…real median household income increased 10.6% among Asian households (from $88,774 to $98,174), 8.5% among Black households (from $42,447 to $46,073), 7.1% among Hispanic households (from $52,382 to $56,113), and 5.7% among non-Hispanic white households (from $71,922 to $76,057), …
There is a second graph on poverty rates and data is included for both graphs, as well as a link to the original Census Bureau data.
If you take the net worth of all white households and divide it by the number of white households, you get $900,600. If you do the same thing for black households, you get $140,000. The difference between these figures — $770,600 — is the best representation of the overall racial wealth gap.
The graphs here from the article show that the wealth in both groups is largely concentrated in the top 10%.
What this means is that the overall racial wealth disparity is being driven almost entirely by the disparity between the wealthiest 10 percent of white people and the wealthiest 10 percent of black people.
This means that even after you have completely closed the racial wealth gap between the bottom 90 percent of each race, 77.5 percent of the overall racial wealth gap still remains, which is to say that the disparity between the top deciles in each race drives over three-fourths of the racial wealth gap.
What this shows is that 97 percent of the overall racial wealth gap is driven by households above the median of each racial group.
Median incomes of married-couple households and those with male householders did not change from 2017.
In 2018, the poverty rate for families with a female householder was 24.9%, higher than that for married-couple families (4.7%) and families with a male householder (12.7%).
However, the poverty rate for families with a female householder declined from the previous year, at 26.2% in 2017.
The full report contains 20 pages of charts and summaries related to income and poverty by numerous categories. The other 50 or so pages are data tables that are also available in excel files (see links on right sidebar of the report page). There is ample data here for use in courses.
Asian women and men earned more than their White, Black, and Hispanic counterparts in 2017. Among women, Whites ($795) earned 88 percent as much as Asians ($903); Blacks ($657) earned 73 percent; and Hispanics ($603) earned 67 percent. Among men, these earnings differences were even larger: White men ($971) earned 80 percent as much as Asian men ($1,207); Black men ($710) earned 59 percent as much; and Hispanic men ($690), 57 percent. (See chart 3 and table 1.)
The earnings comparisons in this report are on a broad level and do not control for many factors that can be important in explaining earnings differences, such as job skills and responsibilities, work experience, and specialization.
Using the stock-options-realized measure, we find that the average compensation for CEOs of the 350 largest U.S. firms was $17.2 million in 2018. Compensation dipped 0.5% in 2018 following a 7.6% gain in 2017.
The fact that CEO compensation has grown far faster than the pay of the top 0.1% of wage earners indicates that CEO compensation growth does not simply reflect a competitive race for skills (the “market for talent”) that also increased the value of highly paid professionals: Rather, the growing differential between CEOs and top 0.1% earners suggests the growth of substantial economic rents in CEO compensation (income not related to a corresponding growth of productivity). CEO compensation appears to reflect not greater productivity of executives but the power of CEOs to extract concessions. Consequently, if CEOs earned less or were taxed more, there would be no adverse impact on the economy’s output or on employment.
Over the last three decades, CEO compensation increased more relative to the pay of other very-high-wage earners than did the wages of college graduates relative to the wages of high school graduates. This finding indicates that the escalation of CEO pay does not simply reflect a more general rise in the returns to education.
There are six tables/graphs in the article and the data is available for download.
June 16th marks the longest period in history without an increase in the federal minimum wage. The last time Congress passed an increase was in May 2007, when it legislated that the minimum wage be raised to $7.25 per hour on July 24, 2009. Since the minimum wage was first established in 1938, Congress has never let it go unchanged for so long.
To get the data for this graph visit The FRED Blog The value(s) of the minimum wage. At the bottom of the page they provide direction on how to recreate the chart with FRED data. Knowing how to do this is valuable and should be incorporated into any statistics or QL course.
The EPI article, Raising the federal minimum wage to $15 by 2024 would life pay for nearly 40 million workers, by David Cooper (2/5/19) covers their analysis of raising the minimum wage. Their graph here shows the gap between the minimum wage and median wage over time. The report is lengthy and detailed. A few quick highlights:
Raising the minimum wage to $15 by 2024 would undo the erosion of the value of the real minimum wage that began primarily in the 1980s. In fact, by 2021, for the first time in over 50 years, the federal minimum wage would exceed its historical inflation-adjusted high point, set in 1968.
All told, raising the minimum wage to $15 by 2024 would directly or indirectly lift wages for 39.7 million workers, 26.6 percent of the wage-earning workforce.
Indexing the minimum wage to the median wage would ensure that low-wage workers share in broad improvements in U.S. living standards and would prevent future growth in inequality between low- and middle-wage workers.
The article has over 20 graphs/charts/tables and each one has the associated data. The report does include “a discussion of the research on the likely effects such a raise would have on businesses, employment, and low-wage workers’ welfare.”
From 2017 to 2018, men at the 95th percentile saw large wage gains, while those at the middle and very bottom of their wage distribution experienced downright wage losses.
The gender wage gap at the 10th percentile remains the smallest across the wage distribution and it has narrowed since 2000; it is currently at 5.9 percent. The regression-adjusted average gender wage gap narrowed slightly from 2000 to 2018 and is currently at 22.6 percent.
In both comparison periods, both men and women at the 10th percentile saw greater wage growth in states with minimum wage changes versus those without.
Over the last 18 years, wage growth for white and Hispanic workers has been about four times faster than that of black workers in the 20th through the 70th percentiles of their respective wage distributions. The 60th and 70th percentiles of the black wage distribution remain below their 2000 levels.
The wages of those with a high school diploma rose faster than the wages of those with a college degree over the last two years, narrowing the gap between college and high school wages. As a result, the college wage premium—the regression-adjusted log-wage difference between the wages of college-educated and high school–educated workers—fell from 50.6 percent to 48.4 percent between 2016 and 2018.
Wage growth has varied depending on numerous factors such as gender, race, income level, and education. The EPI article, America’s slow-motion wage crisis-Four decades of slow and unequal growth by John Schmitt, Elise Gould, and Josh Bivens (9/13/18) summarizes the findings with 30 graphs or tables (data included). For example, the cumulative percent change in inflation-adjusted hourly wages for workers in the 10th, 50th, and 90th percentile is given in the graph here (downloaded from the article).
The first key trend since 1979 is the historically slow growth in real wages. In 2017, middle-wage workers earned just 16.8 percent more than their counterparts almost four decades earlier. This corresponds to an annualized inflation-adjusted growth rate over the 38-year period of just 0.4 percent per year. The real wage increase for low-wage workers (those at the 10th percentile) was even slower: 8.9 percent over 38 years, or a 0.2 percent annualized growth rate.
This slow growth is particularly disappointing for two reasons. First, as we will see in the next section, U.S. workers today are generally older (and hence potentially more experienced) and substantially better educated than workers were at the end of the 1970s.10 Second, for workers at the bottom and the middle, most of the increase in real wages over the entire period took place in the short window between 1996 and the early 2000s. For the large majority of workers over the last four decades, wages were essentially flat or falling apart from a few short bursts of growth.
Quiz Questions: What was the cumulative change in hourly wages from 1979 to 2017 for
What was the cumulative change in hourly wages from 1979 to 2017 for workers with an advanced degree?
What was the cumulative change in hourly wages from 1979 to 2017 for workers with less than a high school diploma?
Which ethnic group had the greatest change?
What was the cumulative change in hourly wages from 1979 to 2017 for Women in the 50th percentile?
What was the cumulative change in hourly wages from 1979 to 2017 for Men in the 50th percentile?
The article and/or corresponding data is ready for use in a stats or QL course in the 90th percentile.
On average, in 2017, black women workers were paid only 66 cents on the dollar relative to non-Hispanic white men, even after controlling for education, years of experience, and geographic location. A previous blog post dispels many of the myths behind why this pay gap exists, including the idea that the gap would be closed by black women getting more education or choosing higher paying jobs. In fact, black women earn less than white men at every level of education and even when they work in the same occupation. But even if changing jobs were an effective way to close the pay gap black women face—and it isn’t—more than half would need to change jobs in order to achieve occupational equity.
Along with the graph copied here, there is a time series from 2000 to 2016 of the Duncan Segregation Index:
the “Duncan Segregation Index” (DSI) for black women and white men, overall and by education, based on individual occupation data from the American Community Survey (ACS). This is a common measure of occupational segregation, which, in this case identifies what percentage of working black women (or white men) would need to change jobs in order for black women and white men to be fully integrated across occupations.