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Many Missouri Counties “Struggling”

Into the discussion of whether sprawl leads to economic growth or economic growth leads to sprawl comes an interesting article by Alan Flippen in The Upshot, a blog published in the New York Times. He and Annie Lowrey ranked counties on 6 measures of education, income, unemployment, and health. They posted a wonderful interactive map on the Times webpage. It shows all the counties in the country. You mouse over them, and their ranking pops up, along with data on the 6 measures. (Find the map here.)

A county that is doing well would be one that is healthy, educated, and has a good economy. One that is struggling has poor health, low education, and a poor economy.

As you look at Missouri on their map, it is clear that taken as a whole, the state would not fare well–most of the state’s counties are struggling, only a few are doing well. There are states that are doing much, much better, but there are also states doing considerably worse – almost the entire South, plus Appalachia.

In Missouri, most of the southern part of the state is seen as struggling, while metropolitan regions and the far Northwest of the state are doing well. While this would appear on the surface to be related to the discussion of sprawl, I really think it is more of an urban-rural dichotomy. Urban centers tend to do better on measures of health, education, and the economy. There is also a north-south split in Missouri, with the struggling counties centered on the Ozarks. This may have something to do with the difference in topography: relatively flat, fertile farmland in the North, and rocky, mountainous land in the South.

This article appeared after I wrote the two preceding articles, but before they went live on the blog. It is strange how often something like that happens. It isn’t a government report or a study in a reviewed journal, so take everything it says with a grain of salt. Still, it is interesting and you might want to check it out.

Source:

Flippin, Alan. June 26, 2014. “Where Are the Hardest Places to Live in the United States?” The Upshot Blog in The New York Times. http://www.nytimes.com/2014/06/26/upshot/where-are-the-hardest-places-to-live-in-the-us.html?ref=us.

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Are Compact or Sprawled Regions More Economically Vital?

It would be easy to read my previous two posts about the Compactness Index and get the impression that sprawl is an evil in-and-of itself, while compactness is similarly a virtue in-and-of itself. I would caution against such easy assumptions, however.

Sprawl is the tendency for people to move away from densely populated central areas into less dense areas on the edge of cities or just outside them. People have been doing it for a long time, as the word “suburban” was apparently invented by Cicero, the ancient Roman orator. The fact that people have been doing it for such a long time, and that the trend continues, might be taken by some as prima facie evidence that suburbs are “better” than city cores.

Sprawl became a topic of significant discussion for American urban planners when the automobile became ubiquitous after World War II, freeing millions of Americans to move to the suburbs. Jobs and commercial development went with them. The causes are complex, but many urban centers depopulated and suburban areas grew like wildfire. Urban centers were sometimes left with shrunken tax bases, reduced populations, empty and decaying buildings, and large infrastructure networks that were no longer fully used and difficult to maintain with decreased revenues. Often it was the impoverished dispossessed who remain behind. This obviously represented problems for those urban areas, and sprawl has been a contentious political issue ever since.

There has been a proliferation of research purporting to show certain advantages or problems associated with both high density and low density. The research is difficult because of inherent problems separating which factors are causes and which are effects, and because there are many, many complicating factors that are virtually impossible to control.

I am comfortable with the idea of developing the Compactness Index. As I noted in the previous post, there may be other factors that tell you more about the differences between regions, nevertheless having a measure of sprawl is bound to help study the phenomenon. Smart Growth America is a national organization that researches and advocates for what have come to be called “smart growth” policies. They are often anti-sprawl. They were one of the sponsors that paid for development of the Compactness Index discussed in my previous two posts. The development of the index and the index values for MSAs and counties was published in Measuring Urban Sprawl and Validating Sprawl Measures, a report by the index developers that is available on the website of the National Cancer Institute.

In addition, however, Smart Growth America published its own report describing the index: Measuring Sprawl 2014. In addition to describing the index and giving index values for MSAs and counties, this report provides illustrations of the way the index can be used in research, and makes some claims for what has been discovered about sprawl. One of these claims disturbed me: “Compactness has a strong direct relationship to upward economic mobility,” the report claims in bold, colored lettering. (p. 9)

I came away from reading this with the impression that the report was claiming that compact areas were economically more vital than sprawled areas. Living in the St. Louis region, where such a claim is obviously not true, I was appalled. Then I read more closely. I could see that it was easy to get that impression, and if you, dear reader, read the report, you might come away with it, too. But it is not exactly what the report claims.

Instead, the report specifically claims that if a child is born into the lowest 1/5 of the income distribution, it has a better chance of making the top 1/5 of the income distribution by age 30 in a compact region than in a sprawled region. Now, this is a bit of an arcane claim. I’m not sure why the extreme of moving from the bottom 1/5 to the top 1/5 should be of general interest. It might seem that the more likely scenario of moving up one quintile would be more important.

I’m also struck by the use of quintiles to begin with. The simple laws of mathematics require that if some people are moving to higher quintiles, they have to be balanced by other people moving to lower quintiles. So, it must be equally true that more people drift down toward the lowest income level in compact areas also. As you might suspect, Smart Growth America doesn’t mention it.

The report gives an example: “The probability of an individual in the Baton Rough, LA area (index score: 55.6) moving from the bottom income quintile to top quintile is 7.2 percent. In the Madison, WI area (index score: 136.6) that probability is 10.2 percent.” (p.9) Thus, by moving from the 6th most sprawled MSA to the 13th most compact MSA , a person’s chances of moving up have increased less than 3%. Not a very big difference, frankly.

Sprawl of Forbes Best & WorstIt made me wonder, though, how does compactness relate to economic growth? And I decided to do my own “back-of-the-envelope” study. In fact, I did two.

First, I looked up the Forbes Magazine list of the most desirable and least desirable places to live in America. I used the Forbes list because the primary factors they consider in their rankings are economic growth and the unemployment rate. I took the 10 most desirable locations and computed the average Compactness Index for them.Then I took the 10 least desirable locations and computed the average Compactness Index for them. There were a couple of places for which there was missing data because Forbes and the Compactness Index defined their metropolitan areas differently. But I found exactly the inverse of what Smart Growth America seemed to be claiming. (See table at right.) The 10 best places to live, presumably the ones with the highest economic growth and lowest unemployment, had an average Compactness Index of 103.01. The 10 worst places to live, presumably the ones with the lowest economic growth and highest unemployment, had a Compactness Index of 109.20. The high economic growth areas were more sprawled, the low economic growth areas were more compact.

Most & Least Econ Change TableI wasn’t comfortable stopping there, however. Forbes is a mass media publication, and the articles I saw didn’t describe their data methods in sufficient detail. So I did my own study. I compared the economic growth of the most compact and least compact MSAs. Specifically, using data from the Bureau of Economic Analysis, I computed the average economic growth rate for 2010-2012 for the 10 most sprawled MSAs and for 10 of the 11 most compact MSAs (economic data for one MSA was not available). The second table at right shows the results. The most sprawled MSAs grew an average of 2.21% per year, while the most compact MSAs grew an average of 1.19% per year. That is more than a 1% per year difference, a very large difference!

Now, these are informal “back-of-the-envelope” studies, and there are some significant methodological problems. The fact that the various lists may not have defined metropolitan areas similarly may not matter, but it might matter a lot. My little studies don’t prove anything. But they do seem to align with common perception, and perhaps they are sufficient to cast doubt on the importance of the Smart Growth America claim.

They also illustrate the difficulty separating cause from effect. Economic growth seems associated with sprawl, but is that because sprawl creates economic growth, or because economic growth creates more sprawl? Interesting question, hard to answer!

The reason I’ve gone into these issues in such detail is because they illustrate two issues that are very important to this blog. I had no problem with the report issued by the developer of the Compactness Index. It was posted on a federal government website. It appeared to me to be a reasonable and competent bit of research. It was only in the report issued by the interest group that I found the problem. That is why I tend not to use reports by interest groups in this blog. There are wonderful interest groups out there, and I don’t mean in any way to impugn the overall work of Smart Growth America. But I can’t use reports from interest groups for this blog.

Second, it illustrates a problem with all statistics. The famous quote says that there are lies, damn lies, and statistics. To really understand something, you have to go beyond the raw statistics and understand what is really being said. This blog is all about statistics. I try to read the statistics I report in this blog with a thoughtful and skeptical eye, but I am not an environmental scientist. If you are aware of problems with statistics I reporrt, I hope you will comment and let me know.

Sources:

For Cicero inventing the word “suburb”: “Suburb.” Wikipedia. Viewed 6/17/14 at http://en.wikipedia.org/wiki/Suburb.

Ewing, Reid, and Shima Hamidi. 2014. Measuring Urban Sprawl and Validating Sprawl Measures. Salt Lake City: Metropolitan Research Center, University of Utah. Downloaded 6/13/14 from http://gis.cancer.gov/tools/urban-sprawl/.

Smart Growth America. 2014. Measuring Sprawl 2014. Downloaded 6/13/2014 from http://www.smartgrowthamerica.org/measuring-sprawl.

Greenburg, Zack O. “America’s Most Livable Cities,” Forbes Magazine, 4/1/2009. Downloaded 6/13/14 from http://www.forbes.com/2009/04/01/cities-city-ten-lifestyle-real-estate-livable-cities.html.

“Gross Domestic Product by Metropolitan Region,” Regional Economic Accounts, Bureau of Economic Analysis. Data downloaded on 6/18/2014 from http://www.bea.gov/regional.

Missouri Is Sprawling

In the previous post I reported on efforts to create a single index to represent how sprawled or compact a metropolitan region was. I included 2 tables, one showing the Compactness Index for 29 counties in Missouri, and another showing the Compactness Index for 3 Missouri metropolitan statistical areas (St. Louis, Kansas City, and Springfield).

The Compactness Index was originally constructed using data from the 2000 census, and recently updated using data from the 2010 census. The composition of the index was changed between the two, but in order to make comparisons between the years consistent, the authors went back and recalculated the 2000 data for counties using the new index.

MO County Change ChartThe chart at right shows the change in compactness for the 26 Missouri counties for which both 2000 and 2010 data were available. Values below zero mean that the county became less compact, more sprawled. Twenty-two out of 26 counties in Missouri became less compact. Bates County led the way, with a whopping 24.16 decline in compactness.

(Click on chart for larger view.)

Similar comparisons for the St. Louis, Kansas City, and Springfield MSAs are unavailable.

Now, here’s a question: Bates County is on this list because it is part of the 14-county Kansas City MSA. However, it is a county of 17,049 souls about midway between Kansas City and Joplin. Butler is the largest town, with a population of 4,219 in the 2010 census. Outside of Butler, the population density is about 20 people per square mile. If a county is not part of an MSA, the Census Bureau requires at least 1,000 people per square mile for it to be urban. I noted in a previous post that small towns can sprawl just like large cities do, but I’m not sure why it makes sense to analyze an entire county like Bates County for urban sprawl.

The same could be said for other counties on the list. Caldwell County, for instance, is part of the Kansas City MSA, but it has only about 21 people per square mile. Lincoln County is part of the St. Louis MSA, and it has about 82 people per square mile. Polk County is part of the Springfield MSA, and it has about 48 people per square mile. Including these counties in analyses of larger MSAs seems like one thing, but why does it makes sense to analyze them separately for urban sprawl?

Let’s take a couple of additional examples to illustrate the point that other factors may tell you more of what you need to know about a region than the sprawl index. The Kansas City MSA has a Compactness Index of 77.60. The next lower MSA on the list is Palm-Bay-Melbourne-Titusville, Florida. This is the coastal region alongside the Cape Canaveral Space Center. Despite being similar on the Compactness Index, I suspect that these two regions are more different than the same.

The St. Louis MSA has a Compactness Index of 82.06. The next higher MSA on the list is Bakersfield-Delano, CA. St. Louis sits alongside the nation’s largest river, a former industrial powerhouse that was founded in 1764. The demographic majority is White, with African-American being the largest minority. Bakersfield was founded a century later. Three of its largest four employers are farming companies, and it is also the seat of the county that produces more oil than any other in the lower 48 states (Kern County). The largest demographic group is Hispanic, with Non-Hispanic Whites being the largest minority. Despite being similar on the Compactness Index, I suspect that these two regions are more different than the same.

So, Missouri is sprawling, as are most places in America. I’m just not sure what it means.

Source:

Ewing, Reid, and Shima Hamidi. 2014. Measuring Urban Sprawl and Validating Sprawl Measures. Salt Lake City: Metropolitan Research Center, University of Utah. Downloaded 6/13/14 from http://gis.cancer.gov/tools/urban-sprawl/.

For county-level oil production: County-Level Oil and Gas Production in the U.S., Economic Research Service, United States Department of Agriculture. Data downloaded 6/19/2014 from http://www.ers.usda.gov/data-products/county-level-oil-and-gas-production-in-the-us.aspx#.U6LaMagU_5I.

“Greater St. Louis,” Wikipedia. Viewed 6/16/2014 at http://en.wikipedia.org/wiki/Greater_St._Louis.

“Bakersfield, California,” Wikipedia. Viewed 6/16/2014 at http://en.wikipedia.org/wiki/Bakersfield,_California.