Green cities will be less hurt by higher gas prices; Sprawling cities are much more vulnerable to gas price hikes.

In sprawling metros like Atlanta, Dallas, Orlando, Nashville and Oklahoma City, higher gas prices will cost the average household twice as much as households living in compact metros like San Francisco, Boston, Portland and Seattle.

Rising gas prices are a pain, but they hurt most if you live in a sprawling metro where you have to drive long distances to work, shopping, schools and social activities.  Some US metros are far less vulnerable to the negative effects of rising gas prices because they have dense neighborhoods, compact urban development, good transit, and bikeable, walkable streets.  Among the 50 largest metro areas, the best performers enable their residents to drive less than half as much as the most car-dependent metros.  Those who live in metro areas where you have to drive, on average, 50 miles or more per day (places like Oklahoma City, Nashville and Jacksonville) will be hit twice as hard by higher fuel prices than the typical household living in a place like San Francisco, Boston or Portland, where people drive, on average, fewer than 25 miles per day.  When gas prices go up, it’s easy being green:  These compact, less car-dependent metros and their residents, will experience far less economic dislocation than metros where long daily car trips are built-in to urban form.

Gasoline prices have shot up in recent days, thanks to the Russian invasion of Ukraine.   A year ago, average gas prices nationally were under $3 gallon.  In February, they averaged around $3.30 per gallon.  After the Russian invasion began, oil prices and gas prices jumped.  On March 14, the national average was $4.30, and rising rapidly, with much higher prices in some markets.

There’s the usual barrage of media hand-wringing about the impact of high gas prices, notwithstanding the widespread support for backing Ukraine, even if it means higher oil prices.  Some 71 percent of Americans favored banning Russian oil imports even at the cost of higher gas prices.  As high as they seem, gas prices today are just now approaching the levels recorded in 2008, when gas prices peaked at $5.09 per gallon (in 2022 dollars).

In our largely car-dependent nation, higher gas prices feel painful, but some Americans feel the pain far more deeply than others, and some feel it not at all.  There’s been more than a little bike advocate schadenfreude on Twitter, pointing out that those who travel by bike or on foot aren’t feeling the pain of higher gas prices.

I want to apologize on behalf of the bike/walk/transit people if we seem smug about gas prices. It’s just… this is the moment we have been preparing for our entire lives 😂

— Angie Schmitt🚶‍♀️ (@schmangee) March 11, 2022

But this isn’t just about individual choices and behavior:  whole communities can be more or less vulnerable to gas price shocks, depending on how much land use patterns effectively necessitate driving.

Some metro areas are vastly more car-dependent than others, and as a result, are more vulnerable to gas price hikes.  We can get a good idea of which metros will be most affected by price hikes by looking at data on average travel distances in different cities.  The big data firm Streetlight Data published its estimates of the amount of daily driving per person for large US metros.  We’ve tabulated their publicly released data for the period just before the advent of the Coronavirus pandemic, to get a reasonable baseline for comparing travel patterns.

On average, the residents of the typical large metro area in the US drive about 30 miles per person per day (that’s a bit higher estimate than the one provided by the US Department of Transportation).  But there are extremely wide variations in average driving among metro areas.  In general, older, denser metros with more extensive transit systems seem to have dramatically less driving per person than newer, sprawling Sunbelt metros with weak transit.

The metros least likely to feel the pain of higher gas prices include Buffalo, San Francisco, Boston, New York, Portland and Seattle, where metro residents drive about 25 percent less than average.

On the other hand, the metros most vulnerable to higher gas prices are those where, due to job and population sprawl, people tend to drive much further.  These highly vulnerable metros include Oklahoma City, Orlando, Nashville, Dallas, Charlotte and Atlanta, where the typical resident drives 50 or more miles per day, according to the Streetlight estimates, nearly double the typical metro area.

Average Miles Driven Per Person Per Day Prior to Covid-21 Pandemic (Streetlight Data)

As we’ve pointed out before, residents of more compact metro areas, with better transit and closer destinations earn the equivalent of a huge green dividend, even when gas is cheap, because they spend far less on cars and gasoline.  Meanwhile, their counterparts in decentralized metros pay a “sprawl tax.”  When oil prices rise, the pain falls disproportionately on those who live in metros where they have to drive a lot.

The differences are significant.  The households living in metros where people drive 50 miles per person per day are conservatively buying twice as much fuel as those living in metros where people drive only 25 miles per day.  So while a family in a compact metro area would be buying say 100 gallons or so of fuel a month, its counterpart in a sprawling metro would be buying 200 gallons.  So a $1 increase in the price of gas would hit about $1,200 harder over the course of a year in a sprawling metro than in a compact one.

In the face of rising fuel prices—whether from a war, or from the the long overdue need to reflect the true social and environmental costs associated with fossil fuels—communities where people don’t have to drive as much, or drive as far, have a real economic advantage over more car-dependent places.  That’s a consideration that ought to play a larger role in local, state and national policies going forward.

The Oregon and Washington transportation departments are using a biased, unscientific survey to market their $5 billion I-5 freeway widening project.

The survey over-represents daily bridge users by a factor of 10 compared to the general population.

The IBR survey undercounts lower and middle income households and people of color and overstates the opinions of White non-hispanics, higher income households, and Clark County residents

As we’ve noted, highway builders are increasingly engaging in woke-washing, claiming—after decades of experience in which freeway projects have devastated communities of color and destroyed city neighborhoods across the country—that wider freeways will somehow be a good thing for low income people and people of color.

The latest example of this comes from the sales campaign to promote the $5 billion I-5 freeway widening between Portland and Vancouver Washington, misleadingly branded as the “Interstate Bridge Replacement” (IBR) project.  The reality is pretty simple:  the primary beneficiaries of a wider roadway would be higher income, overwhelmingly white commuters who drive daily from suburbs in Washington State to jobs in Oregon.  As we documented last month, the peak hour drive-alone car commuters who cross the I-5 and I-205 bridges from Washington State to jobs in Oregon are whiter and wealthier than the region’s population, with median incomes of $106,000, and 86 percent non-Hispanic whites.

But the IBR project has carefully constructed an alternate reality in which this car-centric freeway widening project is really something that benefits low income people and people of color.  The project’s promotional materials—which actually don’t show the project, or acknowledge its price tag, or the fact that it will charge tolls to bridge users—prominently features stock images of people of color.

Here’s what we mean by “woke-washing.”  The project’s home page featured this image . . .

. . . which is a stock photograph used by hundreds of websites, mostly those focusing on women’s health.  (Just an aside: A true health-oriented and equity focused project wouldn’t build a 12-lane wide, 5 mile long freeway guaranteed to increase air pollution and with a long history of destroying neighborhoods.)

In addition to its woke imagery, the IBR project supplements this messaging with a pseudo-scientific web-based survey which purports to show that the project is really for lower income people of color.

Selling a $5 billion freeway widening with a woke-washed fable

The IBR staff have developed a fictional “just so” story of how the freeway widening project is needed to help low income households and people of color, who’ve moved to Clark County for cheaper housing, but have to travel to jobs and other opportunities in Oregon.  The survey is grounded, not in actual scientific data, but the project’s own unscientific and biased web-based survey.

Here is IBR staff person Jake Warr, making this false claim to the January 20, 2022 Executive Steering Committee meeting:

One thing that really came out through this survey that I want to highlight is when we . . . asked how often people drive across the bridge, we found a higher percentage of folks who identified with a race or ethnicity besides white or or in addition to white/Caucasian, the non-white respondents really reported more frequently traveling across the bridge.

So that 53 percent‑that’s listed there, 53 percent‑of our of our BIPOC survey respondents reported traveling across the bridge either daily or a few times a week. That’s compared to closer to 40 percent for the white respondents.

So just something that that really kind of drives home a point that we’ve suspected. It provides further data that you, we’ve seen a trend in our region of folks of color being pushed to further areas of the region, being pushed north of the river, or seeking out more affordable housing north of the Columbia River, but still relying on services jobs etc, in Multnomah County.

And so, there’s that piece that I think this speaks to. We also suspect that related to Covid, as people were answering this question in the context this pandemic, there might be some explanation there, as we know that BIPOC individuals tend to be, disproportionately rely needing to work still in a location and not be able to work from home.

That might have contributed to this but just something that we really found was was a poignant data piece to point out.

The trouble is, this claim is easily disproved by referring to valid survey data from the Census Bureau which shows that commuters across the I-5 and I-205 bridges are actually disproportionately white, and higher income.  Low income workers, and those of color, are dramatically under-represented among bridge commuters.

A biased, unscientific survey from the IBR

The trouble with web-based surveys is they suffer from self-selection bias.  Only highly motivated people take such surveys, and the opinions, experience and demographics of these people differ substantially, and systematically, from the general population.  As a result, it’s simply invalid to make statistical claims (such as people of color are more likely to use the bridge frequently).  That’s especially true when there’s valid scientific data from the American Community Survey, which shows exactly the opposite: peak hour users (for whom the bridge is being expanded) are 86 percent non-Hispanic white and have average incomes of $106,000).

To see just how biased the unscientific IBR web-survey is, we can compare it to other surveys conducted with more valid methodologies.  The correct way to do surveys is with an random selection methodology; the IBR actually commissioned such a survey in 2020.  In its random survey of more than 900 Portland area voters, 13 percent of respondents reported never crossing the I-5 bridge over the Columbia, compared to just 1 percent in the unscientific online survey.  The random survey of voters showed only 5 percent of respondents crossed the I-5 bridge every day, compared to 19 percent in the unscientific online survey.  As a result, the unscientific online survey implies the ratio of daily users to non users is 19 to 1 (there are 19 times as many daily users as never users), while the random survey shows that there are two and a half times as many non-users as daily users of the I-5 bridge.  That means that the unscientific survey overweights the role—and opinions—of daily users relative to non users by more than an order of magnitude relative their share of the overall population of the Portland metropolitan area.

Demographic bias in the IBR unscientific web survey

A quick look at the American Community Survey, which is conducted annually by the Census Bureau, shows that the demographics of the IBR’s unscientific web-based survey are dramatically different from the metro area.

One essential for surveys is that participants should be randomly selected.  If they’re not randomly selected, there’s little guarantee that the results will be representative of the larger population. One of the sure tells of a non-random survey is that the characteristics of survey participants don’t match up well with the characteristics of the overall population of the area being surveyed.  That’s the case here.  The IBR survey systematically over-represents some groups, and systematically underrepresents others, which should cast doubt on the validity of its results.  The survey systematically over-represents white, non-Hispanic people, higher income households, and residents of Washington State, and systematically under-represents people of color, low and moderate income households, and Oregon residents.  Here are the details.

Income:  Higher incomes over-represented.  The respondents to the unscientific web-survey are much higher income than the overall population.  Some 44 percent of survey respondents had household incomes over $100,000; only 38 percent of the region’s households had incomes that high.

Race and Ethnicity:  People of color under-represented.   The respondents to the unscientific web-based survey are much more likely to be non-Hispanic white than the overall population; some 85 percent of survey respondents were non-Hispanic white compared to 72 percent of the region’s population.  People of color were 28 percent of the region’s population, but only 15 percent of survey respondents.  People of color were undercounted by almost half in this unscientific survey.

Residence:  Clark County over-represented.  The respondents to the unscientific web-based survey are disproportionately residents of Clark County.  Clark County accounts for less than 20 percent (488,000 of the region’s 2.5 million residents) but accounts for 43 percent of those taking the survey.  Clark County resident views are given more than double the weight of view of other of the region’s residents in this unscientific survey.

Age:  Young people significantly under-represented. There’s also a strong generational bias:  only 5 percent of survey respondents are under 25, compared to nearly 30 percent of the population.  And these people will be the ones who have to live with the environmental consequences of the project.

No doubt the highway agencies will point with pride to the large number of completed surveys–more than 9,000 to date.  But large numbers are irrelevant if you don’t have a random sample.  For a metropolitan area the size of Portland, you need only about 400 to 800 survey participants to come up with statistically valid results,  if you have a random sample.  If you don’t have a random sample, then even very large numbers (and IBR surveyed only about one-third of one percent of the region’s residents) just aren’t meaningful.  The underlying problem that invalidates the survey is called “Self-Selection Bias.” Because this isn’t a true random survey, and because respondents choose whether to participate, there’s no guarantee that the survey data reflect the views (and experiences) of the larger population.  Because those who are predisposed to care about this issue are likely to differ systematically from the rest of the population, the survey produces results that are biased.

Not asking the most important question:  Who wants to pay a toll?

There’s a lot more to dislike about the survey beyond its poor quality sampling strategy and biased sample.  The questions posed in the survey don’t get at the real issues raised by the freeway widening project.  The project’s financial plan shows that it won’t be built without tolls—something you’d be hard-pressed to learn from any of the “public information” work.  The last estimates prepared for the Columbia River Crossing showed I-5 tolls would be a minimum of $2.30 during off peak hours, rising to $3.25 during rush hour, with additional surcharges for those who didn’t buy transponders for their cars in advance.  The survey didn’t reveal these toll rates, or ask people whether they might prefer a smaller, less expensive bridge with lower tolls, to a larger one with these high tolls, or whether they’d really rather keep the existing bridge if it meant they could avoid tolling altogether.  Despite the fact that the survey avoided talking about tolls, many survey respondents raised the question in answering open-ended questions.

It’s rather like a taste test survey that asks people whether they’d prefer filet mignon to a hot dog, without revealing the price tag of either alternative.  For a project that claims so prominently to care about “centering equity,” failing to reveal that people might have to pay on the order of $1,600 per month to commute daily across this bridge is a monumental omission.  But it’s no accident:  the project’s “public information” campaign is designed is an intentionally misleading way to manufacture consent, not to accurately measure public attitudes.

Surveys can be a useful way to gauge public opinion, if they’re undertaken in a scientifically valid fashion.  But if you aren’t careful, you end up with a classic, garbage-in, garbage-out exercise.  That appears to be the case with survey work commissioned by the “Interstate Bridge Replacement” project, a thinly veiled marketing campaign for freeway widening funded by the Oregon and Washington transportation departments—with “communications” consultants reaping more more than $4 million for their services in the past few years.

What City Observatory did this week

Must read

Cincinnati will have the best bridge that somebody else will pay for.  For some years, Southern Ohio and Northern Kentucky residents have been complaining about traffic on the Brent Spence Bridge, which carries two interstate highways across the Ohio River.  While many say they want a big new bridge that would almost triple  the capacity of the existing structure, neither state has ever found the money.

Now, thanks to the IIJA, the two state’s are hoping that even though they don’t think it’s worth the expense that the federal government will foot the bill.The two states are hoping federal grants will allow them to build the multi-billion dollar bridge without having to charge tolls to the people who actually use it. As the Kevin DeGood of the Center for American Progress tweeted:  “A bridge project that’s so important two states agreed it will only get built if Washington pays for it.”

The high price of electric vehicles.  In yet another record-setting round of corporate subsidies, the state of Michigan is paying General Motors to set up electric vehicle manufacturing operations.  The Guardian reports GM is slated to get $1 billion in state subsides. The company has promised some 4,000 jobs—which works out to a stupendous $310,000 per job, but that’s almost certainly an under-estimate of the true cost.  Job creation counts have routinely been over-promised and under-delivered, and even when automakers have failed in the past to deliver promised jobs, they’ve largely gotten to keep all the subsidies.  It’s ironic in a time of record high profits and record low unemployment that state’s are still easy prey for industrial location blackmail.

New Knowledge

Why going faster doesn’t save us any time.  Central to the economic analysis of transportation projects is the “value of travel time”—an estimate of what potential travel time savings are worth to travelers.  In theory—and thanks to the fundamental law of road congestion, it is way too often just a theory—road investment projects produce economic value because they reduce the amount of time people have to travel to make a particular trip.  But the notion is that a roadway or other transportation system investment that enables us to move faster (more speed) allows us to complete any given trip in less time, and that we can count the value of that time savings as an economic benefit of the transportation project.  (Which is what is commonly done in the benefit-cost studies done to justify roadway improvement projects).

The trouble is there’s no evidence that increased speed gives us additional time that we then devote to other non-transport purposes.  Going faster doesn’t give us more time.  It turns out that we don’t use increased travel speeds to get more time to do other things, we simply end up traveling further and not gaining any additional time for other valuable activities, whether work or leisure:

. . . studies on travel time spending find that the average time persons spend on travelling is rather constant despite widely differing transportation infrastructures, geographies, cultures, and per capita income levels.  The invariance of travel time is observed from both cross-sectional data  and panel data. It suggests that people will not adapt their time allocation when the speed of the transport system changes.

Instead, increased speed of transportation systems is associated with more decentralized land use patterns and longer trips, and all of the supposed “benefit” of increased speed is consumed, in iatrogenic fashion, by the transportation system.  And, importantly, changes in speed trigger changes in land use patterns that can diminish proximity to key destinations:

The higher speed enticed residents of small settlements to shift for their daily shopping from the local shop to the more distant supermarket . . . As a consequence, local shops might not survive, forcing both car owners and others to travel to the city for shopping. The impact of the speed increase is in this case a concentration of shopping facilities, implying a decrease of proximity. The positive impact on accessibility is at least partly reversed by the negative impact on proximity, and the outcome for access is undefined. For those who did not use a car and did not benefit from the speed increase, the result was an unambiguous decrease of the access.

This study suggests that the principal supposed economic benefit of transportation investments–time savings–is an illusion.  Coupled with growing evidence that higher speeds have significant social and environmental costs (lower safety, health effects, and environmental degradation) this suggests that a reappraisal of transport policies is needed.

Cornelis Dirk van Goeverden, “The value of travel speed” Transportation Research Interdisciplinary Perspectives, Volume 13, March 2022.  https://www.sciencedirect.com/science/article/pii/S2590198221002359

Hat tip to SSTI for flagging this research.

What City Observatory did this week

Must read

Homelessness is a housing problem.  Homelessness is a gnarly and growing problem.  But what is at it’s root?  A new analysis from Gregg Colburn and Clayton Page Aldern summarized at the Sightline Institute looks at some of the statistical correlates of homelessness, but comparing data on “point-in-time” counts of those unsheltered with key socioeconomic variables for different cities.  What characteristics and trends are most closely related to high levels of observed homelessness.  You might think that variations in poverty across cities would be a major factor, but statistically, that doesn’t seem to be the case.  The most powerful observed correlation is between housing prices and homelessness:  cities that have very high rents have higher rates of homelessness.

Poverty may be higher in some cities than others, but if rents are low and vacancies are high, then relatively more people, even those with limited incomes, find some shelter.  In contrast, in tight housing markets with high rents and few vacancies, there may simply not be enough housing units to house everyone, and those with the lowest incomes find themselves outbid by those with more money.  The clear implication here is that bringing down rents and expanding housing supply is central to reducing homelessness.

Seattle’s disappointing new waterfront highway.  Seattle is close to putting the finishing touches on the new waterfront roadway that’s being built where the former Alaskan Way viaduct towered over the city for decades.  While getting rid of the viaduct was a boon, the finished product looks to be a major disappointment.  While the project was sold with parklike, green renderings of the waterfront, the reality is that mostly what has been done is to drop the old elevated highway down to street level.  In places, the new highway will be as many as nine-lanes wide, and will separate the city’s downtown from its waterfront with a steady stream of speeding cars.  The Urbanist has this critique:

The Washington State Department of Transportation (WSDOT) tore down its hulking waterfront highway viaduct only to place just as many lanes at ground level — and actually more south of Columbia Street, where the road turns into a giant queuing zone for the Seattle Ferry Terminal.

As is so often the case, the project was sold with a glossy bird’s eye view of the project.  The ground level reality is something altogether different.

It’s a reminder that the devastation to urban space and urban living isn’t just caused by structures, its a product of the volume of cars, and of prioritizing the movement of those who are traveling through the city over those who actually want to be there.

New knowledge

How to save money on transportation:  Don’t own a car.  The Urban Institute’s Yonah Freemark has a thoughtful analysis of how higher gas prices affect households with different income levels based on their car ownership.  Freemark has examined data from the Bureau of Labor Statistics Consumer Expenditure Survey showing what fraction of a household’s income is spent on transportation, based on car ownership by various income groups.

As the following table makes clear, transportation expenditures are most burdensome for low income households who own a car:  those with incomes of less than $25,000 annually who own a car spend close to 25 percent of their household income on transportation.  Interestingly, low income households who don’t own cars spent the smallest fraction of their household income on transportation—a little more than 5 percent.  For higher income households, those who don’t own cars spend noticeably less (between a half and two-thirds as much) on transportation as those households that own cars.

Must read

The problem with the “reckless driver” narrative.  Strong Towns Chuck Marohn eloquently points out the deflection and denial inherent in the emerging “reckless driver” explanation for increasing car crashes and injuries.  Blaming a few reckless drivers for the deep-seated systemic biases in our road system is really a convenient way to avoid asking hard questions about the carnage we accept as routine.  Many drivers routinely engage in risky behaviors, from speeding to texting, to other distractions.  What’s changed during the pandemic, is that their are more opportunities for these risks to turn catastrophic, because there’s less traffic.  Ironically, traffic congestion holds down speeds and forces drivers to pay attention, diminishing possible crashes.  The problem isn’t the recklessness, it’s all the driving.

Focusing on reckless driving is obsessing over the smallest fraction of the underlying cause, but it fits a narrative that engineers, transportation planners, and traffic safety officials are more comfortable with, one that puts the blame on others, primarily the Reckless Driver.

Where college students want to live after graduation.  Axios has a new poll asking an important, post-pandemic (we hope) question:  Where will young workers want to live.  If remote work is as popular and prevalent as some think, young adults seemingly have more choice than ever about where to live and pursue their careers.  The Axios survey shows that the new hotspots are . . . the same as the old hotspots:  big vibrant cities, chiefly on the coasts.

The great tech-hub exodus that didn’t actually happen.  In theory, the advent of work-at-home ought to have undermined the need to be located in an expensive, superstar tech-hub.  Finally, it was supposed to be the opportunity to flourish for second-tier cities that had been bypassed by the continuing concentration of firms and talent in a relative handful of established tech centers.  But according to this article from WIRED, the theory isn’t panning out:  for the most part, tech jobs remain concentrated in the long-established tech hubs.  Drawing on data from the Brookings Institution, they report that:

The tech sector grew by 47 percent in the 2010s, and in the latter half of that decade, nearly half of tech job creation occurred in eight “superstar” metro areas: San Jose, New York, San Francisco, Washington DC, Seattle, Boston, Los Angeles, and Austin. By the end of the decade, those eight cities comprised 38.2 percent of tech jobs.

A key factor underlying the persistent success of these tech centers is knowledge spillovers.  WIRED quotes UC Berkeley’s Enrico Moretti, whose research points out the tech centers serve as force multipliers for idea creation and dissemination:  scientists are more productive when they’re embedded in an environment with others, than when they are widely scattered.

New knowledge

. . . investments in roadways made to reduce traffic congestion lead to inequitable benefits. . .  . because fewer low-income workers and low-income travelers travel by car and at peak times due to their job scheduling and activities. Also, travelled distances of low-income workers are generally shorter so that benefits of flow improvements are more modest. As such, congestion mitigation disproportionally advantages higher-income groups in terms of travel speed and time.

What City Observatory did this week

Freeway widening for whomst:  Woke-washing the survey data.  Highway builders are eager to cloak their road expansion projects in the rhetoric of equity and have become adept at manipulating images and statistics.  In their efforts to sell the $5 billion I-5 freeway widening project in Portland, ODOT and WSDOT have rolled out the usual array of stock photos (this one cribbed from women’s health campaigns, to demonstrate their “commitment” to equity.

More ominously, the two agencies are also using an unscientific and biased web-based survey to falsely claim that the primary beneficiaries of its highway-widening project are low income and people of color.  We dig into their survey data and find it grossly undercounts low income populations, people of color, and young adults, and is biased heavily toward whiter, wealthier groups and those who commute regularly over the bridge.  The data are so skewed and unrepresentative that they can’t be used to make valid statistical statements about who travels where in the region, or how the public feels about the proposed project.  Census data make it clear that the primary beneficiaries of this freeway widening project are peak hour, drive alone commuters who make an average of $106,000 and 86 percent of whom are non-Hispanic whites.  In addition, the survey failed to disclose the project would require tolls of at least $2.60, and didn’t ask any respondents how they felt about tolling.

Must read

A parking inventory for the Bay Area.  Don Shoup’s magisterial work, The High Cost of Free Parking, itemizes the many ways that we have to pay for parking through higher rents, longer distances to all our destinations, and traffic congestion.  Part of the opaqueness of parking economics stems from a lack of data.  We have detailed counts of the population, of businesses, of road traffic, and of housing units, but almost no one comprehensively counts parking spaces.  A new study from the San Francisco Bay Area urban research group SPUR steps into that void.  It shows the Bay Area has roughly 15 million parking spaces, most of them located on public rights of way and “free” to use.  Parking is abundantly supplied:

There are 1.9 spaces per person, 2.7 spaces per employed individual, and 2.4 spaces per auto and light-duty truck. . . . Parking area constitutes 7.9% of the total incorporated area.

That’s in stark contrast to housing.  The Bay Area famously has extremely expensive housing—in part because land use policies have allowed for only 3.6 million housing units for people–less that a quarter of the number of parking spaces available for cars.  And while most parking spaces are free and pay little or nothing in taxes, houses are expensive and heavily taxed and regulated.  The parking inventory clearly signals a regime in which vehicles are vastly more privileged than people.

The “User Pays” Road Finance Myth.  There’s a widespread fiction that the road system is fully paid for by user fees.  A new report from The Frontier Group reminds us, once again, that’s just not true.  User fees, like fuel taxes and vehicle registration fees cover only about half of the direct costs of the road system, and pay almost nothing toward the substantial external and social costs of driving.

The road finance system is regularly bailed out from taxes on unrelated activities (like groceries in Virginia), and Congress has bailed out the Highway Trust Fund with over $156 billion from general funds, in addition to billions for for the IIJA.  Drivers not only don’t pay the costs of the roads they drive on, they impose huge costs on others from crashes ($474 billion), air pollution ($41 billion) and greenhouse gas emissions $70 billion).  By all means, let’s have a user pays transportation system, because we certainly don’t have one now.  Frontier Group has specific recommendations for building on existing revenue systems (the gas tax does tax carbon pollution) and adapting others, like congestion pricing.

Need for a fundamental shift in transportation policies.  California’s Strategic Growth Council has taken a deep dive into the state’s infrastructure policies, and is calling for a dramatic change in funding priorities to tackle climate change.  Key to this is shifting transportation investment away from freeway expansion.  They write:

“. . . a significant share of funds at the state, regional, and local levels continue to be spent on adding highway lanes and other projects that increase vehicle travel. This funding not only adds to the maintenance burden of an aging highway system but also means less available funding for other investments that might move more people (such as running more buses or prioritizing their movement) without expanding roadways or inducing additional vehicle travel and provide Californians with more options to meet daily travel needs. Additionally, in most situations, particularly in urban areas, adding highway lanes will not achieve the goals they were intended to solve (such as reducing congestion) as new highway capacity often induces additional vehicle travel due to latent demand that then undermines any congestion relief benefit over time. Critically, these projects also add burdens to already impacted communities along freeway corridors with additional traffic and harmful emissions, and by further dividing and often displacing homes and families in neighborhoods that were segmented by freeways decades prior.”

The legislatively mandated report sets the stage for better policies.  If California is really serious about its climate change objectives, now is the time to stop building more highway capacity.

New knowledge

Cars make cities less compact.  The chief economic advantage of cities is that they bring people closer together, enably social interaction and promoting productivity.  While at the margin, for an individual, a car makes things in a city easier to reach, that’s not true when more and more people use cars.  Over time, the advent of car ownership has caused population and economic activity to sprawl outward, undercutting the key advantage of proximity.

In this study, a global analysis of car ownership levels and population density shows that cities with higher levels of car ownership have systematically lower levels of density.

That’s long been understood, but there’s by a technical criticism that it may be the low density of places that “causes” more car ownership, rather than the other way around.  This paper tackles that issue by using an instrumental variables methodology that proxies the establishment of car manufacturing facilities for car ownership, and finds that causality runs from car ownership to lower density (the advent of more car manufacturing explains the decline in density.)  While that analysis is convincing, it is very likely the case that, over time, as car ownership increases and density declines, that there is also a feedback loop from lower density to more car ownership:  as land uses become more dispersed due to car ownership, more households are forced to acquire cars to maintain access in the face of falling density, and this in turn triggers further declines in density.  Now, decades after widespread adoption of cars in advanced economies, it may be impossible (and pointless) to try and fully separate cause and effect.  The key finding of this study, however, is that in lower income nations, more widespread car ownership is likely to lead to further declines in population density in cities, which in turn will increase their carbon footprint, and make it all the more difficult to fight climate change.

Francis Ostermeijer, Hans Koster, Jos van Ommeren, Victor Nielsen, Cars make cities less compact, VOX EU, 8 March 2022, and

Ostermeijer, F, H R A Koster, J van Ommeren and V M Nielsen (2022), “Automobiles and urban density”, Journal of Economic Geography, forthcoming.

The Cappuccino Congestion Index shows how you can show how anything costs Americans billions and billions

We’re continuing told that congestion is a grievous threat to urban well-being. It’s annoying to queue up for anything, but traffic congestion has spawned a cottage industry of ginning up reports that transform our annoyance with waiting in lines into an imagined economic calamity. Using the same logic and methodology that underpins these traffic studies, its possible to demonstrate another insidious threat to the nation’s economic productivity: costly and growing coffee congestion.

Yes, there’s another black fluid that’s even more important than oil to the functioning of the U.S. economy: coffee. Because an estimated 100 million of us American workers can’t begin a productive work day without an early morning jolt of caffeine, and because one-third of these coffee drinkers regularly consume espresso drinks, lattes and cappuccinos, there is significant and growing congestion in coffee lines around the country. That’s costing us a lot of money. Consider these facts:

• Delays waiting in line at the coffee shop for your daily latte, cappuccino or mocha cost U.S. consumers $4 billion every year in lost time;
• The typical coffee drinker loses more time waiting in line at Starbucks than in traffic congestion;
• Delays in getting your coffee are likely to increase because our coffee delivery infrastructure isn’t increasing as fast as coffee consumption.

Access to caffeine is provided by the nation’s growing corps of baristas and coffee bars. The largest of these, Starbucks, operates some 12,000 locations in the U.S. alone. Any delay in getting this vital beverage is going to impact a worker’s start time–and perhaps their day’s productivity. It’s true that sometimes, you can walk right up and get the triple espresso you need. Other times, however, you have to wait behind a phalanx ordering double, no-whip mochas with a pump of three different syrups, or an orange-mocha frappuccino. These delays in the coffee line are costly.

To figure out exactly how costly, we’ve applied the “travel time index” created by the Texas Transportation Institute to measure the economic impact of this delay on American coffee drinkers. For more than three decades TTI has used this index to calculate the dollar cost of traffic delays–here we use the same technique to figure the value of “coffee delays.”

The travel time index is the difference in time required for a rush hour commute compared to the same trip in non-congested conditions. According to Inrix, the travel tracking firm, the travel time index for the United States in July 2014  was 7.6, meaning that a commute trip that took 20 minutes in off-peak times would take an additional 91 seconds at the peak hour.

We constructed data on the relationship between customer volume and average service times for a series of Portland area coffee shops.  We used the 95th percentile time of 15 seconds as our estimate of “free flow” ordering conditions—how long it takes to enter the shop and place an order.  In our data-gathering, as the shop became more crowded, customers had to queue up. The time to place orders rose from an average of 30 to 40 seconds, to two to three minutes in “congested” conditions. The following chart shows our estimate of the relationship between customer volume and average wait times.

Following the TTI methodology, we treat any additional time that customers have to spend waiting to place their order beyond what would be required in free flow times (i.e. more than 15 seconds) as delay attributable to coffee congestion.

Based on our observations and of typical coffee shops and other data, we were able to estimate the approximate flow of customers over the course of a day. We regard a typical coffee shop as one that has about 650 transactions daily. While most transactions are for a single consumer, some are for two or more consumers, so we use a consumer per transaction factor of 1.2. This means the typical coffee shop provides beverages (and other items) for about 750 consumers. We estimate the distribution of customers per hour over the course of the day based on overall patterns of hourly traffic, with the busiest times in the morning, and volume tapering off in the afternoon.

We then apply our speed/volume relationship (chart above) to our estimates of hourly volume to estimate the amount of delay experienced by customers in each hour.  When you scale these estimates up to reflect the millions of Americans waiting in line for their needed caffeine each day, the total value of time lost to cappuccino congestion costs consumers more than $4 billion annually. (Math below).

This is—of course—our regular April First commentary, and savvy readers will recognize it is tongue in cheek, but only partly so.  (The data are real, by the way!) The real April Fools Joke here is the application of this same tortured thinking to a description and a diagnosis of the nation’s traffic problems.

The Texas Transportation Institute’s  best estimate is that travel delays cost the average American between one and two minutes on their typical commute trip. While its possible–as we’ve done here–to apply a wage rate to that time and multiply by the total number of Americans to get an impressively large total, its not clear that the few odd minutes here and there have real value. This is why for years, we and others have debunked the TTI report. (The clumping of reported average commute times in the American Community Survey around values ending in “0” and “5” shows Americans don’t have that precise a sense of their average travel time anyhow.)

The “billions and billions” argument used by TTI to describe the cost of traffic congestion is a rhetorical device to generate alarm. The trouble is, when applied to transportation planning it leads to some misleading conclusions. Advocates argue regularly that the “costs of congestion” justify spending added billions in scarce public resources on expanding highways, supposedly to reduce time lost to congestion. There’s just no evidence this works–induced demand from new capacity causes traffic to expand and travel times to continue to lag:  Los Angeles just spent a whopping billion dollars to widen Interstate 405, with no measurable impact on congestion or traffic delays.

No one would expect to Starbucks to build enough locations—and hire enough baristas—so that everyone could enjoy the 15 second order times that you can experience when there’s a lull. Consumers are smart enough to understand that if you want a coffee the same time as everyone else, you’re probably going to have to queue up for a few minutes.

But strangely, when it comes to highways, we don’t recognize the trivially small scale of the expected time savings (a minute or two per person) and we don’t consider a kind of careful cost-benefit analysis that would tell us that very few transportation projects actually generate the kinds of sustained travel time savings that would make them economically worthwhile.

Ponder that as you wait in line for your cappuccino.  We’ll be just ahead of you ordering a double-espresso macchiato (and holding a stopwatch).

Want to know more?

Here’s the math:  We estimate that a peak times (around 10am) the typical Starbucks makes about 100 transactions, representing about 120 customers.  The average wait time is about two and one-half minutes–of which about two minutes and 15 second represents delay, compared to free flow conditions.  We make a similar computation for each hour of the day (customers are fewer and delays shorter at other hours).  Collectively customers at an typical store experience about 21 person hours of delay per day (that’s an average of a little over 90 seconds per customer).  We monetize the value of this delay at $15 per hour, and multiply it by 365 days and 12,000 Starbucks stores.  Since Starbucks represents about 35 percent of all coffee shops in the US, we scale this up to get a total value of time lost to coffee service delays of slightly more than $4 billion.