Archive for the 'Children, Families, and Reproductive Health' Category

Maybe just a nothing burger, but. . .

Funding for fetal tissue research in jeopardy & funding for teen pregnancy prevention axed.

NIH fetal tissue research would be barred under House panel’s spending plan
Lev Facher | STAT News
July 13, 2017

WASHINGTON — A House subcommittee’s draft 2018 spending plan would prohibit federal funds from being spent on research that uses fetal tissue, a symbolic win for conservatives who are also taking aim at money for family planning and public health programs around the country.

Trump administration suddenly pulls plug on teen pregnancy programs
Jane Kay | Reveal: Center for Investigative Reporting
July 14, 2017

The Trump administration has quietly axed $213.6 million in teen pregnancy prevention programs and research at more than 80 institutions around the country, including Children’s Hospital of Los Angeles and Johns Hopkins University.

. . .

Health and Human Services Secretary Tom Price and other top Trump appointees are outspoken opponents of federal funding for birth control, advocating abstinence rather than contraceptives to control teen pregnancies.

. . .

The elimination of two years of funding for the five-year projects shocked the professors and community health officials around the country who run them.

An economist’s best friend: a natural experiment

Male Earnings, Marriageable Men, and non-marital fertility:
Evidence from the Fracking boom

Melissa Kearney and Riley Wilson | NBER Working Paper [23408]
May 2017

This paper takes advantage of the fracking boom to see if an influx of high paying jobs would increase the likelihood of marriage among men without college degrees.

You have to read the paper to find the answer.
Abstract | Paper

Another option is to read the transcript from an interview with one of the authors (Kearney) in Freakonomics Radio link. The last half discusses the findings. This link also goes to a podcast of the interview.

The Fracking Boom, a Baby Boom, and the Retreat from Marriage
Stephen J. Dubner | Freakonomics Radio
July 5, 2017

Missing girls in China maybe weren’t missing after all

China has had a highly unbalanced sex ratio at birth for years leading to an estimate of 30 to 60 million missing girls. The traditional explanation was male preference, exacerbated by the one-child policy, which led to sex selective abortion and/or infanticide. New research presents evidence that maybe the missing girls were never missing after all.

Researchers may have ‘found’ many of China’s 30 million missing girls
Simon Denyer | Washington Post
November 30, 2016

Delayed Registration and Identifying the “Missing Girls” in China
Yaojiang Shi and John James Kennedy | China Daily
November 15, 2016

Data Sleuths at the Census Bureau

The Census Bureau gathered data on fertility by asking a “children ever born” question from 1940 to 1990 in the decennial census. The 2000 Census did not ask a fertility question at all. With the advent of the American Community Survey, fertility was covered but with a different question. It asked if a woman had given birth to a child in the past year. This allows researchers to compute a total fertility rate. It performs reasonably well against the measure produced from the vital statistics system. And, given that geography is not readily available with the natality detail files anymore, this is a welcome solution. The main drawback to the ACS question is that the reference year will not span the calendar year that the vital statistics system is based on. Only the December respondents are referencing a January to December calendar year. See the Background section below for a further discussion of this.

However, recently, the Census Bureau noticed some anomalies in the data for selected areas and determined that some interviewers had been sloppy and asked “Have you given birth” rather than “Have you given birth in the last year.” Many more women will answer yes to the former and inflate the numerator. This is a good illustration of how much effort the Census Bureau goes to for producing accurate and robust statistics.

Data Sleuthing
Addressing Data Collection Errors in the Fertility Question in the American Community Survey
Tavia Simmons | Census Bureau
August 2016

In recent years, a few geographic areas in the American Community Survey (ACS) data had unusually high percentages of women reported as giving birth in the past year, quite unlike what was seen in previous years for those areas. This paper describes the issue that was discovered, and the measures taken to address it.

Background
Indicators of Marriage and Fertility in the United States from the American Community Survey: 2000 to 2004
T. Johnson and J. Dye | Census Bureau
May 2005
[ppt]

Slides 23 to 26 discuss and illustrate how the ACS and Vital Statistics estimates diverge from each other.

Characteristics of Minimum Wage Workers, 2015

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

Parent Work Hours

Nathan Yau has a nice visualization of the change in work hours of mothers and fathers from 1965 to 2014.

Mixed Marriage and How We Think About Race

Jeff Guo of Wonkblog examines research showing trends in how children of mixed marriages report their own race to the Census Report.

In fact, new immigrants may be assimilating a lot faster than than we had ever thought. A new study this week from economists Brian Duncan, of the University of Colorado, and Stephen Trejo of University of Texas, Austin finds that the descendents of immigrants from Latin-American and Asian countries quickly cease to identify as Hispanic or Asian on government surveys.

The Duncan & Trejo paper can be found here.

Who Marries Who?

Bloomberg Business has an interesting (and productivity vortex) interactive chart show who marries who based on profession.

Marriage and Gender Equality

Philip Cohen of Family Inequality charts the correlation between marriage and gender inequality:

I used data from this U.N. report on marriage rates from 2008, restricted to those countries that had data from 2000 or later. To show marriage rates I used the percentage of women ages 30-34 that are currently married. This is thus a combination of marriage prevalence and marriage timing, which is something like the amount of marriage in the country. I got gender inequality from the U.N. Development Programme’s Human Development Report for 2015. The gender inequality index combines the maternal mortality ratio, the adolescent birth rate, the representation of women in the national parliament, the gender gap in secondary education, and the gender gap in labor market participation.

Neighborhoods, Fatherhood and Race

Philip Cohen writes about a new paper by Raj Chetty, et al. and the role race plays, even while it is missing from the data:

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.