Austin Contrarian

Legacy costs

Here's a thoughtful piece from Aaron Renn on an unintended consequence of the Clean Water Act.   EPA mandates are forcing Cleveland to spend $5  billion to overhaul its sewer system.   That's a lot of money for any city, but especially for a struggling rust-belt town.   Cleveland will be forced to raise water and sewer rates dramatically, and probably a bunch of other taxes, too.

Cleveland can't go anywhere, but its residents can.   (This is a city where the police and firefighters openly celebrated an Ohio Supreme Court ruling that allows them to move to the suburbs.)  Renn predicts -- accurately, I think -- that the higher taxes will speed up the depopulation of Cleveland as homeowners have one more reason to move to the suburbs.   In fact, the mandate will kick the city twice:   Cleveland must not only raise taxes, but it will lose money that it could have spent on other improvements that would have attracted suburbanites back to the city.

Cleveland needed to make dramatic improvements in water quality; after all, this is the city whose river famously caught fire in 1969 (which itself provided much of the momentum for the Clean Water Act).  But the Cuyahoga is now clean; residents fish from it, in fact.  Spending another $5 billion to get that last 10% improvement is a bad use of money when Cleveland has more pressing needs.  And it is counter-productive to drive residents to the suburbs to leave rotting infrastructure sitting unused in the central city.

Renn suggests that the federal government assume the cost of replacing ancient sewer systems.  That might be the only solution.  The federal government has no incentive to weigh costs and benefits accurately when it can simply issue a mandate.  And the moral hazard risk is smaller than one might think:  the city's main "crime" is being old enough to need a new sewer system.

Guarding against strategic behavior by a city is tricky anyway since, again, its residents can simply move when things get bad.  Rather than stick central cities with crippling legacy costs, it makes more sense for the federal government to issue reasonable regulations and pick up the tab for unforeseen costs.  

Back and forth

It never surprises me to hear suburban commuters bash congestion tolls.  But I am surprised when a sophisticated transit blogger bashes them.  Yonah Freemark, who writes the very good the transport politic, is the guilty party.  He and Ryan Avent have been going back and forth and back again.  

Yonah's objection is equity:

A huge percentage of the U.S. population pays far too much for transportation; to put it simply, most working adults have no choice other than to own a vehicle and often to drive it dozens of miles every day. Making driving more expensive is a great way to devastate the already impoverished.

It’s true, tolling highways would save “money, time, lives, and emissions.” But it would also sacrifice the mobility of a large segment of America, because the reduced congestion would be a result of the poor and the middle class choosing not to drive because of expense, not because of choices made by the wealthy.

He argues that our public transit systems are too underdeveloped in most places to cure this inequity.

Ryan responds with several good points, but I want to elaborate on why the regressivity argument leaves me cold.

First, congestion tolls are less regressive than toll opponents claims.   The low-income do pay tolls, which means they value the time savings more than the price of the toll.   Plenty of low-income drivers take the toll lanes on SR 91 in California, for example.  The reason many do is that they have little flexibility in their schedules.  They have to be at work or at the daycare center at a specific time.  To compensate for congestion, they must leave much earlier to guarantee a timely arrival.  They thus suffer two types of costs:  scheduling delays and travel delays.  (The value of scheduling delays is very hard to measure, which means that studies like the TTI report almost surely understate the cost of congestion.)  Affluent professionals often have more flexibility.

Second, tolls encourage a number of shifts.  Yes, shifts to transit, which seems to be Yonah's main concern, at least when the transit system is underdeveloped.  But they encourage other shifts, too.  Shifts to other routes and shifts to other times.   Commuters are the least likely to be nudged to other routes or times.  The most sensitive are those who use congested roads for local trips.  Take the soccer mom who hops in the SUV and enters a congested highway to get to the grocery store a mile down the road.  She imposes enormous costs on others.  Tolls make her internalize those costs and nudge her to use the local streets. 

Perhaps this is regressive.  But it doesn't evoke much sympathy from me.  A congestion toll is a charge for getting in everyone else's way.   Behind every claim of regressivity is the assumption that drivers are entitled to get in everyone else's way even when it is not worth all that much to them. 

And that leads to my last point.  The regressivity argument wouldn't move me even if it were true. This is one of those cases in which our desire for efficiency should trump our concern with regressivity.

Here's an apt analogy.  An amusement park owner decides to throw open the gate to all comers on a first-come, first-serve.  Naturally, a long line forms.  But this isn't a typical line where newcomers go to the back of the line.  No, in this queue, newcomers elbow their way to the front of the line and force everyone behind them to wait a little longer.  

Naturally, chaos ensues.  No one leaves for the park knowing how long it will take to get in.   There is "queue rage" and general aggravation.  The park owner loses business.  And many low-income parents find themselves worse off because they have a smaller window of free time and dislike the chaos and aggravation as much as anyone else.  (I've always thought it patronizing to assume that low-income drivers put such a low value on their time and aggravation.)

Now, in the real world, the queue would never work this way.  Those at the rear of the line would use informal sanctions (fist fights) to deter queue jumpers.  And, in fact, there would be only a short  line to get into the park in the first place because the owner would charge for admission.

But this is exactly the crazy system we use to ration highway access.  For whatever reason, our cultural norms have evolved to tolerate a free-for-all.  In almost every other situation we ration scarce goods using price.  Sure, that's regressive in the sense that the poor have less money to spend on things.  But we tolerate some regressivity elsewhere because we recognize that (1) the gains in efficiency outweigh the equity concerns; and (2) there are better ways to ensure an egalitarian distribution of wealth than creating artificial shortages, chaos and mayhem.

Regressivity is not the be all and end all.

Cross-posted at Urban Returns.

TTI hyperbole

There is no question that congestion is a serious problem in this country -- and a crippling problem in some cities.  Nor is there any question that congestion is much worse than it was ten years ago, even if high gas prices and the recession have caused it to level off in some places.

But the Texas Transportation Institute is guilty of a bit of hyperbole when it announces that "[t]he overall cost [of congestion](based on wasted fuel and lost productivity) reached $87.2 billion in 2007 – more than $750 for every U.S. traveler."

TTI uses free-flow traffic as its baseline for measuring congestion.  In particular, it defines "Delay per Peak Traveler" to be "[t]he extra time spent traveling at congested speeds rather than free-flow speeds divided by the number of persons making a trip during the peak period." (Summary report p.1)

Honestly, free-flow speed is not the right baseline.  There is no realistic, hypothetical state of the world in which we would experience perfect, free-flow traffic everywhere.   It would not be feasible to build enough roads (or charge enough for them), particularly since free-flow speeds would entice more drivers onto the road.   So to imply that there is $87 billion of waste to be saved -- and I think TTI does imply this -- is simply wrong.  The TTI report makes the news every year thanks to this spectacular estimate, but this one probably belongs on the tabloid pages.

Anthony Downs makes this point in Still Stuck in Traffic, pp. 23-24 (available on-line at Google Books).   He makes several other reasonable criticisms of TTI's methodology.   Hedoes recognize that  TTI's methodology and findings are useful, and he does not dispute (nor do I) that congestion is a serious problem that we can't simply build our way out of.

(Edited and cross-posted from  Urban Returns.)

Density and congestion, etc.

Whenever I see new data on cities, I'm always tempted to match them to the cities' weighted densities, if for no other reason than no one else does it.  And so with the Texas Transportation Institute's latest report on city congestion.  TTI found a wide range in hours lost due to congestion per year -- e.g., in 2007, Lost Angeles drivers lost an average of 70 hours per year to congestion;  Cleveland drivers, just 12.  (The relevant TTI table is here  (pdf).)  Does weighted density partly explain this variation?

The answer is "No," based on my admittedly simplistic analysis.  

Below the jump I have three charts plotting, for 33 cities, weighted density, standard density and total population against hours lost per traveler to congestion.   (The 33 cities include the 31 largest urbanized areas -- excluding New York City, which is always an outlier -- and Austin and Honolulu.) 

As the scatter plot shows, weighted density explains virtually none of the variation in congestion (adjusted R² = .06).   Standard density explains a bit more  (adjusted R² = .19).  And total population, a bit more than standard density  (adjusted R² = .28). 

Sorting

I've written recently about Glaeser and Resseger's research showing that workers in skilled cities tend to become more productive as their cities grow while workers in unskilled cities do not.   I've also written about Abel et al.'s paper showing that while workers in all cities tend to become more productive as their cities grow denser, workers in skilled cities are especially likely to benefit.  The latter  receive, on average, three times the productivity gains of workers in the least skilled cities.  Growth and densification are good if yours is a highly skilled city.  

But the Glaeser and Abel papers also raise another possibility:  perhaps skilled cities are better off keeping out the unskilled than growing without bound.   

This is arguably an implication of their work. (And one I don't like, by the way.)   Both Glaeser and Abel define highly skilled cities to be those with high percentages of college-educated workers.  The higher the ratio of B.A.s to high school grads, the more skilled the city under their definition -- and the more the workers benefit as the city grows.

One way to keep a high ratio of skilled to unskilled is to price out the unskilled.  The most effective way to price unskilled workers out of a city is to keep the cost of housing high.  And, indeed, the highly-skilled cities on the coasts are adept at (and notorious for) using rigid land-use regulations to inflate home prices.  (Or were until recently; more on that later.)   The incumbent homeowners in these cities of course benefit from a tight housing supply since it raises the value of their properties.  But perhaps their skilled workers benefit too.

I speculated about this  last October without the benefit of Glaeser ir Abel's research:

Perhaps the elites in the superstar cities sense it is better to surround themselves with a uniformly high-quality workforce.  They want to spend their time with other elites; letting in lots of less-skilled workers would introduce so much static, just as if Harvard were to throw open its doors to anyone with a half-decent high school transcript.  In other words, an influx of less-skilled workers might dilute the experience for the high-skilled.

I got my undergraduate degree from Ole Miss and my law degree from Yale.   I studied harder at Ole Miss, took harder classes and spent a lot more time with my professors.  I thought law school was mostly boring and had a suburban home and the premium cable channels by my third year.  But I probably got a better education at Yale than Ole Miss merely by hanging around a bunch of people who were smarter than me.  There were economists, physicians, mathematicians, political scientists, a Broadway actor, an Olympic miler  and, of course, a bunch of smart new college graduates  from all over the country (but mostly from the Ivy League, Standford and Berkeley.).  It was a small class of 175.  It was impossible not to keep up with new ideas or trends because someone you bumped into would know about them.  I wasn't paying a gazillion dollars for the law school classes, I was paying for the spillovers.  It was a fair price.

The housing markets in  LA, San Francisco and New York function as giant sorting machines.  By setting home prices so high, they weed out all but the most skilled -- except for the class of relatively unskilled who are supported by price controls or subsidies.  They're using the  Ivy League model.

So are they better off?  Yes, clearly, if they can shunt the less skilled elsewhere and  continue to grow and densify.  But it's hard to do both.  High prices, in fact, require that the housing supply be kept tight  in order for prices to stay high.  Otherwise, the new supply of housing would drop home prices and the riff-raff (from their perspective) would come flooding back in.  But perhaps merely increasing the density of skilled workers will yield the productivity gains yielded by  growth and densification.  Their motto could be, "We get smarter, not bigger."

I think this is probably wrong, though.  What matters is being close to other people with the same skill set; that's where the knowledge and productivity spills occur.  A software developer benefits from having a lot of other smart software developers around; a musician benefits from having a lot of other good musicians around.  Adding more software developers or musicians who aren't quite as skilled shouldn't dilute this benefit because we city-dwellers largely control whom we interact with.  Firms, in fact, segregate themselves by quality all the time.  Deepening the labor pool simply can't hurt.  I think cities like San Francisco and New York would be even more productive if they loosened their growth restrictions and allowed in more people.

And even if were true that the San Francisco model can achieve greater productivity without growth, there's always the risk that its  sorting machine might break. To wit, a housing market collapse.  Skilled workers cash out what they can and move elsewhere.  Lower home prices attract the less-skilled who had been priced out of the market.  A political and regulatory climate makes the city less hospitable entrepreneurs, who benefit from cheap space and light regulation.

It will be interesting to see what happens to productivity in these wealthy, slow-growth cities as the recession wears on.  My guess is that they will have to begin growing vigorously again if they want to recapture the productivity they had at the peak of the housing boom.

Skilled cities II

While I'm in this nerdy mood, let me point to this paper by Jaison Abel, Ishita Dey and Todd Gabe:

We estimate a model of urban productivity in which the agglomeration effect of density is enhanced by a metropolitan area’s stock of human capital. Using new measures of output per worker for U.S. metropolitan areas along with two measures of density that account for different aspects of the spatial distribution of population, we find that a doubling of density increases productivity by 10 to 20 percent. Consistent with theories of learning and knowledge spillovers in cities, we demonstrate that the elasticity of average labor productivity with respect to density increases with human capital. Metropolitan areas with a human capital stock that is one standard deviation below the mean level realize around half of the average productivity gain, while doubling density in metropolitan areas with a human capital stock that is one standard deviation above the mean level yields productivity benefits that are about 1.5 times larger than average.

This is a little technical, so let me translate:   Cities tend to become more productive as they grow denser.   On average, a city's workforce becomes 10% more productive when the city doubles in density.   But that average obscures the importance of skills.   Less skilled cities benefit a lot less than skilled cities from densification.   In fact, skilled cities, on average, enjoy three times the productivity gain from denser growth than less skilled cities.   This is yet more evidence of the increasing returns and agglomeration benefits from density.

This is a nice complement to the Glaeser and Resseger paper.  Glaeser and Resseger found that workers in skilled cities become more productive as the city grows, while workers in unskilled cities do not.   Abel et al find that workers in skilled cities become more productive as the city grows denser; workers in unskilled cities, less so.

The authors also test their conclusions using a variant of weighted density. They find even greater productivity gains (20% on average) when a city doubles its weighted density.

The authors use a coarse form of weighted density.  They weight urbanized area density by county subdivisions.  But how you chop up a city matters when calculating weighted density.  In order to calculate weighted density, you first divide the city into a bunch of smaller regions.  You then assign each region's density a weight equal to its share of the populations.  In general, weighted density increases as you chop up the city into smaller regions.

I used census tracts for my weighted densities.  There are many more census tracts than county subdivisions.  I thus got a lot more stratification than they did -- e.g., their top weighted density was 19,000 ppsm, while mine was 33,000.  How you divide a city for calculating weighted density is somewhat arbitrary, but I think using census tracts makes more sense than county subdivisions, which are more or less arbitrary.  I suspect the authors would have found even greater returns to density had they weighted density by census tracts rather than by county subdivisions.  

H/t Richard Florida.

Skilled cities

Ed Glaeser and Matthew Resseger have a new paper out examining how worker productivity varies with city size.  They find that workers in skilled cities become more productive as the cities grow; workers in less skilled cities do not:

There is a strong connection between per worker productivity and metropolitan area population, which is commonly interpreted as evidence for the existence of agglomeration economies.  This correlation is particularly strong in cities with higher levels of skill and virtually non-existent in less skilled metropolitan areas.  This fact is particularly compatible with the view that urban density is important because proximity spreads knowledge, which either makes workers more skilled or entrepreneurs more productive.  Bigger cities certainly attract more skilled workers, and there is some evidence suggesting that human capital accumulates more quickly in urban areas.

No one is quite sure exactly why (skilled) city growth makes workers more productive (Glaeser and Resseger included).  One theory is that workers learn more quickly from one another in larger cities; there is more trade-specific information "in the air."  For example,  software engineers and musicians develop their skills more quickly in a city with lots of software engineers and musicians.

The other theory is that a large city has a deeper pool of entrepreneurs and others with "high human capital" (i.e., smart, creative people).  It generates more innovations, which make the city's population more productive, which attracts more workers, who generate more innovation, etc. (This one better matches Jane Jacobs’ theory.)

These are genuinely different explanations. If the first is accurate, then workers’ pay should rise more steeply with experience in large, skilled cities than in small, skilled cities.  The second is a sort of “creative destruction” theory; it means that workers in large, skilled cities face a higher risk of being displaced by the latest innovation.  I think both are true, which (partly) explains why big cities attract some highly skilled people while repelling others.

City growth

The Census Bureau has released its July 1, 2008 city population estimates.  Note that Texas has three of the largest eight (Houston, San Antonio and Dallas) and six of the largest 21 (add Austin, Fort Worth and El Paso).  Houston now trails Chicago by just 600,000, a gap that Houston could close within 20 years if the last decade's growth rates hold.  This is a surprising statistic as long as one ignores metropolitan populations, which are what really count when calculating a city's heft.  Chicago's metro population is still much larger than Dallas and Houston's, which are probably now the fourth and fifith largest metro areas.  And, in general, Texas cities have large boundaries and aggressively annex surrounding areas, which partly accounts for their rapid growth.

What's going on with Fort Worth? It had the fastest growth of the top 25, both between 2007 and 2008 (3.6%) and between 2000 and 2008 (29%).  No other city in the top 25 was close; Charlotte and Phoenix were the closest at 21% and 18%, respectively.  Fort Worth has grown twice as fast as Austin since 2000.  I haven't heard much about Fort Worth's explosive growth.  Strange.

One surprise on the other end:  Philadelphia contracted at a faster rate than Detroit between 2000 and 2008.

The most noteworthy fact here may be that, as the WSJ points out, central cities did very well between July 1, 2007 and July 1, 2008.  

The central-city population in U.S. metropolitan areas with more than one million people (excluding New Orleans) grew at an annual rate of 0.97% between July 2007 and July 2008, compared with a growth rate of 0.90% in 2006-2007, and growth rates around 0.5% in the years between 2002 and 2005.  By contrast, U.S. suburbs in metro areas greater than 1 million people grew at a 1.11% annual rate in 2007-2008, down from growth rates between 1.29% and 1.48% between 2002 and 2005.  Central cities are closing the gap.

The WSJ attributes the shift in growth rates to the recession.  We have a short memory.  2007 was the year of the historic spike in gas prices.  Central cities -- especially older, monocentric cities like Chicago -- began to look a lot more attractive to commuters.  I imagine this played a much bigger role than the nascent recession.   

Why we don't need TxDOT's central planning

Tory Gattis agrees with me that Perry's veto of the so-called "smart growth" bill was a good idea.

Tory, however, disagrees with me on one point:  he thinks TxDOT's control over infrastructure in metropolitan areas is basically a good thing.  Tory's point is that our highway system is a network that connects places and therefore needs a "master architect" rather than cities going their own way.   Without some form of central control, we'd get NIMBYism run amok and be stuck with the equivalent of planned communities' cul-de-sacs rather than the connectivity of street grids.

I don't think this is right, as long as infrastructure decisions are made at the metropolitan level.   Left to themselves, individual cities might indeed seek to shift infrastructure to neighboring cities, which would set off a battle of NIMBYs. But metropolitan areas want to be connected to other metropolitan areas.  Their citizens want to be able to get places and good connections are essential to a city's economy.   As long as metropolitan areas have control over their roads, they'll have the power to curb NIMBYism.

The better analogy is downtown Houston's tunnels.  Developers have linked their office buildings to the tunnel network without central planning.  They could have shorted the network by scrimping on their own infrastructure -- by building very narrow tunnels, for example -- but they haven't; later additions have matched the quality of the earlier ones.  (Or "had" as of the mid-1990s.  I confess I haven't been in the tunnels in 14 or 15 years.)

Local control works just fine as long as we use the right definition of "local."  

Nothing to see here

The Census Bureau has released a new report (pdf) comparing the growth of Metropolitan Statistical Area central and outlying counties between 2000 and 2007.

Wendell Cox says the report shows "that the nation continues to suburbanize, despite the consistent media 'spin' that people are leaving the suburbs to move to core cities."

[T]he conclusion of the new report is clear. The nation’s most remote suburbs – its exurbs – are growing much faster than the central counties. Whether this trend will now reverse, of course, is up to debate. Perhaps demographic changes and higher energy costs will slow expansion on the outer fringes. More likely, the current recession may well lead to less exurban growth, but history suggests this may prove only a short-lived trend.

My own take is that this report offers little meaningful information other than growth and migration rates for the MSAs as a whole.  Breaking out the numbers for central counties and outlying counties tells us little because the Bureau defines "central counties" expansively as those containing all or a substantial portion of the MSA's urbanized area.   Since a city's urbanized area can and often does stretch across several counties, the Bureau's definition sweeps up counties that we typically consider suburban.  For example, Travis and Williamson are "central counties" in the Austin-Round Rock MSA, even though Williamson is the quintessential suburban county.   (Hays is considered an outlying county, but will almost certainly be a central county in the next census due to the rapid spread of Austin's urbanized area.)

Because of the broad definition of "central" counties, almost all MSA population is "concentrated" in these counties.  In MSAs with more than 5 million, for example, 97.4% of the population lived in central counties (2007 estimates).  For all MSAs, the number is 91.8%.

Naturally, because central counties began with a large baseline population, even large absolute increases in population yielded smaller percentage increases than small absolute increases in the less populous exurbs.   For example, in the Midwestern MSAs, the outlying counties grew at nearly twice the rate of the central counties.  But the central counties added 5 times as many people.   The New York-Northern New Jersey-Long Island MSA is an even more extreme example.  Its central counties grew by 2.6% between 2000 and 2007 while its outlying counties grew at an explosive 26.6% rate.   But the central counties added 480,000 people to just 12,000 for the outlying counties, 40 times as many.

For the United States as a whole, MSA central counties added nearly 17 million people compared to 2.4 million for outlying counites.  Central counties in the northeastern region (which includes New York) added nearly 1 million while the outlying counties added fewer than 24,000.  The South Region's outyling regions added the most by far -- nearly 1.8 million -- but even here the outlying growth was dwarfed by the 7.7 million added by the central counties.   

If the Bureau's goal was to tell us something important about the relative growth of exurbs and central cities, it failed.   There's just not much to the data because of the overly-expansive definition of central counties.   As Wendell points out, this report might very well understate suburban growth (in fact, this is almost certainly true), but this report doesn't shed much light on the question.  Wendell himself recognized this limitation on the data, but unreasonably, I think, attempted to draw an unwarranted conclusions from the report anyway.