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.

Table 1

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).

Copy the code below to embed this chart on your website.

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.

Table 2

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).

Copy the code below to embed this chart on your website.

Table 3

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).

Copy the code below to embed this chart on your website.

Tagged

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.

Read more

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).

Figure A

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 

 

ChartData Download data

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

Notes: 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 (Tables H-5 and H-9).

Copy the code below to embed this chart on your website.

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%

Read more

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.

Income

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
ChartData Download data

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

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)

Copy the code below to embed this chart on your website.

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.

Read more