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Tag Archives: inequality

Where are women less likely than men (ages 30-70) to die of a major disease?

The Our World in Data post, Why do women live longer than men?  by Esteban Ortiz-Ospina and Diana Beltekian (8/14/18) answers the question with the graph copied here.

As the next chart shows, in most countries for all the primary causes of death the mortality rates are higher for men. More detailed data shows that this is true at all ages; yet paradoxically, while women have lower mortality rates throughout their life, they also often have higher rates of physical illness, more disability days, more doctor visits, and hospital stays than men do. It seems women do not live longer than men only because they age more slowly, but also because they are more robust when they get sick at any age. This is an interesting point that still needs more research.

Interestingly, it seems that  except for Bhutan it is only countries in Africa where women are more likely to die of a major disease.  The article is an excellent example of telling a story with data while also posing questions.

The evidence shows that differences in chromosomes and hormones between men and women affect longevity. For example, males tend to have more fat surrounding the organs (they have more ‘visceral fat’) whereas women tend to have more fat sitting directly under the skin (‘subcutaneous fat’). This difference is determined both by estrogen and the presence of the second X chromosome in females; and it matters for longevity because fat surrounding the organs predicts cardiovascular disease.

But biological differences can only be part of the story – otherwise we’d not see such large differences across countries and over time. What else could be going on?

The article has three other graphs beyond this one. One compares life expectancy by country for women and men, one for life expectancy for men and women in the U.S. (and three other countries that can be selected) since 1790, and one for the difference in life expectancy at age 45 since 1790 for selected countries.  All graph can be downloaded  and the data is available for each.

How many people are there and how many can the earth support?

The article in The Conversation 7.5 billion and counting: How many humans can the Earth support? by Andrew D. Hwang (7/9/18) provides some details.  The graph here, copied from the article provides population number and future estimates. 

For real populations, doubling time is not constant. Humans reached 1 billion around 1800, a doubling time of about 300 years; 2 billion in 1927, a doubling time of 127 years; and 4 billion in 1974, a doubling time of 47 years.

On the other hand, world numbers are projected to reach 8 billion around 2023, a doubling time of 49 years, and barring the unforeseen, expected to level off around 10 to 12 billion by 2100.

The article provides a link to download the data and discusses key points related to inequality. For example,

Wealthy countries consume out of proportion to their populations. As a fiscal analogy, we live as if our savings account balance were steady income.

According to the Worldwatch Institute, an environmental think tank, the Earth has 1.9 hectares of land per person for growing food and textiles for clothing, supplying wood and absorbing waste. The average American uses about 9.7 hectares.

These data alone suggest the Earth can support at most one-fifth of the present population, 1.5 billion people, at an American standard of living.

This article is useful for QL and Stats classes, as well as anyone that would like to use population data and/or discuss carrying capacity.

What is the poverty rate in OECD countries?

The OECD (Organisation for Economic Co-operation and Development) defines poverty as an income below half the median household income. The chart here was created using the most recent year of data from the OECD poverty rate page .  The U.S. leads the pack with a rate of 17.8%, with Israel right behind at 17.7%. At the bottom are Denmark and Finland with rates of 5.5% and 5.8% respectively.  It is important to note, as the OECD does,

However, two countries with the same poverty rates may differ in terms of the relative income-level of the poor.

The data is available for more than OECD countries on their page and there is an interactive graph, but the graph can’t be dowloaded. The data and R script that created the graph here are available: csv file, R script.

Citation for data:OECD (2018), Poverty rate (indicator). doi: 10.1787/0fe1315d-en (Accessed on 11 July 2018)

What is the story of suicides in the U.S.?

The article in the Conversation, Why is suicide on the rise in the US – but falling in most of Europe? by Steven Stack (6/28/18), tries to get at the story. The first chart (copied here), clearly shows that the suicide rate rose from 199-2015 overall and considerably more for the 45-54 age group (stats regression problem here).  There is a second chart showing changes in suicide rates in Western European countries:

However, suicide rates in other developed nations have generally fallen. According to the World Health Organization, suicide rates fell in 12 of 13 Western European between 2000 and 2012. Generally, this drop was 20 percent or more. For example, in Austria the suicide rate dropped from 16.4 to 11.5, or a decline of 29.7 percent.

The obvious question is why?

There has been little systematic research explaining the rise in American suicide compared to declining European rates. In my view as a researcher who studies the social risk of suicide, two social factors have contributed: the weakening of the social safety net and increasing income inequality.

The article has two more charts showing that the U.S. is low on Social Welfare Expenditures as a percent of GDP and is high on inequality. In all instances the data is available for download and there are links to the original sources.

What economic impacts does some college education have on men?

The article in the Conversation 22 percent of men without college don’t have jobs. Here’s why they’re being left behind. by Erin Wolcott (6/7/2018) makes two points:

But the unemployment rate doesn’t tell the full story because it only includes people actively looking for work. People who report not having looked for work in the previous four weeks are completely left out of this number. The employment rate, which is the share who are actually employed, captures the full picture.

And the numbers are stark. Back in the 1950s, there was no education-based gap in employment. About 90 percent of men aged 25-54 – regardless of whether they went to college – were employed.

The Great Recession was particularly painful for men without any college. By 2010, only 74 percent had a job, compared with 87 percent of those with a year or more of college.

By 2016, from the graph here copied from the article, the gap was 90% vs 78%. For the second point:

The gap extends to the wages of those who actually had jobs as well. As recently as 1980, real hourly wages for the two groups were nearly identical at about US$13. In 2015, men with at least a little college saw their wages soar 65 percent to over $22 an hour. Meanwhile, pay for those who never attended plunged by almost half to less than $8.

The article has another graph for wages. Both graphs are interactive and contain links to download the data. Read the article.

What are the symptoms of inequality?

The Guardian article, Trump’s ‘cruel’ measures pushing US inequality to dangerous level – UN warns by Ed Pilkington (6/1/18) lists some symptoms two of which are:

Americans now live shorter and sicker lives than citizens of other rich democracies;

The US incarceration rate remains the highest in the world;

The article lacks some data, which we provide here. It is true that incarceration rates in the U.S. are shockingly the highest in the world, see the chart here from the Prison Policy Initiative’s States of Incarceration: The Global Context 2018. But, this isn’t much different than in 2016 as compared to Prison Policy Initiative’s States of Incarceration: The Global Context 2016 report. Both PPI pages have links to the data sets at the bottom as well as other graphs.

As for U.S. life expectancy Our World in Data has an interactive life expectancy graph.  The last year for this graph is 2015, but by that time the U.S. already had a lower life expectancy than other wealthy countries. This graph allows us to choose other countries, has a map version, and a link to download the data.

In short, the symptoms of inequality stated in the Guardian article are not new (at least the two we focused on here), although they may be getting worse. The article is worth wording as well as the PPI report. Also explore the Our World in Data life expectancy graph. There is data and context to connect all this to stats or QL courses.

 

 

Do people in poverty work?

The EPI article, 50 years after the Poor People’s Campaign poverty persists because of a stingy safety net and a dysfunctional labor market by Elise Gould and Jessica Schieder (5/24/2018), answers the question with a graph (reposted here) and this:

The bottom bar shows us that, among those working-age individuals who are otherwise employable, 63 percent are working and 45.5 percent are working full time. An additional 37.2 percent are not working, but this share includes 1.6 million people living below the poverty line who are actively seeking a job. The data make it clear that millions of people who are active participants in the labor market are unable to make ends meet, either due to insufficient hours or low wages.

What is the CEO to worker pay gap?

U.S. Publicly held companies now have to report CEO and median worker salaries (this was part of the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010) and Bloomberg has an article, Alphabet CEO Page Makes a Tiny Fraction
Compared to Its Median Employee by Alicia Ritcey and Jenn Zhao (5/15/18), with an interactive graph (see image).   Mattel “wins” with a CEO to median worker pay ratio of 4,987-1. Walmart “wins” in the consumer staple category with 1,188-1 ratio.  In the interactive graph there is a button on the top right that hides outliers. This is useful, but be conscious of whether it is on or off.

The Guardian article ‘CEOs don’t want this released’: US study lays bare extreme pay-ratio problem by Edward Helmore (5/16/18)  provides some context and a summary.  The Bloomberg graph is being updated daily.  Rep. Keith Elliston’s staff prepared the report Rewarding or Hoarding? An Examination of Pay Ratios Revealed by Dodd-Frank, which has the data of the first 225 Fortune 500 companies to report and and details on the data collection. The data in the report can be used in statistics courses to test differences by sector.  At some point maybe Bloomberg will post a spreadsheet of the data (one can also ask for it too).

What are the differences in infant mortality by race?

The NYT has a lengthy article, Why America’s Black Mothers and Babies Are in a Life-or-Death Crisis (4/11/18 by Linda Villarosa)  and Kevin Drum follows this up with the handy chart posted here in his post Our Disgraceful Infant Mortality Epidemic.  He notes that although infant morality has decreased the difference between Black and White infant morality has increase (by percentage):

In 1950, according to the CDC, the black rate of infant mortality was 64 percent higher than the white rate. Today it’s 133 percent higher

We also aren’t keeping up with the rest of world:

In 1960, we ranked 11th in infant mortality among rich countries. Not great, but not terrible. Today we rank 24th out of 27 rich countries, ahead of only Turkey, Mexico, and Chile.

You can find infant mortality data at the CDC’s National Center for Health Statistics page  (tables 10-13).

Are teachers being paid fairly?

An August 2016 report by EPI, The teacher pay gap is wider than ever (8/9/16 by Allegretto and Mishel), suggests not. For instance, the graph here shows that teachers are paid 23% less than other college graduates in 2015 and the gap has been increasing since 1980.

Average weekly wages (inflation adjusted) of public-sector teachers decreased $30 per week from 1996 to 2015, from $1,122 to $1,092 (in 2015 dollars). In contrast, weekly wages of all college graduates rose from $1,292 to $1,416 over this period.

For all public-sector teachers, the relative wage gap (regression adjusted for education, experience, and other factors) has grown substantially since the mid-1990s: It was ‑1.8 percent in 1994 and grew to a record ‑17.0 percent in 2015.

The report includes 8 graphs with data plus two tales. There are comparisons between females and males, as well as union and non-union.