The last post, What are the projections for high school graduates? provided national high school graduation rates from WICHE. I noted in that post that regional data and reports are available along with race and ethnicity. The graph here (for public high school only) is from the report for the northeast (use the drop down menu to select northeast). There is a wealth of information and available data in the WICHE report.
The United States Drought Monitor provides weekly updates of drought in the U.S. Maps such as the one here can be downloaded. For classroom use there is a data page where full data sets can be downloaded including GIS data. There is also an interactive time series graph.
The Pew article The Changing Geography of COVID-19 in the U.S. by Bradley Jones and Jocelyn Kiley provides data about the geographic impact of COVID-19:
Early in the course of the pandemic, the health impacts were felt most severely in dense urban centers. From March to May, congressional districts in the most urbanized parts of the country were experiencing about five times as many deaths on average compared with those in the least dense parts of the country, and in some places this disparity was much larger.
However, by the summertime the urban-rural split had largely disappeared, and over the last several months, those districts with small shares of residents in densely populated places have been experiencing twice as many deaths as those in the parts of the country where all or nearly all residents live in urban neighborhoods.
The article has an interactive graphic of the U.S. with COVID-19 deaths by congressional district over time, along with a few other tables and graphs. There is also a longer report that can be downloaded.
The EPI article Wages for the top1% skyrocketed 160% since 1979 while the share of wages for the bottom 90% shrunk by Lawrence Mishel and Jori Kandra (12/1/2020) reports:
As Figure A shows, the top 1.0% of earners are now paid 160.3% more than they were in 1979. Even more impressive is that those in the top 0.1% had more than double that wage growth, up 345.2% since 1979 (Table 1). In contrast, wages for the bottom 90% grew only 26.0% in that time.
The top 0.1% go off the chart. There are two other tables of data nd the data for the chart copied here is available.
It depends on what we mean by poverty. The World Bank blog post A quarter of the world lives in societal poverty by Marta Schoch, Dean Mitchell Joliffe, & Christoph Lakner (12/2/2020):
Measures of absolute poverty, such as poverty at the US$1.90, US$3.20 and the US$5.50 international poverty lines, have the advantage of remaining fixed (in constant dollars), allowing one to measure poverty against the same benchmark over time and across countries. However, when countries set their own national poverty lines, they typically increase the real value of these lines as their economies evolve.
The absolute poverty line misses the fact that “the ability to participate in society is costlier in richer countries.” So,
In 2018, the World Bank introduced a Societal Poverty Line (SPL),
The SPL is the max of US$1.90 and US$1+ 0.5*median, where median is the daily median income or consumption per capita in the household survey.
The is more information and other graphs in the article.
The October 2020 global land and ocean surface temperature was the fourth highest for October since global records began in 1880 at 0.85°C (1.53°F) above the 20th century average of 14.0°C (57.1°F). Only Octobers of 2015 (+1.03°C / +1.85°F), 2019 (+0.95°C / +1.71°F), and 2018 (+0.93°C / +1.67°F) were warmer. The ten warmest Octobers have occurred since 2005, while the seven highest October temperature departures from average have occurred in the last seven years (2014–2020). October 2020 also marks the 44th consecutive October and the 430th consecutive month with temperatures, at least nominally, above the 20th century average.
Europe was warm:
According to NCEI’s regional analysis, Europe had its warmest October on record, with a temperature departure of +2.17°C (+3.91°F). This surpassed the previous record set in 2001 by 0.06°C (0.11°F).
For the year so far:
Averaged as a whole, this was the second warmest January–October for global land and ocean, with a temperature departure at 1.0°C (1.8°F) above the 20th century average. This value is only 0.03°C (0.05°F) shy of tying the record set in January–October 2016. According to our Global Annual Temperature Rankings Outlook, the year 2020 is very likely to rank among the three warmest years on record.
The data is available in the additional resources box near the top of the page.
NASA’s Vital Signs of the Planet article Beating Back the Tides by Jenny Marder (11/11/2020) provides an update on the increasing frequency of high tides (see the graph copied here for one example).
Between 2000 and 2015, high-tide flooding in the U.S. doubled from an average of three days per year to six along the Northeast Atlantic, according to a 2018 NOAA report. It is especially common along the East Coast and Gulf Coast, where the frequency is up by roughly 200% over the last two decades. In some areas like Annapolis, the numbers are even more extreme. Annapolis had a record 18 days of high-tide flooding from May 2019 to April 2020, according to flooding thresholds for the city established by NOAA. That’s up from the previous record of 12 days in 2018. Before 2015, the record number of high-tide flood days in one year was seven, and the yearly average of high-tide floods from 1995 to 2005 was two.
The article includes a 7 minute video on high tide flooding. There is also a link to NOAA’s Tides and Currents page The State of High Tide Flooding and Annual Outlook. The page has a map of projected high tide flood days for 2020. For more detailed information, including lots of graphs, see the 2019 State of U.S. High Tide Flooding with 2020 Outlook technical report from NOAA.
The U.S. Bureau of Labor Statistics has a Graphics for Economic News Releases page. The graph copied here is median usual weekly earnings of full-time wage and salary workers. Most of the patters are not a surprise, such as men earning more than women. What may be new here is that Asian women ($1224) out earned White men ($1122). Asian men out earned all others at $1542. The page includes seven other charts with the data.
Pew has a summary of voter demographics by party in their article What the 2020 electorate looks like by party, race and ethnicity, age, education and religion by John Gramlich (10/26/2020). For example, see the graph copied here.
White Americans accounted for 67% of eligible voters nationally in 2018, but they represented a much larger share in several key battlegrounds in the Midwest and Mid-Atlantic, including Wisconsin (86%), Ohio (82%), Pennsylvania (81%) and Michigan (79%). The reverse was true in some battleground states in the West and South. For example, the White share of eligible voters was below the national average in Nevada (58%), Florida (61%) and Arizona (63%). You can see racial and ethnic breakdown of eligible voters in all 50 states – and how it changed between 2000 and 2018 – with this interactive feature.
Check out the interactive graph that is referenced in this quote, along with the half a dozen other graphs in the article. All great for a QL or stats based course.
To address this question we start with a recent post by Kevin Drum (10/23/2020): Are Black Homeowners Suffering from Slow Price Growth?
There’s no question that homes in majority-Black neighborhoods are undervalued compared to similar homes in majority-White neighborhoods, but do they also appreciate more slowly?
The article goes through four charts with the last one copied here.
However, if I were forced to choose one of these as the most telling, I’d take the Zillow chart since its data covers the entire nation and it provides a useful time series that fits what I know about the bubble-era lending industry—although I’d sure like to see it extended to the present. It shows that over a somewhat longish term, home appreciation has been lower in Black neighborhoods than in white neighborhoods, primarily because of a huge drop following the housing bubble. The culprit here, however, is not Black neighborhoods per se, but the mortgage industry, which oversold to Black borrowers during the bubble and drove prices far higher than even normal bubble standards. That wretched episode has been documented in considerable detail in a lot of places, but you can read a good outline here if you want to learn more.
One of the articles linked to is Devaluation of housing in black neighborhoods, Part 2: Appreciation by Joe Cortright (7/24/2019):
A key question the Brooking’s report leaves unanswered is whether the black/white housing differential is larger or smaller than it was 10 or 20 years ago. If it was larger in the past and is smaller today, that implies that homes in majority black neighborhoods, although still undervalued relative to homes in predominantly white neighborhoods, have enjoyed greater relative appreciation. From the standpoint of wealth creation, the amount of appreciation since you bought your home is likely to matter more than whether the current price of your house is more or less than otherwise similar properties. Another way of expressing this is that homeowners in black neighborhoods had a lower purchase price (or basis) in their home, and even though it is still undervalued, it may have gained more value in percentage terms than homes in non-majority black neighborhoods.
Indeed, Dan Immergluck and his colleagues at the Georgia State University found that for those who bought homes in 2012, price appreciation for black homebuyers from 2012 through 2017 was higher than for white homebuyers. Immergluck’s data show that in most markets, homes bought by black buyers appreciated more than homes bought by white homebuyers.
This article also references the Zillow study, A House Divided – How Race Colors the Path to Homeownership by Skylar Olsen (1/15/2014), which includes a number of graphs related to homeownership by race. As Drum notes it would be nice if this study was updated.