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.

How fast is Antarctica melting (and a quick calculus project)?

A recent NYT article, Antarctica Is Melting Three Times as Fast as a Decade Ago by Kendra Pierre-Louis (6/13/2018), states clearly that Antarctica is melting, well, three times faster than a decade ago, which is a rate of change statement. Rapid melting should cause some concern since:

Between 60 and 90 percent of the world’s fresh water is frozen in the ice sheets of Antarctica, a continent roughly the size of the United States and Mexico combined. If all that ice melted, it would be enough to raise the world’s sea levels by roughly 200 feet.

Any calculus student can roughly check the melting statement.  Antarctica ice data is available at NASA’s Vital Signs of the Planet Ice Sheets page. There you can download change in Antarctica ice sheet data since 2002. (Note: The NYT article has a graph going back to 1992, but ends in 2017 as does the NASA data.) A quick scatter plot and a regression line shows that the change is not linear and the data set is concave down. (The graph here is the NASA data and produces in R – the Calculus Projects page now has some R scripts for those interested.)  Now, a quadratic fit to the data followed by a derivative yields that in 2007 the Antarctica was losing 95 gigatonnes of ice per year and in 2017 it was 195.6 gigatonnes per year. Even with this quick simple method melting has more than doubled from 2007 to 2017. The NYT article states:

While that won’t happen overnight, Antarctica is indeed melting, and a study published Wednesday in the journal Nature shows that the melting is speeding up.

This is an excellent sentence to analyze from a calculus perspective. Given that the current trend in the data is not linear and at least about quadratic, then melting is going to increase each year.  On the other hand, maybe they are trying to suggest that melting is increasing more than expected under past trends, for example the fit to the data is more cubic than quadratic. In other words, is the derivative of ice loss linear or something else? If everyone knew calculus the changes in the rate of ice loss could be stated precisely.

How much are the oceans warming?

A year ago Climate Central posted the article Oceans Are Heating Up with a graph of sea surface temperature anomalies while providing context on issues of ocean warming:

 93 percent of the excess heat absorbed by the climate system goes into our oceans, creating major consequences. While more extreme storms and rising sea levels are some of the impacts of warmer oceans, rising CO2 levels and the resulting warmer oceans are impacting ocean health itself. The most well­ known effects are coral bleaching and ocean acidification, but an emerging issue is the decreasing oxygen levels in the warming waters.

The graph here is from NOAA’s Global Ocean Heat and Salt Content page. There you will find numerous updated graphs related to ocean heat content.  For related data go to NOAA’s Basin time series of heat content page to find about 50 time series on ocean heat.

For context on units, a person at rest typically generates about 60 joules of heat per minute while the graph here has y-axis units of 10^22 Joules.

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 state of the Rio Grande?

The NYT article, In a Warming West – the Rio Grande Is Drying Up by Henry Fountain (5/24/2018) answers the question.

Even in a good year, much of the Rio Grande is diverted for irrigation. But it’s only May, and the river is already turning to sand.

“The effect of long-term warming is to make it harder to count on snowmelt runoff in wet times,” said David S. Gutzler, a climate scientist at the University of New Mexico. “And it makes the dry times much harder than they used to be.”

With spring runoff about one-sixth of average and more than 90 percent of New Mexico in severe to exceptional drought, conditions here are extreme. Even in wetter years long stretches of the riverbed eventually dry as water is diverted to farmers, but this year the drying began a couple of months earlier than usual. Some people are concerned that it may dry as far as Albuquerque, 75 miles north.

What the article is missing is data. For example, we have here a graph of daily discharge in cubic feet per second at the Albuquerque station (directions below on how to obtain this graph and associated data.).  Note, that the graph is on a log scale and so is there is downward trend in this data?  Since 1991, the Rio Grande hasn’t stopped flowing in Albuquerque, although is came close around 2014.  Other stations farther south have periods of zero discharge. Use the directions below to explore water flow of the Rio Grande at several locations.  The data is naturally collected as a rate and so it is interesting for calculus classes as well as statistics classes.

To obtain water flow data at any USGS station around the country start at the National Water Information System: Mapper (Note: Different sites around the country will have different dates and type of data available.) Click on any of the sites to get a window with a link to access the data.  The graph here comes from selecting the USGS 08330000 RIO GRANDE AT ALBUQUERQUE, NM station. On that page under Available data for this site  select Time series: Current/Historical observations. For this specific graph we selected a time frame for the whole data set and selected Graph.  You can also select tab-separated file, as well as a few other options.  Further historical data for the Rio Grande can be found at the Rio Grande Historical Mean Daily Discharge Data page.

How old is Arctic sea ice?

From the NYT: In the Arctic, the Old Ice Is Disappearing

The NYT article In the Arctic, the Old Ice Is Disappearing by Jeremy White and kendra Pierre-Louis (5/14/2018) notes

In the Arctic Ocean, some ice stays frozen year-round, lasting for many years before melting. But this winter, the region hit a record low for ice older than five years.

In fact, in March of 1984 5+ year old ice made up about 70% of all ice and now it makes up only a few percent. There is also less ice overall.

If you really want to explore changes in the age of  Arctic ice go to the NSIDC Satellite Observations of Arctic Change interactive graph.  You can choose a year from 1985 through 2916, see a map of the ice, a bar chart of ice by month by age, and have the graph animate through the months of the year. The differences over the years is extreme. You can get related data from the EASE-Grid Sea Ice Age, Version 3 page, although you will have to register.

What is the Great Gatsby curve?

From The 9.9 Percent Is the New American Aristocracy: The class divide is already toxic, and is fast becoming unbridgeable – You’re probably part of the problem by Matthew Stewart (June 2018) in The Atlantic. (Figure 2)

The Great Gatsby curve represents the correlation between income inequality and intergenerational income elasticity. In short, the greater the income inequality in a country the greater the relationship between a child’s income and their parent’s income.

The Atlantic article, The 9.9 Percent Is the New American Aristocracy: The class divide is already toxic, and is fast becoming unbridgeable – You’re probably part of the problem by Matthew Stewart (June 2018)  is an excellent example of weaving important quantitative information (great for a QL course), including the Great Gatsby curve, to tell an important story.

Rising immobility and rising inequality aren’t like two pieces of driftwood that happen to have shown up on the beach at the same time, he noted. They wash up together on every shore. Across countries, the higher the inequality, the higher the IGE (see Figure 2). It’s as if human societies have a natural tendency to separate, and then, once the classes are far enough apart, to crystallize.

The post What is The Great Gatsby Curve? by David Vandivier (6/11/2013) has an animated gif that explains the curve well. To update or recreate the chart, you can get country gini values from the CIA World Factbook.  Intergenerational income elasticity can be found in figure 1 of a the paper Inequality from generation to generation:the United States in Comparison by Miles Corak (2012).  Intergenerational Social Mobility in OECD Countries January 2010 OECD Journal: Economic Studies 2010(1):6-6 Orsetta Causa  and Åsa Johansson is another source.  If you find more recent data let us know.

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What are the prospects for new college grads?

EPI has an answer with its report Class of 2018 College edition by Elise Gould, Zane Mokhiber, & Julia Wolfe  (3/10/18).  The report has 16 key findings and 10 graphs (the graphs and associated data are available).  For example,

Women make up about half of 21- to 24-year-olds, but well over half (57.3 percent) of young college degree holders are women.

While the unemployment rate for white graduates has essentially recovered to within 0.5 percentage points of its 2000 level, unemployment rates for other racial/ethnic groups remain higher than for whites and are significantly higher than their 2000 levels. (see the graph here from EPI)

Whites represent just over half (54.7 percent) of the young adult population but two-thirds of those with a college degree; AAPIs are also disproportionately represented among those young adults with a college degree. Young black and Hispanic adults between the ages of 21 and 24 are far less likely to be college graduates relative to their representation in the population.

The report is worth reading and using in QL or data driven courses.

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).