Austin Contrarian

U-haul stat o' the day

I don't normally do the Austin booster thing, but courtesy of Mark Schill at Newgeography:

When comparing California with Texas, U-Haul says it all. To rent a 26-foot truck oneway from San Francisco to Austin, the charge is $3,236, and yet the one-way charge for that same truck from Austin to San Francisco is just $399. Clearly what is happening is that far more people want to move from San Francisco to Austin than vice versa, so U-Haul has to pay its own employees to drive the empty trucks back from Texas.

Schill also lists some net domestic migration numbers.  In 2008, Austin-Round Rock had the highest net domestic migration rate among all U.S. metropolitan areas with more than 1.5 million people.  Austin-RR had 22 net domestic migrants per 1,000 residents.  Comps:  Houston, 6.6; Dallas, 7.0; Washington DC, -3.4; Portland, 8.3; Denver, 7.3; Detroit, -13.9.

People sometimes take net domestic migration flows as evidence that one place is better than another.  This is wrong.  Flows instead show which cities are overvalued and which are undervalued.  That's why I don't put any stock in "best cities" lists.  You can figure out the "best cities" (whether for quality of life or jobs) by looking at property values.  You can figure out the "best bargains" by looking at  domestic migration flows.

PS.  Sorry to pick on Detroit again -- no schadenfreude here -- but these numbers show just how grim things are there.  Despite a low median home sales price -- $91,000 in April 2008 -- the Detroit metro area experienced a net outflow of 13.9 residents per 1,000 residents in 2008.  The metro area was grossly overpriced despite being very cheap.  Well overpriced:  the median sales price had dropped to a little under $45,000 by last April.  (Things are much worse in Detroit proper.)  

Central-core job density and metropolitan growth

As I mentioned last time, I have a couple of problems with Elizabeth Kneebone's study of "job sprawl."  The main one is that there is less to the study than might appear at first glance.

But there is a very interesting phenomenon lurking in her data that deserves some discussion

We should expect large metropolitan areas to have more jobs in the outer rings than small metropolitan areas.  That's just a function of size.  While scanning her data, though, I noticed that large metropolitan areas invariably have more jobs in their central cores as well.  Because Kneebone uses the same land area for all central cores -- the area within a 3-mile radius of the CBD --  this means that large metropolitan areas have a higher job density in their central cores than small metropolitan areas.

I decided to test this a little more rigorously.  I regressed central-core job densities on the number of metropolitan area jobs within 35 miles of the CBD.  (Actually, I used logs, but I don't want to get bogged down in the technicalities.)   I expected there to be an association between the two, but I was surprised by the tightness of the fit:

The correlation is .89 and the R-squared is .79.  This means, roughly speaking, that 80% of the variation in central-core job density can be explained by the number of jobs in the metropolitan area.  Doubling the number of metropolitan area jobs tends to increase the central-core job density by about 68%. (The slope of the trend line is 0.75.)

Think about this a second. This data set includes small metropolitan areas and large metropolitan areas. Young cities and old cities. Sunbelt cities and Northeastern cities.  Western cities and Midwestern cities. Cities with manufacturing economies and cities with information economies. Transit-oriented cities and autocentric cities. Dense cities and sparse cities. And yet central-core job densities grow at roughly the same rate across all types of cities; city form or structure doesn't matter much.*

Why?  One explanation might be that as cities add jobs, they invariably need more lawyers, insurance companies, banks and other support jobs.  This is true regardless of the type of economy or the distribution of jobs within the metropolitan area.  Perhaps this "invariant" (too strong?) shows that these service jobs benefit from a central location regardless of how the city grows outside the central core.  In other words, this might be evidence that certain professions believe there are benefits to agglomeration.  Just a theory. 

Or perhaps I'm making too big a deal about this.  In any event, I think this is the interesting story and one I'd like to see Kneebone or some other smart person address.

*Detroit and New York City are outliers here.  Detroit is an outlier because its central city is emptying out at an alarming rate.  New York is always an outlier because of Manhattan's extreme density.  Los Angeles is somewhat of an outlier but I think that's a function of Kneebone's narrow definition of CBD's; Los Angeles has some fairly old, dense concentrations of jobs (Long Beach, for example), that she excludes from the central-city core.

Update:  Spreadsheet on Google Docs.

Austin's "job sprawl"

This paper on "job sprawl" from Brookings has been getting lots of buzz.  The author, Elizabeth Kneebone, used Census data to measure the shift of jobs from central cities to suburbs for the 98 largest metropolitan areas.

She concludes that employment steadily shifted to the suburbs between 1998 and 2006:

Employment steadily decentralized between 1998 and 2006: 95 out of 98 metro areas saw a decrease in the share of jobs located within three miles of downtown. The number of jobs in the top 98 metro areas increased overall during this time period, but the outer-most parts of these metro areas saw employment increase by 17 percent, compared to a gain of less than one percent in the urban core. Southern metro areas were particularly emblematic of the outward shift of job share with a 2.6 percentage-point decline in urban core job share and a 4.8 point gain in the outermost ring, outpacing the 98 metro average (a 2.1 point decline and a 2.6 point gain, respectively).

I've got a few problems were her analysis (and her term "job sprawl"), but I thought the Austin statistics were surprising. 

In 2006, the 45 largest metropolitan areas  -- those with more than 500,000 jobs -- had an average of 19.6% of their jobs within 3 miles of their CBDs.  Austin was well above average:  24.4% of its jobs lay within the "urban core."  By contrast, Dallas had 10.6% of its jobs within the urban core, Houston had 11.6% and San Antonio had 14.7%.  (Although the San Antonio metropolitan area has 14% more jobs than the Austin metropolitan area, Austin has 45% more jobs in its urban core.)

That isn't really the surprising part, though; Houston and Dallas, at least, are gigantic, sprawling metropolitan areas with several major employment centers each.  Austin has three major major employment centers (UT, the State Capitol Complex and downtown) in its core.

What was surprising was the change in urban-core employment.  Although the share of Austin's urban-core employment declined from 27.8% to 24.4% between 1998 and 2006, it actually added jobs to its urban core.  A lot of jobs.  Austin's urban-core added 16,400 jobs between 1998 and 2006, a 12.6% increase.  By contrast, Dallas lost 17,683 urban-core jobs (a 6.5% decrease); Houston's urban core lost 19,356 jobs (a 7.8% decrease); and San Antonio's urban core lost 2,655 jobs (a 2.6%) decrease.  Thus, of the four large Texas metropolitan areas, Austin was the only one to grow its urban-core job base.

I frequently use Columbus, Ohio as a benchmark for Austin.  They both have large universities in their urban cores, and both are state capitals.  But Columbus looks a lot more like Dallas or Houston than Austin:  Between 1998 and 2006, it lost 19,950 urban-core jobs, an 11.8% decrease.  (And its urban-core's share of all jobs dropped from 23.2% to 19.3%).  

This is surprising for a couple of reasons.  First, Austin's central city-to-suburb transportation network is primitive, bacically just hypercongested MoPac and I-35.  Houston and Dallas have much more extensive networks, and Dallas has a rail network.  Since transportation costs act like a tariff on central-city employment, I expected to see most growth take place in Austin's 'burbs.  Instead, it was the only one of the big four to add jobs to the central city.

Second, I'm surprised to see Austin add so many jobs to its urban core given its relative lack of density.  Both Houston and Dallas are denser than Austin using the weighted density metric.  While they both have several major job centers scattered throughout the metropolitan area, I did not expect the least dense city add the most central-city jobs.  

Simpson's paradox

Counterintuitive fact o' the day (and one I'm a little embarrassed I just learned).

Let's say you run an experiment on a sample population.  You do this by dividing the population into two subgroups and running the experiment on each separately.  The experiment succeeds for each subgroup.

If the experiment succeeded for each sub-sample, then it necessarily succeeded for the combined sample, right?

Nope.  Sometimes an experiment's apparent success on two samples disappears  when the samples are combined.  This is Simpson's paradox.

Example:  A pharmaceutical company wants to determine whether a new drug performs better than an old drug.  The manufacturer tests New Drug on 300 patients in Chicago and 300 patients in Cleveland.  In Chicago, 240 of the patients get New Drug and the other 60 get Old Drug.  Ninety of the former (37.5%) and 20 of the latter (33.3%) recover.  Thus, New Drug performs better than Old Drug in the Chicago trial.

In Cleveland, 60 of the patients get New Drug and 240 get Old Drug.  Thirty of the former (50%) and 110 of the latter (45.8%) recover.  Hence New Drug performs better than Old Drug in the Cleveland trial, too.

But New Drug's apparent superiority disappears once the samples are combined -- 120 of the 300 that took New Drug recovered (40%) while 130 of the 300 that took Old Drug recovered (43.3%).  Thus Old Drug did better than New Drug in the aggregate sample even though New Drug did better than Old Drug in each of the two sub-samples.*

Weird.

(*Example lifted from Simon & Blume, Mathematics for Economists)

Potential demand for density

I noted recently that the 30 largest U.S. urbanized areas (excluding NYC) display no association between density and the number of households with children (as a percentage of all households).  I have put the numbers below the fold for the curious.

Interestingly, Tampa and Pittsburgh have the lowest percentages of households with children (I thought San Francisco would be at the bottom; it ranks just above of Tampa and Pittsburgh), while LA had the third-highest percentage, ahead of Dallas, San  Antonio and Atlanta.

The chart illustrates my point about density's irrelevance perhaps better than my scatterplot.  For example, the urban densities of Philadelphia, St. Louis, D.C., Detroit, Las Vegas and Cincinatti range from 3,274 ppsm to 8,457 ppsm, but their percentages of HWCs vary by just 4/10ths of one percent (between 35.3% and 35.7%).  (Remember, "urbanized area" includes the 'burbs contiguous to the urban core.)

The other thing that struck me was that households without children are a large majority in almost every large city.  They exceed 60% in all but five of the thirty.  Since I think such households tend to be more tolerant of density than households with children, there may be more market demand for infill density than most people think.  Neighborhood-activist types often complain that we don't need all those apartments and condos because families with children don't want to live in them.  Even if they're right about families with children, those households are a relatively small segment of the market.  

By the way, I am not suggesting that singles or couples would rather live in a 100-unit condo than a single-family home.  I imagine that, all else being equal, most singles or couples would rather have a single-family home.  My wife and I owned our own house for years before we had children.  And I certainly am not suggesting that singles or couples ought to live in multi-family units.  Not at all.  People should get the kind of housing they want.

But preferences depend on price. I prefer a 2009 Infiniti M45 to a twice-wrecked 2002 I35, but I drive the I35.  As home prices rise, and all else being equal, small households are more willing (on average) to switch to denser housing than larger households with children.  Their aggregate demand for SF housing is simply more elastic, more sensitive to price.  Rising property values really do generate more demand for dense housing, regardless of what families with children want.

Weighted density and households with children

There is a stereotype that dense places are filled with singles and childless couples while low-density, suburban cities are filled with families with children.  I'm sure this stereotype is true if one compares central cities to suburbs.  It's true for Austin, for example.  Children make up less than 15% of the population of San Francisco proper.*

But I was curious whether this stereotype holds when we compare apples to apples -- i.e., urbanized areas to urbanized areas.  Are denser urbanized areas less likely to have households with children?

I thought the answer would be "Yes," but it is "No."

The chart below plots the weighted densities of the 30 largest urbanized areas (excluding the outlier New York City) against the percentage of households with children.   As you can tell at a glance, there is essentially no association between the two:

The line is pretty darned flat.  A 1,000 ppsm increase in weighted density is associated with just a one-tenth of one percent decrease in the percentage of households with children.   (It is not a statistically significant association.)

This is counter-intuitive.  It's also strange given the fairly strong association between weighted density and renting:

 

In this case, a 1,000 ppsm increase in weighted density is associated with a 1.2% increase in the percentage of households that rent.  Weighted density accounts for about 30% of the variation in form of household tenure.  It is a statistically significant association.

This is strange because families with children, who comprise the majority of households with children, mostly own their homes.  Perhaps very dense pockets soak up households without children and leave more single-family homes for households with children.  In other words, density might change the distribution of households within the urbanized area but not affect the overall composition of households.  Dunno. 

This is a pretty crude analysis so don't take it too seriously.  But be skeptical the next time someone claims that densification runs off the children.  It might just move them around instead.

*Dear friends without children:  I am not exalting children or parenthood or denigrating those of you who are single (or those who rent).  Promise.  I'm simply curious about the effect of density on the urban environment, and the presence of children is a nice, easy variable to measure.  

Explanation?

Addendum to my post on Austin households with children . . . 

Ryan Robinson, Austin's city demographer, produces lots of interesting charts and tables.  He has created a neat map depicting the concentration of married-with-children households by 2000 census block, which I have cropped to focus on the urban core:

Married families with children are just a small, small percentage of central Austin households. 

So why do most families with children choose the suburbs over central Austin?

Here are some potential explanations:

1. Crime.
2. Schools.
3. Home prices.
4. Home size.
5. Yard size.
6. Because families with children want to live near lots of other families with children, which means the suburbs.  

I don't buy 1 or 2.  I live in central Austin and I don't worry about crime.  Anyway, many of the neighborhoods with higher crime rates have lots of children. 

Central Austin does have some bad schools, but it also has some good ones (I'm willing to send my kids to either Zilker or Barton Hills elementary schools), and Austin High School is as good as any public school in the suburbs.  Maybe I'm just underestimating the draw of Laura Bush Elementary, though.

I don't believe 5, either.  Home lots in the suburbs, or at least in some subdivisions, tend to be quite small.  It's true you can't get a 2- or 3-acre lot in central Austin, but that's not what most suburban families are buying.

I think 6 is a possibility.  Families with children like being around other families with children -- they like their kids to have other kids to play with, family-oriented businesses tend to cluster around subdivisions with lots of families with children, and parents with children may feel they have more in common with other parents with children.  6 wouldn't explain why families moved to the suburbs in the first place, but it would explain why married couples tend to move to the suburbs after they have children.

I think a combination of 3 and 4 is also a possibility.  I should probably phrase it as "home price per square foot."  One can get a bigger house for the money in the suburbs.  The tradeoff is being farther away from downtown, Zilker Park, UT, South Congress -- the amenities that make central Austin so desirable.  Families with children tend to put a higher value on living space than do singles or couples without kids, and so tend to choose bigger houses over living close to downtown.

Can anyone think of other explanations?

(Please note that I'm talking about trends.  A particular family could have different preferences.  For example, we live in a central Austin infill subdivision with few other families with children; we have next to no yard; and, while we live in a decent-size house, we live in a smaller house than we'd have if we lived in the suburbs.  We haven't moved because we like being close to downtown and central Austin's parks.)

Central Austin maps: households with children

While working on a piece for Newgeography, I generated a couple of Census maps depicting the percentage of various central Austin block groups populated by households with children.  I was particularly curious about the change in the composition of central Austin households between 1990 and 2000.  I've put the maps below the jump.

As expected, the maps show that the percentage of households with children generally declined between 1990 and 2000.  I'm not trying to make any other point than that.  I just like this kind of stuff.

Suburb-city differences in gasoline consumption.

Last in this series . . . 

Kahn and Glaeser have also estimated the difference in carbon emissions between cities and suburbs for 48 MSAs.  I've again converted that to gallons of gasoline.  (See the last post for their methodology and caveats.)

Nashville, surprisingly, tops the list:

Note that suburbanites are not always much worse off than central city residents when gas prices start rising.  A $1 increase in the price of a gallon of gas will cost Kahn/Glaeser's hypothetical Denver suburban household an extra $123 per year in gas relative to their cousins living in an apartment in town. $10 bucks  a month. Suburban Austinites must pay an extra $210 per year because of the 210 extra gallons they consume. 

These are pretty crude estimates.  Others have attempted more finely-grained estimates down to the census block level.  Both methods rely on a snapshot of the data; as gas prices rise, drivers adjust their driving by switching vehicles, chaining errands, or simply going out less.  These adjustments will narrow those differences some, but the fact remains that a $2 increase in gasoline makes our hypothetical Austin suburbanite a few hundred dollars poorer relative to the those living close to downtown.

How gasoline use varies among metropolitan areas

Back in March, I wrote about economists Matthew Kahn and Ed Glaeser's work comparing carbon emissions among metropolitan areas.

Among other things, they estimated how carbon emissions from driving vary across metropolitan areas.  The variation in gasoline use is just as interesting, though.  Kahn and Glaeser did not explicitly calculate this, but I did the simple arithmetic to convert their estimates of carbon emissions to estimates of gasoline use.  

In my last post, I was working from their relatively short, "popular" article, which provided data for just ten MSAs.  I have now put my hands on their full paper[1] (gated, unfortunately), which provides estimates for 66 MSAs.  I've again converted their estimates of carbon emissions to estimates of gasoline use.   

What's neat about Kahn and Glaeser's approach is that they've tried to make an apples-to-apples comparison.  Simply calculating gasoline use per household is misleading because some metropolitan areas are wealthier than others, and wealthier people tend to use more gasoline, all else being equal.  Also, households tend to use more gasoline as they increase in size; thus, a metropolitan area with lots of large households will use more gasoline than a metropolitan area with lots of one-person households.  Kahn and Glaeser have tried to fix this problem by estimating how household income and size affect gasoline consumption.  They then estimated gasoline consumption for a household with 2.62 members earning $62,500/year.

They also estimated the impact on gasoline consumption of MSA density, census tract density, and distance from the Central Business District.   And they found that gasoline use varies across regions; Southerners simply drive more than people out West, for example, even after controlling for things like density.  Using these estimates, they predicted, for each MSA, the "standard" household's gasoline consumption. 

The results are below.  Just for fun, I compared gasoline consumption in Austin to gasoline consumption in other MSAs.  Austin does not fare well under their methodology, mainly because it is not very dense and a large percentage of the population lives relatively far from the CBD. 

(Here's the spreadsheet on Google Docs) 

Note that this allows a rough estimate of the relative amount of pain inflicted by gas price increases.  For example, using their estimates, a $1 increase in the price of gasoline costs the standard household in Houston $60 more per year than the standard household in Portland.  (Remember that these are aggregate MSA estimates; they don't permit comparisons between the residents of Houston's suburbs and the residents of central Portland.  They also have not explicitly factored in the effect of transit on gasoline consumption, although that will be captured to some extent by their adjustment for density.)      

[1] Kahn & Glaeser, The Greenness of Cities: Carbon Dioxide Emissions and Urban Development August 2008 NBER Working Paper #14238 www.nber.org.