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.
Looking for evidence of wage-led productivity growth
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.
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 |
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
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 dollars 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).
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
Bipartisan Senate budget bill could damage the economy during recessions
Last week, the Senate Budget Committee passed a bipartisan set of budget reforms out of committee. While they include some important steps forward, such as effectively eliminating the archaic debt limit, their centerpiece is a deeply damaging provision that, if passed into law, would make recessions far more damaging by forcing Congress to consider steep cuts just when the economy would be most hurt by them.
Under the reforms, instead of passing a budget every year, Congress would be on a two-year budget cycle. This is not totally objectionable. The damaging provisions are the “special reconciliation instructions“ provided in the second year of this budget cycle. In the first year, the Congressional Budget Office (CBO) would project the debt-to-GDP ratio from the budget. In the second year, CBO would report on whether the federal government is meeting those debt-to-GDP targets, and if not, trigger the special reconciliation instructions. These instructions would require the Senate Budget Committee to recommend an amount of deficit reduction in response to missing the debt-to-GDP targets and create a fast track for passing those deficit reductions.
Others have rightly focused on the extent to which this could line up budget cuts to programs that U.S. families rely on, like Medicaid, Medicare, and the Affordable Care Act. For example, revenues have come in even lower than CBO expected following the Republican Tax Cuts and Jobs Act (TCJA). If this reform bill were in place, Congress would be expected to respond to these larger-than-expected tax cuts for the rich with deficit reduction. This has been in the Republican leadership playbook all along, as they have made it abundantly clear that cuts to vital programs for low- and moderate-income families are the intended next step after passing regressive tax cuts for the rich and corporations. Read more
Where do the Democratic presidential candidates stand on migrant workers and labor migration?
The Trump administration’s harsh enforcement tactics and human rights violations at the border have rightly gotten most of the attention in press coverage about immigration lately, and enforcement has been the basis for the very few questions that Democratic presidential candidates have been asked about immigration so far in the primary debates. What’s gotten less attention and no discussion after five Democratic primary debates are the 17% of workers in the U.S. labor force who are foreign-born, including the 5% of the workforce who are vulnerable to wage theft and other abuses because they lack an immigration status, or the 1% who have an immigration status that is mostly owned and controlled by their employer, by virtue of being employed through U.S. temporary work visa programs.
Only a miniscule number of mentions have been made in the candidates’ published immigration plans about the intersection of immigration and the labor market, and there’s been no discussion on the debate stages about what the Democratic candidates would propose to reform future U.S. labor migration—i.e., migration for the purpose of work. In the past this has sometimes been referred to as “future flows” of migrants: the pathways available to persons from abroad who want to come to the United States to be employed, or avenues for employers that wish to hire migrants, either through temporary work visa programs or as permanent immigrants.
The fifth Democratic Presidential Primary Debate on November 20 was no different than the past four: virtually no discussion of immigration in general—with only one narrow question about the border wall—and no discussion at all about labor migration. Will this change during the sixth debate in December? I hope so, because a positive vision of U.S. labor migration that is fair to immigrants and Americans and fosters solidarity—rather than a corporate-driven race to the bottom on wages and labor standards, which employer groups often push for—is something worth talking about and an argument that progressives can win.
Migrants in the United States are living and working during a time when the president in office clearly doesn’t value their contributions, but nevertheless benefits economically from their labor: President Trump has hired undocumented workers at his companies—some of whom have alleged they were exploited—as well as guestworkers with temporary visas in programs he has expanded, where migrant workers are tied to employers and often underpaid—all while demonizing and scapegoating migrants as criminals and rapists. For the most part, President Trump has gotten a pass on his blatant hypocrisy.
By failing to bring up labor migration issues, the Democratic presidential candidates have not managed to expose Trump’s glaring weakness on the issue. While a significant share of the blame for not discussing the topic at the debates falls at the feet of the moderators, the candidates are making a mistake by not mentioning the contributions that migrant workers make or the challenges they face in the workplace. The candidates also haven’t offered many details about how they would re-make the immigration system so that future migrant workers can enter the U.S. labor market with equal rights and fair pay in their plans for immigration that are published on their campaign websites. A quick summary of what’s included in the immigration plans of a few of the major candidates makes this abundantly clear.Read more
Latina workers have to work nearly 11 months into 2019 to be paid the same as white non-Hispanic men in 2018
November 20 is Latina Equal Pay Day, the day that marks how long into 2019 a Latina would have to work in order to be paid the same wages her white male counterpart was paid last year. That’s nearly 11 months longer, meaning that Latina workers had to work all of 2018 and then this far—to November 20!—into 2019 to get paid the same as white non-Hispanic men did in 2018. Put another way, a Latina would have to be in the workforce for 57 years to earn what a non-Hispanic white man would earn after 30 years in the workforce. Unfortunately, Hispanic women are subject to a double pay gap—an ethnic pay gap and a gender pay gap. And, this pay gap widened over previous year when it “only” took until November 1 for Hispanic women catch up to non-Hispanic men.
The date November 20 is based on the finding that Hispanic women workers are paid 53 cents on the white non-Hispanic male dollar, using the 2017 March Current Population Survey for median annual earnings for full-time, year-round workers. We get similar results when we look at average hourly wages for all workers (not just full-time workers) using the monthly Current Population Survey Outgoing Rotation Group for 2018—which show Hispanic women workers being paid 56 cents on the white male dollar.Read more
The Tax Cuts and Jobs Act isn’t working and there’s no reason to think that will change
Proponents of the Tax Cuts and Jobs Act (TCJA) made bold claims about the effects that the TCJA’s corporate rate cuts would have on the paychecks of U.S. households. The economic theory rests on corporate rate cuts bringing forth enough additional savings to finance new investment spending. Specifically, higher after-tax corporate profits are passed down to shareholders in the form of higher dividends. These higher dividends attract more savings from abroad and incentivize U.S. households to save more. These extra savings finance new investments in plants and equipment, which boost the productivity of workers, and eventually that increased productivity boosts workers’ wages.
We pointed out at the time that in practice, this theory wasn’t likely to hold. After the TCJA passed, we indicated that by increasing deficits, the specifics of the TCJA didn’t even conform to the economic theory that was supposed to support it.
But that wasn’t enough to stop the TCJA’s proponents from making disingenuous arguments about the effects it was having on the economy. Proponents pointed to corporate claims that they were giving out bonuses or raising wages in the wake of the TCJA. The economic theory above shows clearly how this was nothing but a corporate PR ploy. Even in theory, it takes time for corporate profits to trickle down into worker wages, and we weren’t the only ones pointing this out. Unsurprisingly, data since then show those bonuses didn’t materialize for workers.Read more
What to Watch on Jobs Day: Anticipated distortions to payroll employment and wage growth
The uneasy question on everyone’s lips these days seems to be about when the next recession is coming. Ironically, every month that gets added to the longest economic recovery in modern history brings increasing scrutiny to even the slightest sign of a downturn. As we turn our attention to the Bureau of Labor Statistics (BLS) October Employment Situation Report this week, two of those signs—a drop in payroll employment and a slowdown in nominal wage growth—are deserving of deeper exploration.
First, we expect some noise in the October payroll estimates due to two temporary, but fully anticipated and measurable effects. According to the BLS CES Strike Report, October payroll estimates will be reduced by 46,000 because of the General Motors (GM) strike, which started in mid-September 2019 and ended last Friday. What that means, in practical terms, is that private sector payroll employment for the month of October, in the absence of the GM strike, was actually 46,000 higher than what will be reported. Another event that could have some effect on the number of jobs added in October will be temporary hiring for the Decennial Census, which could potentially inflate the number of public sector jobs.
While the October jobs report may not be the most straightforward indicator of current job growth patterns, in August BLS reported a major downward revision in the number of jobs added over the past year. Specifically, the release of the preliminary estimate of its benchmark revision to payroll employment revealed that there were a half million fewer jobs created between April 2018 and March 2019 than was originally reported. Given weaker private sector employment growth in September relative to the prior 3- to 6-month averages, we will be watching for whether October employment growth, net of the effects of the GM strike and Census hiring, is stronger or weaker than recent trends.Read more
Wage growth targets are good economics—if you get the details right: EPI Macroeconomics Newsletter
Josh Bivens, director of research at EPI
Earlier this month, Olivier Blanchard—the former chief economist at the International Monetary Fund and an influential figure in macroeconomics—suggested that the Federal Reserve should consider targeting inflation in nominal wages rather than (or in addition to) inflation in prices. I was predictably intrigued by this: I proposed a nominal wage inflation target for the Fed a few years back.
This edition of the newsletter quickly sketches out the logic of a nominal wage inflation target to guide Fed decision-making on interest rates, and it highlights one particularly important detail: the assumed rate of productivity growth used to specify the target. If the rate of productivity growth is endogenous to the degree of labor market slack (as some evidence indicates), then using real-time estimates of productivity growth as an input into the wage target could threaten to lock in the damage to wage growth done by too-slack labor markets.
A little-known agency that is supposed to protect workers is instead eroding workers’ basic labor rights
Donald Trump ran for president promising to uplift workers. But his actions have done the exact opposite.
According to a new EPI report, Trump appointees on the board of a small, independent agency called the National Labor Relations Board (NLRB)—and the NLRB’s Trump-appointed general counsel (GC)—are working hard to undermine workers’ rights to join together in collective action to improve pay and working conditions.
“Scabby the Rat,” Chad Laird, licensed under CC BY-NC-SA 2.0
As authors Celine McNicholas, Margaret Poydock, and Lynn Rhinehart warn, Trump’s appointees have ticked off one by one the 10 items on a U.S. Chamber of Commerce hit list of NLRB policies to overturn. And they’re not done yet: The NLRB plans to go after more worker protections in the months ahead.
Under the National Labor Relations Act (NLRA), most nonsupervisory private-sector workers have the right to join together in collective action—whether that is through forming a union or some other means—to negotiate with employers about the terms and conditions of their employment. The NLRB was established to safeguard those rights by investigating and prosecuting violations of the law.
Instead, the three Trump appointees to the agency’s board and the agency’s Trump-appointed GC are systematically rolling back workers’ rights through a flurry of employer-friendly case decisions, rulemakings, and guidance memos. At the same time, the agency has downsized by 10 percent of its staff: The ratio of covered workers to NLRB staff is now roughly 96,000-to-1, up from 65,000-to-1 in 2011.
Here, in general terms, are just a few of the things the Trump NLRB is doing (those of you who know your way around labor law can go directly to the report):Read more
Seven questions EPI’s experts would ask at tonight’s debate
For all of the hype surrounding U.S. electoral debates, the flashy cable news forum and gladiator-style tone of the questions often lead to candidates jostling for soundbites rather than debating actual substance.
Economic inequality and the erosion of worker power are not only central to EPI’s mission, they are also key to the American political landscape today. With that in mind we tapped our experts for a bit of a wishful thinking exercise, collecting questions on a variety of issues that are core to our research.
Here are seven issues we would like to see raised in tonight’s presidential debate:
- Stagnant wages are one of the main challenges facing American workers. What do you see as the chief culprit and what policies would you implement to address this problem?
- What do you see as the key causes of income inequality, and what are your top two solutions? Is CEO pay too high? What would you do to rein it in?
- How do you plan to address America’s racist institutions, and the persistent lack of minority and woman representation in the most powerful offices of the land?
- Trump’s trade policies are chaotic, but he appears to have tapped into a problem that resonates with voters—trade deals that favor corporations over people. What is your positive alternative to Trump on trade?
- Name one way in which your thinking about the economy has changed over time. What’s an economic policy you’ve supported in the past that you no longer support?
- Teachers in Chicago are on the brink of a massive strike, part of a nationwide trend, as they push for social and educational justice for students of color. What is your long-term plan to fully support America’s public schools and how would you ensure that students of color get additional resources needed to overcome decades of disinvestment?
- Upon taking office, you will inherit a humanitarian crisis at the border that is mostly the result of Trump’s draconian policies and his administration’s mismanagement. What would you do to address the reports of human rights violations by agents of the United States government and to end the poor conditions inside ICE immigration jails and Border Patrol facilities?
Black and Hispanic men could face disproportionate job loss due to transportation automation
On August 12, 2019, Democratic presidential candidate Andrew Yang tweeted, “I’ve done the MATH, it’s not immigrants taking our jobs, it’s automation. Instead of blaming immigrants, let’s give our citizens the means to thrive through the fourth industrial revolution.” This, like much of Yang’s and others’ current discourse regarding automation, is focused on an exaggerated fear that automation can and soon will replace workers’ roles in production, resulting in widespread job loss. But for hundreds of years, technological progress has continually reshaped the way work is done—and yet this progress has never resulted in a long-term decline in the labor force. Focusing on overstated risks of job loss from automation distracts from efforts to advocate for higher wages, better benefits, and increased bargaining power—issues that have been, and will continue to be, essential to the well-being of workers and their families.
However, while there is no reason to believe that automation will lead to widespread, sustained decline in the overall number of jobs, there will be specific jobs, industries, and workers for whom the impact of automation will come with real costs, at least in the short term. One industry in which concerns about automation may be warranted in the near term is transportation. Ford and Volvo have both announced plans to put fully autonomous vehicles on the road as early as 2021; Honda has announced a partnership with GM to begin developing autonomous vehicles; and Nissan recently introduced “no-hands driving” on highways in its ProPilot 2.0. While consumer skepticism may slow down the industry’s timelines, many advances have already been made: Most new cars have computerized driver assistance options; Tesla’s Autosteer has logged at least one billion miles of supervised autonomous driving; and Caterpillar is already producing autonomous vehicles for hauling mining materials.Read more
What to Watch on Jobs Day: How big is the teacher shortfall?
On Friday, the Bureau of Labor Statistics will release September’s numbers on the state of the labor market. As usual, I’ll be paying close attention to nominal wage growth as well as the prime-age employment-to-population ratio, which are two of the best indicators of labor market health. Friday’s report will also give us a chance to examine the “teacher shortfall”—the gap between local public education employment and what is needed to keep up with growth in the student population.
Thousands of local public education jobs were lost during the recession which began in 2008, and those losses continued deep into the official economic recovery, even as more students started school each year. This has been true of public sector jobs in general—continued austerity at all levels of government has been a drag on public sector employment, which has failed to keep up with population growth.
Teacher strikes in several states over the last few years have highlighted deteriorating teacher pay as a critical issue. My colleagues Sylvia Allegretto and Larry Mishel find that average weekly wages of public school teachers have fallen over the last two decades and the teacher wage penalty continues to grow, reaching a record 21.4% in 2018. My colleagues Emma García and Elaine Weiss have further documented shortcomings and teacher shortages and recently how much teachers have to pay out of their own pockets for school supplies for their classrooms. Low pay makes it harder to attract and retain teachers who have the qualifications associated with teacher effectiveness in the classroom.
The costs of a significant teacher employment gap are high, consequences measurable: larger class sizes, fewer teacher aides, fewer extracurricular activities, and changes to curricula. Last year, the local public education job shortfall remained large. To solve this problem, state and local governments need to fund more teaching positions and raise pay to close the teacher pay gap and attract and retain the qualified teachers our children deserve. On Friday, I will compare where jobs in public education should be, using the pre-recession ratio, student population growth, and the most recent jobs numbers.
Household income growth was slower and less widespread in 2018 than in 2017
The state income data from the American Community Survey (ACS), released this morning by the Census Bureau, showed that in 2018, household incomes across the country rose—albeit more slowly, and in fewer states, than in the previous year. From 2017 to 2018, inflation-adjusted median household incomes grew in 33 states and the District of Columbia (14 of these changes were statistically significant.) This marks a decline from the broader growth seen between 2016 and 2017 when median household incomes grew in 40 states and the District of Columbia, with 24 of those changes being statistically significant.
The ACS data showed an increase of 0.2% in the inflation-adjusted median household income for the country as a whole—an increase of just $130 for a typical U.S. household and a slowdown in growth compared to the past three years: household incomes increased by 3.8% in 2015, 2.0% in 2016, and 2.5% in 2017. [i] Despite these increases, households in 23 states still had inflation-adjusted median incomes in 2018 below their 2007 pre-recession values, which makes this year’s slowdown particularly disappointing.
From 2017 to 2018, the largest percentage gains in household income occurred in Idaho, where the typical household experienced an increase of $2,085 in their annual income—an increase of 3.9%. Maryland remains the state with the highest median household income at $83,242, having experienced a slight increase (0.6%) from 2017 to 2018. The District of Columbia has the highest median household income in the country at $85,203—though comparing D.C. to states is problematic, since D.C. is a city, not a state. Read more
Poverty continues to fall in most states, though progress appears to be slowing
The 2018 American Community Survey (ACS) data released today shows that the slowdown in income growth from 2017 to 2018 reported earlier this month by the Census Bureau also indicates a slowdown in progress reducing poverty in many states. From 2017 to 2018, the poverty rate decreased in 36 states and the District of Columbia, with 14 of those states experiencing statistically significant declines. For comparison, from 2016 to 2017, poverty fell in 42 states plus the District of Columbia, with 20 states and the District of Columbia having statistically significant reductions.
The poverty rate rose in 14 states, with increases of 1.3 percentage points in Rhode Island, and 0.8 percentage points each, in Connecticut and Arkansas—although only Connecticut’s increase was statistically significant.
The continued reductions in poverty rates for most states are welcome news; however, most states have still not recovered to their 2007, pre-Great Recession poverty rates. Moreover, 38 states had higher poverty rates in 2018 than in 2000.
The national poverty rate, as measured by the ACS, fell 0.3 percentage points to 13.1 percent in 2018, making it nearly the same as the ACS poverty rate in 2007, when it was 13.0 percent. It remains 0.9 percentage points above the rate from 2000.
Between 2017 and 2018, West Virginia had the largest decline in its poverty rate (-1.3 percentage points), followed by Delaware (-1.1 percentage points), Louisiana (-1.1 percentage points), Idaho (-1.0 percentage points), and Arizona (-0.9 percentage points). Poverty increased most in in Rhode Island (1.3 percentage points), Connecticut (0.8 percentage points), Arkansas (0.8 percentage points), Maine (0.5 percentage point), Montana (0.5 percentage point), and Iowa (0.5 percentage point). Read more
More than eight million workers will be left behind by the Trump overtime rule: Workers would receive $1.4 billion less than under the 2016 rule
Yesterday, the U.S. Department of Labor announced 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.
For quick details on the history of this rulemaking, see this statement. The two tables below show just how many workers this administration is turning its back on with this rule, and how much money workers will lose. Using the same methodology used by the Department of Labor in their estimates of the economic impact of the rule, I estimate 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. As the table shows, this administration is turning its back on 4.2 million women, 2.7 million parents of children under the age of 18, 2.9 million people of color, and 4.6 million workers without a college degree.
Number of salaried workers left behind by the Trump overtime rule, by demographic group
| Workers left behind by 2019 rule | Under the 2016 rule | Under the 2019 rule | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Total workers left behind | Workers who would have gotten new protections under 2016 rule | Workers who would have gotten strengthened protections under 2016 rule | Total affected workers | Workers with new protections | Workers with strengthened protections | Total affected workers | Workers with new protections | Workers with strengthened protections | Total salaried workers | |
| All | 8,210,000 | 3,230,000 | 4,980,000 | 13,470,000 | 4,550,000 | 8,920,000 | 5,260,000 | 1,320,000 | 3,950,000 | 59,140,000 |
| Gender | ||||||||||
| Male | 4,000,000 | 1,410,000 | 2,590,000 | 6,560,000 | 1,970,000 | 4,590,000 | 2,560,000 | 560,000 | 1,990,000 | 32,570,000 |
| Female | 4,210,000 | 1,820,000 | 2,390,000 | 6,910,000 | 2,580,000 | 4,340,000 | 2,710,000 | 760,000 | 1,950,000 | 26,570,000 |
| Parental Status | ||||||||||
| Not a parent | 5,500,000 | 2,170,000 | 3,330,000 | 9,060,000 | 3,060,000 | 6,000,000 | 3,550,000 | 890,000 | 2,660,000 | 37,470,000 |
| Father | 1,330,000 | 450,000 | 870,000 | 2,130,000 | 630,000 | 1,510,000 | 810,000 | 180,000 | 630,000 | 12,210,000 |
| Mother | 1,380,000 | 600,000 | 770,000 | 2,280,000 | 860,000 | 1,420,000 | 900,000 | 250,000 | 650,000 | 9,460,000 |
| Race/ethnicity | ||||||||||
| White | 5,260,000 | 2,230,000 | 3,030,000 | 8,220,000 | 3,120,000 | 5,100,000 | 2,960,000 | 890,000 | 2,070,000 | 40,680,000 |
| Black | 1,000,000 | 340,000 | 650,000 | 1,680,000 | 480,000 | 1,200,000 | 680,000 | 140,000 | 540,000 | 5,460,000 |
| Hispanic | 1,240,000 | 360,000 | 880,000 | 2,410,000 | 530,000 | 1,880,000 | 1,170,000 | 170,000 | 1,000,000 | 7,230,000 |
| Asian | 560,000 | 240,000 | 320,000 | 930,000 | 340,000 | 580,000 | 370,000 | 100,000 | 260,000 | 4,810,000 |
| Others | 140,000 | 50,000 | 90,000 | 230,000 | 70,000 | 160,000 | 90,000 | 20,000 | 70,000 | 960,000 |
| Age | ||||||||||
| 16–24 | 500,000 | 200,000 | 290,000 | 1,000,000 | 320,000 | 680,000 | 500,000 | 120,000 | 380,000 | 2,800,000 |
| 25–34 | 2,400,000 | 1,040,000 | 1,360,000 | 3,840,000 | 1,420,000 | 2,420,000 | 1,440,000 | 380,000 | 1,060,000 | 13,510,000 |
| 35–44 | 1,830,000 | 710,000 | 1,120,000 | 2,930,000 | 980,000 | 1,950,000 | 1,100,000 | 270,000 | 830,000 | 14,550,000 |
| 45–54 | 1,800,000 | 670,000 | 1,130,000 | 2,880,000 | 940,000 | 1,940,000 | 1,080,000 | 260,000 | 810,000 | 14,330,000 |
| 55–64 | 1,330,000 | 470,000 | 860,000 | 2,170,000 | 670,000 | 1,500,000 | 840,000 | 200,000 | 650,000 | 10,720,000 |
| 65+ | 350,000 | 130,000 | 220,000 | 660,000 | 220,000 | 440,000 | 310,000 | 90,000 | 220,000 | 3,220,000 |
| Education | ||||||||||
| Less than high school | 310,000 | 40,000 | 270,000 | 800,000 | 60,000 | 740,000 | 500,000 | 30,000 | 470,000 | 1,980,000 |
| High school | 1,900,000 | 450,000 | 1,450,000 | 3,470,000 | 680,000 | 2,780,000 | 1,570,000 | 230,000 | 1,340,000 | 9,240,000 |
| Some college | 2,400,000 | 830,000 | 1,570,000 | 4,040,000 | 1,210,000 | 2,830,000 | 1,640,000 | 380,000 | 1,270,000 | 12,080,000 |
| College degree | 2,650,000 | 1,330,000 | 1,320,000 | 3,800,000 | 1,790,000 | 2,000,000 | 1,150,000 | 460,000 | 680,000 | 20,810,000 |
| Advanced degree | 950,000 | 580,000 | 370,000 | 1,360,000 | 800,000 | 570,000 | 410,000 | 220,000 | 190,000 | 15,030,000 |
| States | ||||||||||
| All | 8,210,000 | 3,230,000 | 4,980,000 | 13,470,000 | 4,550,000 | 8,920,000 | 5,260,000 | 1,320,000 | 3,950,000 | 59,140,000 |
| Alabama | 110,000 | 40,000 | 70,000 | 180,000 | 70,000 | 110,000 | 70,000 | 20,000 | 50,000 | 720,000 |
| Alaska | 10,000 | – | 10,000 | 20,000 | 10,000 | 10,000 | 10,000 | – | 10,000 | 100,000 |
| Arizona | 150,000 | 70,000 | 80,000 | 240,000 | 90,000 | 150,000 | 90,000 | 20,000 | 70,000 | 1,130,000 |
| Arkansas | 80,000 | 30,000 | 40,000 | 130,000 | 50,000 | 80,000 | 50,000 | 10,000 | 40,000 | 450,000 |
| California | 780,000 | 300,000 | 480,000 | 1,290,000 | 430,000 | 870,000 | 510,000 | 130,000 | 380,000 | 6,640,000 |
| Colorado | 170,000 | 60,000 | 110,000 | 280,000 | 90,000 | 190,000 | 110,000 | 30,000 | 80,000 | 1,240,000 |
| Connecticut | 70,000 | 30,000 | 40,000 | 120,000 | 40,000 | 70,000 | 40,000 | 10,000 | 30,000 | 720,000 |
| Delaware | 30,000 | 10,000 | 20,000 | 40,000 | 10,000 | 30,000 | 20,000 | – | 10,000 | 180,000 |
| Washington, D.C. | 20,000 | 10,000 | 10,000 | 30,000 | 10,000 | 20,000 | 10,000 | – | 10,000 | 240,000 |
| Florida | 680,000 | 270,000 | 420,000 | 1,160,000 | 380,000 | 780,000 | 480,000 | 110,000 | 370,000 | 3,880,000 |
| Georgia | 340,000 | 130,000 | 210,000 | 570,000 | 180,000 | 390,000 | 230,000 | 50,000 | 180,000 | 2,100,000 |
| Hawaii | 40,000 | 10,000 | 30,000 | 60,000 | 20,000 | 50,000 | 30,000 | 10,000 | 20,000 | 250,000 |
| Idaho | 40,000 | 20,000 | 20,000 | 70,000 | 20,000 | 40,000 | 30,000 | 10,000 | 20,000 | 250,000 |
| Illinois | 330,000 | 140,000 | 190,000 | 510,000 | 180,000 | 330,000 | 190,000 | 40,000 | 140,000 | 2,500,000 |
| Indiana | 160,000 | 70,000 | 90,000 | 270,000 | 100,000 | 170,000 | 110,000 | 30,000 | 80,000 | 1,090,000 |
| Iowa | 80,000 | 30,000 | 40,000 | 120,000 | 50,000 | 70,000 | 40,000 | 10,000 | 30,000 | 510,000 |
| Kansas | 60,000 | 30,000 | 40,000 | 110,000 | 40,000 | 70,000 | 40,000 | 10,000 | 30,000 | 480,000 |
| Kentucky | 110,000 | 40,000 | 60,000 | 170,000 | 60,000 | 110,000 | 70,000 | 20,000 | 50,000 | 660,000 |
| Louisiana | 120,000 | 40,000 | 80,000 | 200,000 | 60,000 | 140,000 | 80,000 | 20,000 | 60,000 | 730,000 |
| Maine | 30,000 | 10,000 | 20,000 | 50,000 | 20,000 | 30,000 | 20,000 | – | 10,000 | 220,000 |
| Maryland | 150,000 | 60,000 | 90,000 | 250,000 | 90,000 | 160,000 | 90,000 | 30,000 | 70,000 | 1,400,000 |
| Massachusetts | 180,000 | 80,000 | 110,000 | 300,000 | 110,000 | 190,000 | 120,000 | 30,000 | 80,000 | 1,670,000 |
| Michigan | 190,000 | 90,000 | 110,000 | 300,000 | 120,000 | 180,000 | 100,000 | 30,000 | 70,000 | 1,530,000 |
| Minnesota | 130,000 | 50,000 | 80,000 | 180,000 | 70,000 | 110,000 | 50,000 | 10,000 | 40,000 | 1,060,000 |
| Mississippi | 70,000 | 20,000 | 40,000 | 120,000 | 30,000 | 80,000 | 50,000 | 10,000 | 40,000 | 410,000 |
| Missouri | 160,000 | 80,000 | 90,000 | 260,000 | 100,000 | 160,000 | 100,000 | 20,000 | 70,000 | 1,030,000 |
| Montana | 20,000 | 10,000 | 10,000 | 30,000 | 10,000 | 20,000 | 10,000 | – | 10,000 | 130,000 |
| Nebraska | 50,000 | 20,000 | 30,000 | 80,000 | 30,000 | 50,000 | 30,000 | 10,000 | 20,000 | 330,000 |
| Nevada | 70,000 | 20,000 | 50,000 | 120,000 | 40,000 | 80,000 | 50,000 | 10,000 | 30,000 | 430,000 |
| New Hampshire | 30,000 | 20,000 | 20,000 | 50,000 | 20,000 | 30,000 | 20,000 | 10,000 | 10,000 | 280,000 |
| New Jersey | 280,000 | 100,000 | 180,000 | 450,000 | 140,000 | 320,000 | 170,000 | 40,000 | 130,000 | 2,200,000 |
| New Mexico | 40,000 | 10,000 | 20,000 | 70,000 | 20,000 | 50,000 | 30,000 | 10,000 | 20,000 | 280,000 |
| New York | 600,000 | 210,000 | 390,000 | 1,000,000 | 290,000 | 710,000 | 400,000 | 80,000 | 320,000 | 4,250,000 |
| North Carolina | 280,000 | 100,000 | 170,000 | 440,000 | 150,000 | 290,000 | 170,000 | 40,000 | 120,000 | 1,820,000 |
| North Dakota | 20,000 | 10,000 | 10,000 | 30,000 | 10,000 | 20,000 | 10,000 | – | 10,000 | 120,000 |
| Ohio | 230,000 | 100,000 | 120,000 | 370,000 | 150,000 | 220,000 | 150,000 | 50,000 | 100,000 | 1,770,000 |
| Oklahoma | 100,000 | 40,000 | 60,000 | 170,000 | 50,000 | 110,000 | 70,000 | 20,000 | 50,000 | 640,000 |
| Oregon | 90,000 | 40,000 | 50,000 | 150,000 | 50,000 | 90,000 | 50,000 | 20,000 | 40,000 | 670,000 |
| Pennsylvania | 310,000 | 130,000 | 180,000 | 490,000 | 190,000 | 310,000 | 190,000 | 60,000 | 130,000 | 2,220,000 |
| Rhode Island | 20,000 | 10,000 | 10,000 | 40,000 | 20,000 | 20,000 | 10,000 | – | 10,000 | 190,000 |
| South Carolina | 150,000 | 60,000 | 90,000 | 230,000 | 80,000 | 150,000 | 80,000 | 20,000 | 60,000 | 870,000 |
| South Dakota | 20,000 | 10,000 | 10,000 | 30,000 | 10,000 | 20,000 | 10,000 | – | 10,000 | 120,000 |
| Tennessee | 180,000 | 80,000 | 100,000 | 280,000 | 100,000 | 180,000 | 110,000 | 30,000 | 80,000 | 1,090,000 |
| Texas | 820,000 | 300,000 | 520,000 | 1,430,000 | 430,000 | 1,000,000 | 610,000 | 130,000 | 480,000 | 5,480,000 |
| Utah | 60,000 | 30,000 | 40,000 | 100,000 | 40,000 | 60,000 | 40,000 | 10,000 | 30,000 | 500,000 |
| Vermont | 20,000 | 10,000 | 10,000 | 30,000 | 10,000 | 20,000 | 10,000 | – | 10,000 | 110,000 |
| Virginia | 220,000 | 80,000 | 140,000 | 380,000 | 120,000 | 260,000 | 160,000 | 40,000 | 120,000 | 1,890,000 |
| Washington | 150,000 | 60,000 | 100,000 | 230,000 | 80,000 | 160,000 | 80,000 | 20,000 | 60,000 | 1,300,000 |
| West Virginia | 40,000 | 10,000 | 20,000 | 60,000 | 20,000 | 40,000 | 30,000 | 10,000 | 20,000 | 240,000 |
| Wisconsin | 120,000 | 50,000 | 70,000 | 180,000 | 70,000 | 110,000 | 60,000 | 20,000 | 40,000 | 930,000 |
| Wyoming | 10,000 | – | 10,000 | 20,000 | 10,000 | 10,000 | 10,000 | – | 10,000 | 80,000 |
Note: Subtotals may not add up to totals due to rounding. Following the methodology used by the U.S. Department of Labor, the estimates include all workers affected by the federal salary threshold increase, and do not account for higher state salary thresholds.
Source: EPI analysis of pooled Current Population Survey Outgoing Rotation Group microdata, 2016–2018, following the methodology used in the U.S. Department of Labor’s 2019 final rule, “Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees,” 29 CFR Part 541 (published September 24, 2019).
With this rule, the Trump administration is cheating workers out of billions. The annual wage gains from this rule are $1.4 billion dollars less than they would have been under the 2016 rule—and these annual earnings losses balloon over time because the Trump administration neglected to include automatic indexing in their rule. Once again, President Trump has turned his back on the working people of this country.
The total annual wages workers will lose under the Trump overtime rule will grow to $1.8 billion in the first 10 years of implementation : Projected wages workers lose under the Trump overtime rule relative to the 2016 rule in the first 10 years of implementation of the Trump rule
| Projected standard threshold under the 2016 rule | Standard threshold under the 2019 rule | Wages lost under the 2019 rule relative to the 2016 rule | Total wage increase under the 2016 rule | Total wage increase under the 2019 rule | |
|---|---|---|---|---|---|
| 2020 | $51,064 | $35,568 | $1,431,100,000 | $1,787,200,000 | $356,100,000 |
| 2021 | $51,064 | $35,568 | $1,334,500,000 | $1,606,000,000 | $271,500,000 |
| 2022 | $51,064 | $35,568 | $1,246,300,000 | $1,477,100,000 | $230,800,000 |
| 2023 | $55,055 | $35,568 | $1,579,900,000 | $1,770,700,000 | $190,800,000 |
| 2024 | $55,055 | $35,568 | $1,459,000,000 | $1,632,400,000 | $173,400,000 |
| 2025 | $55,055 | $35,568 | $1,360,300,000 | $1,504,200,000 | $144,000,000 |
| 2026 | $59,098 | $35,568 | $1,663,800,000 | $1,798,500,000 | $134,700,000 |
| 2027 | $59,098 | $35,568 | $1,560,800,000 | $1,687,000,000 | $126,200,000 |
| 2028 | $59,098 | $35,568 | $1,473,600,000 | $1,595,800,000 | $122,200,000 |
| 2029 | $63,346 | $35,568 | $1,826,900,000 | $1,938,300,000 | $111,400,000 |
Notes: Subtotals may not add up to totals due to rounding. Following the methodology used by the U.S. Department of Labor, the estimates include all workers affected by the federal salary threshold increase, and do not account for higher state salary thresholds. Calculations account only for wage increases of workers with new protections (i.e., they do not account for workers with strengthened protections).
Source: EPI analysis of pooled Current Population Survey Outgoing Rotation Group microdata, 2016–2018, following the methodology used in the U.S. Department of Labor’s 2019 final rule, “Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees,” 29 CFR Part 541 (published September 24, 2019).
The total annual wages workers will lose under the Trump overtime rule in 2020, by state
| Wages lost under the 2019 rule relative to the 2016 rule | Total wage increase under the 2016 rule | Total wage increase under the 2019 rule | |
|---|---|---|---|
| US Total | $ 1,431,100,000 | $ 1,787,200,000 | $ 356,100,000 |
| Alabama | $ 17,600,000 | $ 23,700,000 | $ 6,100,000 |
| Alaska | $ 2,400,000 | $ 3,100,000 | $ 800,000 |
| Arizona | $ 29,000,000 | $ 35,900,000 | $ 6,800,000 |
| Arkansas | $ 11,200,000 | $ 14,600,000 | $ 3,400,000 |
| California | $ 133,000,000 | $ 167,100,000 | $ 34,100,000 |
| Colorado | $ 32,400,000 | $ 44,600,000 | $ 12,200,000 |
| Connecticut | $ 12,400,000 | $ 15,800,000 | $ 3,400,000 |
| Delaware | $ 3,200,000 | $ 4,000,000 | $ 800,000 |
| Washington, D.C. | $ 4,700,000 | $ 6,000,000 | $ 1,300,000 |
| Florida | $ 98,700,000 | $ 117,500,000 | $ 18,700,000 |
| Georgia | $ 43,400,000 | $ 53,200,000 | $ 9,700,000 |
| Hawaii | $ 4,400,000 | $ 5,200,000 | $ 900,000 |
| Idaho | $ 6,400,000 | $ 8,300,000 | $ 1,900,000 |
| Illinois | $ 68,500,000 | $ 81,000,000 | $ 12,400,000 |
| Indiana | $ 33,000,000 | $ 40,300,000 | $ 7,300,000 |
| Iowa | $ 20,400,000 | $ 23,700,000 | $ 3,300,000 |
| Kansas | $ 15,300,000 | $ 17,900,000 | $ 2,600,000 |
| Kentucky | $ 21,400,000 | $ 28,800,000 | $ 7,300,000 |
| Louisiana | $ 20,300,000 | $ 25,100,000 | $ 4,800,000 |
| Maine | $ 8,500,000 | $ 9,900,000 | $ 1,400,000 |
| Maryland | $ 30,800,000 | $ 42,100,000 | $ 11,300,000 |
| Massachusetts | $ 38,500,000 | $ 51,500,000 | $ 13,000,000 |
| Michigan | $ 49,100,000 | $ 64,100,000 | $ 15,100,000 |
| Minnesota | $ 28,500,000 | $ 34,100,000 | $ 5,600,000 |
| Mississippi | $ 9,500,000 | $ 12,400,000 | $ 2,900,000 |
| Missouri | $ 34,400,000 | $ 39,700,000 | $ 5,300,000 |
| Montana | $ 4,500,000 | $ 5,300,000 | $ 800,000 |
| Nebraska | $ 10,000,000 | $ 12,500,000 | $ 2,500,000 |
| Nevada | $ 10,000,000 | $ 12,200,000 | $ 2,100,000 |
| New Hampshire | $ 6,800,000 | $ 8,800,000 | $ 2,000,000 |
| New Jersey | $ 34,800,000 | $ 44,300,000 | $ 9,500,000 |
| New Mexico | $ 5,100,000 | $ 6,800,000 | $ 1,700,000 |
| New York | $ 80,100,000 | $ 99,300,000 | $ 19,100,000 |
| North Carolina | $ 45,700,000 | $ 55,100,000 | $ 9,400,000 |
| North Dakota | $ 3,200,000 | $ 3,900,000 | $ 700,000 |
| Ohio | $ 45,000,000 | $ 60,900,000 | $ 15,900,000 |
| Oklahoma | $ 14,700,000 | $ 19,900,000 | $ 5,200,000 |
| Oregon | $ 19,400,000 | $ 26,500,000 | $ 7,100,000 |
| Pennsylvania | $ 51,500,000 | $ 67,600,000 | $ 16,100,000 |
| Rhode Island | $ 4,600,000 | $ 6,700,000 | $ 2,100,000 |
| South Carolina | $ 19,400,000 | $ 23,700,000 | $ 4,300,000 |
| South Dakota | $ 3,300,000 | $ 3,600,000 | $ 400,000 |
| Tennessee | $ 33,000,000 | $ 42,000,000 | $ 9,100,000 |
| Texas | $ 141,700,000 | $ 173,100,000 | $ 31,400,000 |
| Utah | $ 16,500,000 | $ 19,900,000 | $ 3,400,000 |
| Vermont | $ 4,100,000 | $ 4,700,000 | $ 600,000 |
| Virginia | $ 28,200,000 | $ 35,300,000 | $ 7,100,000 |
| Washington | $ 40,500,000 | $ 44,800,000 | $ 4,300,000 |
| West Virginia | $ 5,000,000 | $ 6,400,000 | $ 1,300,000 |
| Wisconsin | $ 24,100,000 | $ 31,200,000 | $ 7,100,000 |
| Wyoming | $ 2,600,000 | $ 3,200,000 | $ 600,000 |
Notes: Subtotals may not add up to totals due to rounding. Following the methodology used by the U.S. Department of Labor, the estimates include all workers affected by the federal salary threshold increase, and do not account for higher state salary thresholds. Calculations account only for wage increases of workers with new protections (i.e., they do not account for workers with strengthened protections).
Source: EPI analysis of pooled Current Population Survey Outgoing Rotation Group microdata, 2016–2018, following the methodology used in the U.S. Department of Labor’s 2019 final rule, “Defining and Delimiting the Exemptions for Executive, Administrative, Professional, Outside Sales and Computer Employees,” 29 CFR Part 541 (published September 24, 2019).
Trump’s labor board wants to deprive graduate student workers of their basic right to form unions
The Trump-appointed National Labor Relations Board proposed a rule last week that would rob graduate teaching assistants and other student employees of the rights to organize and collectively bargain. This is just the most recent example of the board’s attack on working people. Last month, the board determined that misclassifying workers as independent contractors does not violate the National Labor Relations Act (NLRA). Before that, the General Counsel’s office released a deeply flawed memo that found that Uber drivers were not employees under the NLRA.
The trend with the Trump board seems to be to take a statute which broadly protects private sector workers and whittle away at its scope. At a time when worker advocates are demanding more workers have the right to a union and collective bargaining, the Trump board’s graduate teaching assistant proposal demonstrates a fundamental lack of understanding of the modern workforce.
Had the Trump board considered any data or conducted any meaningful analysis of the academic workplace in developing the proposed rule, it would have discovered that the last several decades have seen significant changes in labor conditions. Universities have increasingly relied on graduate teaching assistants and contingent faculty, with the growth in graduate assistant positions and non-tenure track positions outpacing the increase in tenured and tenure-track positions between the Fall of 2005 and Fall 2015.
These positions have dramatically lower compensation than faculty. The average salary of a graduate teaching assistant during the 2015-2016 school year was $35,810. Individuals who are working while enrolled in graduate school deserve livable wages. One way to address this issue is through collective bargaining—the very right the Trump board seeks to rob from these workers.
Further, in spite of the majority’s insistence that collective bargaining will harm “academic freedom,” there is a wealth of evidence to the contrary. Public universities have had graduate student worker unions for 50 years. In 2016, more than 64,000 graduate student employees were unionized at 28 institutions of higher education in the public sector. The colleges and universities with union represented student employees have not reported a loss of “academic freedom” as the Trump board suggests.
In reality, union-represented graduate student employees at public universities have reported that they enjoy higher levels of personal and professional support than that reported by non-union represented students. Unionized and nonunionized student employees report similar perceptions of academic freedom. However, union-represented graduate student workers did report receiving higher pay than non-union represented graduate student workers. Perhaps this is one reason why there have been so many successful organizing campaigns on campuses across the country the last few years. Student employees at several private universities have unionized and won better working conditions–better pay, better health care, better child care. The Trump board’s proposal would rob student employees of these gains.
The Trump board is committed to rolling back workers’ rights to a union and collective bargaining. They routinely advance political proposals based on flawed facts and legal reasoning. Through decisions, general counsel memos, and rulemaking the agency is making it more and more difficult for working people to have a voice in the workplace. All workers deserve the basic right to a union. The NLRB is the agency responsible for ensuring that right and we must hold them accountable for betraying their statutory duty.
Members of the public are invited to comment on the Trump board’s most recent proposal. Comments can be submitted here.
What’s luck got to do with it? When it comes to money, quite a bit
The notion that hard work is all that’s needed to achieve a prosperous or even comfortable living in the United States has come under increasing scrutiny in recent years as stagnant wages for most workers have led to talk about the demise of the American Dream.
Randy Schutt, a long-time progressive activist and researcher, has created a simple model to help illustrate just how much dumb luck, mere chance and circumstance, can play a role in who becomes wealthy and who remains poor.
The project, intended to illustrate certain nuances about economic inequality to students and researchers, is called “The Chancy Islands: A Land of Equally Capable People But With Unequal Luck.”
His imaginary archipelago includes places like Rugged Island and Mercy Island, the first unforgiving, the latter much less so, and everything in between—Flat Island, Combo Island, Parity Island, etc.
“We’re always told that if you work hard and persist through adversity that you can rise above your humble (or horrible) circumstances and become wealthy. But that isn’t true,” Schutt said. “Most people are so beaten down by our economic system that they have to be lucky just to get by. And they have to be very lucky to do well and extremely well to get super rich.”
The statistics bear our Schutt’s narrative. Economic mobility, defined as the chance that someone born in the bottom fifth of the income distribution can sweat their way to the top fifth, is extremely low in the United States (around 7.5%)—and actually much lower than other rich nations, because of a much weaker social safety net.
You can explore the models for yourself by going to the website. But Schutt comes to the following conclusion after having examined all of the different combinations and possibilities exhaustively:
“It turns out that even with absolutely no differences in talent or effort, severe inequality can still arise just from the random shocks of wealth-depleting natural events such as serious illnesses, bad accidents, and natural disasters,” said Schutt. “Some households will amass vast fortunes without having done anything to justify their windfall; others will slide into poverty and homelessness without having done anything to warrant their impoverishment.”
Schutt adds, on a hopefully note, that his model also suggests “a few simple mitigation measures can almost completely rebalance such a society, essentially eliminating any long-term inequality.”
Such policies include, perhaps unsurprisingly, taxing the wealthy in ways that are becoming increasingly popular with the American electorate.
Why is the economy so weak? Trade gets headlines, but it’s more about past Fed rate hikes and the TCJA’s waste
Josh Bivens, director of research at EPI
The Federal Reserve meets this week against a backdrop of mounting evidence of a slowing economy. Since the last Federal Open Market Committee (FOMC) meeting, revised data on gross domestic product (the widest measure of the nation’s economic activity) and job growth have shown that 2018 saw much slower growth than previously reported.
Between April 2018 and March 2019, for example, the economy created 500,000 fewer jobs than had originally been reported. Only 105,000 jobs were created in August if temporary Census positions are excluded: this is roughly half the pace of growth that characterized pre-revision estimates of average job growth in 2018.
These clear signs of an economic slowdown raise the obvious question, “Why has growth faltered?”
While many pundits and economists have blamed the escalating trade conflict between the Trump administration and China, there are much more obvious sources of this slowdown: the Fed’s own premature interest rate increases between December 2015 and 2018 and the utter waste of fiscal resources that was the Tax Cuts and Jobs Act (TCJA) passed at the end of 2017.
To be clear, the Trump administration’s trade conflict is stupid and destructive, and its attempt to pin the blame for the slowdown on the Fed is self-serving. And the Trump administration’s scapegoating others for the weak economy takes real hubris given that its signature economic policy initiative—the TCJA—has been such an obvious failure in terms of spurring growth.
Racial and ethnic income gaps persist amid uneven growth in household incomes
Yesterday’s Census Bureau report on income, poverty, and health insurance coverage in 2018 shows that while there was a slowdown in overall median household income growth relative to 2017, income growth was uneven by race and ethnicity. Real median income increased 4.6% among Asian households (from $83,376 to $87,194), 1.8% among African American households (from $40,963 to $41,692), 1.1% among non-Hispanic white households (from $69,851 to $70,642), and only 0.1% among Hispanic households (from $51,390 to $51,450), as seen in Figure A. The only groups for which income growth was statistically significant were Asian and Hispanic households.
In 2018, the median black household earned just 59 cents for every dollar of income the median white household earned (unchanged from 2017), while the median Hispanic household earned just 73 cents (down from 74 cents).
Real median household income, by race and ethnicity, 2000–2018
| Year | White | Black | Hispanic | Asian | White-imputed | Black-imputed | Hispanic-imputed | Asian-imputed | White | Black | Hispanic | Asian | White | Black | Hispanic | Asian |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2000 | $66,712 | $43,380 | $48,500 | $69,069 | $44,614 | $46,989 | ||||||||||
| 2001 | $65,835 | $41,899 | $47,721 | $68,161 | $43,091 | $46,234 | ||||||||||
| 2002 | $65,646 | $40,839 | $46,334 | $73,660 | $67,965 | $42,001 | $44,890 | $79,501 | ||||||||
| 2003 | $65,388 | $40,633 | $45,160 | $76,231 | $67,698 | $41,789 | $43,753 | $82,276 | ||||||||
| 2004 | $65,178 | $40,292 | $45,670 | $76,631 | $67,481 | $41,438 | $44,247 | $82,708 | ||||||||
| 2005 | $65,458 | $39,898 | $46,360 | $76,873 | $67,771 | $41,033 | $43,846 | $84,991 | ||||||||
| 2006 | $65,449 | $40,116 | $47,169 | $78,291 | $67,762 | $41,257 | $45,699 | $86,560 | ||||||||
| 2007 | $66,676 | $41,388 | $46,958 | $78,343 | $69,032 | $42,565 | $45,495 | $86,616 | ||||||||
| 2008 | $64,923 | $40,154 | $44,326 | $74,913 | $67,217 | $41,296 | $42,945 | $82,824 | ||||||||
| 2009 | $63,895 | $38,423 | $44,628 | $74,982 | $66,153 | $39,516 | $43,238 | $82,901 | ||||||||
| 2010 | $62,857 | $37,114 | $43,433 | $72,402 | $65,078 | $38,170 | $42,080 | $80,048 | ||||||||
| 2011 | $62,001 | $36,215 | $43,217 | $71,139 | $64,192 | $37,245 | $41,870 | $78,653 | ||||||||
| 2012 | $62,465 | $36,945 | $42,738 | $73,415 | $64,672 | $37,996 | $41,406 | $81,169 | ||||||||
| 2013 | $62,915 | $37,547 | $44,228 | $70,687 | $65,138 | $38,615 | $42,850 | $78,153 | $65,138 | $38,615 | $42,850 | $78,153 | ||||
| 2014 | $63,976 | $37,854 | $45,114 | $78,883 | $63,976 | $37,854 | $45,114 | $78,883 | ||||||||
| 2015 | $66,721 | $39,440 | $47,852 | $81,788 | $66,721 | $39,440 | $47,852 | $81,788 | ||||||||
| 2016 | $68,059 | $41,924 | $49,887 | $85,210 | $68,059 | $41,924 | $49,887 | $85,210 | ||||||||
| 2017 | $69,806 | $41,584 | $51,717 | $83,314 | $69,806 | $41,584 | $51,717 | $83,314 | $69,851 | $40,963 | $51,390 | $83,376 | ||||
| 2018 | $70,642 | $41,692 | $51,450 | $87,194 |
Note: Because of a redesign in the CPS ASEC income questions in 2013, we imputed the historical series using the ratio of the old and new method in 2013. Solid lines are actual CPS ASEC data; dashed lines denote historical values imputed by applying the new methodology to past income trends. The break in the series in 2017 represents data from both the legacy CPS ASEC processing system and the updated CPS ASEC processing system. White refers to non-Hispanic whites, black refers to blacks alone or in combination, Asian refers to Asians alone, and Hispanic refers to Hispanics of any race. Comparable data are not available prior to 2002 for Asians. Shaded areas denote recessions.
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement Historical Poverty Tables (Table H-5 and H-9)
Based on EPI’s imputed historical income values (see the note under Figure A for an explanation), 11 years after the start of the Great Recession in 2007, only African American households remained below their pre-recession median income. Compared with household incomes in 2007, median household incomes in 2018 were down 2.1 percent for African American households, but up 0.7% for Asian households, 2.3% for non-Hispanic white households, and 13.1% for Hispanic households. Asian households continued to have the highest median income, despite large income losses in the wake of the recession.
The 2018 poverty rates also reflect the patterns of income growth between 2017 and 2018. As seen in Figure B, poverty rates for all groups were down slightly or unchanged, but remained highest among African Americans (20.7%, down 1.0 percentage point), followed by Hispanics (17.6%, down 0.7 percentage points), Asians (10.1%, up 0.4 percentage points), and whites (8.1%, down 0.4 percentage points). African American and Hispanic children continued to face the highest poverty rates—28.5% of African Americans and 23.7% of Hispanics under age 18 lived below the poverty level in 2018. African American children were more than three times as likely to be in poverty as white children (8.9%).Read more
Government programs kept tens of millions out of poverty in 2018
**Correction: The SSI number in Figure B was corrected to 2,949,000 from 3,949,000.**
From 2017 to 2018, the official poverty rate fell by 0.5 percentage points, as household incomes rose modestly, albeit at a slower pace than the previous three years. This was the fourth year in a row that poverty declined, but the poverty rate remains half a percentage point higher than the low of 11.3% it reached in 2000.
Since 2010, the U.S. Census Bureau has also released an alternative to the official poverty measure known as the Supplemental Poverty Measure (SPM).
The SPM corrects many deficiencies in the official rate. For one, it constructs a more comprehensive threshold for incomes families need to live free of poverty, and adjusts that threshold for regional price differences. For another, it accounts for the resources available to poor families that are not included in the official rate, such as food stamps and other in-kind government benefits.
As shown in Figure A, a larger proportion of Americans are in poverty as measured by the SPM than as measured by the official measure. (Importantly, however, researchers who constructed a longer historical version of the SPM found that it shows greater long-term progress in reducing poverty than the official measure.) In 2018, the SPM increased by 0.1 percentage points to 13.1%. Under the SPM, 42.5 million Americans were in poverty last year, compared with 38.1 million Americans under the “official” poverty measure.Read more
Slowdown in household income growth continues in 2018
Today’s report from the Census Bureau shows a marked slowdown in median household income growth relative to previous years. Median household incomes rose only 0.9%, after rising 1.8% in 2017 and following impressive gains in the two years prior: a 5.1% gain in 2015 and a 3.1% gain in 2016. Median nonelderly household income saw a similar rise of 1.0% this year after gaining 2.5%, 4.6%, and 3.6% in the prior three years, respectively.
After falling for both men and women by 1.1% each in 2017, inflation-adjusted full-time annual earnings for both men and women rose in 2018, by 3.4% and 3.3%, respectively. Men’s earnings are finally above both their 2007 and 2000 levels.
While the gains in household income are markedly slower than in previous years, they nonetheless represent another small step toward reclaiming the lost decade of income growth caused by the Great Recession. Part of the slowdown in income growth in 2017 and 2018 relative to 2015 and 2016 is driven by increases in the pace of inflation. However, as discussed below, this year’s report reminds us that the vast majority of household incomes (when corrected for a break in the data series in 2013) have still not fully recovered from the deep losses suffered in the Great Recession.
Nonelderly household incomes improve
The Census data show that from 2017 to 2018, inflation-adjusted median household income for nonelderly households (those with a householder, or head of household, younger than 65 years old) increased 1.0%, from $70,944 to $71,659, as shown in Figure A. Median nonelderly household income is an important measure of an improving economy, as those households depend on labor market income for the vast majority of their income. This continued, albeit much slower, increase after larger gains in the prior three years is better than nothing. Median household income for nonelderly households, which finally recovered to its pre-recession level in 2017, was 1.2%, or $876 above its 2007 level in 2018. It’s important to note that the Great Recession and its aftermath came on the heels of a weak labor market from 2000 to 2007, during which the median income of nonelderly households fell significantly, from $73,322 to $70,783—the first time in the post–World War II period that incomes failed to grow over a business cycle. Altogether, from 2000 to 2018, the median income for nonelderly households fell from $73,322 to $71,659, a decline of $1,663, or 2.3%. In short, the last four years should not make us forget that incomes for the majority of Americans have experienced a lost 18 years of growth.Read more
By the Numbers: Income and Poverty, 2018
Jump to statistics on:
• Earnings
• Incomes
• Poverty
• Policy / SPM
This fact sheet provides key numbers from today’s new Census reports, Income and Poverty in the United States: 2018 and The Supplemental Poverty Measure: 2018. Each section has headline statistics from the reports for 2018, as well as comparisons to the previous year, to 2007 (the final year of the economic expansion that preceded the Great Recession), and to 2000 (the historical high point for many of the statistics in these reports). All dollar values are adjusted for inflation (2018 dollars). Because of a redesign in the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) income questions in 2013, we imputed the historical series using the ratio of the old and new method in 2013. All percentage changes from before 2013 are based on this imputed series. We do not adjust for the break in the series in 2017 due to differences in the legacy CPS ASEC processing system and the updated CPS ASEC processing system, but these differences are small and statistically insignificant in most cases.
Earnings
Median annual earnings for men working full time grew 3.4 percent, to $55,291, in 2018. Men’s earnings are up 1.0 percent since 2007, and are 1.5 percent higher than they were in 2000.
Median annual earnings for women working full time grew 3.3 percent, to $45,097, in 2018. Women’s earnings are up 5.8 percent since 2007, and are 12.3 percent higher than they were in 2000.
Median annual earnings for men working full time in 2018: $55,291
Change over time:
- 2017–2018: 3.4%
- 2007–2018: 1.0%
- 2000–2018: 1.5%
Median annual earnings for women working full time in 2018: $45,097
Change over time:
- 2017–2018: 3.3%
- 2007–2018: 5.8%
- 2000–2018: 12.3%
What to watch for in the 2018 Census data on earnings, incomes, and poverty
Next Tuesday is the Census Bureau’s release of annual data on earnings, income, poverty, and health insurance coverage for 2018, which will give us a picture of the economic status of working families 11 years into what is now the longest economic expansion in United States history. This data is particularly important because it gives us insight into how evenly (or unevenly) economic growth has been distributed across U.S. households. Other data sources that are released more than once a year too often provide only averages or aggregates— but next week’s Census release gives a much more textured picture of how the U.S. economy is working for typical households. In particular, next week’s release will help us chart the progress made by the typical American household in clawing back nearly two decades of lost income growth—the result of a failure of incomes to return to the business cycle peaks of 2000 during the slow early-2000s recovery and expansion, and the Great Recession. We’ll be paying particular attention to differences in the recovery across racial and ethnic groups.
What happened with incomes in recent years?
After adjusting the series to account for changes to the survey made in 2013, in 2017 real (inflation-adjusted) median incomes for American households rose just 1.8 percent and only managed to return to their pre-Great Recession peaks, even coming off of two years (2015 and 2016) of impressive across-the-board improvements. It is important to note, however, that some of the improvements in inflation-adjusted income we saw in 2015 and 2016 were driven by atypically low inflation—0.1% in 2015, and 1.3% in 2016. We didn’t get a similar boost from low inflation in 2017 (inflation increased 2.2% in 2017), and don’t expect one in 2018 (inflation increased 2.4% in 2018). We anticipate that an additional year of even modest growth will likely bring the broad middle class back to 2000 incomes. But, for non-elderly households, the latest data will be likely still below the peak reached 18 years prior.
Real median household income, all and non-elderly, 1995–2017
| All households | All households- imputed series | All households- new series | Non-elderly households | Non-elderly households- imputed series | Non-elderly households- new series | |
|---|---|---|---|---|---|---|
| 1995 | $54,600 | $56,330 | $62,727 | $64,677 | ||
| 1996 | $55,394 | $57,150 | $63,898 | $65,885 | ||
| 1997 | $56,533 | $58,325 | $64,722 | $66,734 | ||
| 1998 | $58,612 | $60,470 | $67,372 | $69,467 | ||
| 1999 | $60,062 | $61,966 | $69,079 | $71,226 | ||
| 2000 | $59,938 | $61,838 | $69,419 | $71,577 | ||
| 2001 | $58,609 | $60,466 | $68,324 | $70,448 | ||
| 2002 | $57,947 | $59,784 | $67,650 | $69,753 | ||
| 2003 | $57,875 | $59,709 | $67,031 | $69,115 | ||
| 2004 | $57,674 | $59,502 | $66,246 | $68,305 | ||
| 2005 | $58,291 | $60,138 | $65,792 | $67,837 | ||
| 2006 | $58,746 | $60,608 | $66,698 | $68,772 | ||
| 2007 | $59,534 | $61,421 | $67,015 | $69,098 | ||
| 2008 | $57,412 | $59,232 | $64,817 | $66,832 | ||
| 2009 | $57,010 | $58,817 | $63,932 | $65,920 | ||
| 2010 | $55,520 | $57,280 | $62,280 | $64,217 | ||
| 2011 | $54,673 | $56,406 | $60,775 | $62,664 | ||
| 2012 | $54,569 | $56,298 | $61,346 | $63,254 | ||
| 2013 | $54,744 | $56,479 | $56,479 | $61,605 | $63,520 | $63,520 |
| 2014 | $55,613 | $62,667 | ||||
| 2015 | $58,476 | $65,541 | ||||
| 2016 | $60,309 | $67,917 | ||||
| 2017 | $61,372 | $69,628 |
Note: Because of a redesign in the CPS ASEC income questions in 2013, we imputed the historical series using the ratio of the old and new method in 2013. Solid lines are actual CPS ASEC data; dashed lines denote historical values imputed by applying the new methodology to past income trends. Non-elderly households are those in which the head of household is younger than age 65. Shaded areas denote recessions.
Source: EPI analysis of Current Population Survey Annual Social and Economic Supplement Historical Income Tables (Tables H-5 and HINC-02)
What do we expect in this year’s release?
Given the data we’ve seen for 2018 from other sources, it is likely that earnings, income, and poverty in the 2018 Census data will show some improvement over the past year. But it is also likely that this pace of improvement will be significantly slower than the average of the previous three years. As the economy steadily strengthens, we’ve seen progress in key labor market indicators, including participation in the labor market and payroll employment, which should boost household labor earnings. The unemployment rate ticked down another 0.5 percentage points in 2018, similar to the drop between 2016 and 2017. The overall labor force participation rate was unchanged between 2017 and 2018, but the employment-to-population ratio continued to increase, 0.3 percentage points overall and 0.8 percentage points for the prime-age population (25-54 years old). These are similar to the increases found between 2016 and 2017.
What to Watch on Jobs Day: Wage growth is key to a sustainable recovery
There’s a reason millions of American workers are still feeling left out from what on the surface looks like a fairly strong economy: a distinct absence of consistently strong wage growth.
The unemployment rate has stayed at or below 4.0 percent since March 2018. But, nominal wage growth continues to be weaker than expected and, in fact, appears to be decelerating this year so far. In our nominal wage tracker that measures year-over-year changes, wage growth has flat-lined in recent months and has yet to reach the Federal Reserve’s target zone (given inflation targets and productivity potential). Looking at more-recent trends—wage growth between the first and second quarters of this year—there has actually been a deceleration in wage growth this year. The Employment Cost Index, released last month, also shows a marked deceleration in private sector wage growth.
Last month, the Bureau of Labor Statistics (BLS) also released preliminary benchmark revisions to payroll employment for April 2018 through March 2019. Each year, the BLS benchmarks total nonfarm payroll employment to state unemployment insurance tax records. While revisions in most years tend to be relatively small and don’t get officially incorporated into the historical numbers until the final revisions are released in February, this year’s 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 large in comparison. And, usually the difference between the preliminary revision and final is plus or minus 40,000. Therefore, it’s likely the final revisions will also be around 500,000 fewer jobs in that period.
The figure below illustrates what this means for job growth over the last two years. Here, I’m comparing April 2017 through March 2019, linearly interpolating the 501,000 losses equally over the 12-month period. Initially, it appeared that payroll employment growth increased between the year ending in March 2018 and March 2019, with monthly employment growth going from an average of 193,000 to 210,000. With these sizable downward revisions, average monthly employment growth actually fell from 193,000 to 168,000 over those two periods.Read more