Tag Archives: inequality

What is the connection between attending college and parental income?

The World Inequality Database  summarize the paper by Bonneau and Grobon in the article Unequal Access to Higher Education (2/7/2022).

In this paperCécile Bonneau and Sébastien Grobon provide new stylized facts on inequalities in access to higher education by parental income in France. At the bottom of the income distribution, 35% of individuals have access to higher education compared to 90% at the top of the distribution. This overall level of inequality is surprisingly close to that observed in the United States. The authors then document how these inequalities in access to higher education by parental income combine with inequalities related to parental occupation or degree. Finally, they assess the redistributivity of public spending on higher education, and present a new accounting method to take into account the tax contribution of parents in our redistributivity analysis.

The article lists 11 key findings such as:

Inequalities in access to higher education create large inequalities in public spending on higher education: Those in the bottom 30 percent of the income distribution receive between 7,000 and 8,000 euros of investment in higher education between the ages of 18 and 24, compared to about 27,000 euros –of which 18,000 euros correspond to public spending and 9,000 to private spending through tuitions paid by parents– for those in the top 10 percent of the income distribution (Figure 5a);

The paper (link in the first quote) has numerous graphs and the details of the modeling.

How much did wage inequality change in 2020?

The EPI article Wage inequality continued to increase in 2020 by Lawrence Mishel and Jori Kandra (12/13/2021) provides the graph copied here. As for the share of the overall pot:

This disparity in wage growth reflects a sharp long-term rise in the share of total wages earned by those at the very top: the top 1.0% earned 13.8% of all wages in 2020, up from 7.3% in 1979. That marks the second highest share of earnings for the top 1.0% since the earliest year, 1937, when data became available (matching the tech bubble share of 13.8% in 2000 and below the share of 14.1% in 2007). The share of wages for the bottom 90% fell from 69.8% in 1979 to just 60.2% in 2020.

The article also has two tables of data that could be useful in stats or QL course.

Has much has poverty decreased?

The Our World in Data article Extreme poverty: how far have we come, how far do we still have to go by Max Roser (11/22/2021) provides numerous graphs that quantify changes in poverty. The most general graph is copied here. This one is for the world but users can select specific countries instead of the world to produce a related graph.

The overall conclusion is summed up well by their summary:

Two centuries ago the majority of the world population was extremely poor. Back then it was widely believed that widespread poverty was inevitable. But this turned out to be wrong. Economic growth is possible and poverty can decline. The world has made immense progress against extreme poverty.

But even after two centuries of progress, extreme poverty is still the reality for every tenth person in the world. This is what the ‘international poverty line’ highlights – this metric plays an important (and successful) role in focusing the world’s attention on these very poorest people in the world.

The poorest people today live in countries which have achieved no growth. This stagnation of the world’s poorest economies is one of the largest problems of our time. Unless this changes millions of people will continue to live in extreme poverty.

 

There are some distribution type graphs that could be useful for statistics classes and most of the graph have an option to download the data.

Who is going to use more electricity in the home?

The eia article Use of electricity in houses to grow more quickly in developing economies by Courtney Sourmehi (11/5/2021) is a good example of the difference between totals and per capita.

Reference case, we project that residential buildings outside the Organization for Economic Cooperation and Development (OECD) will consume more electricity than all residential and commercial buildings combined in OECD countries by 2050. However, people in non-OECD countries will, on average, still consume less than half as much residential electricity as in OECD countries.

What is driving the increase use of electricity?

Population and household income are key drivers of residential electricity consumption. Over the next 30 years, we expect the populations in non-OECD countries to grow three times faster than the populations in OECD countries. As standards of living rise in non-OECD countries, as reflected in increases in household income, we also project increased demand for electricity to power new household electronic devices and appliances, such as air conditioners and electric cooking ranges. In OECD countries, electricity consumption will grow more slowly because of less population growth, gains in energy efficiency, and slower increases in household income.

There are links to sources in the article.

How did COVID impact K-12 learning based in income?

The Pew article What we know about online learning and homework gap amid the pandemic by Katherine Schaeffer (10/1/2021) has this to say:

Parents with lower incomes whose children’s schools closed amid COVID-19 were more likely to say their children faced technology-related obstacles while learning from home. Nearly half of these parents (46%) said their child faced at least one of the three obstacles to learning asked about in the survey, compared with 31% of parents with midrange incomes and 18% of parents with higher incomes.

This technology divide isn’t new:

Even before the pandemic, Black teens and those living in lower-income households were more likely than other groups to report trouble completing homework assignments because they did not have reliable technology access. Nearly one-in-five teens ages 13 to 17 (17%) said they are often or sometimes unable to complete homework assignments because they do not have reliable access to a computer or internet connection, a 2018 Center survey of U.S. teens found.

There are four other charts in the article.

How did CEOs do during the pandemic?

Did CEOs take a pay hit like many workers did during the pandemic? The article CEO pay has skyrocketed 1,322% since 1978 by Lawrence Mishel and Jori Kandra (8/10/2021) suggests CEOs did just fine last year. Their chart shows that realized CEO compensation grew during 2020 compared to the average worker.

Details on the metric:

We focus on the average compensation of CEOs at the 350 largest publicly owned U.S. firms (i.e., firms that sell stock on the open market) by revenue. Our source of data is the S&P ExecuComp database for the years 1992 to 2020 and survey data published by the Wall Street Journal for selected years back to 1965. We maintain the sample size of 350 firms each year when using the ExecuComp data.

The realized measure of compensation includes the value of stock options as realized (i.e., exercised), capturing the change from when the options were granted to when the CEO invokes the options, usually after the stock price has risen and the options values have increased. The realized compensation measure also values stock awards at their value when vested (usually three years after being granted), capturing any change in the stock price as well as additional stock awards provided as part of a performance award.

The granted measure of compensation values stock options and restricted stock awards by their “fair value” when granted (Compustat estimates of the fair value of options and stock awards as granted determined using the Black Scholes model).

Well maybe CEO pay just went down less than worker pay and that is why the ratio went up. In table 1, realized pay for 2019 is $20,351,000 with 2020 projected as $24,194,00. There are other graphs in the article and data available for download.

How much debt do students have by race?

The EducationalData.org post Student Loan Debt by Race by Melanie Hanson (6/9/21) has three excellent graphs such as the one copied here. It may not be surprising that Asians have the least debt given Asians have the highest income, but Hispanic and Latino debt is almost identical to White and Caucasian debt yet their income is typically closer to the Black and African American community.  From a statistical standpoint the first bullet in the highlights

Black and African American college graduates owe an average of $25,000 more in student loan debt than White college graduates.

is a bit misleading. Given the skewness of the data (the 17% in the top category for Black and African American) one should also report a median difference, which looks to be closer to around $10,000. Interestingly, in all cases the median debt is below the $39,000, which is manageable college debt in most cases. The question that comes to mind is how much lower would this be if median income increased at the same pace as the stock market or top 1%?

The article has sources but no easily downloadable data set.

 

Who has access to a smartphone or broadband?

The Pew article Mobile Technology and Home Broadband 2021 by Andrew Perrin (6/3/2021) summarizes the results of their smartphone and home broadband survey.

Smartphone ownership (85%) and home broadband subscriptions (77%) have increased among American adults since 2019 – from 81% and 73% respectively. Though modest, both increases are statistically significant and come at a time when a majority of Americans say the internet has been important to them personally. And 91% of adults report having at least one of these technologies.

There are differences between various groups (see their graph copied here):

The share of Americans with home broadband subscriptions has similarly grown since 2019 – from 73% of adults saying they have one in the previous survey to 77% today. There are more pronounced variations across some demographic groups, particularly in differences by annual household income and educational attainment. For example, 92% of adults in households earning $75,000 or more per year say they have broadband internet at home. But that share falls to 57% among those whose annual household income is below $30,000.

There are other graphs in the article and Pew provides a methodology section with access to data.

What is the relationship between COVID-19 deaths, education, and race/ethnicity?

The working paper, from the Harvard Center for Population and Development Studies, Intersectional inequalities in COVID-19 mortality by race/ethnicity and education in the United States, Jan 1, 2020-Jan 31, 2021 by J.T. Chen, et. el. (2/23/2021) contains the graph copied here.

It is interesting to note that within educational categories, Hispanic mortality rates were consistently lower than rates among Non-Hispanic Whites. This suggests that the overall increased mortality rates experienced by Hispanics is driven in large part by their overrepresentation in more disadvantaged education groups. Similarly, for the non-Hispanic Black population, their equivalent mortality rates to Non-Hispanic Whites in the two lowest educational strata, and their only slightly elevated risk in the higher educational strata suggests that it is the inequities in educational distribution that drive the overall higher crude rates among the non-Hispanic Black vs non-Hispanic White populations.

This provides evidence that COVID-19 deaths are connected to education more so than race/ethnicity. This, of course, isn’t causation, as education level is likely a marker for risk factors of COVID-19 such as health habits and employment.

This paper also supplies a nice example of Simpson’s paradox. Graph 1b provides mortality rates per 100,000 by race/ethnicity (157  Non-Hispanic White, 199 Non-Hispanic-Black, 171 Hispanic). By education category the Hispanic population had lower death rates than Non-Hispanic White, but in the aggregate it is the other way around.

What is the connection between life expectancy and education?

The PNAS paper Life expectancy in adulthood is falling for those without a BA degree, but as educational gaps have widened, racial gaps have narrowed by Anne Case and Angus Deaton (3/16/2021) provides an answer. From the abstract:

We construct a time series, from 1990 to 2018, of a summary of each year’s mortality rates and expected years lived from 25 to 75 at the fixed mortality rates of that year. Our measure excludes those over 75 who have done relatively well over the last three decades and focuses on the years when deaths rose rapidly through drug overdoses, suicides, and alcoholic liver disease and when the decline in mortality from cardiovascular disease slowed and reversed. The BA/no-BA gap in our measure widened steadily from 1990 to 2018. Beyond 2010, as those with a BA continued to see increases in our period measure of expected life, those without saw declines.

By 2018, intraracial college divides were larger than interracial divides conditional on college; by our measure, those with a college diploma are more alike one another irrespective of race than they are like those of the same race who do not have a BA.

The appendix has 7 graphs including the one copied here. A few observations: Hispanics with a BA have a greater life expectancy by sex. In fact, a Hispanic female with no BA has a life expectancy similar to that of a White Male with a BA. The gap in life expectancy between Black and White by sex is about the same by BA/no BA (about 1 year in all 4 cases) but the gap between those with a BA and those without is larger.  For example, a Black male with a BA lives almost 3 years longer than a White male without a BA. This is about 2 years for women.  The no BA group has seen decreasing life expectancy, in general, since about 2010, while the BA group has continued with an increasing life expectancy.

I didn’t find the data in the appendix but there is an email to contact an author and they may provide it if you ask.