Our World In Data put together 5 charts which show how global living conditions have changed over the last two centuries. The topics include poverty, literacy, health, freedom, fertility, and education.
Archive for the 'Population Dynamics' Category
The Census Bureau just released its 2016 Population Estimates. Let’s take a peek at what the Electoral College might look like in 2020 using the PSC Apportionment calculator. The easiest calculation is to just put the 2016 estimates into the calculator (remember to delete Washington, DC). In that scenario:
The losers: Illinois, Michigan, Minnesota and Pennsylvania
The winners: Florida, North Carolina, Oregon, and Texas
If we take the 2010 to 2016 growth rate and extend it to 2020, this is the scenario:
Losers: Alabama, Illinois, Michigan, Minnesota, New York, Ohio, Pennsylvania, Rhode Island, West Virginia
Winners: Arizona, Colorado, Florida (2), North Carolina, Oregon, Texas (3)
Notable in this scenario is Rhode Island losing an electoral seat. It is just slightly larger than Montana – 1,056,426 vs 1,042,520. But, Rhode Island has had an extra seat since 1990 when Montana lost 1 seat in the House of Representatives. Montana is on the cusp of getting that 2nd representative in the House – it just needs ~5,000 more people than our 2020 projection, which is not an unrealistic scenario.
One thing that is unrealistic about the previous scenario is the fast growth of North Dakota during this period. North Dakota has been the fastest growing state for the past 4 years, but its growth rate dropped to 37th fastest in 2016 due to the collapse of oil prices and thus the fracking industry. Thus, a more realistic estimate might be to use the 2015-2016 rate for the last 4 years of the decade. In that scenario, the results are exactly the same, except that now Montana needs only 550 more people to gain a 2nd seat in the House of Representatives.
Vintage Population Estimates (2016)
State Population Estimates (2016)
PSC Apportionment Calculator
Representations apportioned to each state (1790 to 2010)
Congressional Apportionment Resource
Two researchers have created a map of megaregions in the US based on commuting data from the American Community Survey (ACS). The results are covered in both the popular press and in PLOS One. The latter provides more details about how they constructed the maps – it wasn’t just via a mapping program.
How 4 Million Commutes Shape America’s ‘Megaregions’
Laura Bliss | Atlantic: City Lab
December 7, 2016
An Economic Geography of the United States: From Commutes to Megaregions
Garrett Nelson and Alisdair Rae
November 30, 2016
If you are so inclined the authors have made their data available for replication via Figshare.
Ben Casselman writes in FiveThirtyEight about the ways immigrants help to keep the U.S. population young and keeps the labor force participation at a relatively high rate: Immigrants Are Keeping America Young — And the Economy Growing
If approved, the new category would appear on the 2020 Census and could have far-reaching implications for racial identity, anti-discrimination laws and health research. Currently, people from the Middle East are categorized as white: this was the result of a ruling a century ago in which Syrian Americans argued against being in the Asian category and therefore denied citizenship under the 1882 Chinese Exclusion Act. Read more from USA Today: White House wants to add new racial category for Middle Eastern people.
The Chronicle of Education has gathered race and ethnicity information on more than 4,600 postsecondary institutions, including undergraduate, graduate, and professional schools and presented it in a searchable and sortable table. Note that the search function is very basic: searching for “Michigan” turns up only schools which start with Michigan (e.g. Michigan State U.), and searching for “University of Michigan” gives no results since it is listed as U. of Michigan. Results can be filtered by state.
H/T Flowing Data
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.
Addressing Data Collection Errors in the Fertility Question in the American Community Survey
Tavia Simmons | Census Bureau
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.
Indicators of Marriage and Fertility in the United States from the American Community Survey: 2000 to 2004
T. Johnson and J. Dye | Census Bureau
Slides 23 to 26 discuss and illustrate how the ACS and Vital Statistics estimates diverge from each other.
This is a nice tool for getting net migration reports based on IRS tax return data. Note that because these data are based on tax returns, one can also tell whether, on average, a state is losing/gaining wealthier residents. One can generate reports for counties by state or for states. The former is really tedious because one has to generate the county reports one by one.
And here’s the link to raw data for those who find widgets tedious. Note that the site has nice explanations for the methodology, including changes over time in how these files are created: SOI Tax Stats – Migration Data
Prison populations from big cities have been dropping since 2006, while those from small rural counties have been rising. The New York Times Upshot examines this trend:
Just a decade ago, people in rural, suburban and urban areas were all about equally likely to go to prison. But now people in small counties are about 50 percent more likely to go to prison than people in populous counties.
The stark disparities in how counties punish crime show the limits of recent state and federal changes to reduce the number of inmates. Far from Washington and state capitals, county prosecutors and judges continue to wield great power over who goes to prison and for how long. And many of them have no interest in reducing the prison population.
This is a report on the NCI/SEERS web portal on a way to create residential histories of respondents/decadents for epidemiological research. The report (below) details how three commercial vendors were able to match the residential history of a small sample of federal government employees. Also available are the algorithms and software to reconcile conflicting addresses. Interested folks might want to browse other tools/papers in the NCI Geographical Information Systems and Science for Cancer Control webiste. https://gis.cancer.gov/index.html