Sustainability Math A Quantitative Literacy and Mathematics Resource for Instructors

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.

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.

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 30% 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.

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.

Never miss a post. Go to sustainabilitymath.org and sign up for email alerts or follow us on twitter @SustMath.

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.

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).

Fenaba R. Addo has an explanation in the article Parents’ Wealth Helps Explain Racial Disparities in Student Loan Debt at the Federal Reserve bank of St Louis.

An analysis of data from a youth survey found that 58 percent of black young adults reported that their parents contributed an average of $4,200 over the course of their college career. That compares to an average of $12,000 given by 72 percent of white families.

Finances by race is summarized in table 1, copied here. It is note that “All averages are statistically different at the 5 percent level by race, indicating that the differences are not a result of random chance.”  (This can be used in a statistics course and if you contact the author you might even get the data.) The article goes on to note how this may impact the future of these students:

As early as age 25, racial wealth gaps begin to emerge. In the age 25 asset survey, college-educated white young adults reported having approximately $17,000 more wealth than black young adults who had attended college. We calculated that a $10,000 increase in young adult net wealth is associated with 7.6 percent less student loan debt. Young adults with high net wealth may have benefited from transfers of wealth from their parents and subsequently may be in a better position to pay down their student loans quicker.

Every year the EIA (U.S. Energy Information Agency) updates their energy flow and consumption diagrams. They are now available for 2017 energy use and the graph here is primary energy consumption by source and sector. For example, petroleum fulfills 37% or our energy use, 72% of petroleum is for transportation, and petroleum represents 92% of our transportation energy uses. Fossil fuels (petroleum, natural gas, and coal)  generated 78.1 quadrillion BTUs, which is 80% of our energy production, in 2017.  Links to this graph and the energy flow diagrams (total, petroleum, natural gas, coal, & electricity) are found at the bottom of the right side bar on the EIA Monthly Energy Review.

Past diagrams, dating back to 1996, are available at the Energy Flow Archives.  In 2016 fossil fuels generated 78.5 quadrillion BTUs, which was 81% of our energy production.  In 2008 (the first year this diagram appears) it was 83.4 quadrillion BTUs and 84%.

Federal government spending is reported on the usgovernmentspending.com website. On the main page you will find this pie chart of fiscal year 2018 (Oct 2017 through Sept 2018). The two biggest categories are health care 22% and pensions including social security 19%, with interest at 6%. For some context you can read  What does the federal government spend your tax dollars on? Social insurance programs, mostly by  D. Desilver (4/4/17).

In fiscal year 2016, which ended this past Sept. 30, the federal government spent just under $4 trillion, and about $2.7 trillion – more than two-thirds of the total – went for various kinds of social insurance (Social Security, Medicaid and Medicare, unemployment compensation, veterans benefits and the like). Another $604 billion, or 15.3% of total spending, went for national defense; net interest payments on government debt was about $240 billion, or 6.1%. Education aid and related social services were about $114 billion, or less than 3% of all federal spending. Everything else – crop subsidies, space travel, highway repairs, national parks, foreign aid and much, much more – accounted for the remaining 6%.

The usgovernmentspending.com page is a maze of information, but you can find plenty of data and charts if interested. For example, you can find total government spending (fed, state, local) data  and charts by categories. There are certainly projects for many courses, including stats, waiting to be created from these pages.

The State of Global Air 2018 has an interactive air pollution graph to compare countries and regions.  Graph and data are both available. For example, the graph here is Average Seasonal Population-Weighted Ozone (ppb) for Canada, Mexico, and the U.S. (in yellow), as well as the global average (in black).   We can select ambient particulate matter pollution and household air pollution from solid fuels, along with most countries or regions. There is also a tab for health impact as the number of deaths (this is not a rate so larger countries will likely have more deaths) related to  the particular air pollution for the selected country. The State of Global Air 2018 explains their methods, has a full report, and maps.