Tag Archives: MSA

Brookings map shows MSAs mapped the right way

The previous post discussed the problems with maps of Metropolitan Statistical Areas that showed the extent of the counties included. It included this map from the Census giving the misleading impression that the area of the greatest population increase was in the southwestern United States, the large dark purple area:

Percentage Change in Metropolitan and Micropolitan Statistical Area Population: 2000 to 2010. Source: Metropolitan and Micropolitan Statistical Area Population: 2000 to 2010. Source: U.S. Bureau of the Census. 2011. Population Distribution and Change: 2000 to 2010. 2010 Census Briefs.

Source: U.S. Bureau of the Census. 2011. Population Distribution and Change: 2000 to 2010. 2010 Census Briefs.

In that post I also presented an alternative map of MSAs that avoids this problem and referred to a note with a more extensive discussion of these issues. That note ended with my doubts about whether the way MSAs were mapped would change. I was wrong.

A recent post by William Frey of the Brookings Institution looked at recent population changes from a new census report (US population disperses to suburbs, exurbs, rural areas, and “middle of the country” metros). It includes a map illustrating population changes from 2016 to 2017 for the 100 largest metropolitan areas:

Source: William H. Frey analysis of U.S. Census Population Estimates, released March 22, 2018

Source: William H. Frey analysis of U.S. Census Population Estimates, released March 22, 2018

Hooray! Point symbols are used to map the MSAs and their population changes. The map does not give the misleading impression of the Census map shown above.

One very minor suggestions to Brookings for further improvement: The points appear to be located at the centers of the MSAs. It would be even better if they were located in the vicinity of where most of the populations of the MSAs were located.

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The problem with maps of Metropolitan Statistical Areas

Metropolitan Statistical Areas (MSAs) are one of the most important statistical units for the reporting of data by federal agencies. It is common to see maps of showing those areas, such as this map from the census illustrating changes in population from 2000 to 2010:

Percentage Change in Metropolitan and Micropolitan Statistical Area Population: 2000 to 2010. Source: Metropolitan and Micropolitan Statistical Area Population: 2000 to 2010. Source: U.S. Bureau of the Census. 2011. Population Distribution and Change: 2000 to 2010. 2010 Census Briefs.

Source: U.S. Bureau of the Census. 2011. Population Distribution and Change: 2000 to 2010. 2010 Census Briefs.

The MSAs are colored with various shades of purple, darker for greater percentage population change. (The green areas are the Micropolitan Statistical Areas, the smaller analogues of the MSAs.)

A large area of MSAs can be seen in the southwestern United States, extending from eastern Arizona to the Pacific (and up through California). But much of this area is hardly metropolitan in any meaningful sense. It is sparsely settled mountains and desert land. The only reason this is within MSAs is that MSAs are composed of entire counties. And many counties in the West are very large, resulting in such empty areas being included along with the portions of the counties that are truly metropolitan. (See my earlier post on not calculating densities for MSAs for further discussion.)

This not only affects perceptions of the extent of metropolitan areas, it can also be quite misleading when MSAs are used to map data. Consider the map shown above. The darkest purple areas are the MSAs that had the greatest percentage population increase over the decade. One immediately observes the very large dark purple area extending across southern California, Arizona, and even into Nevada and Utah. So is this where large population gains were most dominant? Looking more closely at the map, you might notice that numbers of the MSAs in Texas are also dark purple. In comparison, these areas look small and scattered. But they include all of the largest MSAs in Texas and many smaller ones. And the Texas MSAs in this highest growth category had a total population in 2010 that was over twice that of the highest-growth MSAs in the southwest. Sizes of MSAs can be very misleading.

But MSAs do include entire counties, so what is the alternative for mapping these areas? One possibility is to use point symbols in place of the county areas for showing the presence and location of MSAs. And if one wants to show some characteristic of the MSAs, the sizes of those symbols can be varied. This is an alternative map of MSAs with the symbols graduated to show the population sizes of the areas:

Metropolitan Statistical Areas by Population 2010.

Metropolitan Statistical Areas by Population 2010.

A more extensive discussion is in the note, “The Problems with Maps of Metropolitan Statistical Areas,” which can be downloaded here.

What you can’t say about variation within metropolitan areas

The New York Times recently published an article titled (on the web) “Why Outer Suburbs in the East and Midwest Have Stopped Booming.” It’s a curious piece, based on data by county across the U.S., showing those counties in which deaths have exceeded births. Indeed, the article includes an animated map of the entire country showing such counties from 1991 to 2016 and notes that over 1,200 counties had more deaths than births in 2016. This map of the counties, by the way, provides absolutely no way of identifying the counties in the outer suburbs of metropolitan areas or, for that matter, metropolitan area counties in general.

But the primary focus of the article, from the first paragraph to the last, is on what the title refers to as “outlying suburbs.” The article states that “about one in four outer-ring suburbs were experiencing more deaths than births, including 18 of 30 such counties in New York, New Jersey and Pennsylvania,” equating the outer-ring suburbs with counties. I won’t quibble about the lack of any definition of how a county is considered to be an “outer-ring suburb.” This is, after all, a piece of journalism, not a scholarly article.

The problem with drawing the conclusion about regional variation in births and deaths in outlying counties (claimed to be an issue in the Northeast and Midwest) is that this requires the existence of such “outer-ring suburb” counties. And the reporter’s view does not go that far west of the Hudson River, as is so often the case with the New York Times. Note the reference to the counties in New York, New Jersey, and Pennsylvania.

In order for a metropolitan area to have outer suburban counties, the metropolitan area must have a sufficient number of counties so that these can be distinguished from the inner suburban counties and from the urban area counties. For this to be the case, the metropolitan area must be fairly large and the counties must be quite small. And this is the problem. The Northeast and Midwest have numerous metropolitan areas that meet these criteria, for which one can draw such conclusions about “outer-ring suburbs.” Some metropolitan areas in the South also meet these criteria–the Atlanta metropolitan area would be a prime example, consisting of many counties.

But metropolitan areas in the West, where counties tend to be larger–often much larger–have few, if any counties that could be considered to be “outer-ring.” The San Diego Metropolitan Statistical Area (MSA) consists of one county. The Los Angeles MSA has 2 counties. San Francisco-Oakland MSA has 4 counties, but none could reasonably be considered to be “outer-ring suburbs.” If one took a more expansive view of the metropolitan areas than the MSA definition (which I would advocate), it might be plausible to identify a few counties as being outlying suburban counties. But even then, these would be few and isolated. Nowhere near the number of counties for which you could draw conclusions like the 18 of 30 counties in New York, New Jersey, and Pennsylvania.

Bottom line: It may be the case that “outer-ring” suburban counties in the Northeast and Midwest are now experiencing more deaths than births (though this is necessarily a weak conclusion given the lack of a definition of those counties). But stating this conclusion implies that this is not the case in the South and West. And it is impossible to draw any conclusions about “outer-ring” suburbs in most of the West based on county-level data.

You cannot say anything meaningful about variation within metropolitan areas across the U.S. using county level data. Differences in the sizes of counties and the very large counties in the West make this impossible.

On the choice of Combined Statistical Areas

Last year, I wrote a post discussing why I chose to use the larger Combined Statistical Areas (CSAs) for my urban patterns research rather than the commonly used Metropolitan Statistical Areas (MSAs). I followed this up with a second post giving examples of how the sharing of transportation infrastructure–commuter rail and airports–could be an indicator of the integration of areas that should be considered together as a single, larger metropolitan area.

This decision to use the CSAs is of such fundamental importance to my research that I felt it deserved more extended, formal treatment. I prepared the paper “On the Choice of Combined Statistical Areas” that provides greater background, covers the topics addressed in those blog posts in more detail, and addresses some other implications of the the choice of CSAs over MSAs. It also shows how the CSAs are comparable in extent to MSAs as they had been defined earlier for the 2000 census. This last topic was also addressed in an earlier post.

The paper is posted on the Research page of the website and can also be downloaded here.

Defining exurban areas

For the urban patterns research, in addition to delineating the urban areas for each year, I wanted to delineate exurban areas beyond the urban areas that could reasonably be considered to be parts of the metropolitan area related to the urban core. Unlike the census Urbanized Areas, however, there is no accepted standard definition for exurban areas. Fortunately, a thorough review of past studies of exurban areas and how they were defined has been provided by Berube and others (Finding Exurbia, Brookings, 2006).

A minimum population or housing unit density–obviously much lower than the urban density threshold–was the most common criterion used in defining exurban areas. Other factors were also considered, especially commuting to the urban area. Data are not available over the entire period of the urban patterns dataset to allow the use of commuting. However, the maximum extent of the exurban area would be limited to the area of the Combined Statistical Area (CSA) or Metropolitan Statistical Area (MSA), which at a minimum guarantees interaction with the urban area for 2010 for the counties as a whole, if not for individual tracts.

I decided to define exurban areas as the sets of contiguous tracts that were adjacent to the urban areas and had housing unit densities greater than some value. The minimum density levels used to define exurban areas in various studies varied widely, from 40 acres per housing unit down to about 10 acres per unit. (For studies using the lowest densities, the extent of the exurban areas was most often limited by the commuting criterion rather than density.) I approached the problem by mapping the tracts meeting different minima in 2010 to make a judgment as to what looked reasonable.

The very low minimum density thresholds of 30 or 40 acres per unit frequently resulted in all or most of the CSA or MSA being considered exurban, with the tracts meeting these levels extending far beyond those areas, especially in the eastern U.S. On the other hand, a density minimum of 10 acres per unit produced much smaller exurban areas than seemed reasonable and consistent with personal observation.

The choice came down to thresholds of either 15 acres per unit or 20 acres per unit. The resulting exurban areas generally looked appropriate for most areas. The final choice of 15 acres per unit came down to a number of specific situations where the lower density level produced areas that seemed too large. I’ll give two examples: The exurban area for Indianapolis in 2010 would have extended south at least halfway to Louisville, through area I would never consider exurban. And the Portland exurban area would have encompassed a large portion of the Willamette valley.

A further check reinforced my decision on the minimum density for exurban areas of 15 acres per unit, which is one-fifth of the urban density theshold. For CSAs or MSAs adjacent to other CSAs or MSAs, it was not uncommon for both exurban areas to extend to the common boundary. But for areas not adjacent to others, the extent of contiguous exurban density tracts was generally either confined within the boundaries of the CSA or MSA or extended beyond the boundary at only one or two points, with a string of exurban density tracts along a highway. (This is much like census Urbanized Areas, which frequently have such tendrils of urban development extending outward.) So the density threshold for exurban areas seems consistent with the areas of significant metropolitan interaction as indicated by the CSA and MSA boundaries.

Data for studying urban patterns over time

I want to study urban spatial structure over an extended period of time. Here are my data requirements: Data for population or housing units that can show the level of urban development. Data for small areas that enable the definition of the extent of urban development and the examination of distributions within the urban areas. Data for multiple points in time–as many as possible. Data for the same small areas at each point in time, to allow examination of changes in those areas over time.

My dataset begins with a unique resource, the Neighborhood Change Database created by the Urban Institute and Geolytics. This dataset includes census tract data from the 1970 through 2000 censuses, with the data for the years from 1970 through 1990 normalized for the 2000 census tract boundaries. So that’s 4 points in time. The block data from the 2010 census for population and housing units can be aggregated to the year 2000 tract boundaries, giving another year.

While many studies use population and population densities to study urban patterns, I have chosen to use housing units (as have others). They are more fixed and I think better represent the pattern of urban development. (The Census Bureau uses a minimum population density threshold to define urban areas. It is literally possible for an area to go from rural to urban from one census to the next without any new housing being developed. All it would take is an increase in population, for example, some babies being born.)

Using housing units also provides the opportunity to extend the data back in time. The census and the Neighborhood Change Database include the distribution of housing units by the year in which they were built. One can use this information for 1970 to estimate numbers of housing units that existed in earlier years. There are errors, as this approach cannot take into account changes to the stock of the older units that have occurred in the interim. I did an analysis that considered the extent of the error and concluded that it was reasonable to estimate housing units for the tracts back two decades, to 1950 but not further. This is discussed in a note Year-built Estimates Analysis on the Research page.

A remaining question involved which areas to examine and what would be their extent? As I noted in an earlier post, I believe Combined Statistical Areas (CSAs) better represent the extent of metropolitan areas than Metropolitan Statistical Areas (MSAs). I am choosing to examine urban patterns within the 59 CSAs (or MSAs, for areas not included in a CSA) that had populations over 1,000,000 in 2010.

Documentation of the urban patterns dataset is provided in a note Urban Patterns Dataset Description on the Research page.

Problems with the urban and metropolitan area definitions

The previous post described how the changes to the metropolitan area definition resulted in the splitting of numbers of large Metropolitan Statistical Areas (MSAs) as they were delineated for the 2000 census into 2 or more MSAs in 2003. This raised the obvious question, what was it about the new definition that produced these changes? The answer proved to be complex and bizarre, and the situation was only made worse by a horrible decision made by the Census Bureau with the 2010 Urbanized Area (UA) definition.

A major change made in the MSA definition first used in 2003 was to begin the delineation with the Urbanized Areas, including all counties with substantial portions of a UA in the MSA. After that, commuting to those central counties was used to add outlying counties to the MSA. The definition included provisions for merging adjacent MSAs using the same commuting criterion, but this made it highly unlikely that adjacent large MSAs could ever be merged. So as a result, the general extent of MSAs was determined by the extent of the UAs. If an area of contiguous urban settlement were split into 2 or more UAs, this would likely produce multiple MSAs.

So now we have to go to the UA definition. The new UA definition for the 2000 census provided for the splitting of large urban agglomerations into multiple UAs using the MSA (and CMSA and PMSA) boundaries as delineated for the census. So the extent of the MSAs depended on the UAs, and the extent of the UAs depended on the MSAs! It is a circular definition!

So what happens with the UAs for 2010? The Census proposed to maintain the status quo, keep the largest UAs with populations over a million the same, but not split smaller urban agglomerations, so contiguous UAs would be merged. This generated opposition from those in areas that would be merged, as this could affect the receipt of federal funding. The. Census response was to surrender and make the decision that the set of UAs that were delineated in 2000 would be frozen! Each 2000 UA would continue to be a UA in 2010! And since the MSAs continued to be based on the UAs, they would be largely frozen as well.

Since the beginning of the UA and MSA definitions in the mid-twentieth century, the areas had been allowed to evolve, with areas being combined as formerly separate areas grew together and were more reasonably considered a single entity. For example, Dallas and Fort Worth started as separate UAs and MSAs but for decades have been considered to be a combined area. What the Census Bureau did with the 2010 UA definition was to say that the delineation of urban and metropolitan America would be frozen as it was in 2000 and would not be allowed to further evolve. This was a truly horrible decision. And the Census Bureau knew it, as was clear from the misleading obfuscation of what they were doing in the Federal Register notice for the 2010 UA definition.

Far more detail is provided in a research note discussing the problems with the urban and metropolitan area definitions that is posted on the Research page and can also be downloaded here.