Urban Returns

Market Urbanism on congestion pricing

Market Urbanism has posted a fairly technical explanation why the congestion price that maximizes throughput also maximizes total revenue. I'm not sure his explanation is correct because he ignores drivers' sensitivity to price.  If they are relatively insensitive, then the revenue-maximizing toll will be higher than the through-put maximizing toll. We have plenty of real-life examples. TxDOT charges tolls for SH45 even when traffic is light. Total revenue from these tolls exceeds the revenue that the optimal toll ($0) would generate.

That's a debate for a different day.

What I want to point out here is that Market Urbanism's argument does not affect my transit-subsidy hypothetical.  (To be fair, I'm not sure that he's offering a rebuttal to my hypothetical.)

In my hypothetical, I assumed that both bridge users and transit riders are charged the optimal toll.  I'm happy to assume these tolls also maximize revenue.

My hypothetical was about transit subsidies.  The optimal transit fare might maximize revenue but still not cover the cost of the transit.  But that's OK, libertarians, as long as the bridge users generate excess revenue -- i.e., more than the cost of the bridge.  As long as everyone is charged the optimal fare, and the combined revenue covers the combined costs, the "network" -- bridge + transit -- is efficient, despite the transfer from drivers to riders.

That the optimal toll on one branch of the network maximizes revenue from that branch does not prove that the revenue will cover the cost of that branch.  Nor does it show that the optimal toll should cover the cost of that branch when the system as a whole is revenue neutral.

Connect the right dots

Dallas is the fourth most populous metropolitan area in the United States.  Houston will pass Philly for fifth any day now.  So why oh why is the Obama administration proposing a high-speed rail network that does not link Houston and Dallas?  Or at least Houston and Austin?

It is a strange vision indeed that sees a Dallas-Little Rock or Houston-Swamp Country-New Orleans line as a better investment of a few billion dollars than a line connecting two metropolitan areas with a combined population of 12 million.

Someone in DC evidently has been reading Richard Florida, so I guess he deserves the blame.

Congestion pricing: practical problems

I've been pushing congestion pricing on this blog for a couple of years now.   I've argued ad nauseum that variable congestion pricing would get traffic flowing at the least cost, and would enhance general welfare better than the continual and counterproductive expansion of highways. 

To be honest, though, I need to disclose the practical problems with congestion pricing.

Economists first began lecturing traffic engineers about congestion pricing 40 or so years ago.   The conversation's gone something like this:

Economist:  "You guys need to stop building roads to alleviate congestion.  If you price the roads right, you can eliminate congestion and enhance overall welfare." 

Traffice engineer:  "I hear what you're saying, but we don't know how to implement congestion pricing."

Economist:  "It's easy.  Just charge a high enough price to get traffic flowing."

Traffic engineer:  "But we don't know how to do that."

Economist:  "What's not to understand?  Just charge a high enough price to get traffic flowing."

Traffic engineer:  "You don't understand.  We don't know how to figure out what that price is and we don't know how to communicate that information to drivers in time for it to do any good and we'd have to price other roads in order for the system to work and we don't know how to price networks.  Plus, everyone hates tolls and I like my job."

Economist:  "I'm sorry.  I wasn't listening.  I'm working on an interesting paper on the Herfindalh-Hirschman index and models of stochastic processes in hyperbolic discounting."

Traffic engineer:  "Whatever."

The traffic engineer goes back to work widening roads.

Here's the information problem:  The optimal congestion toll should be set just high enough to achieve free-flow (45 mph) traffic.  But if the toll is set too high, it will induce too many drivers to shift to other times, routes or modes of transportation.  That's bad, too (at least if you ignore other externalities like pollution.)

Traffic engineers can generally predict the high-demand days, but there's a fair amount of randomness in traffic patterns.  Some days an unusually large number of drivers just happen to drive to work at the same time.

The optimal toll therefore should be variable -- the greater the demand, the higher the toll.  But that's very hard to implement as a practical matter.  How do we get would-be drivers the information they need to make timely decisions?  There's no point in raising prices on drivers once they've entered the road; raising prices can no longer influence their behavior (except perhaps to launch them into a homicidal rampage). 

Price changes might affect the behavior of drivers who are about to enter the highway.  But they are just a fraction of the drivers targeted by congestion pricing.  Congestion prices are also intended to shift drivers' time of travel and mode of transportation.  That requires getting them the price in advance, in real time (via the internet, for example).  But that, in turn,  creates a real risk of herd behavior.  If the posted price is high, most drivers will respond by taking alternate routes or leaving too late.  If the posted price is low, drivers will rush to their cars to take advantage of the low tolls, creating a sudden surge in demand and unnecessary spikes in prices.  There's a sort of Heisenberg uncertainty principle at play.

There are other practical problems.  For example, charging tolls might hurt businesses that have based their investments on the assumption that roads would remain free.  Pricing's impact varies industry by industry, and consumer by consumer.  The Oregon Transportation Commission has commissioned several white papers examining some of the practical problems.

Most experts therefore assume that the best pricing system will be a second-best system, like cordon charges or charges fixed by time of day.  These systems erode some of the advantages of congestion pricing but, in my opinion, are still vastly superior to the unpriced alternative.  London, for example, has had good success with its cordon-pricing system.  (See VTPI's case study here.)

And congestion pricing is still very new.  We've had the technology for electronic toll collection for only a few years; congestion pricing isn't feasible with toll booths.  Let's experiment and get some data.  I'm confident the engineers will eventually develop effective models.  But there will be some glitches at first, and we'll need some patience.  

Avent

Ryan Avent, the best urban economics blogger around, is moving to Portfolio.com.

This is likely bad news for the rest of us who've enjoyed his thoughts on urban economics for the last couple of years.  Ryan promises to continue writing about urban issues, but given Portfolio's finance slant, I fear he will have less time for urban issues.

Bad for me.  Good for Ryan.  Congratulations to him, and the best of luck.  

Dead malls

A blog devoted to them.  Highland Mall is not on the list -- yet.

McBlogger doesn't like congestion pricing

McBlogger is a boisterous critic of tolls.  No surprise, then, that he doesn't buy my arguments for congestion pricing I-35 and MoPac.  He's written a pretty long critique -- and raised an objection I've never addressed -- so I need to respond.

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.

Local option

The Chronicle reports that state senators (mostly Republicans) are throwing obstacles in front of Senator John Carona's "local option" bill.  This bill would allow counties to choose from a menu of fees and taxes to fund transportation projects as they see fit.  Options would include imposing a local gas tax or raising vehicle registration or driver's license renewal fees.  "No taxes or fees" would be on the menu, too -- and any increase would require voter approval.

This is a measure long overdue.  Cities and counties need to regain control of their local infrastructure.  Cities and counties know their needs better than TxDOT.  Cities and counties certainly know their preferences better than TxDOT.  We need to devolve more control to the locals, and "control" requires money.  This bill doesn't go far enough, in fact; counties and cities not only need the right to raise new money, they need to get back some of the money they now send TxDOT. 

State Republicans are raising a ruckus, though:

Sen. Dan Patrick, R-Houston, called it a "disaster" that, with so many exemptions added, puts the whole new tax burden on "my two favorite people, the police officer married to the school teacher."

There are a couple of points worth making here.  The first is that Patrick's "police officer married to the school teacher" probably lives in the 'burbs, and suburbanites suffer especially hard from dilapidated infrastructure.  Perhaps the police officer and school teacher prefer better roads (or a rail option) to slightly higher fees and taxes.  There are always trade offs.  Under the local option, they'd at least get to vote in a local election.  Patrick and company apparently think the policeman and school teacher are better off when the decision is made for them by suddenly paternalistic Republican senators sitting a couple hundred miles away. 

That leads to the second point.  The "local option" bill is not a tax hike.  It gives county voters discretion to tax themselves if they'd like better infrastructure.  Voters in some counties might prefer creaky infrastructure to higher gas taxes or vehicle registration fees.  Others might prefer more roads, or better roads, or more money for transit.  The point is that counties could sort themselves according to their own preferences.  And gain more say over their urban form rather than having it dictated to them by the bureaucratic TxDOT.

Perhaps that's the senators' real objection.  They fear that if urban areas get even a limited choice over their own infrastructure, they might make choices that the Legislature doesn't like.  The Lege doesn't like the "local" in "local option."

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.  

Hypothetical

Congestion pricing is hard. The fact that it floats up and down with demand is confusing. As is the fact that someone paying a congestion toll is not, technically, paying for either road construction or road upkeep. He’s just paying for getting in everyone else’s way.

Where it gets really confusing, though, is that while congestion revenue is not collected to pay for the road, congestion revenue can be used to pay for the road. And when it’s done right, congestion — or, more precisely, the price people pay to avoid it — pays for the whole thing.

I’ve tried to explain this here before without much success. This time I’ll try an example.