Emily Badger of Wonkblog looks what happens when a neighborhood — Bedford-Stuyvesant in Brooklyn, specifically — experiences a sharp increase in home values, but income remains the same.
Archive for the 'Socioeconomic & Spatial Mobility/Inequality' Category
A new report from the Bureau of Labor Statistics us a picture of minimum wage workers in 2015. Some highlights (from the report website):
Age. Minimum wage workers tend to be young. Although workers under age 25 represented only about one-fifth of hourly paid workers, they made up about half of those paid the federal minimum wage or less. Among employed teenagers (ages 16 to 19) paid by the hour, about 11 percent earned the minimum wage or less, compared with about 2 percent of workers age 25 and older. (See table 1 and table 7.)
Gender. Among workers who were paid hourly rates in 2015, about 4 percent of women and about 3 percent of men had wages at or below the prevailing federal minimum. (See table 1.)
Full- and part-time status. About 7 percent of part-time workers (those who usually work fewer than 35 hours per week) were paid at or below the federal minimum wage, compared with about 2 percent of full-time workers. (See table 1 and table 9.)
State of residence. The states with the highest percentages of hourly paid workers earning at or below the federal minimum wage were in the South: Alabama, Louisiana, Mississippi, and Virginia (all were about 6 percent). The states with the lowest percentages of hourly paid workers earning at or below the federal minimum wage were in the West: Alaska, California, Oregon, and Washington (all were about 1 percent). It should be noted that some states have laws establishing higher minimum wage rates than the federal minimum wage. (See table 2 and table 3.)
H/T Data Detectives
Richard Hodes, director of the National Institute on Aging, wrote in the Inside NIA bog about their updated version of the NIA’s Strategic Directions, Aging Well in the 21st Century.
NIA’s previous strategic approach was published in 2007. Since then, we have made a number of important revisions. Most critically, we have organized our approach into three “functional” areas:
- Understanding the Dynamics of the Aging Process
- Improving the Health, Well-Being, and Independence of Adults as they Age
- Supporting the Research Enterprise
Jeff Guo of Wonkblog examines how the absence of 1.6 million people from economic statistics affects the decisions politicians and policymakers make:
Though there are nearly 1.6 million Americans in state or federal prison, their absence is not accounted for in the figures that politicians and policymakers use to make decisions. As a result, we operate under a distorted picture of the nation’s economic health.
There’s no simple way to estimate the impact of mass incarceration on the jobs market. But here’s a simple thought experiment. Imagine how the white and black unemployment rates would change if all the people in prison were added to the unemployment rolls.
Maurice Chammah, writing for The Marshall Project, writes about the St. Louis police departments’ use of crime-predicting software.
HunchLab, produced by Philadelphia-based startup Azavea, represents the newest iteration of predictive policing, a method of analyzing crime data and identifying patterns that may repeat into the future. HunchLab primarily surveys past crimes, but also digs into dozens of other factors like population density; census data; the locations of bars, churches, schools, and transportation hubs; schedules for home games — even moon phases. Some of the correlations it uncovers are obvious, like less crime on cold days. Others are more mysterious: rates of aggravated assault in Chicago have decreased on windier days, while cars in Philadelphia were stolen more often when parked near schools.
H/T Flowing Data
Keith Humphreys, writing for WonkBlog, examines recent changes in the U.S. incarceration rates:
After decades of growth, the U.S. imprisonment rate has been declining for the past six years. Hidden within this welcome overall trend is a sizable and surprising racial disparity: African-Americans are benefitting from the national de-incarceration trend but whites are serving time at increasingly higher rates.
The tricky thing with this data, and I don’t blame Chetty et al. for this, although I would like them to say more about it, is that they don’t know the race of the children. The data are from tax records, which allow you to know the income and marital status of the parents, but not the race. But they know where they grew up. So if they have a strong effect of the racial composition of the county kids grow up in, but they don’t know the race of the kids, you have to figure a big part of that is race of the kids — and by “you” I mean someone who knows anything about America.
The Sunlight Foundation has created a project called Hall of Justice which gathers publicly available criminal justice datasets and research.
While not comprehensive, Hall of Justice contains nearly 10,000 datasets and research documents from all 50 states, the District of Columbia, U.S. territories and the federal government. The data was collected between September 2014 and October 2015. We have tagged datasets so that users can search across the inventory for broad topics, ranging from death in custody to domestic violence to prison population. The inventory incorporates government as well as academic data.
H/T Flowing Data
Jeff Guo of the Wonkblog writes about new research into the reasons behind the educational achievement gap between boys and girls:
A team of economists from MIT, Northwestern, and the University of Florida has been investigating the question of the female advantage using a vast trove of data collected by the state of Florida. In their preliminary research, they have found that upbringing counts for a lot. The gender gap gets wider in poorer families. Girls from disadvantaged backgrounds are much more likely to succeed than boys raised under the same circumstances.
Now, in a new paper released Monday, the economists have found additional evidence that bad schools exacerbate the differences in academic achievement between boys and girls.
Max Ehrenfreund, writing for Wonkblog, examines research presented at the 2016 American Economic Association’s annual meeting by Anuj Shah and collaborators showing that the the poor do better on tests of financial common sense:
If you spend all your time thinking about money, chances are, you’re going to get pretty good at thinking about money. Indeed, new research suggests that the poor — for whom concerns about cash are inescapable — are not as prone to certain financial mistakes often made by the affluent.
“The poor spend a lot more time on mundane, everyday expenses. They’re focused on money,” said Anuj Shah, a psychologist at the University of Chicago and one of the authors of the research, which was published last year and presented earlier this month at the American Economic Association’s annual meeting.