Wednesday, December 7, 2016

Why Are Voters Mad?


Because the pre-tax incomes of the bottom 50 percent stagnated while average national income per adult grew, the share of national income earned by the bottom 50 percent collapsed from 20 percent in 1980 to 12.5 percent in 2014. Over the same period, the share of incomes going to the top 1 percent surged from 10.7 percent in 1980 to 20.2 percent in 2014.7 As shown in Figure 2, these two income groups basically switched their income shares, with about 8 points of national income transferred from the bottom 50 percent to the top 1 percent. The gains made by the 1 percent would be large enough to fully compensate for the loss of the bottom 50 percent, a group 50 times larger.
To understand how unequal the United States is today, consider the following fact. In 1980, adults in the top 1 percent earned on average 27 times more than bottom 50 percent of adults. Today they earn 81 times more. This ratio of 1 to 81 is similar to the gap between the average income in the United States and the average income in the world’s poorest countries, among them the war-torn Democratic Republic of Congo, Central African Republic, and Burundi. Another alarming trend evident in this data is that the increase in income concentration at the top in the United States over the past 15 years is due to a boom in capital income. It looks like the working rich who drove the upsurge in income concentration in the 1980s and 1990s are either retiring to live off their capital income or passing their fortunes onto heirs.
Trump's policies are just going to worsen these trends.  He can jawbone companies into keeping some decent paying jobs in the States, but overall, there is downward pressure on the middle class, and messing with Medicare and cutting taxes for rich people aren't going to change that.  Even decent paying public sector jobs are getting squeezed out, and the Republicans elected with Trump are all for strangling them further:
Back in 2009, Rick Erickson was happy with his job as a teacher in one of the state’s northernmost school districts on the shores of Lake Superior. He made $35,770 a year teaching chemistry and physics, which wasn’t a lot of money, but then again, he received stellar healthcare and pension benefits, and could talk honestly with administrators about what he needed as a teacher every two years when his union sat down with the school district in collective bargaining sessions.
Then, five years ago, Wisconsin passed Act 10, also known as the Wisconsin Budget Repair Bill, which dramatically limited the ability of teachers and other public employees to bargain with employers on wages, benefits, and working conditions. After Act 10, Erickson saw his take-home pay drop dramatically: He now makes $30,650. His wife is a teacher, too, and together they make 11 percent less than they did before Act 10. The local union he once led no longer exists, and so he can’t bargain with the school district for things like prep time and sick days. He pays more for health care and his pension, and he says both he and his wife may now not be able to retire until they are much older than they had planned....Data suggests that Erickson is by no means unique. Total teacher compensation in Wisconsin has dropped 8 percent, or $6,500 since Act 10, according to an extensive study by Andrew Litten, a Ph.D. candidate at the University of Michigan who used state data showing compensation of all teachers in the state of Wisconsin. What’s more, he found that the most experienced and highest-paid teachers experienced the biggest reduction in benefits.
This will continue, and voters will continue to be mad.  Trump won't solve anything.

The Big Cloth

The Big Cloth from Dog Leap on Vimeo.

Tuesday, December 6, 2016

U.S. Megaregions

National Geographic:

To try to solve this geographical problem, Garrett Nelson of Dartmouth College and Alasdair Rae of the University of Sheffield used census data on more than four million commuter paths and applied two different analyses, one based on a visual interpretation and the other rooted in an algorithm developed at MIT. Their results and maps appear today in the open-access journal PLOS ONE....But where should planners draw the edges of a megaregion encompassing this activity? Which connections are statistically significant? Which are important for regional transit planning? Should they focus on the cities surrounding the bay, or is Sacramento just as important to the Bay Area economy?
 For answers to these questions, Nelson and Rae turned to an algorithm-based tool designed by MIT’s Senseable City Lab to mathematically recognize communities. The algorithm only considers the strength of connections between nodes (more than 70,000 census tracts in this case), ignoring physical locations. This made for a nice test of Waldo Tobler’s “first law of geography”: that things that are near each other are more related than those that are farther apart.... 
One of the decisions the researchers made was to limit the algorithm to 50 megaregions, which can be seen in the map above, where every node is colored according to the region it belongs to. This made the map more plausible visually. While 50 may sound like an arbitrary number, it makes sense mathematically because a very high percentage of commutes lie entirely within a megaregion relative to paths that cross boundaries between regions.
I would guess selecting the number 50 explains the region I live in, which covers Cincinnati, Dayton, Lima, Columbus and areas down to southern West Virginia.  Regardless, that is a pretty cool map.  If one were to make a map of my drives, it would be dominated by a small triangle between my house, my job and the farm where my cows are, with a few small detours for feed, food and beer.  It would dominate a small portion of my county.  I honestly can't imagine a daily commute to Columbus.  I thought 20 miles to the next county's seat was pretty long.