930 71793
Jul-2015 70052 71964
Aug-2015 70108 72030
Sep-2015 70202 72069
Oct-2015 70378 72232
Nov-2015 70503 72342
Dec-2015 70646 72479
Jan-2016 70762 72453
Feb-2016 70950 72497
Mar-2016 71100 72581
Apr-2016 71213 72679
May-2016 71296 72611
Jun-2016 71454 72735
Jul-2016 71672 72853
Aug-2016 71783 72877
Sep-2016 71931 72999
Oct-2016 71968 73090
Nov-2016 72017 73211
Dec-2016 72133 73310
Jan-2017 72208 73487
Feb-2017 72285 73551
Mar-2017 72327 73636
Apr-2017 72399 73777
May-2017 72453 73851
Jun-2017 72546 73987
Jul-2017 72683 74054
Aug-2017 72761 74163
Sep-2017 72795 74147
Oct-2017 72885 74317
Nov-2017 73012 74410
Dec-2017 73098 74498
Jan-2018 73234 74533
Feb-2018 73421 74676
Mar-2018 73520 74759
Apr-2018 73646 74829
May-2018 73837 74908
Jun-2018 73999 75008
Jul-2018 74091 75094
Aug-2018 74229 75238
Sep-2018 74329 75246
Oct-2018 74480 75372
Nov-2018 74605 75443
Dec-2018 74724 75551
Jan-2019 74890 75697
Feb-2019 74994 75649
Mar-2019 75119 75677
Apr-2019 75233 75779
May-2019 75329 75745
Jun-2019 75381 75871
Jul-2019 75549 75869
Aug-2019 75668 75969
Sep-2019 75832 75998
Oct-2019 75958 76024
Nov-2019 76107 76131
Dec-2019 76246 76137
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Source: EPI analysis of Bureau of Labor Statistics' Current Employment Statistics public data series

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Turning to the household survey, the labor market continues to not only absorb population growth, but also chip away at the slack remaining in the labor market—namely workers who continue to be sidelined and who I expect will enter or re-enter the labor market as opportunities for jobs and better pay expand. As the unemployment rate has continued to fall between 2018 and 2019, labor force participation has increased as people re-enter the labor market and find jobs. Since December 2018, the unemployment rate dropped 0.4 percentage points (3.9% to 3.5%) while the employment-to-population ratio, or the share of the population with a job, rose 0.4 percentage points (60.6% to 61.0%). This means the unemployment rate over the last year fell for the right reasons—not because workers gave up looking, but because more would-be workers actually found jobs.

Read more

What to watch on jobs day: An assessment of the 2019 labor market

The last Bureau of Labor Statistics (BLS) jobs report of 2019 comes out on Friday, giving us a chance to step back and look at how working people fared over the entire year. The report also marks the 12th anniversary of the official start of the Great Recession. My expectation is that the December data will confirm that the economy has nearly recovered its immediate pre-Great Recession health—the last year before the Great Recession hit. Wage growth, which slowed over the last year, is a notable exception.

However, as I have often noted, 2007 should not be considered a benchmark for a fully healthy economy for America’s workers. Almost all labor market measures were notably weaker in 2007 than they were at the previous business cycle peak in 2000. There was very little reason to think that the U.S. economy in 2007 was at full employment. If one looks at the stronger business cycle peak of 2000 as a more appropriate benchmark, the economy in 2019 looks even further from full employment. Many working people are still not seeing the recovery reflected in their paychecks—and the economy will not be at genuine full employment until employers are consistently offering workers meaningfully higher wages.

In this blog post—and Friday when the December numbers come out—I’m going to look at average payroll employment growth over the last several years. Because there is always a bit of volatility in the monthly data—especially in the household series that has a smaller sample size—taking a year-long approach allows us to smooth out the bumps and take stock of the key measures: payroll employment growth, the unemployment rate, the employment-to-population ratio, and nominal wage growth.

The figure below shows average nonfarm employment growth for 2007–2018 and for the first 11 months of 2019. With an average of 180,000 new jobs being added each month, job growth in 2019 is a bit softer than 2018 and more in line with what we saw in 2017. This pickup in 2018 can be attributed to the shift in federal policy from austerity to stimulus in the form of both tax cuts and an increase in government spending. In particular, Congress boosted spending by almost $150 billion, contributing significantly to economic growth in 2018. But, in 2019, spending held steady at $150 billion, meaning there was no additional government spending to continue stimulating demand, and we saw a mild softening of employment growth.

Figure A

Average monthly total nonfarm employment growth, 2006–2019

Year Average monthly total nonfarm employment growth
2006 175
2007 95
2008 -296
2009 -421
2010 86
2011 173
2012 181
2013 192
2014 251
2015 227
2016 193
2017 179
2018 223
2019 180
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Note: Because full 2019 monthly employment data are not yet available, the chart compares average monthly job growth between January and November for 2019.

Source: Data are from the Current Employment Statistics (CES) series of the Bureau of Labor Statistics and are subject to occasional revisions. This chart was based on data accessed in January 2020.

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At the current pace of growth, however, the labor market continues to not only absorb population growth, but also chip away at the slack remaining in the labor market—namely workers who continue to be sidelined and who I expect will enter or re-enter the labor market as opportunities for jobs and better pay expand. As it turns out (and what we’ve long argued), workers who left or never entered the labor force during the Great Recession and its aftermath were not necessarily permanently sidelined, but have systematically been returning to the labor market as job opportunities have strengthened. Over the last few years, the newly employed have been coming both from the ranks of the unemployed as well as from outside the labor force, those who were not actively seeking work the month prior to finding a job. In fact, as the figure below illustrates, the share of newly employed workers who did not look for work the previous month is at a historic high. About three-fourths of newly employed workers are coming from outside the labor force.

Figure B

Share of newly employed workers who said that they were not actively searching for work in the previous month

date Share of newly employed workers who said that they were not actively searching for work in the previous month
Apr-1990 61.9%
May-1990 62.6%
Jun-1990 62.0%
Jul-1990 62.0%
Aug-1990 61.6%
Sep-1990 62.3%
Oct-1990 61.0%
Nov-1990 61.2%
Dec-1990 60.4%
Jan-1991 59.9%
Feb-1991 59.0%
Mar-1991 58.5%
Apr-1991 57.7%
May-1991 57.6%
Jun-1991 57.2%
Jul-1991 58.0%
Aug-1991 57.8%
Sep-1991 57.7%
Oct-1991 57.3%
Nov-1991 56.9%
Dec-1991 57.0%
Jan-1992 56.8%
Feb-1992 57.1%
Mar-1992 57.1%
Apr-1992 57.2%
May-1992 57.3%
Jun-1992 56.6%
Jul-1992 56.4%
Aug-1992 56.1%
Sep-1992 55.9%
Oct-1992 55.7%
Nov-1992 55.8%
Dec-1992 56.1%
Jan-1993 56.6%
Feb-1993 57.7%
Mar-1993 58.3%
Apr-1993 58.4%
May-1993 58.2%
Jun-1993 58.1%
Jul-1993 57.5%
Aug-1993 57.5%
Sep-1993 58.0%
Oct-1993 58.9%
Nov-1993 58.5%
Dec-1993 58.3%
Jan-1994 58.8%
Feb-1994 59.2%
Mar-1994 59.1%
Apr-1994 58.7%
May-1994 58.3%
Jun-1994 58.5%
Jul-1994 58.6%
Aug-1994 59.0%
Sep-1994 59.1%
Oct-1994 59.8%
Nov-1994 60.1%
Dec-1994 60.3%
Jan-1995 60.4%
Feb-1995 59.5%
Mar-1995 59.7%
Apr-1995 59.7%
May-1995 59.2%
Jun-1995 59.5%
Jul-1995 59.5%
Aug-1995 60.0%
Sep-1995 60.2%
Oct-1995 59.9%
Nov-1995 60.6%
Dec-1995 59.9%
Jan-1996 59.8%
Feb-1996 60.3%
Mar-1996 60.7%
Apr-1996 61.0%
May-1996 60.7%
Jun-1996 60.8%
Jul-1996 61.5%
Aug-1996 60.8%
Sep-1996 60.9%
Oct-1996 60.2%
Nov-1996 60.6%
Dec-1996 59.6%
Jan-1997 59.1%
Feb-1997 58.9%
Mar-1997 60.3%
Apr-1997 61.4%
May-1997 61.8%
Jun-1997 61.1%
Jul-1997 60.4%
Aug-1997 61.3%
Sep-1997 61.9%
Oct-1997 62.5%
Nov-1997 62.7%
Dec-1997 62.8%
Jan-1998 63.3%
Feb-1998 62.7%
Mar-1998 62.9%
Apr-1998 62.4%
May-1998 63.5%
Jun-1998 63.2%
Jul-1998 64.2%
Aug-1998 64.0%
Sep-1998 65.2%
Oct-1998 65.1%
Nov-1998 65.1%
Dec-1998 64.9%
Jan-1999 65.6%
Feb-1999 65.5%
Mar-1999 64.2%
Apr-1999 65.3%
May-1999 66.1%
Jun-1999 67.4%
Jul-1999 66.4%
Aug-1999 65.7%
Sep-1999 65.3%
Oct-1999 65.5%
Nov-1999 65.3%
Dec-1999 65.1%
Jan-2000 64.4%
Feb-2000 65.4%
Mar-2000 65.7%
Apr-2000 65.9%
May-2000 65.6%
Jun-2000 65.9%
Jul-2000 65.4%
Aug-2000 65.5%
Sep-2000 65.6%
Oct-2000 66.5%
Nov-2000 67.4%
Dec-2000 68.1%
Jan-2001 69.0%
Feb-2001 68.6%
Mar-2001 67.9%
Apr-2001 66.9%
May-2001 65.8%
Jun-2001 65.3%
Jul-2001 65.7%
Aug-2001 66.2%
Sep-2001 66.6%
Oct-2001 65.5%
Nov-2001 64.4%
Dec-2001 62.9%
Jan-2002 62.6%
Feb-2002 62.3%
Mar-2002 61.7%
Apr-2002 61.9%
May-2002 62.8%
Jun-2002 64.4%
Jul-2002 64.5%
Aug-2002 64.0%
Sep-2002 63.1%
Oct-2002 63.1%
Nov-2002 63.7%
Dec-2002 64.1%
Jan-2003 64.2%
Feb-2003 64.2%
Mar-2003 64.5%
Apr-2003 64.3%
May-2003 63.7%
Jun-2003 63.5%
Jul-2003 63.1%
Aug-2003 63.2%
Sep-2003 63.4%
Oct-2003 64.3%
Nov-2003 64.7%
Dec-2003 63.7%
Jan-2004 63.6%
Feb-2004 63.4%
Mar-2004 64.9%
Apr-2004 64.3%
May-2004 64.3%
Jun-2004 63.7%
Jul-2004 64.2%
Aug-2004 64.5%
Sep-2004 64.1%
Oct-2004 64.2%
Nov-2004 64.0%
Dec-2004 64.4%
Jan-2005 64.6%
Feb-2005 64.8%
Mar-2005 64.9%
Apr-2005 65.1%
May-2005 65.8%
Jun-2005 66.1%
Jul-2005 66.6%
Aug-2005 65.9%
Sep-2005 66.5%
Oct-2005 66.2%
Nov-2005 66.0%
Dec-2005 65.9%
Jan-2006 65.8%
Feb-2006 67.3%
Mar-2006 67.3%
Apr-2006 67.6%
May-2006 67.3%
Jun-2006 67.2%
Jul-2006 66.7%
Aug-2006 66.4%
Sep-2006 65.9%
Oct-2006 66.9%
Nov-2006 67.6%
Dec-2006 68.3%
Jan-2007 68.0%
Feb-2007 67.0%
Mar-2007 66.5%
Apr-2007 65.8%
May-2007 66.2%
Jun-2007 67.6%
Jul-2007 67.7%
Aug-2007 67.6%
Sep-2007 66.9%
Oct-2007 67.0%
Nov-2007 67.5%
Dec-2007 66.6%
Jan-2008 66.4%
Feb-2008 65.4%
Mar-2008 65.6%
Apr-2008 64.7%
May-2008 65.1%
Jun-2008 64.9%
Jul-2008 65.3%
Aug-2008 64.2%
Sep-2008 62.9%
Oct-2008 62.1%
Nov-2008 61.9%
Dec-2008 62.3%
Jan-2009 62.2%
Feb-2009 61.6%
Mar-2009 60.8%
Apr-2009 59.8%
May-2009 59.6%
Jun-2009 58.3%
Jul-2009 57.5%
Aug-2009 57.0%
Sep-2009 56.8%
Oct-2009 57.6%
Nov-2009 56.7%
Dec-2009 57.7%
Jan-2010 57.9%
Feb-2010 58.8%
Mar-2010 58.7%
Apr-2010 57.4%
May-2010 56.4%
Jun-2010 56.6%
Jul-2010 57.2%
Aug-2010 58.4%
Sep-2010 58.8%
Oct-2010 58.9%
Nov-2010 58.9%
Dec-2010 58.4%
Jan-2011 59.1%
Feb-2011 59.5%
Mar-2011 60.1%
Apr-2011 60.4%
May-2011 60.2%
Jun-2011 59.7%
Jul-2011 59.8%
Aug-2011 59.6%
Sep-2011 60.6%
Oct-2011 59.8%
Nov-2011 59.8%
Dec-2011 59.1%
Jan-2012 59.2%
Feb-2012 59.1%
Mar-2012 59.4%
Apr-2012 60.3%
May-2012 60.9%
Jun-2012 61.6%
Jul-2012 61.8%
Aug-2012 62.3%
Sep-2012 62.3%
Oct-2012 62.0%
Nov-2012 61.8%
Dec-2012 62.5%
Jan-2013 62.2%
Feb-2013 61.5%
Mar-2013 61.6%
Apr-2013 63.1%
May-2013 63.5%
Jun-2013 63.2%
Jul-2013 62.3%
Aug-2013 62.9%
Sep-2013 63.5%
Oct-2013 64.3%
Nov-2013 64.1%
Dec-2013 63.6%
Jan-2014 63.9%
Feb-2014 63.6%
Mar-2014 63.9%
Apr-2014 62.8%
May-2014 64.2%
Jun-2014 64.5%
Jul-2014 66.0%
Aug-2014 65.5%
Sep-2014 65.3%
Oct-2014 64.9%
Nov-2014 65.3%
Dec-2014 65.8%
Jan-2015 67.2%
Feb-2015 67.8%
Mar-2015 68.4%
Apr-2015 68.0%
May-2015 68.5%
Jun-2015 68.2%
Jul-2015 69.0%
Aug-2015 68.6%
Sep-2015 68.8%
Oct-2015 68.6%
Nov-2015 68.6%
Dec-2015 69.0%
Jan-2016 68.6%
Feb-2016 69.8%
Mar-2016 70.5%
Apr-2016 70.7%
May-2016 69.7%
Jun-2016 69.1%
Jul-2016 68.9%
Aug-2016 69.4%
Sep-2016 69.2%
Oct-2016 68.2%
Nov-2016 67.7%
Dec-2016 68.8%
Jan-2017 69.4%
Feb-2017 69.1%
Mar-2017 68.8%
Apr-2017 69.4%
May-2017 70.2%
Jun-2017 70.7%
Jul-2017 70.2%
Aug-2017 70.7%
Sep-2017 70.4%
Oct-2017 70.7%
Nov-2017 70.8%
Dec-2017 70.7%
Jan-2018 71.2%
Feb-2018 71.0%
Mar-2018 70.6%
Apr-2018 70.7%
May-2018 71.2%
Jun-2018 72.6%
Jul-2018 73.1%
Aug-2018 73.0%
Sep-2018 72.9%
Oct-2018 73.0%
Nov-2018 73.3%
Dec-2018 73.1%
Jan-2019 72.5%
Feb-2019 72.4%
Mar-2019 71.6%
Apr-2019 71.7%
May-2019 72.7%
Jun-2019 73.6%
Jul-2019 74.2%
Aug-2019 73.9%
Sep-2019 73.7%
Oct-2019 74.6%
Nov-2019 74.6%
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Note: Because of volatility in these data, the line reflects three month moving averages

Source: Bureau of Labor Statistics, Labor Force Flows: Unemployed to Employed (16 Years and Over) [LNS17100000], and Not in Labor Force to Employed (16 years and over) [LNS17200000], retrieved from FRED (Federal Reserve Bank of St. Louis).

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Further evidence of a steadily improving economy is the unemployment rate, which—after falling steadily for eight years from its peak in the fourth quarter of 2009—continued to fall through 2019 to a low of 3.5% in November, an average of 3.7% for the first 11 months of the year. It is now far below its Great Recession peak (10.0%), and significantly below its pre-Great Recession low of 4.4% in the spring of 2007. But despite today’s low water mark, there is still room for improvement. And evidence suggests that the unemployment rate may be overstating the strength of the labor market. The previous figure supports this claim, given that a record high share of newly employed workers are coming from outside the labor force and are not counted in the official measure of unemployment in the previous month, despite clearly being ready and willing to work.Read more

College athletes and Ph.D. students both work for the university, but only one earns a salary

Beginning in January 2021, new rules will go into effect that will allow NCAA student-athletes to profit from the use of their names, images, and likeness. While the details of these new rules will require much deliberation among each NCAA division, one thing will not be considered—salaries for college athletes from the universities.

Why won’t college athletes be paid a salary?

Several reasons are floating around. One reason is the NCAA does not consider college athletes employees of the universities. Another reason is that these players are given a lot of perks. In a recent Los Angeles Times article, Dan Radakovich, athletic director at Clemson University, argued against paying college athletes since they have access to “world-class facilities, world-class coaching, and incredible academic support.”

But there already exists a group of students who are employees of the university, have access to world-class facilities, teaching, and academic support, and no one calls them selfish when they receive their salaries. Who are these students? Ph.D. students.

Wait, are you saying Ph.D. students receive a salary?

Yes, because they work for the university. A large percentage of Ph.D. students are funded via fellowships or assistantships. Funding, which covers tuition and provides a stipend, varies across institutions and doctoral programs due to what can be viewed as “educational hierarchy.” Assistantships require that Ph.D. students’ work anywhere from 20 to 40 hours per week that include duties such as grading, managing labs, or lecturing. Additionally, doctoral students are awarded (or sometimes apply for) money that allows them to attend international or out-of-state conferences to present their research and network with others in their field.

In short, Ph.D. students sign a contract with an institution, agree to work a certain number of hours per week, maintain a certain GPA, and conduct research. In exchange, the university covers their tuition and pays them a salary. What do college football players do? Sign a contract (you may have seen signing day on ESPN), maintain a certain GPA, and kick butt on Saturday, which requires countless hours of practice! Additionally, their success can help recruit up to tens of thousands of students and generate millions of dollars for the institution.

Read more

Nearly 7 million workers will start the new year with higher wages

Note: This post was updated to clarify that Delaware’s minimum wage increase took effect on October 1, 2019.

At the start of the new year, minimum wages will have gone up in 22 states, lifting pay for 6.8 million workers across the country.i In total, workers affected by the increases will earn an extra $8.2 billion over the course of 2020 as a result of the changes. The increases range from a $0.10 inflation adjustment in Florida to $1.50 per hour raises in New Mexico and Washington. Affected workers who work year-round will see their annual pay go up between $150 and $1,700, on average, depending on the size of the minimum wage increase in their state.

The map and table below describe the increases in each state. Note that these estimates do not account for changes in local minimum wages separate from state law.ii There are 22 cities and counties with higher minimum wages taking effect on January 1, all of which can be found in EPI’s Minimum Wage Tracker. The estimates also do not include any “indirectly affected workers” making just above the new minimum wage who may receive raises as employers adjust their overall pay scales.

Figure A

State minimum wage increases will raise pay for nearly 7 million workers on January 1: States with minimum wage increases effective January 1, 2020, by type of increase

State Share of workforce directly benefiting Type of increase New minimum wage as of Jan. 1, 2020 Amount of increase Total workers directly benefiting Total increase in annual wages Average increase in annual earnings of year-round workers
Alabama -1 0.00%
Connecticut 0 0.00%
Georgia -1 0.00%
Hawaii 0 0.00%
Idaho -1 0.00%
Indiana -1 0.00%
Iowa -1 0.00%
Kansas -1 0.00%
Kentucky -1 0.00%
Louisiana -1 0.00%
Mississippi -1 0.00%
Nebraska 0 0.00%
Nevada 0 0.00%
New Hampshire -1 0.00%
North Carolina -1 0.00%
North Dakota -1 0.00%
Oklahoma -1 0.00%
Oregon 0 0.00%
Pennsylvania -1 0.00%
Rhode Island 0 0.00%
South Carolina -1 0.00%
Tennessee -1 0.00%
Texas -1 0.00%
Utah -1 0.00%
Virginia -1 0.00%
Washington D.C. 0 0.00%
West Virginia 0 0.00%
Wisconsin -1 0.00%
Wyoming -1 0.00%
Ohio 1 1.60% Inflation adjustment  $                   8.70  $       0.15                        84,000  $        12,303,000.00  $                                        150.00
South Dakota 1 1.70% Inflation adjustment  $                   9.30  $       0.20                          7,300  $           1,560,000.00  $                                        220.00
Florida 1 1.90% Inflation adjustment  $                   8.56  $       0.10                      160,700  $        23,766,000.00  $                                        150.00
Montana 1 1.90% Inflation adjustment  $                   8.65  $       0.15                          8,900  $           1,588,000.00  $                                        180.00
Minnesota 1 2.40% Inflation adjustment  $                 10.00  $       0.14                        68,100  $        11,030,000.00  $                                        162.00
New Mexico 2 2.70% Legislation  $                   9.00  $       1.50                        22,900  $        20,736,000.00  $                                        900.00
Alaska 1 3.00% Inflation adjustment  $                 10.19  $       0.30                        10,500  $           5,348,000.00  $                                        510.00
Illinois 2 3.30% Legislation  $                   9.25  $       1.00                      192,900  $      173,533,000.00  $                                        900.00
Michigan 2 3.40% Legislation  $                   9.65  $       0.20                      147,000  $        32,907,000.00  $                                        220.00
Delaware 2 4.00% Legislation  $                   9.25  $       0.50                        17,200  $        10,811,000.00  $                                        630.00
New York 2 4.00% Legislation  $                 11.80  $       0.70                      411,700  $      399,246,000.00  $                                        970.00
Vermont 1 5.20% Inflation adjustment  $                 10.96  $       0.19                        16,200  $           3,932,000.00  $                                        240.00
Missouri 3 5.40% Ballot measure  $                   9.45  $       0.85                      153,600  $      123,505,000.00  $                                        800.00
Maryland 2 7.60% Legislation  $                 11.00  $       0.90                      204,300  $      216,530,000.00  $                                    1,060.00
Arkansas 3 11.00% Ballot measure  $                 10.00  $       0.75                      119,300  $      113,142,000.00  $                                        950.00
Washington 3 11.60% Ballot measure  $                 13.50  $       1.50                      386,000  $      655,972,000.00  $                                    1,700.00
New Jersey 2 11.70% Legislation  $                 11.00  $       1.00                      460,400  $      480,308,000.00  $                                    1,040.00
Massachusetts 2 12.00% Legislation  $                 12.75  $       0.75                      420,600  $      409,981,000.00  $                                        970.00
Colorado 3 12.10% Ballot measure  $                 12.00  $       0.90                      318,400  $      382,354,000.00  $                                    1,200.00
California 2 16.90% Legislation  $                 13.00  $       1.00                  2,950,200  $  4,376,241,000.00  $                                    1,480.00
Maine 3 16.90% Ballot measure  $                 12.00  $       1.00                      102,900  $      130,250,000.00  $                                    1,270.00
Arizona 3 17.70% Ballot measure  $                 12.00  $       1.00                      511,900  $      653,915,000.00  $                                    1,300.00

 

Notes: *The New York minimum wage changes take effect on December 31, 2019. Delaware's minimum wage increase took effect on October 1. “Legislation” indicates that the new rate was established by the legislature. “Ballot measure” indicates the new rate was set by a ballot initiative passed by voters. “Inflation adjustment” indicates that the new rate was established by a formula, reflecting the change in prices over the preceding year.

Directly affected workers will see their wages rise because the new minimum wage rate exceeds their current hourly pay. This does not include additional workers who may receive a wage increase through “spillover” effects, as employers adjust overall pay scales.

Estimates for New York reflect changes in the minimum wage applicable to upstate New York ($11.80) and Nassua, Suffolk, and Westchester counties ($13.00). New York City's minimum wage reached $15 at the end of 2018 and there are no further increases scheduled.

Population growth between the data period and January 2020 estimated using state-specific projections for growth in the total population or the population ages 15—69, where available. Nominal wage growth between the data period (2017) and January 2020 estimated using the 3-year average of nominal wage growth of the bottom 20 percent of wage earners in each state from 2015 to 2018.  A full methodology is available in Minimum Wage Simulation Model Technical Methodology.

 

Source: Economic Policy Institute Minimum Wage Simulation Model using data from the Census Bureau, Bureau of Labor Statistics, and Congressional Budget Office. See Minimum Wage Simulation Model technical methodology [https://www.epi.org/publication/minimum-wage-simulation-model-technical-methodology/].

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In seven states, the changes are the result of automatic annual inflation adjustments. Alaska, Florida, Minnesota, Montana, Ohio, South Dakota, and Vermont all have provisions in their state minimum wage laws that require the wage be adjusted annually to reflect changes in prices over the preceding year. Doing so ensures that the minimum wage never declines in purchasing power, and workers paid the minimum wage can afford the same amount of goods and services year after year. 10 other states and the District of Columbia have enacted similar automatic adjustment provisions in their minimum wage laws that will begin after their minimum wages reach a higher statutory level in the coming years.

The increases in nine states—California, Delaware, Illinois, Maryland, Massachusetts, Michigan, New Jersey, New Mexico, and New York—are the result of legislation passed by state lawmakers to raise their state’s wage floors. Lawmakers in six of these states—California, Illinois, Maryland, Massachusetts, New Jersey, and New York—enacted legislation that will eventually bring their state minimum wages to $15 an hour. For 2020, minimum wages in these states will range between $11.00 and $13.00.

In six states—Arizona, Arkansas, Colorado, Maine, Missouri, and Washington—the January 1 raises result from ballot measures passed by the state’s voters. In the last several election cycles, voters have increasingly passed higher minimum wages, often in the face of inaction by their state legislatures. In fact, voters in Missouri passed a higher state minimum wage at the ballot box after state lawmakers nullified city minimum wage ordinances that had been enacted by local governments in Kansas City and St. Louis.Read more

Top 1.0% of earners see wages up 157.8% since 1979

Newly available wage data for 2018 show that annual wages for the top 1.0% were nearly flat (up 0.2%) while wages for the bottom 90% rose an above-average 1.4%. Still, the top 1.0% has done far better in the 2009–18 recovery (their wages rose 19.2%) than did those in the bottom 90%, whose wages rose only 6.8%. Over the last four decades since 1979, the top 1.0% saw their wages grow by 157.8% and those in the top 0.1% had wages grow more than twice as fast, up 340.7%. In contrast those in the bottom 90% had annual wages grow by 23.9% from 1979 to 2018. This disparity in wage growth reflects a sharp long-term rise in the share of total wages earned by those in the top 1.0% and 0.1%.

These are the results of EPI’s updated series on wages by earning group, which is developed from published Social Security Administration data and updates the wage series from 1947–2004 originally published by Kopczuk, Saez and Song (2010). These data, unlike the usual source of our other wage analyses (the Current Population Survey) allow us to estimate wage trends for the top 1.0% and top 0.1% of earners, as well as those for the bottom 90% and other categories among the top 10% of earners. These data are not top-coded, meaning the underlying earnings reported are actual earnings and not “capped” or “top-coded” for confidentiality.

Figure A

Cumulative percent change in real annual wages, by wage group, 1979–2018

Year Bottom 90% 90th–95th 95th–99th Top 1%
1979 0.0% 0.0% 0.0% 0.0%
1980 -2.2% -1.3% -0.2% 3.4%
1981 -2.6% -1.1% -0.1% 3.1%
1982 -3.9% -0.9% 2.2% 9.5%
1983 -3.7% 0.7% 3.6% 13.6%
1984 -1.8% 2.5% 6.0% 20.7%
1985 -1.0% 4.0% 8.1% 23.0%
1986 1.1% 6.4% 12.5% 32.6%
1987 2.1% 7.4% 15.0% 53.5%
1988 2.2% 8.2% 18.4% 68.7%
1989 1.8% 8.1% 18.2% 63.3%
1990 1.1% 7.1% 16.5% 64.8%
1991 0.0% 6.9% 15.5% 53.6%
1992 1.5% 9.0% 19.2% 74.3%
1993 0.9% 9.2% 20.6% 67.9%
1994 2.0% 11.2% 21.0% 63.4%
1995 2.8% 12.2% 24.1% 70.2%
1996 4.1% 13.6% 27.0% 79.0%
1997 7.0% 16.9% 32.3% 100.6%
1998 11.0% 21.3% 38.2% 113.1%
1999 13.2% 25.0% 42.9% 129.7%
2000 15.3% 26.8% 48.0% 144.8%
2001 15.7% 29.0% 46.4% 130.4%
2002 15.6% 29.0% 43.2% 109.3%
2003 15.7% 30.3% 44.9% 113.9%
2004 15.6% 30.8% 47.1% 127.2%
2005 15.0% 30.8% 48.6% 135.3%
2006 15.7% 32.5% 52.1% 143.4%
2007 16.6625450273242% 34.0650819079098% 55.3586221137521% 156.174314731946%
2008 16.0% 34.2% 53.8% 137.5%
2009 16.0% 35.3% 53.5% 116.2%
2010 15.2% 35.7% 55.7% 130.8%
2011 14.5% 36.2% 56.9% 134.0%
2012 14.6% 36.3% 58.3% 148.3%
2013 15.1% 37.1% 59.4% 137.5%
2014 16.6% 38.7% 62.3% 149.0%
2015 20.5% 43.1% 67.9% 156.2%
2016 21.0% 43.5% 68.1% 148.1%
2017 22.2% 44.2% 69.3% 157.3%
2018 23.9% 45.7% 71.3% 157.8%
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Source: EPI analysis of Kopczuk, Saez, and Song (2010, Table A3) and Social Security Administration wage statistics

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As Figure A shows, the top 1.0% of earners are now paid 157.8% more than they were in 1979. Even more impressive is that those in the top 0.1% had more than double that wage growth, up 340.7% since 1979 (Table 1). In contrast, wages for the bottom 90% only grew 23.9% in that time. Since the Great Recession, the bottom 90%, in contrast, experienced very modest wage growth, with annual wages—reflecting growing annual hours as well as higher hourly wages—up just 6.8% from 2009 to 2018. In contrast, the wages of the top 0.1% grew 19.2% during those nine years.Read more

Three Republican-appointed white men are now deciding whether you have rights on the job

Yesterday marked the end of Democratic National Labor Relations Board (NLRB) Member Lauren McFerran’s term. McFerran ended her term offering the lone dissenting voice in the Trump board’s efforts to slow down union elections to give employers more time to campaign against the union, give employers the ability to make unilateral changes without bargaining with their workers’ union, weaken remedies when employers break the law, and more.

McFerran is the former Chief Labor Counsel for the Senate Committee on Health, Education, Labor, and Pensions (HELP Committee) and is widely respected by both labor and management. Her departure leaves a second open seat on the board that the Trump administration is tasked with filling. However, the Trump administration has not yet acted to nominate McFerran for a second term, nor has it nominated a Democrat to fill the other vacant Democratic seat that has been open since August 2018. The failure of the Trump administration to act is not for lack of a qualified nominee with widespread support. Former deputy general counsel and longtime NLRB career attorney Jennifer Abruzzo has reportedly been under consideration.

As a result, the NLRB has only Republican appointees for the first time in its 85-year history, and the three Republicans are all white men—two lawyers who represented corporations before coming to the NLRB, and one former Republican congressional staffer. There is no Democratic appointee to offer alternative views on workers’ rights under the National Labor Relations Act (NLRA), or to issue dissenting opinions when the Trump board goes off track. And there are no women or people of color participating in these decisions, even though women and people of color make up the majority of workers.

EPI previously reported on the unprecedented rollback of workers’ rights happening at the hands of these three NLRB appointees. The U.S. Chamber of Commerce—the nation’s largest business lobby—is 10 for 10 in winning action on its top 10 “wish list” for the Trump board. Unfortunately, things are likely to get worse, not better. With no Democratic appointee there to provide an alternative or dissenting viewpoint on the Trump board’s actions, we are likely to see a continued rollback of workers’ rights under this bedrock statute that, after all, is supposed to protect workers’ rights.

On its second anniversary, the TCJA has cut taxes for corporations, but nothing has trickled down

It’s been two years since Republicans passed their Tax Cuts and Jobs Act (TCJA), enough time for its effects to have come into full view. As we lay out in a report released today with the Center for Popular Democracy, the economic data that has come in since its passage has not been kind to the argument of the TCJA’s proponents.

The centerpiece of the TCJA was a large cut in the corporate tax rate. Supporters of the TCJA made the supply-side argument that higher corporate profits would juice investment, which would eventually trickle down to faster productivity growth that would mechanically boost workers’ wages. The theory behind this relied on a long chain of economic events occurring, and it was clear from the very beginning that there was little reason to trust a single link in the chain.

Despite some disingenuous and cynical arguments surrounding wages and bonuses, if the TCJA is to work as its supporters claimed, then the first thing we would see is a substantial uptick in investment. After two years, there is no evidence of any investment boom. Instead, investment growth followed along its pre-TCJA trend for a couple of quarters and then cratered. Year-over-year investment growth has sunk from 5.4% at the time of the TCJA’s passage to just 1.3% in the most recent quarter.

Figure A

More evidence the Trump tax cuts aren’t working as advertised: Change in real, nonresidential fixed investment shows no investment boom

Years Real, nonresidential fixed investment
2003-Q1 -2.3%
2003-Q2 1.6%
2003-Q3 4.0%
2003-Q4 6.8%
2004-Q1 5.2%
2004-Q2 4.9%
2004-Q3 5.7%
2004-Q4 6.5%
2005-Q1 9.2%
2005-Q2 8.2%
2005-Q3 7.4%
2005-Q4 6.1%
2006-Q1 8.0%
2006-Q2 8.2%
2006-Q3 7.8%
2006-Q4 8.1%
2007-Q1 6.5%
2007-Q2 7.0%
2007-Q3 6.8%
2007-Q4 7.3%
2008-Q1 5.8%
2008-Q2 3.8%
2008-Q3 0.2%
2008-Q4 -7.0%
2009-Q1 -14.4%
2009-Q2 -17.1%
2009-Q3 -16.1%
2009-Q4 -10.3%
2010-Q1 -2.3%
2010-Q2 4.1%
2010-Q3 7.5%
2010-Q4 8.9%
2011-Q1 8.0%
2011-Q2 7.3%
2011-Q3 9.3%
2011-Q4 10.0%
2012-Q1 12.9%
2012-Q2 12.6%
2012-Q3 7.2%
2012-Q4 5.6%
2013-Q1 4.3%
2013-Q2 2.3%
2013-Q3 4.4%
2013-Q4 5.4%
2014-Q1 5.5%
2014-Q2 8.1%
2014-Q3 8.4%
2014-Q4 6.9%
2015-Q1 5.0%
2015-Q2 2.5%
2015-Q3 0.8%
2015-Q4 -0.9%
2016-Q1 -0.7%
2016-Q2 0.0%
2016-Q3 1.1%
2016-Q4 2.4%
2017-Q1 4.2%
2017-Q2 4.3%
2017-Q3 3.5%
2017-Q4 5.4%
2018-Q1 6.0%
2018-Q2 6.9%
2018-Q3 6.8%
2018-Q4 5.9%
2019-Q1 4.8%
2019-Q2 2.6%
2019-Q3 1.3%
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Note: Chart shows year-over-year change in real, nonresidential fixed investment from 2003Q1 to 2019Q3.

Source: Adapted from Figure A in Hunter Blair, "The Tax Cuts and Jobs Act Isn’t Working and There’s No Reason to Think That Will Change," Working Economics (Economic Policy Institute blog), October 31, 2019.

Source: Adapted from Figure A in Hunter Blair, The Tax Cuts and Jobs Act Isn’t Working and There’s No Reason to Think That Will Change, Economic Policy Institute, October 2019. Data are from EPI analysis of data in Table 1.1.6 from the National Income and Product Accounts (NIPA) from the Bureau of Economic Analysis (BEA).

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To be blunt, this means that the $4,000 annual boost to average incomes that the White House Council of Economic Advisers promised to working families because of the TCJA did not—and will not—happen. While it’s been worse-than-advertised for working families, the TCJA has been an even bigger boon to large corporations and rich households. In fact, corporate tax revenues have come in even lower than the Congressional Budget Office originally projected, allowing corporations and their shareholders to make out like bandits.

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The Farm Workforce Modernization Act allows employers to hire migrant farmworkers with H-2A temporary visas for year-round jobs: Impacts are unknown and other wage-setting formulas should be considered

My last blog post described in detail how the Farm Workforce Modernization Act (FWMA)—a bipartisan piece of legislation in the House of Representatives that would legalize unauthorized immigrant farmworkers, make major reforms and expansions to the H-2A temporary work visa program, and require farm employers to use E-Verify—included an updated H-2A wage rule that could lower wages for migrant farmworkers. I also called on the House of Representatives to further assess the impacts of that the FWMA could have on the farm labor market by holding public hearings in the relevant committees of jurisdiction with expert testimony before voting on the bill. One of the other major provisions in the bill that also desperately needs a closer look is the FWMA’s proposal to allow H-2A jobs—which currently must only offer temporary or seasonal work—to become eligible for year-round agricultural occupations.

A look at annual average employment in in the Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW) data set shows there were just over 419,000 jobs in greenhouse and nursery production (155,000) and animal production and aquaculture (264,000), which represent the major year-round occupational categories in agriculture. Farm employers have been clamoring for years for Congress to allow them to hire temporary H-2A workers for many of these 419,000 permanent, year-round jobs, especially on dairies. Since they haven’t had the requisite support to pass legislation that would accomplish this, members of Congress have attempted multiple times to circumvent the regular legislative process by pushing to make the change through legislative riders on annual omnibus appropriations bills.

The FWMA contains provisions to make H-2A year round: For the first three years after enactment, 20,000 three-year H-2A visas per year would be made available for year-round agricultural jobs—meaning 60,000 after three years—with half allocated for the dairy industry. Although the maximum allowed number of year-round H-2A jobs seems relatively small at first, the number could rise rapidly—in years four through 10, the cap could increase by 12.5% per year—and after the tenth year, the cap could be eliminated.

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Looking for evidence of wage-led productivity growth: EPI Macroeconomics Newsletter

While unemployment rates are sitting at their lowest levels in decades, wage growth (adjusted for inflation) remains slower than in previous periods of comparably low unemployment. Part of the reason why wage growth remains subdued is that productivity growth has been generally weak since the Great Recession ended. This week’s newsletter provides some guidance on a key question for macroeconomic policymakers like the Federal Reserve: do we need to take this slow rate of productivity growth as a given, or can we nudge productivity upward by allowing unemployment to sink even lower for longer?

Specifically, I address the widespread speculation about the possibility of “wage-led productivity growth”—the hypothesis that tight labor markets that push up labor costs lead firms to invest more in labor-saving equipment and practices. Some suggestive evidence of this wage-led productivity growth has been shown in patterns of macroeconomic data. This newsletter provides some more suggestive evidence from patterns of productivity growth broadly but also across a set of very detailed industries when the labor share of industry income rises and falls. Here are the key findings:

  • At the aggregate level, a rise in the labor share of corporate-sector income is associated with a small but significant rise in the pace of average productivity growth over the subsequent two years.
  • At detailed industrial levels (looking at 124 industries mostly in manufacturing), this relationship is even stronger: a 1 percentage-point rise in the labor share of industry income is associated with a 0.1 percentage-point increase in the average pace of productivity growth over the subsequent two years.
  • These relationships between labor share of income and productivity growth are consistent with a scenario in which firms try harder to make labor-saving investments and organizational changes when labor becomes scarcer and the need to pay higher wages threatens to pinch profits. If the labor share of corporate-sector income rose from today’s 78% to the 82% that characterized the tight labor markets of 2000, this would imply a boost to productivity of roughly 0.4 percentage points—an amount that would cut almost in half the gap between the productivity growth in recent years and the productivity growth of the late 1990s.

These results are obviously suggestive, not dispositive. The key challenge to testing the causal link that runs from higher pressure labor markets to increased effort by firms to find and adopt labor-saving practices and investments is finding truly exogenous changes in labor market tightness. This search for exogenous changes in the cost pressures firms face should be a prime preoccupation for macroeconomic policymakers in the near future. In the rest of this newsletter, we’ll describe our findings in a bit more detail and discuss their potential implications.Read more

House vote imminent on the bipartisan Farm Workforce Modernization Act—which would lower wages for migrant farmworkers: Hearings and assessments of impacts still needed

On October 30, Representatives Zoe Lofgren (D-Cal.) and Dan Newhouse (R-Wash.), along with dozens of other bipartisan cosponsors, introduced the Farm Workforce Modernization Act (FWMA), a compromise bill negotiated between representatives of agribusiness, farmworker advocates, and unions that would legalize unauthorized immigrant farmworkers, make major reforms and expansions to the H-2A temporary work visa program, and require farm employers to use E-Verify, an electronic employment verification system, to verify whether newly hired workers are authorized to be employed in the United States. The FWMA could legalize hundreds of thousands of unauthorized farmworkers while restructuring the landscape for farm employment. The House of Representatives looks set to vote on the FWMA as early as this week.

The FWMA would solve an important farm labor issue—perhaps the most important issue—legalizing unauthorized farm workers and their families. But it would also change the rules of a problematic temporary work visa program, H-2A, where migrant workers are indentured to their employers, often abused and exploited in the fields, paid low wages and robbed of their wages, sometimes live in substandard housing, and have at times been victims of human trafficking.

The H-2A rule changes in the FWMA would expand the H-2A program to year-round occupations, prohibit wage growth that might otherwise occur in the free market, and codify into law most of a new H-2A wage regulation that was recently put into place by the Trump administration—which is geared towards lowering the wages of most migrant workers in the H-2A program—and which many worker advocates opposed publicly. These provisions should raise concerns about the impact of the FWMA on the H-2A program and the future farm labor force but have not yet been explored in any congressional hearing focusing on the FWMA or through the publication of any government reports, or even credible research by non-governmental organizations.

Considering the large and emerging role of H-2A in farm labor, perhaps the single biggest question about the FWMA from a labor standards perspective is: what will happen to H-2A wage rates under the bill? The FWMA updates and codifies a new H-2A wage rule—known as the Adverse Effect Wage Rate or AEWR. In the absence of any existing credible analysis of the FWMA, I offer some comments below outlining my concerns with some of the H-2A wage provisions in the bill. In order to understand its possible impact however, a brief discussion of the current AEWR and the recently proposed Trump H-2A wage rule is needed because the FWMA mostly incorporates the proposed Trump H-2A wage rule.Read more

What to watch on jobs day: Concerning slowdown in job growth and weakening wage growth

As we approach the end of 2019, it’s important to keep the long-run perspective on economic health in mind, but also investigate new trends that have emerged in the last several months that need to be closely monitored. Two concerning trends are the slowdown in nominal wage growth as well as the slowdown in payroll employment growth.

Let’s start with payroll employment growth. On its face, the pace of job growth in 2019 hasn’t been particularly troubling. The economy continues to move in the right direction—though at a slightly slower pace than the last couple of years—soaking up sidelined workers as the unemployment rate remains at historically low levels. But, when you factor in the preliminary benchmark revisions—which showed a half million fewer jobs created between April 2018 and March 2019—the data indicate weaker employment growth this year than originally reported. The final benchmark revisions won’t be released until the January 2020 employment numbers are released in February, but the preliminary release is troubling. And large downward revisions are sometimes associated with early signs of a recession because it means the Bureau of Labor Statistics (BLS)’s model for predicting the births and deaths of firms is off, often accompanied by a turning point in the economy. These revisions don’t tell us a recession is necessary on the immediate horizon, but they are certainly something to keep in mind as the year winds down.

While the topline numbers are important to track, it’s also important to look under the hood. Manufacturing employment, for instance, has exhibited a notable slowdown in employment growth this year. The figure below shows the month-to-month change in manufacturing employment over the last two years with two important modifications. First, I’m using a three-month moving average to smooth the volatility in the series. Second, I’m removing the effect of the 46,000 striking GM workers that depressed the October numbers.

Figure A

Manufacturing employment growth tapers off: Manufacturing monthly employment growth, in thousands, three month moving average, October 2017–October 2019

Date Three month moving average
2017-10-01 23.3
2017-11-01 19.3
2017-12-01 26.0
2018-01-01 24.7
2018-02-01 25.0
2018-03-01 22.3
2018-04-01 24.3
2018-05-01 21.0
2018-06-01 25.0
2018-07-01 24.3
2018-08-01 20.0
2018-09-01 15.3
2018-10-01 18.3
2018-11-01 24.7
2018-12-01 25.3
2019-01-01 21.3
2019-02-01 15.0
2019-03-01 7.3
2019-04-01 2.7
2019-05-01 0.7
2019-06-01 5.0
2019-07-01 5.3
2019-08-01 5.3
2019-09-01 0.3
2019-10-01 2.3
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Note: Adjusted for striking workers: https://www.bls.gov/ces/publications/strike-report.htm.

Source: EPI analysis of Bureau of Labor Statistics' Current Employment Statistics public data series

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This obvious slowdown in manufacturing employment is troubling in itself, but the reason to look more closely at manufacturing isn’t simply because it’s a significant share of the economy (10% of private-sector employment) and historically has been a place for decent non-college jobs—largely due to the relatively high levels of unionization in that sector in the past. Manufacturing is one of the most cyclical sectors, bested only by construction (among major industries) in its prediction of upcoming economic slowdowns. And, construction isn’t looking too hot either. Average monthly construction job growth so far in 2019 is about half as fast as it was in 2018. This does not mean we are necessarily headed toward a recession, but this is certainly an indicator to keep an eye on in coming months.

The Federal Reserve is doing the right thing by cutting the federal funds rate this year, helping to keep the economy from stalling and for workers to hopefully see stronger wage growth. The figure below shows year-over-year nominal wage growth over the last several years. After rising to 3.4% in February 2019, the rate of growth has been tapering off. Wage growth is now back down to 3.0% over the year, significantly lower than levels consistent with inflation targets and productivity potential. This is slower than expected given that the unemployment rate has been at or below 4.0% for 20 months in a row. All else equal, the relative scarcity of workers should be driving up wages as employers have to compete to attract and retain the workers they want.Read more

OECD highlights temporary labor migration: Almost as many guestworkers as permanent immigrants

The 2019 edition of the Organization for Economic Cooperation and Development’s (OECD) annual International Migration Outlook report included a new chapter, “Capturing the ephemeral: How much labour do temporary migrants contribute in OECD countries?” It’s a good question, and one that had not yet been answered.

There is a dearth of data on temporary labor migration programs (TLMP) or schemes—aka guestworker programs, where migrants are employed temporarily in a country outside their own—and it hinders the ability of policymakers to make informed decisions. The OECD declared TLMPs are “a core concern in the public debate across OECD countries” but warns that their impacts are “understudied.” This information deficit exists despite the fact that TLMPs are controversial and make up an increasing share of labor migration, and in the United States in particular have been at the center of debates about how to reform the U.S. immigration system.

Why are TLMPs controversial and at the center of public debates? First, their size. One of OECD’s key findings is that the 4.9 million temporary labor migrants that entered OECD countries in 2017 is “almost as many… as permanent migrants in all categories combined.” Ignoring temporary labor migration in the OECD means ignoring nearly half of all migration.

Many employers want larger TLMPs and fewer regulations governing their use. But there are high economic, social, and psychological costs for the migrant workers who participate in temporary programs, including frequent human rights violations suffered in both countries of origin and destination. Further, some abuses that are technically legal are facilitated by the legal frameworks of TLMPs. In most TLMPs, employers control the visa status of their temporary migrant employees or “guestworkers”—which means getting fired makes them deportable. In part, that’s why TLMPs have been called things like “The New American Slavery.”

TLMPs raise technical issues that are not easily resolved. For example: Which industries are permitted to hire migrant workers? How will appropriate numerical limits in TLMPs be determined? What rights will migrants have once they’ve been admitted into receiving country labor markets? Can they bring their families? Will migrants be tied to one employer or be allowed to change jobs and employers? How will receiving country governments ensure that migrants return after their employment contracts end, or will migrants be allowed to become permanent residents? Do citizens in receiving countries have first preference for jobs that employers want to fill with migrants? Will migrants be paid the same wages as similarly situated local workers?Read more

Workers will lose more than $700 million annually under proposed DOL rule

In October, the Trump administration published a proposed rule regarding tips which, if finalized, will cost workers more than $700 million annually. It is yet another example of the Trump administration using the fine print of a proposal to attempt to push through a change that will transfer large amounts of money from workers to their employers. We also find that as employers ask tipped workers to do more nontipped work as a result of this rule, employment in nontipped food service occupations will decline by 5.3% and employment in tipped occupations will increase by 12.2%, resulting in 243,000 jobs shifting from being nontipped to being tipped. Given that back-of-the-house, nontipped jobs in restaurants are more likely to be held by people of color while tipped occupations are more likely to be held by white workers, this could reduce job opportunities for people of color.

The background: Employers are not allowed to pocket workers’ tips—tips must remain with workers. But employers can legally “capture” some of workers’ tips by paying tipped workers less in base wages than their other workers. For example, the federal minimum wage is $7.25 an hour, but employers can pay tipped workers a “tipped minimum wage” of $2.13 an hour as long as employees’ base wage and the tips they receive over the course of a week are the equivalent of at least $7.25 per hour. All but eight states have a subminimum wage for tipped workers.

In a system like this, the more nontipped work that is done by tipped workers earning the subminimum wage, the more employers benefit. This is best illustrated with a simple example. Say a restaurant has two workers, one doing tipped work and one doing nontipped work, who both work 40 hours a week. The tipped worker is paid $2.50 an hour in base wages, but gets $10 an hour in tips on average, for a total of $12.50 an hour in total earnings. The nontipped worker is paid $7.50 an hour. In this scenario, the restaurant pays their workers a total of ($2.50 + $7.50) * 40 = $400 per week, and the workers take home a total of ($12.50 + $7.50) * 40 = $800 (with $400 of that coming from tips).

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Analyses claiming that taxes on millionaires and billionaires will slow economic growth are fundamentally flawed

In recent weeks, a number of policy analyses of progressive economic policies—a surtax on high-incomes, a wealth tax, and Social Security expansion—have claimed these policies would damage economic growth. Policymakers should give these analyses very little weight in debates about these issues, for a number of reasons.

First, and most important, is the fact that all of these analyses are grounded in an economic view of the world that sees growth as constrained by the economy’s productive capacity (or the supply side of the economy) and not by the spending of households, businesses and government (the economy’s demand side). These estimates have other problems too—they are not even particularly convincing supply-side estimates and even if the economy’s growth really was constrained by supply, these estimates would still be misleading about the effects of these policies on welfare. But the biggest reason why policymakers should give these analyses zero weight is because they assume that growth is almost never demand-constrained.

Before the Great Recession, the assumption that growth was nearly always supply constrained was almost universally held by economists and macroeconomic policymakers. It was recognized that demand (or aggregate spending) could occasionally be too weak to fully employ the economy’s productive capacity and hence cause rising unemployment, but it was generally thought that such periods were rare and would end quickly after the Federal Reserve sensibly cut interest rates. Because shortfalls of demand relative to supply were rare and short and easy to fix, the reasoning went, any real constraint on the economy’s growth over the long-run must be the pace of growth of supply. Growth in supply is generally driven by growth in the quality of the workforce, the productive stock of plants, equipment and research, and growth in technological progress, which together lead to growing productivity—or the amount of income or output generated in an average hour of work.

The assumption that supply constraints are much more likely to bind overall growth than demand constraints drove almost all macroeconomic policymaking in the decades before the Great Recession. For example, the Federal Reserve for decades feared lower unemployment far more than lower inflation. Lower unemployment was a signal that demand was rising relative to supply, and if one thinks growth was generally supply-constrained, this meant that demand growth would quickly outstrip supply growth and lead to rising inflation. Lower inflation, conversely, meant that supply growth was outpacing demand growth—but that was always a temporary and easy-to-fix condition. The decades-long bipartisan overreaction to rising federal budget deficits is also a byproduct of assuming the economy’s growth is supply constrained. Deficits boost demand growth. If one assumes that demand is generally marching in lock-step with supply, then larger deficits that boost demand imply that supply constraints will soon bind and cause inflation (or interest rate increases). Smaller deficits, conversely, reduce demand growth. But if the danger of demand growth slowing too much is low and easy-to-fix, then that’s not a problem.Read more

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