Archive for the 'Socioeconomic & Spatial Mobility/Inequality' Category

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Reasons People Give for Not Being in the Labor Force, 2004 & 2014

The Bureau of Labor Statistics has released a chart comparing the reasons given for not being in the labor force in 2004 and 2014.

The proportion of the working-age population reporting school attendance as the main reason for being out of the labor force rose from 5.0 percent in 2004 to 6.4 percent in 2014. The percentage who cited illness or disability as the main reason increased from 5.5 percent to 6.5 percent over that same period. The proportion citing home responsibilities declined from 6.0 percent in 2004 to 5.4 percent in 2014.

For more information, see the Beyond the Numbers article “People who are not in the labor force: why aren’t they working?,” by Steven F. Hipple.

H/T Data Detectives

Classifying Countries by Income

The World Bank has released a new working paper by Neil Fantom and Umar Serajuddin reviewing the World Bank’s classification of countries by income.

Abstract:

The World Bank has used an income classification to group countries for analytical purposes for many years. Since the present income classification was first introduced 25 years ago there has been significant change in the global economic landscape. As real incomes have risen, the number of countries in the low income group has fallen to 31, while the number of high income countries has risen to 80. As countries have transitioned to middle income status, more people are living below the World Bank’s international extreme poverty line in middle income countries than in low income countries. These changes in the world economy, along with a rapid increase in the user base of World Bank data, suggest that a review of the income classification is needed. A key consideration is the views of users, and this paper finds opinions to be mixed: some critics argue the thresholds are dated and set too low; others find merit in continuing to have a fixed benchmark to assess progress over time. On balance, there is still value in the current approach, based on gross national income per capita, to classifying countries into different groups. However, the paper proposes adjustments to the methodology that is used to keep the value of the thresholds for each income group constant over time. Several proposals for changing the current thresholds are also presented, which it is hoped will inform further discussion and any decision to adopt a new approach.

Read a summary of the findings.
Download the PDF.

Inequality and Political Turmoil

Jay Ulfelder, writing for FiveThirtyEight, argues that the widely held belief that economic inequality causes political upheaval is a difficult thing to prove:

Just because a belief is widely held, however, does not make it true. In fact, it’s still hard to establish with confidence whether and how economic inequality shapes political turmoil around the world. That’s largely because of the difficulty in measuring inequality; on this subject, the historical record is full of holes. Social scientists are busy building better data sets, but the ones we have now aren’t sufficient to make strong causal claims at the global level.

Philip Cohen’s response to the piece is on his blog, Family Inequality.

Pre-K and Academic Achievement

Andrew Flowers of FiveThirtyEight examines a recent study by Lipsey, Farran and Hofer of Tennessee’s voluntary pre-K program, which finds that kids from low income families who went to pre-K tend to fare worse academically than those who did not. Flowers also looks at a new NBER working paper which disputes this result.

Full text of the papers:
A Randomized Control Trial of a Statewide Voluntary Prekindergarten Program on Children’s Skills and Behaviors through Third Grade

Early Childhood Education

2014 Income and Poverty Estimates for School Districts, Counties, and States

The Census Bureau released the 2014 estimates from it Small Area Income and Poverty Estimates program last week.

From Data Detectives:

Tables provide statistics on the number of people in poverty, the number of children younger than age 5 in poverty (for states only), the number of children ages 5 to 17 in families in poverty, the number younger than age 18 in poverty, and median household income. At the school district level, estimates are available for the total population, the number of children ages 5 to 17 and the number of children ages 5 to 17 in families in poverty.

Urban and Suburban Charter Schools

Susan Dynarski examines the research on charter schools for The Upshot:

Social scientists, like medical researchers, can confirm only whether, on average, a given treatment is beneficial for a given population. Not all charter schools are outstanding: In the suburbs, for example, the evidence is that they do no better than traditional public schools. But they have been shown to improve the education of disadvantaged children at scale, in multiple cities, over many years.

Family Transitions and Student Achievement

Nicholas Zill examines how family transitions affect student achievement for the Family Studies blog:

Among journalists who write about education, the stock explanation for student underachievement and school discipline problems is poverty. Yet there are examples in every school system of students from impoverished family circumstances who do well academically, as well as instances of students from affluent families who get D’s and F’s or wreak havoc in class. When poverty is overemphasized as a cause of instructional ills, other aspects of family life—such as conflict between parents or changes in student living arrangements due to divorce or remarriage—are typically ignored or underemphasized.

Moving Out of Minimum Wage Jobs

Ben Casselman of FiveThirtyEight analyzed data from the Current Population Survey and the Survey of Income and Program Participation and found that minimum wage workers are less likely to move out of those jobs than they were in the mid-1990s.

Even those who do get a raise often don’t get much of one: Two-thirds of minimum-wage workers in 2013 were still earning within 10 percent of the minimum wage a year later, up from about half in the 1990s. And two-fifths of Americans earning the minimum wage in 2008 were still in near-minimum-wage jobs five years later, despite the economy steadily improving during much of that time.

Income Inequality and Political Polarization

Ana Swanson of Wonkblog examines a new study by Nolan McCarty, John Voorheis and Boris Shor that shows that the growing ideological gap between Republicans and Democrats may be due in part to the widening gap between rich and poor.

By looking at extensive data on U.S. states over the last few decades, the researchers show that the widening gap between the rich and the poor in recent decades has moved state legislatures toward the right overall, while also increasing the ideological distance between those on the right and those on the left.

The paper is Unequal Incomes, Ideology and Gridlock: How Rising Inequality Increases Political Polarization

U.S. Department of Education Releases College Scorecard Data

The U.S. Department of Education released the data it used for the College Scorecard, along with data on completion rates, financial aid, debt and earnings.

Via Flowing Data: “And it doesn’t look and work like an outdated government site. With all of my frustrations with government sites, the education release feels pretty great. It’s as if the department actually wants us to look at the data. Imagine that.”