Sustainability Math A Quantitative Literacy and Mathematics Resource for Instructors

According to the 3rd chart of EPI’s Top Charts of 2017, U.S. minimum wage would be $19.33 per hour if it grew at the same rate as productivity.  If it simply grew at the rate of average workers it would be $11.62 per hour.

The expectation that the minimum wage rise in step with broader trends in the economy would not have been unreasonable for previous generations—that was the trend throughout the 1950s and 1960s. Today’s minimum wage workers have been harmed both by the failure to raise the minimum wage in step with pay for typical workers and by the huge and growing gap between these nonsupervisory wages and economy-wide productivity. The Raise the Wage Act of 2017 would raise the federal minimum wage to $15 by 2024. Such a raise would certainly bring the pay of minimum wage workers closer to providing a decent quality of life, even though it would still fall short of what the economy could have delivered for low-wage workers over the past 50 years.

All twelve of EPI’s Top Charts of 2017 include data and you can download the chart.

The EPI provides evidence for yes in the 6th of their top charts of 2017, The racial wealth gap is the clearest legacy of past discrimination in housing markets. Their chart shows the differences for mean and median household wealth for black and white households. They key is housing:

Besides facing discrimination in employment and wages, black families historically have been shut out of the most important wealth-building market: housing. Overall, home equity makes up about two-thirds of all wealth for the typical household. In short, for median families, the racial wealth gap is overwhelmingly a housing wealth gap. And this housing wealth gap is no accident; it is the outcome of intentional policies at all levels of government, in particular housing policies that prevented blacks from acquiring land, created redlining and restrictive covenants, and encouraged lending discrimination. These policies created and reinforced the racial wealth gap we are still struggling to address.

You can download the data and graph for all of EPI’s top charts of 2017.

Happy New Year and thank you to all of you who have stopped by Sustainability Math this past year. If people didn’t visit the blog, then I’d stop writing.  Posts will begin again next week. In the meantime, consider following Sustainability Math on Twitter and Facebook. Also, please let friends and colleagues know about the blog.

The New York Times article, Beavers Emerge as Agents of Arctic Destruction, explains:

… as climate change warms the Arctic and thaws the permafrost, the growing season extends. What was once tundra gives way to brush.

This may allow beavers to move north.

But in the tundra, the vast treeless region in the Far North, beaver behavior creates new water channels that can thaw the permanently frozen ground, or permafrost.

What remains is a pitted landscape, with boggy depressions, that directs warmer water onto the permafrost, leading to further thawing. As permafrost thaws it releases carbon dioxide and methane, which in turn contributes to global warming and helps increase the speed that the Arctic, which is already warming faster than the rest of the planet, defrosts.

This is an interesting article with satellite photos showing how beavers have changed the landscape.

Find out by going to Climate Central’s post, See How Much Winters Have Been Warming in Your City.  The winner is Burlington, Vermont, with about 7 degrees F of warming since 1970 (graph here from the post). There is a drop down menu where you can select from most major cities in the U.S. They don’t provide the data, unfortunately, but they do provide a clear methodology so that you can create the data set for your city. You can get weather data from NOAA Climate Data Online. There is great potential here for student projects in statistics courses.

You go to NOAA’s Event Tracker. The initial page is captured in the image here. Each dot represents an event. Scroll over the dot to get a title and summary, which you can then click on to go to the main story. On the bottom right you can select a month since December 2010 to see the events from just that month.

The International Energy Agency’s Energy Access Outlook 2017 has your answer. For example, the chart here answers the question for 2000 and 2015 with an interesting graphic that includes how the change occurred. In 2000, 1684 million people lacked access, 1130 million people gained access, but population grew by 557 million people, leaving 1111 million people without access in 2015. The graph is interactive on the page and breaks these changes down into four regions. There are eight other interesting charts related to electricity as well as access to clean cooking.

The Our World in Data blog post, A sense of units and scale for electrical energy production and consumption has the graph here. It provides a comparison of the scale of different types of electricity production along with comparisons to consumption. For example the Three Gorges Dam is worth 270,000 MWh while the Hoover Dam provides 11,000 MWh.  On the other hand the Alta onshore wind form generates 7,342 MWh.  The post has a nice discussion of units as well as information about the types of electricity generation they highlight in the graphic.

If you read the post by Our World in Data, Meat and Seafood Production & Consumption, you will be able to impress your friends. The post consists of 34 graphs. You can download the images and the data for each.  The graph here is Greenhouse gas emissions per gram of protein by food type.  Beef is far more CO2 intensive than any other protein source.  The second chart here shows Meat consumption vs. GDP per capita (2013) and the U.S. is one of the top two consumers of meat.

The Economic Policy Institute has the answer with their post Latina workers have to work 10 months into 2017 to be paid the same as white non-Hispanic men in 2016. They compare not only wages by percentile (graph here), but also compare by occupation and education.

Much of these differences are grounded in the presence of occupational segregation. Latina workers are far more likely to be found in certain low-wage professions than white men are (and less common in high-wage professions). But, even in professions with more Latina workers, they still are paid less on average than their white male colleagues.

As Hispanic women increase their educational attainment, their pay gap with white men actually increases. The largest dollar gap (more than $17 an hour), occurs for workers with more than a college degree.

The EPI post includes downloadable graphs (such as the one here) as well as the data.