Homes with better transit access command higher prices, especially in cities with good transit.

Our friends at Redfin, the real estate data and analytics company, have an interesting new report exploring the connection between transit access and home prices. Redfin computes and freely publishes a Transit Score for all of the nation’s houses. Transit Score is a sibling of Walk Score, and is a measure of the number and frequency of bus, train and other transit lines that run in close proximity to a given property.  The closer your house is to a bus stop or train station, and the more lines that serve that stop, the higher your Transit Score.

Their new study uses house price data from 14 cities to look at the relationship between home prices and Transit Score. Redfin uses a workhorse economic tool, called hedonic modeling, to tease out the contribution of different aspects of a home (its size, number of bedrooms, bathrooms, age, neighborhood characteristics, etc.) to the home’s sales price. What they find is that, after controlling for these other observable characteristics that we know influence home values, that each additional point of Transit Score is associated with an average of about $2,000 in higher home value.  They’ve modeled the impact of an additional point of Transit Score on different cities, and shown how it relates to local housing prices.

The value of accessibility

If that finding sounds a bit familiar, it should. We, and separately later, others at Zillow and Redfin, have replicated this kind of analysis looking at the connection between home values and Walk Score.  Although there’s been a bit of variation in the exact details, all three researchers have found a statistically significant connection between home prices and walkability. The more walkable neighborhood a home is located in, the higher its value tends to be.

So does this mean that you can add the value associated with a point of Transit Score to the increase value associated with Walk Score?  Probably not. First, this Redfin study looked only at Transit Score, and not at Walk Score, so statistically, it can’t say anything about the separate (or joint) impacts of the two different measures.  Second, and more importantly, we know that there’s a pretty strong correlation between transit access and walkability. Using transit and walking are strong complements (most bus and train riders are also pedestrians at both ends of their trip), and transit lines tend to provide higher levels of service to denser and more walkable neighborhoods. As a result, given the overlap between walkable neighborhoods and transit-served ones, its probably difficult, and maybe impossible, to tease out the separate contribution of the two factors.

While that may be frustrating statistically, its probably much less of a problem for policy. Given the complementarity between walking and transit, we probably want to build neighborhoods that foster both kinds of transportation.  In effect, measures like Walk Score and Transit Score (and a third sibling, Bike Score) are actually alternate ways of measuring a home’s accessibility: how easy it is to reach a range of common destinations. The greater the level of accessibility, by all these modes, as well as by automobile, the greater the value a home is likely to command.

Is transit worth more in transit-rich cities?

Keeping in mind that some of what is being measured in the Redfin study is the lagniappe from walkability and bikeability being greater in transit-served areas, we thought there was one other interesting aspect of the study’s data. The effect of Transit Scores on home values varied considerably across cities. While the average effect of an additional one point of transit score was to increase home values by $2,000 or between one-half of one percent and one percent in most cities, the impact was noticeably greater in some cities than others.  In Boston, where citywide transit grades out at a very high Transit Score of 74, the impact of a point of Transit Score is 1.1 percent.  In the cities with the lowest levels of city-wide transit accessibility, the value impact of one point of Transit Score was much less. In Phoenix (citywide Transit Score 32) it was just 0.14 percent; in San Diego (citywide score 37) only 0.18 percent. In Orange County (an outlier), where the citywide Transit Score was just 27, the effect of transit access was negative. This suggests of couple of things: First, in some place (Orange County) access to transit is a disamenity: homes are worth less, all other things equal if they’re near the (relatively few and infrequent) bus lines. Second, and more optimistically, transit is even more valuable in cities where the whole transit system works well. This suggests a kind of network externality:  If a city has a good, well-connected transit system, access to transit has an even bigger impact on an individual house’s value.

This latest research is another reminder that consumers place a positive value on city living.  Neighborhoods that are walkable, have great transit access, and are bikeable command higher prices because consumers value them more that places without these characteristics. Even though we face some statistical obstacles to separating out the different contributions of each ingredient, its clear that the combination of biking, walking and transit help underpin urban property values. And you can take that to the bank.

La-La Land voters deal a crushing defeat to a “NIMBYism on steroids” 

The latest returns show Los Angeles’ Measure S–the self-styled “Neighborhood Integrity Initiative”–failing by a 31 percent “Yes” to 69 percent “No” margin. If it had passed, Measure S was predicted  to bring new housing development in Los Angeles to a screeching halt for the next two years, and probably longer.

This was a landslide vote against one of the most NIMBY ballot measures we’ve ever seen. And strikingly, it came under a set of circumstances that should have greatly favored the NIMBY cause. The proponents of the ballot measure cleverly chose to place it on the March local election ballot, rather than on last November’s general election ballot.  Not only is turnout in local elections much lower (it was an estimated 13 percent of registered voters in Los Angeles yesterday*, compared to about 74 percent in the Presidential election), but the demographics of the local election voters skew much more heavily to older, whiter voters, and importantly to homeowners.

For a long time, the “homevoter” theory has held that restrictive local zoning regulations represent profit-maximizing behavior by local homeowners. Restricting the supply of new housing in your neighborhood, the argument goes, not only means that there are more free-curb parking spaces, but the value of your home increases.

While that logic holds strongly at the neighborhood level, the defeat of Measure S signals that at a larger level (and Los Angeles is a city of 3.9 million residents) it’s possible–just possible–for people to recognize that the policies that might make a neighborhood more livable or valuable, only result in higher rents and displacement when applied to a larger geography.  Opponents of Measure S argued that it would have blocked new development, aggravating the region’s housing shortage and further driving up rents.  Apparently their arguments were successful, even with this very much smaller segment of the electorate who ought to have been more pre-disposed to accept the NIMBY arguments.  Like the 2015 rejection of a proposal in Boulder, Colorado, to allow a neighborhood level veto of new development, there’s growing public support for policies that enable housing supply to increase. This also tends to confirm the logic that if we make land use decisions at larger geographic levels (city-wide, rather than by neighborhood), we tend to get results that are more inclusive.

It’s too early to call this a turning point, but the strong rejection of this measure in a setting that should have maximized the chances of NIMBY success is a hopeful sign that American’s are recognizing that we have a shortage of cities, and that our affordability problems are a manifestation of the need to accommodate the growing demand for urban living. Who knows, maybe we can actually talk about “supply and demand” in the context of housing markets, and voters will respond.

What Measure S would have done

While nominally aimed at correcting the supposed abuses of the city’s re-zoning process–it’s common for many new developments to have to seek rezoning to move forward–the effect of Measure S provisions would have been much more sweeping. The proponents of Measure S made a  lot of political hay by pointing out how out-dated and broken the city’s land use plans have become. Most of the city’s neighborhood plans are hopelessly out of date, and as a result, most sizable new developments require separate city council approval of plan amendments to move forward. To be sure, this is a political process, where the City Council gets to flex its muscles, and look out for the interests of citizens and constituents on a case-by-case basis. And when new development does move forward, there’s always the implication that developers curried political favor to get approval. The Yes on Yes on Measure S campaign made this a key talking point:

“Yes on Measure S released today a special report of official city information that reveals how L.A. City Hall works behind closed doors, on behalf of developers and usually without the knowledge of the public, to get around the city’s zoning rules. Most developers donate to L.A. elected leaders throughout the backroom process”

Nominally, Measure S would have called a time out–in the form of a two-year moratorium on most spot-zoning type plan amendments–until such time as full neighborhood plans are up dated.  But the measure would have done more than that. Others have already offered up keen analyses of the flaws in Measure S. Planetizen’s Reuben Duarte explains that the Measure’s requirement that comprehensive plan amendments involve not less than 15 acres, and that they may not allow an increase in overall density:

More ominously, and less discussed than the moratorium, Measure S amends Los Angeles’ Charter to require all future potential general plan amendments meet a minimum threshold of 15 acres, and require all future plan updates to limit increases in density based on the existing average density of the planning area.

An impressive group of Los Angeles based academicians excoriated Measure S as likely to lead to increased sprawl and traffic, to worsen the city’s affordability problems, and make it harder for the children and grandchildren of today’s Angelenos to live in the city.

Measure S wouldn’t have made Los Angeles any less desirable as a place to live, but it will surely would have made it much harder to build new housing. As we’ve seen in cities around the country, the combination of rising demand and fixed supply has the fully predictable effect of driving up rents and making housing less affordable. Had it passed, it seems like a near certainty that Measure S would have made the plight of Los Angeles renters even worse.

California is one state where ballot box zoning has become increasingly common. In San Francisco, voters have decided height limits for individual projects. Voters in Davis cast up or down votes on subdivisions. These initiatives have made it difficult, expensive and highly uncertain for new development to move forward, limiting the growth in housing supplies and driving up rents.

Who votes in local elections

The defeat of Measure S is all the more surprising, because of the sponsor’s decision to place it on the March municipal election ballot, rather than last fall’s general election ballot. Not only was turnout in yesterday’s municipal election dramatically lower, it skewed heavily toward older, whiter voters and homeowners, the heart of the NIMBY constituency. As our friends at Portland State University have shown, the electorate in local elections is, on average, a generation older than those voting in general elections. Los Angeles has just shy of 2 million registered voters. In last November’s general election, about 58 percent of them (1.1 million) made it far enough down the ballot to vote on city measure JJJ, an affordable housing measure (it passed 65 percent to 35 percent). But in yesterday’s election, it looks like total voter turnout will be something like 13 percent.

While we won’t have final data on turnout for a few more days, the data on the characteristics of early voters clearly suggested this election was headed in an ominously NIMBY-leaning direction. In Los Angeles, more than 40 percent of registered voters received their ballots in advance. As of March 6, about 117,000 ballots had been returned. The election consulting firm  Political Data, Inc, tracks these ballot returns.  They reported than about 47 percent of the ballots were cast by those 65 or older (who represent about 20 percent of registered voters), and only 13 percent were cast by those 34 and younger (who constitute 34 percent of those registered.  The firm also estimates turnout by homeowners and renters.  While homeowners make up about 48 percent of those sent ballots in advance, they represented fully 60 percent of the ballots returned as of March 6. (Hat tip to Jordan Fraade for pointing us to this excellent data).

* – As of Wednesday March 8, about 250,000 ballots had been tabulated from about 2 million registered Los Angeles voters. In California, voters who receive vote by mail ballots have to have the ballots post-marked not later than election day, and received by the election office not later than three days after the election.  Some additional vote-by-mail ballots will come in during the next few days and increase the turnout slightly.

What City Observatory did this week

1. Are restaurants dying and taking city economies with them? In a column at Governing, Alan Ehrenhalt raises the alarm that a city economic revival predicated on what he calls “cafe urbanism” is at risk if there’s a collapse in the restaurant sector. Apparently, a number of restaurants in his local Virginia suburb have failed. We look at the national data on restaurants and find that overall, they’re still increasing robustly. In fact, Americans now spend more on food consumed outside the home than they do on groceries. This sector of the economy appears to be doing quite well, at least so far.

2. Affordability beyond the median.  The standard yardstick for judging housing affordability is to look at the median level of rents or home prices. As we all remember from statistics, the median is the observation in the middle of the distribution. And while for many purposes, it’s a reliable indicator of typical prices, in some neighborhoods, particularly those with a mix of expensive and cheap housing, the median is actually a weak indicator of affordability. We illustrate with some real world examples how this problem arises, and discuss how to look past the median to better understand neighborhood affordability.

3. How fast are America’s metropolitan areas? If often seems like transportation policy is obsessed with how fast we move. But which metropolitan areas have the fastest travel speeds? Using data from the US DOT’s national transportation survey, and adjusting for typical trip lengths, the University of California’s Victor Couture and co-authors have estimated the average speed of travel in each of the nation’s largest metros. We have the complete ranking: Louisville tops the list, traveling on average 22 percent faster than the typical metro area; while Miami travels the most slowly, about 12 percent slower.

4. Going faster doesn’t make us happier. We combined Victor Couture’s estimates of the relative speed of travel in different metropolitan areas, with survey data on the level of satisfaction local residents report in their transportation system.  We found that places with faster travel times didn’t have higher levels of satisfaction. What they did have, however, was longer trips, as measured by vehicle miles traveled (VMT) per person per day.  Simply put: faster speeds are correlated with more driving. And interestingly, VMT has a strong negative correlation with satisfaction with the transportation system. People who live in metros with the highest levels of VMT per capita are generally the least satisfied with their transportation systems.

Must read

1. The Trump Budget and Transit. The Trump Administration’s budget for the coming fiscal year would effectively wipe out funding for new transit projects under the New Starts and Small Starts programs that have been the linchpin for funding most of the nation’s rail transit, bus rapid transit and streetcar projects. Yonah Freemark lists the projects now in the pipeline that are in jeopardy. Of course, Congress will have to agree to these cuts, but its an ominous sign from the new administration. Further bad news for cities: big cuts at the Department of Housing and Urban Development, including zeroing out the community development block grant program which is a major funder for neighborhood redevelopment and housing improvement.

2. Mini-Ubers are blooming in Austin.  Last year, Lyft and Uber both pulled out of Austin after voters there turned down an initiative that would have exempted transportation network companies from the city’s existing driver finger-printing requirements and other regulations. At the time, we wrote that the city should view this as an opportunity to encourage the growth of home-grown alternatives. “Let a thousand Uber’s bloom,” we said. And according to a new article in CNNTech, that’s just what seems to be happening.  As we suggested, it was probably a bad idea to pull out of a city full of independent minded customers, smart programmers and serial entrepreneurs.

3. The run down on Uber.  Uber has been in the news so much lately that its hard to keep track of what’s being said. For a great synopsis of all of these events, read CityLab’s run-down, with copious links to media coverage. Laura Bliss has covered the waterfront, from the company’s financial problems to charges of sexual harassment.

4. Are tiny houses an answer to homelessness? In Portland, Multnomah County leaders have proposed an innovative program to buy tiny houses–those super compact, space efficient living units–and give them to local homeowners, provided they place them in their yards and allow an otherwise homeless family to live in them for at least five years. The county calculates that housing people in tiny houses is less expensive than the cost of shelters, and new units could be put in place much more rapidly than with new construction. Already, the city of Portland has permitted one innovative project to develop a cluster of tiny houses to house the homeless.

New research

The importance of economic integration to academic success. A new paper in the Journal of Urban Economies from George Galster and three co-authors looks at the results of a natural experiment in Denver. (Hat tip to the Chicago Policy Review for flagging this work). The Denver Housing Authority had a program that quasi-randomly assigned eligible households to housing in a variety of neighborhoods. Galster and his co-authors looked at data on the school performance of children in these families, and examined the correlations between neighborhood characteristics and educational performance. This avoids the problem of “selection bias” that plagues many studies of such relationships, i.e.  that families that move to higher opportunity neighborhoods self-select and may be different in unobservable ways from other families. They find that “neighborhoods having less social vulnerability, higher occupational prestige and lower percentages of African American residents robustly predict superior secondary educational performance.”  Its yet more evidence that economically integrated neighborhoods are a key to overcoming the disadvantages of poverty.

What City Observatory did this week

1. 13 propositions about autonomous vehicles. Despite occasional setbacks–like last week’s crash of an Uber self-driving car in Phoenix–it looks increasingly likely that autonomous vehicles will play an important role in urban transportation in the not-too-distant future.  There’s a lot to ponder about what effects they might have on cities, on land use patterns, on transportation and public finance.  To help fuel your thinking, we outline 13 propositions about the character of travel demand, the costs of new technology, and the kinds of public policies that will shape its implementation. There’s a much longer conversation to be had here, but we invite your reactions to our initial thoughts.

2. Breaking Bad: Why breaking up big cities would hurt America.  New York Times columnist Russ Douthat thinks that big, liberal cities have garnered an unfair monopoly on the nation’s economic assets (like universities and productive industries) and that we’d be better off if we dispersed these resources to the rest of the country. In our view, this fundamentally misunderstands the economic role cities play; they actually foster the entrepreneurship, knowledge creation, and productivity that drive the US economy. Making cities smaller would actually reduce national income and productivity.

3. The cost of segregation. Its widely acknowledged that racial and economic segregation are unfair, unwise and at odds with our democratic values, but a new report from the Urban Institute shows that segregation imposes its own significant economic costs. This statistical study shows that higher rates of segregation are associated with lower earnings for African Americans, lower educational attainment and higher crime.  In just one city–Chicago–simply reducing segregation from its current high level to the level found in the typical metro area would be expected increase the average income of African Americans by $3,000 annually and cut homicides by nearly a third.

4. Revisiting the cappuccino congestion index. Looking to get the jump on April Fool’s Day, we’ve dusted off our cappuccino congestion index, which turns a traffic engineer’s eye on those annoying lines that we have to wait in to get our daily coffee fix. If you apply the same tools and assumptions to assess the “cost of congestion” at your neighborhood coffee house that is commonly asserted to apply to roads, you could conclude that we waste $4 billion annually waiting in line for coffee. But the fact that Starbucks (and all its competitors) don’t build enough stores, buy enough espresso machines, and hire enough baristas that we never have to wait in line is a really good indication that the cost of added capacity is much larger than the supposed costs in time lost. The same conclusion applies to roads.

Must read

Trump and Clinton Counties compared. Brookings demographer Bill Frey has a terrific statistical profile comparing the differences in age, education, race, ethnicity, and place of birth between counties that voted for Hillary Clinton as opposed to Donald Trump in the 2016 election. Trump won more counties, but Clinton won the more populous ones, and the population of Clinton Counties (177 million) was vastly greater than Trump counties (146 million). Counties which voted for Trump were older, and whiter. Counties that voted for Clinton were better educated and had more immigrants. Just imagine if we apportioned electoral votes according to county population, rather than by state.

A road to nowhere. Building more roads and bridges is a favorite old-timey elixir for rural economic development, and there’s a born-again enthusiasm for thinking that one more road will somehow turn around a struggling town. But as Tony Dutzik patiently explains at The Frontier Group, highways can’t heal what ails the rustbelt. Not only do they fail to address the root problems of economic decline, but also add their own negative effects (often undercutting the viability of existing city centers), and necessarily consume a huge amount of resources that could be better used elsewhere.

Making roads more dangerous to keep us safe. Its a perennial battle: traffic engineers and fire chiefs are telling us that wider roads will make us safer. Wider travel lanes mean more space between cars and (theoretically) should reduce collisions. Wider roads mean giant fire engines can roar faster to emergencies, with that time savings saving lives. This drama is playing out, once again, in Celebration, Florida the new urbanist model town. The trouble is, as Steve Mouzon reports at CNU, wider roads encourage cars to travel faster, making roads more dangerous. That, and lopping off trees and removing on-street parking makes pedestrians feel even more vulnerable so they walk less. Less walking and faster cars turns out to more than erase suppose the health and safety advantages of wider roads.

New ideas

Segregation.  See this week’s post on the Urban Institute’s new report, the Cost of Segregation, (above).  Its a comprehensive statistical analysis of economic and racial/ethnic segregation in the nation’s 100 largest metro areas, with detailed data for 1990, 2000 and 2010.

City Observatory in the news

In an article entitled “This is the start of the retail store reckoning,” Forbes cites our recent commentary looking at which metropolitan areas are most over-stored and are likely to see a decline in retail employment as that sector continues to restructure.

Milwaukee Sentinel Journal featured research findings from our study of concentrated poverty, Lost in Place, in their article “An intractable problem,” looking at economic restructuring and the persistence of poverty in Milwaukee.

What City Observatory did this week

1. The US retail industry is getting marked down in a big way, with hundreds of stores operated by well-established chains including Macy’s, J. C. Penney, and the Gap, as well as others, closing or slated for closing in the next few months. By global standards the U.S. is “over-stored” with far more square feet of retail space per person than similarly rich countries. There’s also a big variation in retail square footage among U.S. metro areas. We review the data for the top 50 metro areas and handicap the cities with the biggest space overhang which may be in line to experience the biggest declines as retailing retrenches.

2. Critical mass and neighborhood revitalization. A few weeks ago, we pushed back on those who criticized Detroit’s nascent recovery as being too unequal, with only a few neighborhoods showing improvement, while others continue to languish or decline. We argued that that city’s rebound, when it comes, will only take off in places where there’s a critical mass of new residents, businesses and investments. A new economic study tries to more precisely estimate the nature and size of these agglomeration economies, and predict which neighborhoods in Detroit have the greatest potential to trigger a positive feedback loop that will drive development forward.

3. How transit influences home values. For a long time, we’ve been highlighting research that shows that walkability is positively correlated with home values. A new study from real estate mavens at Redfin also shows that there’s a positive link between that company’s “Transit Score” measure (which looks at the proximity of transit stops and frequency of bus and train service) and home values. They find that in the typical city, each additional one point on the transit score measure increases a home’s value by about $2,000. Once caveat, in our view: the value gains associated with transit score at least partly reflect the walkability of the most transit served neighborhoods; the underlying source of the gain in both cases is the improved accessibility via all modes of transportation.

4. Big city metros are increasingly driving the US economy. In the recovery from the Great Recession, US job growth has been led chiefly by the nation’s largest metro areas. We show that since the economy last peaked in December 2007, about 87 percent of all net new jobs have been created in metro areas with a population of one million or more. Smaller metro areas have grown only about half as fast as larger metros, and non-metro/rural America is still more than 2 percent below the level of employment it had a decade ago. This is further evidence of how city-centered US economic growth has become.

Must read

1. Building codes that ban small tiny apartments aggravate housing affordability and homelessness. Writing at the Sightline Institute, David Nieman relates latest chapter in the the continuing saga of how building code regulations in otherwise progressive Seattle are making that city’s affordability problems worse. His article–”How Seattle Killed Micro-Housing, Again“–tells how the city has made most forms of congregate housing (where residents may share a bathroom or cooking facilities with neighbors) simply illegal. It’s tried, largely in vain, to legalize 225 square foot efficiency apartments (which must have kitchens, full plumbing and closets), but the city’s specific requirements have steadily (and stealthily) inflated the size and budget of such units.  Its a tragic self-inflicted wound.

2. Boring tunnels won’t solve traffic congestion: only road pricing will. UCLA’s Herbie Huff writing the Los Angeles Times schools Elon Musk on the idea that building more roads (whether under or above ground) holds any prospect of ameliorating traffic congestion. This is a nice, well-argued, and non-technical summary of why road pricing can work, and why adding more capacity, by whatever means, will simply be swamped by induced demand unless consumers are asked to pay.  Huff pushes back on the usual arguments offered against tolls, noting that they’re both fairer and more efficient than our current system of taxing everyone, and letting queueing ration use.

3. LaCrosse doesn’t want more highway lanes, thank you. Next City’s Rachel Kaufman tell’s of LaCrosse, Wisconsin’s efforts to drag that state’s highway department kicking and screaming into the 21st Century. Like many cities, it has witnessed a big increase in pedestrian and bicycle travel, and the city’s population growth has exceeded that of surrounding suburbs. But state highway planners, still relying on pre-recession forecasts of ever increasing car travel, are calling for more highway capacity through the city.

New ideas

More evidence for the “time-budget” hypothesis. One theory of transportation and commuting behavior holds that humans have a rough optimum daily time budget for travel for regular activities like work. (This is also often called Marchetti’s constant, and is based on the observation that as transportation technologies have changed, from walking, to horse-drawn streetcars, to electric streetcars, then automobiles and mass transportation, that most commute trips average about 30 minutes each direction per day. A new study of travel behavior in Hungary between 1988 and 2010 by Tamas Fleischer and Melinda Tir, finds more evidence of this effect. Even though the total share of travel by private car more than doubled during this period (displacing slower public transit, cycling and walking), total daily travel time stayed almost constant, between 60 and 65 minutes. This suggests that travelers used improved technology (the car) not to save time, but to travel further (to more distant homes or jobs) than they did previously.  A relatively fixed time budget means that transportation investments change land use patterns rather than save time.

What City Observatory did this week

1. More flawed congestion rankings. Traffic analysis firm Inrix released yet another report purporting to estimate the dollar cost of congestion and ranking the world’s cities from most to least traffic burdened. Our review shows that the report suffers from many of the same problems that plagued its predecessors. Chief among them: congestion indices ignore differences in commute distances among cities, understating the travel time advantages enjoyed by residents of more compact metro areas. The new Inrix report differs just enough from previous versions that its not possible to do time series analysis, which undercuts the practical value of the data. Finally, despite claims that congestion costs commuters billions, the report never identifies any feasible set of investments that would provide enough capacity to alleviate congestion at a cost lower than the supposed cost of congestion, and without triggering additional induced traffic.

2. Uber & Lyft swamping New York streets. For a while, the growth of transportation network companies, aka “ride-sharing,” mostly took market share away from yellow cabs. But as they’ve continued to grow, they’re actually increasing the total volume of vehicles on New York City streets, pushing the city toward gridlock, according to a new report from Bruce Schaller, a former city transportation official. Ride-sharing companies have added 600 million vehicle miles of travel to city streets, and their growth has pushed reversed a 24 year trend in which most additional trips were taken by transit.

3. The real welfare cadillacs have 18 wheels. Truck freight movement gets a subsidy of between $57 and $128 billion annually in the form of uncompensated social costs, over and above what trucks pay in taxes, according to the Congressional Budget Office. If trucking companies paid the full costs associated with moving truck freight, we’d have less road damage and congestion, fewer crashes, and more funding to pay for the transportation system.

4. What the meltdown by Uber’s CEO tells us about the company’s prospects. Between sexual harassment charges, a powerful #DeleteUber campaign, and defending claims that it has stolen another company’s self-driving car technology, it’s been a tough month for Uber. Tellingly, the video of a blow-up between CEO Travis Kalanick and one of the company’s drivers reveals that competition is having a material effect on the company’s strategy and profits. Kalanick’s admission that they’ve had to cut rates to meet competition seems to confirm many of the doubts that analysts have expressed about the long-term financial viability of the firm’s business model. By some estimates, Uber’s investors are underwriting 59 cents of every dollar it costs to provide a ride.

Must read

1. Another take on Detroit. Pete Saunders, who blogs at the Corner Side Yard, weighs in with his views on last week’s brouhaha over whether to view Detroit’s economic recovery as a glass half-full or half-empty. Pete’s clearly in the “half-full” camp: “Detroit’s recovery? O Yeah, its Real Alright.” By his reckoning, in its decline, Detroit’s fallen further than just about any other city in the US. And that’s what makes its rebound all the more remarkable. As one measure of the city’s challenges, Saunders charts the change in the city’s white population compared to other older industrial cities. While other cities such as Cleveland, St. Louis and Buffalo all experienced white flight, none experienced anything like Detroit, where each decade after 1970, the white population fell by half, for a cumulative 96 percent decline in the white population from 1950 through 2010. Given this backdrop, the modest gains recorded in recent years are a clear reversal of a well-established downward trend.

2. Why aren’t we building more middle income housing? At Rooflines Rick Jacobus tries to answer this perennial question about housing markets. The framing goes like this: while the private market mostly builds housing for upper income households, and we have public and subsidized housing for low income households, who’s building housing for those in the middle? Part of the answer, Jacobus points out, is that the opportunities to build new units are numerically constrained by local zoning laws. If the market is constrained to a certain number of houses, builders find it most profitable to build for the high end of the market, unlike say in the market for automobiles, where car makers, who don’t face a numeric limit on their output build different models for different segments of the market. Its a bit more complicated than that, as Jacobus acknowledges, because houses are much more long-lived than cars, and also because their are important spillover effects (your neighbor’s house has a much bigger impact on your house than your neighbor’s car). While this is an important question to contemplate, Jacobus doesn’t really offer up any answers, and one suggestion–that planner’s spend more time talking explicitly about the class identity neighborhoods–seems fraught with controversy.

New research

1. Immigrants and crime. Despite the President’s claims to the contrary, immigrants to the United States are less likely than native born Americans to commit crimes. Writing in the Journal of Ethnicity in Criminal Justice, Robert Adelman and co-authors look at 40 years of data on crime rates and immigrant status by metropolitan area.  They find that immigration is linked to lower levels of  violent crimes and property crimes. “The results show that immigration does not increase assaults and, in fact, robberies, burglaries, larceny, and murder are lower in places where immigration levels are higher.

2. Who are your peer cities? The Federal Reserve Bank of Chicago has developed an interesting new tool that let’s you see which cities score similarly to yours on a series of indicators, including equity, resilience, economic outlook and housing. In each of these four areas, the tool identifies cities that are roughly similar as measured by selected data in that category.  Housing comparisons, for example, are based on the share of pre-1980 housing, the vacancy rate, the home price to income ratio, the homeownership rate and the share of rent-burdened households.  Comparisons are just for cities (i.e. using municipal boundaries), not metropolitan areas, and is therefore subject to our usual warning about the highly variable nature of city geographies. The housing peers of Los Angeles include a number of other California cities, and somewhat surprisingly, Lawrence Massachusetts.

City Observatory in the news

An an Associated Press feature published in the Detroit News and other metropolitan dailies, City Observatory’s research on the “Young and Restless” was featured. “The Plight of company towns” looked at the growing trend of company’s to move headquarters operations from smaller cities and suburban locations to urban centers in order to be able to easily hire talented young workers.

What City Observatory did this week

1. Shrinking offices: What it means for cities. Its not just you’re imagination: offices are becoming less common and smaller, and a variety of space-sharing and space-saving practices are taking hold in businesses around the nation. The number of square feet of office space leased per new office employee has fallen from about 175 square feet in the late 1990s, to only about 50 square feet in the past six years. This greater space efficiency coincides with the growth of city focused industries like software and professional services, and suggests we can accommodate a good deal of job growth within the existing footprint of the nation’s cities.

2. What economists say about rent control. Rising rents around the country are bringing back demands for a long-discredited policy: rent control. While economists have been almost unanimously opposed to rent control schemes, some advocates have pointed to more nuanced analyses which concede that “temperate” or “second-generation,” rent controls have fewer adverse effects. A close reading of key studies by economists Tony Downs and Richard Arnott shows that actually neither author endorses these new age forms of rent control, and in fact the absence of negative effects from some schemes is mostly because they don’t actually limit rents much below market rates.

3. LaLaLand: The Triumph/Twilight of NIMBYism? Los Angeles voters resoundingly rejected Measure S, an initiative that would have imposed a two year moratorium on most plan changes, and which would have made it much harder to increase density in the city. The measure’s proponents campaigned on a range of issues, including traditional NIMBY-concerns about effects of new development and a city planning process seen as highly ad hoc and politicized. Nonetheless voters rejected the measure with 69 percent voting “No.” The election’s outcome is even more surprising given the proponents maneuver to have the measure voted on at this March local election, rather than at the November general election. Turnout in March was not only much lighter, but heavily skewed toward older voters and homeowners, much more of a NIMBY friendly demographic. One key to fighting NIMBYism seems to be to tackle planning issues at the broadest possible geographic scale, rather than development by development or neighborhood by neighborhood.

Must read

So much to read this week: There must be something in the water.

It’s the prices, stupid.  Land Use and Vehicle Miles Traveled.  The past week has been dominated by discussions of a usually arcane, chiefly academic topic: how does urban form, including density, influence how much people travel. The debate played out initially in a meta-analysis of studies by Mark Stevens showing the connection between urban form and driving was less strong than earlier claimed.

It was challenged by excellent commentaries by Chris Nelson, Susan Handy and Reid Ewing all pushing back on the thesis in one way or another.  All are well-argued and worth reading.  But to our way of thinking, Michael Manville‘s paper drops a scimitar through the Gordian knot here.  Manville points out that all of the guessing about how aspects of the built environment influence driving (density, design, mixed use, etc) ignore the central point, which he neatly summarizes in just a few words. It’s short enough to make a haiku or a plausible tattoo:

That’s it.

We give away road space for free, both for travel and private car storage. We also require most new stores and houses to build and maintain free parking at private expense.These policies–which are routinely ignored in the land use/VMT studies–trump all of the other variations in policy and form in incentivizing driving. Manville’s observation squares with the evidence we printed earlier about the strong connection between parking prices and transit ridership. Build as dense and well-designed, as walk friendly and transit-served as city as you like, and so long as you subsidize road space and car storage, you’ll get lots of driving.

Tactics, strategy and vision: In a blog post neatly reviewing this whole contretemps at the Frontier Group, Tony Dutzik agrees with the logic of Manville, but raises doubts about the political feasibility of implementing road pricing–at least any time soon. The underlying problem, as Dutzik eloquently explains, too much of our thinking about planning and transportation is predicated on the unrealistic assumption that we can regain a largely fictional world of cheap (heavily subsidized) housing, short commutes and negligible traffic. Until we develop more realistic expectations of what’s possible, we’re just courting disappointment and increasing distrust, which will make political agreement about solutions even harder.

Exaggerating the economic benefits of highway projects. Our friend Chuck Marohn of StrongTowns takes out the trash on the inflated claims that are made about the economic benefits of building highways. Like every big highway project, Shreveport’s ‘s I-49 connector has an accompanying economic impact analysis which claims that the project will produce millions in benefits from time savings and greater productivity. The productivity claim is based on a very expansive reading of a French economic study called “Size, speed and sprawl.” Chuck shows how highway advocates have twisted and exaggerated this academic work to gin up big numbers to support their project.

Self-driving cars can’t cure congestion, but pricing roads can. The New York Times Upshot has a nice synthesis of the recent discussion of the impact of transportation network companies (and someday, maybe soon, autonomous vehicles) on urban traffic. They’ve presented to the mass audience several of the key points we’ve discussed here at City Observatory: notably, the recent Schaller study showing that Uber, Lyft and other ride-sharing services are responsible for growing traffic and slower travel times in New York. Conor Daugherty concludes that self-driving vehicles likely won’t solve this problem, but as many economists have argued, pricing the roads could.

Glaeser: Cities are the lifeblood of our nation’s economy. Jennifer Rubin interviews Ed Glaeser for the Washington Post. She gets Glaeser to dive deep into the critical role that cities play, not just in attracting and aggregating talent, but making us smarter. Cities are forges for human capital, and the longer workers spend in cities, the more productive and better paid they become, as the acquire more skills and find their way to the institutions and endeavors that best match their strengths. Its the dynamic, self reinforcing aspect of talent in cities that makes them especially important for national economic success.

New research

Economic development incentives. The Upjohn Institute’s Tim Bartik, perhaps the nation’s leading scholar on economic development, has new research and a publicly available database on the number and extent of state business incentives.  Over at CityLab, Richard Florida summarizes Bartik’s research in a short essay. Bottom line: in 2015 tax breaks cost more than $45 billion, and were overall, ineffective.  Given the variation in state tax systems, the complexity of different businesses and the arcane nature of tax breaks, this has been a prodigious undertaking. The full database, which covers 33 states, and two decades, is available through the Upjohn Institute.

Which cities move the fastest? Does it matter?

The raison d’etre of the highway engineer is making cars go faster. That’s reflected in chronic complaints about traffic congestion, and codified in often misleading studies, like those produced by the Texas Transportation Institute.

The latest contribution to the literature on inter-metropolitan differences in transportation system performance is titled “Speed.”  This new paper from Victor Couture, Gilles Duranton, and Matthew Turner, presents a  more systematic set of estimates for comparing travel speeds in different metro areas. The names Duranton and Turner should be familiar to City Observatory readers: they’re the co-authors of “The Fundamental Law of Road Congestion,” which persuasively shows how additional road capacity leads to longer trips and more traffic.  One of the complicating factors of speed estimation is that speeds vary by length of trip, time of day, and trip purpose.  In general, shorter trips involve lower speed travel. That makes sense:  if you’re just traveling a mile or two, especially between your home and some other destination, its likely you’ll travel mostly on local streets, frequently encountering stop signs and traffic signals. But for longer trips, it makes more sense, even if its not the shortest distance, to travel part way on higher speed arterials or limited access freeways. Couture and his co-authors use detailed micro-data on trip taking in the National Household Transportation Survey to estimate variations in speed across metropolitan areas, after controlling for differences in trip distances and other demographic factors.

After crunching all the data, they come up with their estimates of which metropolitan areas have the fastest highways, and which have the slowest.  Their estimates are expressed as a relative travel time, indexed to the average speed for the 50 large metropolitan areas in their study.  Values greater than one represent faster than average speeds (traffic in Louisville travels 22 percent faster than the typical metropolitan area). Values less than one represent slower average speeds (traffic in Miami moves, on average, about 12 percent faster than in the typical metro).  Here are the largest metros, ranked from fastest to slowest.

A couple of observations are in order about these data.  First, it’s worth nothing the dispersion between the fastest and slowest metropolitan areas.  Speeds in the fastest metropolitan area (Grand Rapids) are about 22 percent greater than the median; speeds in the slowest metro area (Miami) are about 12 percent less than the median.  Second, the largest, densest and most economically vibrant metropolitan areas have among the lowest speeds.  The three largest (New York, Los Angeles and Chicago) are among the six slowest.  Seattle and San Francisco, famous for livability and technology clusters are also slower.  Third, the fastest speeds tend to be a combination of smaller sunbelt metropolitan areas (Raleigh, Oklahoma City, Nashville), and slower growing smaller cities in the Northeast/Midwest: Grand Rapids, Buffalo, Rochester.  Couture and his co-authors were also able to look at differences in travel speeds as they relate to demographic, as well as geographic characteristics. Earlier, we reported their striking finding that African-American drivers travel on average about 8 percent more slowly that white drivers, which strikes us as strong evidence that they’re fastidiously trying to avoid being pulled over for driving while black.

Speeds seem highly correlated with measured traffic congestion. You may recall the recent estimates from Inrix on how congested roads were in major metropolitan areas. We’ve plotted the Couture et al estimates of average speeds against the Inrix estimates of metro area congestion. Keep in mind that the Inrix data are for 2016, while the Couture speed data are from 2008.  Despite the 8 year difference in the data estimates, there’s a fairly strong correlation. Traffic moves fastest in the cities that Inrix reports have the least congestion (Louisville, Kansas City) and slower in cities that Inrix says are more congested (Miami, Los Angeles).  But as the line on the chart suggests, the relationship between average speed and this particular congestion index is non-linear:  the big differences in average speeds is among cities with relatively low levels of congestion; as the congestion index rises (across cities) the speed index falls, but more slowly. This suggests that unless you get a very large reduction in congestion, you don’t see much of an increase in measured speeds.

Just like Keanu Reeves and Sandra Bullock, everyone seems deathly of afraid of going slower. But for cities, and their inhabitants, its far from clear that being the fastest actually gets you anywhere. We’ll take a closer look at the implications of speed tomorrow.

Editors note: In the original version of this post, we got Victor Couture’s surname wrong. We apologize.

For a long time, we’ve been critical of the way we commonly talk about housing affordability.  We’ve published a three–part series about why the way we measure housing affordability is all wrong. In particular, we objected to using the 30 percent ratio of housing prices to income as the benchmark of “affordable,” basically because depending on income and other necessary expenses, a given household might actually be able to spend way more than 30 percent of their money on housing—or way less.

But now we have another nit to pick. To wit, the nit: measuring housing prices by only looking at the median. Recall from math class that in any given area, the median-priced home is the one for which an equal number of homes are more and less expensive. But most of the time—San Francisco and New York and their peers in housing market dysfunction notwithstanding—we’re not mostly concerned with the median housing purchaser; rather, affordability problems will be concentrated in the lower part of the earnings scale, and so what really matters is the lower end of the home price scale.

For an illustration of this problem, imagine two neighborhoods. In both places, the median home costs $300,000. But in the first neighborhood, every home costs exactly $300,000, while in the second, there are a range of homes from $100,000 to $500,000. Although both neighborhoods have the same median home price, the second neighborhood has some homes affordable to low-income people, while the first neighborhood does not.

So rather than the median, or 50th percentile, home price, we really care about something like the 25th percentile: the home for which 75 percent of homes are more expensive.

Now, to be fair, the price of a place’s 50th percentile home strongly predicts the price of the 25th percentile home. If the median housing price hits a million dollars—as it does in, say, San Francisco—you can be quite confident that the 25th percentile home is also far, far too expensive.

But in more normal markets, there is enough variation in 25th percentile prices in places with the same 50th percentile price to make a meaningful difference in affordability for lower-income people. Let’s take Chicago, for example. Happily, the Census has home price estimates for both the 25th and 50th percentile homes (and 75th—the home for which just a quarter of all homes are more expensive—but we’ll leave that to another post). If you plot these two prices by ZIP code in Cook County, which includes Chicago and its inner-ring suburbs, this is what you get:

As we said, the median home price of a given ZIP code very strongly predicts its 25th percentile price. But let’s zoom in a bit—to, say, anywhere with a median price within $25,000 of $250,000.

Now we can see a strong amount of difference. Right on the $250,000 median price line, for example, ZIP code 60645 has a 25th percentile home price of about $149,000, while ZIP code 60422 has a 25th percentile home price of $187,000. In the simplest terms, then, a low-price home in 60422 is a full 25 percent more expensive than a low-price home in 60645—even though an average-price home is almost exactly the same in both places.

How does that happen? Well, zooming in on what these two ZIP codes actually look like on the ground, we can hazard a guess. ZIP code 60422 is in suburban Flossmoor, which has a small, walkable, “illegal neighborhood”-type downtown around a commuter rail station, but otherwise is almost entirely made up of single family homes, ranging from medium-sized to large.

ZIP code 60645 is in the West Ridge neighborhood of Chicago’s far North Side. It has its share of medium-to-large single family homes; but it also has a large number of multi-family buildings, from a large tower-in-a-park development to copious numbers of two-flats, three-flats, and larger lowrise apartment buildings.

The contrast is actually a brilliant illustration of one of our favorite topics, which is the way that traditional, “illegal neighborhoods” can use a diversity of buildings to create a diversity of people. West Ridge simply has many more kinds of homes than Flossmoor: there are single family houses for parents and their children who can afford a $250,000 (or more) home; there are relatively large apartment and condo units in lowrise buildings; and there are smaller apartment and condo units in lowrise and highrise buildings that provide a stock of affordable housing without subsidies.

It helps, too, that West Ridge has buildings from a variety of time periods, dating back to the early 1900s. As we’ve written before, new construction is almost never affordable to people of low or moderate incomes—but often homes that are built for the upper middle class become much more affordable after a generation or two. Much of the low-priced housing in West Ridge fits this story.

All these differences add up to very different neighborhood demographics. West Ridge has a median age, income, and poverty level that are all fairly close to those of the city of Chicago or metropolitan area averages. In Flossmoor, by contrast, the median age is 46—more than a decade older than the metro area median—in part because there are few homes suitable for young people who might not yet have a stable middle-class income. Moreover, just 2.9 percent of residents in ZIP code 60422 live below the poverty line. As we’ve covered before, while that might sound like a good thing, in a region where nearly 14 percent of people live below the poverty line, such a low level in an individual city isn’t a sign of economic success—it’s a sign that Flossmoor has (in part) used its built environment to exclude low-income people from one of the most opportunity-rich parts of Chicago’s south suburbs. Economically integrated West Ridge, by contrast, manages to keep a strong middle class while remaining inclusive of people whose incomes are much lower.

But none of these differences can be explained by median home price—because West Ridge and Flossmoor have almost identical median prices. Instead, we need to look at the price of a typical low-priced home to understand what’s going on.

The nation’s largest city-centered metro areas are powering national economic growth.

2017 will mark a decade since the peak of the last economic cycle (which according to the National Bureau of Economic Research was December 2007.  Since then, we’ve experienced the Great Recession (the biggest economic downturn in eight decades), and a long and arduous recovery.

We’ve always maintained that the word “recovery” is a misleading term, because it seems to imply that we get back exactly the same economy, industries and jobs that we lost to the recession. In fact, that’s not true:  the jobs created since the bottom of the recession in 2009 are in different firms, in different industries, and importantly, in different places than the jobs we lost to the recession.

It’s illuminating to look to see where the jobs that have been created in this recovery are actually located. There’s no question that large metros are important to the economy. These 51 metros with a million or more population are home to 168 million Americans, and account for about 65 percent of the nation’s gross domestic product. But the big question is, how important are they to national growth? It turns out that in this particular recovery, big city metros, those with a population of 1 million or more, have dramatically outperformed the rest of the nation’s economy.

Today we’re revisiting a data series that has been compiled and tracked by our friend Josh Lehner, an economist in the Oregon Office of Economic Analysis. Josh uses Bureau of Labor Statistics employment data to track employment growth by size of metropolitan area. His analysis divides the nation into four groups: the 51 metropolitan areas of 1 million population or more, two groups of mid-sized and smaller metropolitan areas, and nonmetropolitan America.

The latest data show that, as a group, large metropolitan areas have dramatically out-performed the rest of the country in the last economic cycle (dating from the peak of the economy in December 2007). In the aggregate, metros with 1 million or more population have fully recovered the employment lost in the Great Recession, and grown to 6.6 percent above their pre-recession peak. As of September, 2016, smaller and mid-sized areas, collectively were about 2-3 percent above their 2007 peak level of employment. And non-metropolitan America is still 2.3 percent below where it was in 2007.

Here’s another way to think about this same data.  As of September 2016, total U.S. employment was up about 5.3 million jobs from the previous peak recorded in December 2007 (133.03 million jobs in 2007; 138.37 million jobs in 2016).  The fifty-one largest metropolitan areas recorded an increase of 4.66 million jobs between 2007 and 2016. Collectively, these big city metro’s accounted for about 87 percent of the net job growth nationally.

This time is different

What’s new and different here is that big city metros haven’t been the one’s that have driven US economic growth in previous cycles.  It’s usually the case that small and mid-sized metros, as a group, have grown faster than big city metros.  Using Josh’s data, we prepared a second chart, showing the growth in employment for large, middle-sized and small metros and non-metros, for the period 2002 through 2007. During that growth period, small and mid-sized metros decidedly out-performed larger metros in job growth.  The smallest metros grew their employment by 7.5 percent, mid-sized metros grew about 6.5 percent, and large metros grew about 5.5 percent.

As we’ve pointed out in our report, Surging City Center Job Growth, the last few years have witnessed a historic reversal in the patterns of job growth within large metropolitan areas. After decades of steady decentralization, employment growth in urban centers substantially outpaced that in more peripheral locations from 2007 through 2011. We think there’s strong evidence that this process is driven by employers looking to tap the growing labor market in city centers, which itself is a product of the movement of well-educated young adults back to cities (as we documented in Young and Restless).

All this evidence points to one thing: City centers are the big drivers of national economic growth. Big metros are significantly out-performing smaller metros, which in turn are out-performing rural areas. Within large metros, the decades-long pattern of job decentralization has reversed—and jobs are growing faster in city centers than in the metropolitan periphery. In this economic expansion, the nation’s economic growth is tied to the performance of its large metros and their robust city centers.

Many thanks to Josh Lehner for compiling this data and sharing it. Be sure to visit the Office of Economic Analysis blog for more detail, including a national map showing patterns of county-level job growth since 2007.

• Truck freight movement gets a subsidy of between $57 and $128 billion annually in the form of uncompensated social costs, over and above what trucks pay in taxes, according to the Congressional Budget Office.
• If trucking companies paid the full costs associated with moving truck freight, we’d have less road damage and congestion, fewer crashes, and more funding to pay for the transportation system.

What with all the speculation about a possible trillion dollar spending package for infrastructure, we’ve been hearing a lot about about crumbling bridges, structurally deficient roads, and the need for more highway capacity.

It’s clear that our transportation finance system is broken. To make up the deficit, politicians frequently call for increased user fees – through increased taxes on gasoline, vehicle miles traveled, or even bikes. All the while, one of the biggest users of the transportation network – the trucking industry – has been rolling down the highway fueled by billions in federal subsidies.

A 2015 report from the Congressional Budget Office estimates that truck freight causes more than $58 to $129 billion annually in damages and social costs in the form of wear and tear on the roads, crashes, congestion and pollution – an amount well above and beyond what trucking companies currently pay in taxes.

CBO doesn’t report that headline number, instead computing that the external social costs of truck freight on a “cents per ton mile basis” range between 2.62 and 5.86 cents per ton mile. For the average heavy truck, they estimate that the cost works out to about 21 to 46 cents per mile travelled.

That might not sound like a lot, but the nation’s 10.6 million trucks travel generate an estimated 2.2 trillion ton miles of travel per year (Table A-1, page 32). When you multiply the per ton mile cost of 2.52 to 5.86 cents per mile times 2.2 trillion ton-miles, you get an annual cost of between $57 and $128 billion per year.

Unfortunately, trucking companies don’t pay these costs. They are passed along to the rest of us in the form of damaged roads, crash costs, increased congestion and air pollution. Because they don’t pay the costs of these negative externalities, the firms that send goods by truck don’t have to consider them when deciding how and where to ship goods. This translates into a huge subsidy for the trucking industry of of between 21 and 46 cents per mile.

For comparison, CBO looked at the social costs associated with moving freight by rail. Railroads have much lower social costs, for two reasons: first, rail transport is much more energy efficient and less polluting per ton mile of travel; second, because railroads are built and maintained by their private owners, most of the cost of wear and tear is borne by private users, not the public. Railroad freight does produce social costs associated with pollution and crashes, but the social costs of moving freight by rail are about one-seventh that for truck movements: about 0.5 to 0.8 cents per ton mile, compared to 2.52 to 5.86 per ton mile for trucks.

As we always point out, getting the prices right – whether for parking or road use – is critically important to creating an efficient transportation system. When particular transportation system users don’t pay their full costs, demand is too high, and supply is too low.  In this case, large federal subsidies for trucking encourages too much freight to be moved by truck, worsening congestion, pollution and road wear, while the fees and taxes paid by trucking companies aren’t enough to cover these costs. The classic solution for these currently unpriced external costs is to impose an offsetting tax on trucks that makes truck freight bear the full cost associate with road use, crashes and environmental damage. The CBO report considers a number of policies that could “internalize” these external costs associated with trucking – including higher diesel taxes, a tax on truck VMT, and even a higher tax on truck tires.

The revenues produced would be considerable: a VMT tax that internalized social costs of trucking would generate an estimated $68 billion per year. To put that number in context, consider that in 2014, total public spending – federal, state and local – on roads and highways was $165 billion. In addition, the higher tax would reduce freight moving by road – mostly by shifting cargo to rail – and lead to benefits of lower pollution, less congestion and less wear and tear on roads. We’d also save energy: net diesel fuel consumption for freight transportation would fall by 670 million gallons per year – a savings of about $2 billion annually at current prices.

There are good reasons to believe that the CBO report is conservative, and if anything, understates the social costs associated with trucking. For example, the report estimates that social costs associated with carbon emissions at somewhere between $5 and $45 per ton. Other credible estimates – from British economist Nicholas Stern – suggest that the cost today is about $32 to $103 per ton, rising to $82 to 260 per ton over the next two decades.

The external social costs of truck and rail freight, per ton mile, are estimated as follows:

Such a tax would make truck freight more expensive, but other costs – now borne by the rest of us – would go down by a comparable amount. And there would be important savings in costs for freight either moved by other modes (especially rail, which is about two-thirds cheaper), or sourced from closer locations.

There’s a clear lesson here: It may seem like we have a shortage of infrastructure, or lack the funding to pay for the transportation system, but the fact that truck freight is so heavily subsidized means that there’s a lot more demand (and congestion) on the the roads that there would be if trucks actually paid their way. On top of that, there’d be a lot more money to cover the cost of the system we already have.

So the next time someone laments the sad state of the road system, or wonders why we can’t afford more investment, you might want to point out some 18-wheelers who are now getting a one heck of a free ride, at everyone’s expense.

View the full report: “Pricing Freight Transport to Account for External Costs: Working Paper 2015-03“