An article at the Urbanophile gives us a helpful graphic explaining the old and new “Donut” conceptions of the city. In the “Old Donut,” we have an impoverished central city with a ring of thriving suburbs around it.
An example of that model appears in this graph, which shows the percentage of adults over 25 with college degrees in the Charlotte, NC metro area in 1990. The x-axis is distance from the center of downtown.
Like many people, I’ve been inclined to explain Virginia’s decades of explosive population growth in terms of migration and the Federal government’s expansion in Northern Virginia. While that’s certainly part of the equation, “natural increase” has actually driven most of the growth, just as it has across the country. Natural increase simply means more people are born than die in a year. Even in Northern Virginia and Hampton Roads, natural increase is the largest generator of population growth. But “natural increase” does not mean that we are having lots and lots of babies. In fact, it has much more to do with the fact that we had a lot of babies a while back and since then people started living a lot longer.
You hear, on this blog and elsewhere, about the “aging population,” but I wanted to show exactly what that means. Here’s the one gif you need to see to understand population growth in Virginia:
Recently, I’ve been comparing a number of traits of metropolitan areas based on distance from the core. Here I’m looking at the average densities of each metro area as you travel outwards from the center, calculated using census blocks and 2010 short-form census data. I’ve graphed them in groups of three. Cities with a strong core will have high densities on the left (near the center) that fall off as you travel outwards. Cities whose densities fall off quickly on the right have clearer edges, while those that taper off slowly are more spread out. Click on the graphs to view them full screen.
First are the three major metro areas. Note that the Northern VA graph includes only Virginia census blocks, not the rest of the DC area. Northern VA has the largest population by far, with fairly high densities even several miles into the suburbs. Richmond has the smoothest curve. I used downtown Norfolk as the core for Hampton Roads, but the area’s polycentricity is obvious.
One of the most fundamental things that distinguishes the Virginia Poverty Measure (VPM) from the Official Poverty Measure is who “counts” as part of a family unit. While applying a different definition of the family unit is only one aspect of improving the measure of economic (in)security, it is an important change because it lays the groundwork for an accurate account of income and expenses.
The official poverty rate is calculated by the Census Bureau using income limits applied to families depending on number and age of family members. Larger families have higher income limits–“poverty thresholds”–than do smaller families. Families headed by adults over the age of 65 years have lower income limits than families headed by younger adults. According to the Census Bureau, a family is one or more people living together and related by birth, adoption, or marriage.
To understand why broadening the definition of family unit sets up a more accurate measure of economic (in)security, consider the following situations that arise under the Official Poverty Measure: Continue reading →
When you sat down to fill out the 2010 Census form, what category did you choose for your relationship to the household head? Did you choose “husband or wife”? Or maybe “stepson or stepdaughter”? “Roommate”? Did it strike you as odd that you couldn’t choose “concubine,” or “polygamous wife”? Or, better yet, did you wonder why the form even requested your relationship status in the first place?
This is one of my favorite demographic maps. It was produced by the Census Bureau to show the most commonly reported ancestry for each county in the United States in 2000. Even though the data is over 13 years old, the map remains very popular.
Since a follow-up map for 2010 has not been produced yet, I thought it would be more than worthwhile to create this map using Census American Community Survey data.
Largest Ancestry: 2010
The methodologies used in making the 2000 and 2010 ancestry maps are similar, but there is one important alteration in the 2010 map. Ancestries that can be logically grouped together were combined so they might be better represented on the map. For example, Scandinavian ancestries: Norwegian, Danish, Swedish and Finnish, are very common in the Upper Midwest. Individually, they are the most popular ancestries in only a few counties, but when grouped together, Scandinavian is the most common ancestry in over 70 Upper Midwest counties.
Much has been made of the living preferences and economic situation of millenials. In the current economy, most localities can expect to lose almost all of their brightest young people to college towns. Whether these localities are able to lure these college graduates back is another story, and an important one since (many argue) it’s during the free-and-easy years after college that most young people will start businesses, launch careers, and develop regional networks and allegiances.
In this post, I’ll take a closer look at the people who were in their 20’s during the 2010 census. That’s people born between 1980 and 1990. As one might expect, those 80’s babies were reasonably well-distributed when the prior census was taken in 2000. At this point, the millennials were anywhere from 10 to 19 years old. There was an uptick in college towns (18 and 19 year-olds), but it wasn’t huge. In fact, that uptick helps to balance out the number of millenials who were undergraduates during the 2010 census (20 and 21 year-olds).
Ten years later, some of those kids are still in college or graduate school, some are young professionals, some are in the military, some are in prison, and some have young families with several kids.
Metropolitan Statistical Areas (MSAs) or Metro Areas are perhaps the most common way to define an urban region. Because many urban areas cross into multiple localities, such as in Hampton Roads, MSAs are frequently used in the public and private sector to understand an urban area and its suburbs. Despite the widespread usage of MSAs, it is actually very difficult to find an up-to-date map of Virginia’s MSAs, which is why I created this updated map following the 2013 definitions from the Office of Management and Budget.