Austin Contrarian

If Okies can do it . . .

Oklahoma City plans to re-route an interstate highway away from downtown:

In Oklahoma City, the interstate will be moved five blocks from downtown to an old railroad line. The new 10-lane highway, expected to carry 120,000 vehicles daily, will be placed in a trench so deep that city streets can run atop it, as if the highway weren't there.

The old highway will be converted into a tree-lined boulevard city officials hope will become Oklahoma City's marquee street.

By tearing down the Crosstown Expressway, the city hopes to spur development of 80 city blocks stretching from downtown to the Oklahoma River — an area that contains vacant lots, car repair shops and a few small homes.

"We've always been a good place to live, but we've never had a city we could show off," Oklahoma City Mayor Mick Cornett says. "Moving the expressway makes it possible for a day to come when hundreds or thousands of people will live downtown."

The project will cost $557 million, mostly federal and state funds. The city will pay to spruce up the boulevard, build parks and put a pedestrian bridge over the new below-ground interstate.

If Oklahoma City can do this, why not Austin? 

Housing + Transportation Affordability Index

Check out this totally cool site that maps housing plus transportation costs (plus a whole bunch of other statistics, like average block size) by census block group.  They use census data to estimate the average home and transporation costs as a percentage of median income. The map's creators' point is that those suburban homes are a whole lot more expensive when you factor in transportation  costs. 

I'm fuzzy on their methodology for estimating transportation costs.  I spot-checked the block groups around my neighborhood, and found big differences in transportation costs that I'm skeptical exist.  And bear in mind that housing + transportation costs may take a huge bite out of, say, a Pflugerville household's income, but they would probably be a mere nibble compared to the bite of a central Austin mortgage payment.

Still, this is the coolest thing I've seen in a while.  (I admit that I probably have a warped sense of "cool.")

H/t Smart Growth around America.

More on weighted density for the crackpot blogging stats geeks

I've hit on this in the comments to other posts, but one of the nice features of weighted density is that it permits us to compare apples to apples (even though the comparison may be royal gala to red delicious).  Standard density is extremely sensitive to geographic boundaries.  This is why most debates over density quickly turn into squabbles over the proper geographic unit.  CMSA?  MSA?  Urbanized area?  Central city?  And then it's just a matter of time before someone brings up City  X's moutains or parks or other uninhabitable land that drag down its density. 

Because weighted density is determined by the density at which most people live, adding or subtracting land at the margin -- even a lot of land -- does not matter much unless the land contains a large chunk of the population.  Weighted density does not depend on precisely how the geographic area is defined.

Example:  In 2000, Houston's urbanized area had a population of 3,822,000 and a standard density of 2,951/square mile.  Houston's Primary Metropolitan Statistical Area* had nearly four times the land area but only about 355,000 (10%) more people.  (The PMSA has a lot of cows.)  As a result, Houston's PMSA had a measley 706 persons per square mile, just a little over one person/acre.

The PMSA's weighted density, however, was a more respectable 4,296.  That's only 5% off the urbanized area's weighted density of 4,514.  Adding a bunch of cow pastures does not change the fact that the vast majority of the PMSA population was bunched at a much higher density.

The same holds for Portland.  In 2000, its PMSA had a standard density of just 381/square mile.  But the PMSA's weighted density was 3,943/square mile, down just 10% or so from the urbanized area's weighted density of 4,383. 

Note that a lot of the vacant land around Houston is vacant simply because no one has gotten around to developing it yet.  A lot of the land around Portland is vacant because of policies designed to preserve open space and slow sprawl.  This difference is often a flash point for disagreements over geographic boundaries. Weighted density allows us to sidestep these arguments by focusing on the density at which the average person lives.

*A PMSA consists of one or more counties within an MSA that have substantial commuting interchange.

Density calculations for U.S. urbanized areas, weighted by census tract

I recently calculated the weighted densities for a number of cities using the Census Bureau's "central place/non-central place" classification.  As I explained in that post and the comments, this is actually a coarse measure of weighted density because central places themselves are usually large cities with pockets of wildly varying density.

I have now calculated the weighted density of 34 large urbanized areas using census tracts.  (See my last post for an explanation of weighted (or "perceived") density.)

I took the 32 largest U.S. urbanized areas and added Austin and Honolulu for good measure.  I pulled the Census data on each census tract partially or completely contained within each of these urbanized areas.  I calculated the standard density (i.e., total population/total land area) for each census tract.  I also calculated each census tract's share of the total population of the urbanized area.  I then assigned each tract's density a "weight" equal to its share of the total population.  I summed the weights to get the weighted density for the urbanized area. 

I'm preparing a permanent page with more information on the methodology and limits of this approach.  (It's a very good method, though, in my opinion.)

But that technical stuff can wait a few days.  Here are the weighted densities, ranked from most dense to least dense:

         

(Chart on Scribd)

This approach obviously does a much better job of reflecting our perceptions of a city's density.  LA's urbanized area is denser than NY's when using the standard density metric; NY's urbanized area is almost three times denser using weighted density.  (LA is still quite dense, though.) 

Weighted densities straighten out a lot of other counterintuitive "facts."  Austin and Tampa are not really denser than Boston (as the standard density figures suggest), and the sprawling suburbs of Riverside County are not actually denser than Chicago. 

Note that Portland's urbanized area is less dense than Houston's.  The urbanized area most like Portland's, viewed strictly by their density profiles, is Riverside-San Bernardino.

New York is an outlier at the upper end, while Atlanta is an outlier at the lower end.

The "density gradient index" is a term I made up to dignify what is a pretty simple calculation:  weighted density divided by standard density.  The index would be an even 1 if a city's population were uniformly distributed across the landscape.  The larger the index, the more uneven the distribution.  I'll go into this in more detail on the permanent page, but you can get a rough idea of a city's urban form just by looking at the weighted density, standard density and density gradient index.

(There really is something called the "density gradient," but it is a curve rather than a number, and there is no "index" for it, as far as I know.)

More here.

The geography of gasoline consumption

I've done some more thinking about the Glaser and Kahn paper I bogged about the other day.  Glaser and Kahn examine total energy use among major metropolitan areas in order to compare cities carbon emissions.  But their data also allow us to compare gasoline use city by city.  That's just as interesting a comparison, at least to me.

Glaser and Khan even allow us to make an apples-to-apples comparison because they have constructed a composite "median" household for each city to use as their points of reference.  For example, they don't use per capita gasoline consumption as their point of comparison.  They instead estimate the expected gasoline consumption of a hypothetical $62,000/year household with 2.62 members for each city, using survey data and (I assume) some fancy statistical techniques.

They report pounds of carbon emitted rather than gallons of gasoline consumed, but since they tell us how much carbon they assume one gallon emits (23.47 pounds), we can easily convert their data into gallons. 

Here is the relevant table from their paper:

Here is a chart I compiled from their data depicting relative gasoline consumption:

The thing that struck me when I looked at the numbers was the relatively small difference in gasoline consumption between Houston and most other cities.  (Third column.)  Glaser and Kahn's hypothetical $62,000/year household uses only 55 more gallons per year in Houston than in D.C.  It uses only 135 gallons more gallons per year than the corresponding Sana Francisco household.  The Houston-Chicago gap is only 118 gallons per year.

The gap between Houston and old-line northeastern cities (particularly New York) is larger, but is largely offset by their greater consumption of heating oil.  (Remember Hugo Chavez offering free heating oil to Boston's poor?)

This chart makes the point better:

There is no question that steep gas price hikes would hurt Houston (or Dallas or Austin) households.  At $3/gallon, the Houston household is already spending 5.4% of its gross income on gasoline.  At $4/gallon, it would have to spend 7.2% of gross income on gasoline, assuming no change in gasoline consumption.  But the Sana Francisco household is spending 4.8% of its gross income on gasoline, a figure that would rise to 6.4% with a $1 increase in the price of gasoline.  That 0.8% difference is smaller than I expected.

Glaser and Kahn also compare city and suburban gasoline use:

I summarize the corresponding gasoline consumption numbers in columns 5 and 6 of my chart, and compare suburban Houston households with central city residents elsewhere in column 7.  No surprise that the gap grows significantly.  But it is possible that, given their much higher housing costs, central city residents may be even more susceptible to price variations in commodities like gasoline.  Those suburban Houston households pay a lot less per square foot of housing than similarly situated households in LA, Sana Francisco or DC.

These simple charts don't tell the whole story, of course.  Gasoline consumption is not completely inelastic, especially over the long run.  One could argue that because residents of central cities have access to better mass transit, it is easier for them to substitute away from gasoline use, making their demand for gasoline more elastic than suburb dwellers.  Put simply, city dwellers can cut down on their driving more easily than suburbanites.

That's certainly plausible.  However, city dweller's access to better transit is already reflected in their lower gasoline consumption.  They've already picked the low-hanging fruit, so to speak.  The barrier to additional transit use is often not the difference in monetary cost, but the difference in time and convenience costs. 

Of course, there is some price at which drivers will begin to substitute to mass transit wholesale.  But the suburban drivers have options, too.  A Houston suburbanite who switched to riding the bus or carpooling would save (on average) more gasoline per commute than a central city resident.   Likewise, a Houston suburbanite who combined two errands would save (on average) more gasoline per errand. 

This is ultimately an empirical question.  Like everyone else, I think gas prices are headed up, at least over the next few years.  It will be interesting to see the relative adjustments made by Houston drivers and those in the more compact northeastern and western cities. 

Relative elasticities aside, the numbers are still interesting, especially the aggregate metropolitan area data.  I never would have guessed that a "typical" metropolitan Houston household uses only 5 more gallons per month than its metropolitan D.C. counterpart.

One final point.  There is one area where western and northeastern cities wipe the floor with us, the denizens of the hellishly hot places:  Electricity.  We use fiendish amounts of the stuff.  (There's archaeological evidence that Austin was inhabited before the invention of air conditioning, but some scholars dispute its conclusiveness.)  If electricity prices shoot up like gas prices, we will suffer a lot more than our friends out west and up north, and there'll be nothing we can do about it. 

Perceived density

Every once in a while -- invariably in a debate over sprawl -- someone will toss out the "fact" that the Los Angeles metropolitan area is denser than the New York metropolitan area. 

It's true.  At least, it's true if one uses the standard definition of density as gross population divided by gross land area.  According to 2000 U.S. census data, the Los Angeles "urbanized area" has a density of 7,068 persons per square mile.  The New York urbanized area has 5,309 persons per square mile.  Ergo, Los Angeles is denser than New York.

But common sense tells us that this coarse statistic is misleading.  Ryan Avent puts it well:

Los Angeles is hemmed in by its geography, so it can’t just keep spreading at ever lower densities out into the wilderness. As such, its density profile is like a plateau–not all that tall at anyone point, but with a respectable average height, because the long tails are excised. New York, by contrast, is like a mountain. It has an enormous peak containing most of the mass, but the flattening sides of the mountain continue on for miles.

In other words, the fact that the last million or so people in the New York metro area occupy an incredibly large area while the last million or so Angelenos are in moderate density suburbs packed against the very edge of the basin, skews the relative density figures, making them pretty uninformative.

A more meaningful metric is "weighted" density or "average perceived density."  Carve the metropolitan area into distinct regions (census tracts, for example), compute the density of each, and then assign each a weight based on its percentage of the total population.  This discounts large, sparsely populated census tracts, and gives extra weight to densely populated tracts.

An extreme but simple example:  Suppose Metropolis consists of a central core of 100,000 residents on 10 square miles, and a suburb of 10,000 on 100 square miles.  Its standard density is 1,000 persons per square mile. 

But this is a meaningless number.  Most of the residents of Metropolis live in a very dense environment.   The roughly 90% who live in the core are packed in at 10,000 per square mile, while just 10% live at the rural density of 100 per square mile.  By giving the core's density a weight of 90%, we get an adjusted density of 9,100 persons per square mile, a much better description of the density perceived by the average resident. 

I show the weighted densities for some U.S. cities below the jump.