ACCESS goes digital.

After publishing paper copies since its founding in 1992, and also publishing online since 1998, ACCESS will become entirely digital starting with this issue. Changes in readership have led to this change in format. During the past year, ACCESS had 191,000 page views from 122,000 readers in 70 countries, so we are eliminating the cost of paper and following our readers to where we now find them.

The goal of ACCESS remains the same: to make transportation research useful for policymakers and practitioners. After transportation scholars have published policy-relevant research in an academic journal, we invite them to prepare shorter and more readable versions for ACCESS, which has the luxury of stressing readability because a journal has already stressed rigor. Anyone who wants greater depth or more detail can refer to the original journal article. ACCESS can thus present scientific research in plain, intelligent, and even lively prose. Condensing a journal article for publication in ACCESS can catapult academic research into the public debate and help convert knowledge into action.

Easy reading is hard writing, both for authors and editors. In the editing we rely greatly on the contributions of graduate students who spend many hours helping our authors say what they mean. This year we are grateful to Sam Blake, Katherine Bridges, Lily Brown, Timothy Douglas, Jordan Fraade, David Leipziger, Rosemary McCarron, Taner Osman, Heidi Schultheis, Ryan Sclar, Qi Song, Jacqueline Su, Ryan Taylor-Gratzer, and Gus Wendel. It has been a great pleasure to work with them.

I am especially grateful to John Mathews, our Managing Editor for the past seven years. John has been both a great manager and a great editor. He is largely responsible for the growing online prominence of ACCESS, and for the many awards we have received, including the American Planning Association’s highest honor for a publication, the National Excellence Award for Communications Initiative.

I also want to thank Madeline Brozen for managing the publication of this first all-digital issue of ACCESS. She has been wonderful to work with and has set a high standard for the future.

Finally, I would like to thank both the California and the United States Departments of Transportation for providing the funds necessary to publish ACCESS. Their support has enabled our authors to take the vital last step in transportation research: make the results useful to public decision makers.

Donald Shoup
Editor of ACCESS

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Public transit receives a large share of transportation funds but accounts for only 1 percent of passenger miles traveled nationwide. Nevertheless, public transit subsidies remain popular in many areas. For example, in 2008, 67 percent of Los Angeles County voters approved a half-cent sales tax to raise $26 billion for transit over 30 years.

Why does the public support transit subsidies if so few voters are frequent riders? The simplest explanation is the promise of congestion relief: commuters expect to benefit from reduced congestion even if they rarely use public transit themselves. A large body of transportation and economic research, however, concludes that public transit has little effect on reducing congestion.

An important detail that has received little attention is that commuters on different roadways in the same metropolitan area face sharply differing levels of congestion depending upon the time and location traveled. Therefore, determining which drivers are willing to ride public transit is essential in determining transit’s impact on congestion. Travel-time costs dominate most commuters’ choice between transit and driving.

Intuition suggests — and studies confirm — that transit is most attractive to commuters who face the worst congestion. Thus a high number of transit riders are commuters who would otherwise have driven on the most congested roads at the most congested times. Reducing the number of commuters driving on heavily trafficked roads can greatly reduce congestion even if these drivers represent only a modest fraction of total commuters.

Reducing the number of commuters driving on heavily trafficked roads can greatly reduce congestion even if these drivers represent only a modest fraction of total commuters.

The Effects of a Transit Shutdown

To determine whether public transit can greatly reduce traffic congestion, I collected data on freeway speeds during a strike by Los Angeles County Metropolitan Transportation Authority (Metro) workers. The strike caused an abrupt shutdown of the LA transit system, halting both buses and rail service. I then tested the prediction that transit greatly reduces congestion.

The first step in this research was to quantify the effects of the shutdown, and then to calculate the congestion relief benefits that the LA transit system yields. The estimated benefit of congestion relief is between $1.20 and $4.10 per peak-hour transit passenger-mile, or over $1 billion per year.

Metro provides heavy rail (subway), light rail, and bus service for approximately 10 million people in a service area of approximately 1,400 square miles. In October 2003, Metro workers began a strike that shut down bus and rail service for 35 days. I gathered hourly speed data from before, during, and after the strike from 640 vehicle detectors across major Los Angeles freeways. I then used a regression model that controls for additional factors that might affect congestion over the sample period. This isolated the traffic congestion associated with the strike itself.

Figure 1 plots the average delay by week across all major freeways for a 28-week period before, during, and after the strike. Delay is measured in minutes per mile relative to a free-flow speed of 60 mph; one minute of delay, for example, corresponds to a speed of 30 mph since it takes two minutes, instead of one, to traverse one mile. Delay is measured during peak periods (weekdays from 7 am to 10 am, and 2 pm to 8 pm) when most congestion occurs. The two vertical dashed lines in the figure indicate the beginning and the end of the strike.

In the 12 weeks leading up to the strike, travel delay averaged around 0.4 minutes per mile. When the strike began, average delay jumped to 0.6 minutes per mile, an increase of 46 percent. Travel delay continued to increase as the strike persisted, suggesting that the impacts were not confined to the initial week of the strike. Delays fell following the strike, but took several weeks to return to pre-strike levels.

Several reasons explain the gradual ebb in delay. First, service was slowly phased back in over the first week following the strike. Second, the week of Thanksgiving—which occurred two weeks after the strike ended—tends to have higher-than-average delays. Finally, commuters may have taken some time to return to their original travel patterns following the strike.

I expected the largest increases in congestion to occur on freeways that parallel busy transit lines, since commuters will likely move to the closest highway in the event of a transit shutdown. Figure 2 plots the average delay on US-101, which parallels the Metro Red Line subway (the line with the highest ridership in Metro’s system). Figure 3 plots the average delay on Interstate 105, which parallels the Green Line light rail (the fourth-busiest Metro line). In both cases, an impressive and sustained increase in average delay occurred after the strike began.

Could the sharp increases in congestion observed at the strike’s start be due to other unobserved factors? This seems very unlikely. One possibility is that, in order to maximize the strike’s perceived impact, the transit workers’ union timed it to begin on days when they knew traffic would be bad. However, the strike’s timing was determined not by the union, but by the judiciary: it occurred on the first business day following the expiration of a 60-day court-ordered injunction on striking.

It is possible that important events affecting traffic congestion might correlate with the strike’s beginning simply by chance. For example, the strike began following a three-day holiday (Columbus Day weekend). To rule out bias in the results, I conducted two tests. First, I estimated the strike’s effect on traffic in neighboring Orange and Ventura Counties. Portions of these counties lie within LA Metro’s jurisdiction, but neither is served by Metro; thus both should be unaffected by the strike. The second test examined delays on LA freeways one year after the strike. If seasonal effects drive the results, then similar results should appear a year later. In both tests I found no effects on traffic congestion, which strongly suggests that the strike, not chance, caused the increased delays.

Transit’s Congestion Relief Benefits

How large are the congestion-relief benefits of public transit during peak hours? I calculated the potential benefits under two scenarios. The first scenario focuses on the reduction in freeway delays. In Los Angeles, people drive 36 billion miles on the freeways each year during peak hours. An increase of 0.19 minutes of delay per mile traveled—the average increase in delay observed during the 2003 Metro strike—translates to an increase of 114 million hours of delay per year. If time is valued at half the average hourly wage, or $10.30 for Los Angeles County, transit yields an annual congestion-relief benefit of $1.2 billion per year. Previous research has found, however, that motorists place a higher cost on time spent stuck in traffic than on time spent driving on uncongested roads. If driving in congestion adds 80 percent to the time cost of travel, a factor in line with previous studies, the congestion-relief benefit becomes $2.1 billion per year.

In the second scenario, I assumed that eliminating transit service increased delays on arterial roads by the same amount that it increases delays on freeways. There are strong reasons to believe that congestion on arterial roads increased as much as, or more than, congestion on freeways. In particular, ramp meters restrict vehicle flows onto Los Angeles freeways and thus act as a barrier to additional congestion, but they are not used on arterial roads. If we assume that arterial road delays increased by the same amount as freeway delays, the congestion-relief benefit of transit is then $2.3 billion per year for both freeways and arterial roads during peak hours. This amount comes from valuing time at half the hourly wage. When factoring in the higher time cost of driving in congested traffic, the congestion-relief benefit is $4.1 billion.

Metro carried approximately one billion passenger-miles during peak hours in 2003. The congestion-relief benefit per transit-passenger mile is between $1.20 and $4.10 during peak hours, depending on assumptions about the value of time and the level of congestion on arterial roads. I also estimate that average consumer surplus — the value to the rider who chooses to take transit instead of driving — is about $0.24 per mile for rail passengers and $0.11 per mile for bus passengers. Comparing the $1.20–$4.10 benefit per passenger mile for congestion relief to the $0.11–$0.24 consumer surplus per mile for transit riders suggests that freeway congestion-relief benefits are much larger than the private benefits gained by transit riders.

Long-Run Effects

A key issue in calculating transit’s benefits is that, when faced with an extended shutdown, individuals may adapt to increased traffic congestion by using strategies that are not feasible in the short term. Indeed, the “fundamental law of road congestion” implies that in the long run, individuals respond to increases in congestion by reducing travel, ultimately leaving congestion unchanged. The congestion caused by a long-term public-transit shutdown is likely different from the short-term effects of a temporary shutdown. Potential long-term travel adaptations that may not be available in the short run include telecommuting, ride sharing, changes in work schedules, moving closer to work or school, and moving out of the metropolitan area. The first three represent reductions in travel demand, while the last two represent a relocation of travel demand.

If the transit system were to shut down permanently, would enough commuters change their behavior to reduce congestion to pre-shutdown levels? A simple travel supply-demand model suggests that the response of travel demand to congestion would need to be implausibly large to return congestion to near pre-shutdown levels. Estimates from natural experiments, such as London’s congestion charge and sharp increases in gasoline prices, suggest that travelers do respond to increased costs by reducing travel. Their responses, however, would not be nearly enough to bring congestion back to its pre-shutdown level. Ultimately, the congestion-relief benefits of transit in the LA metro area are $1 billion per year or more. Contrary to conventional wisdom, the total benefits of building and operating the Metro rail system around 2003 likely exceeded the costs.

Limitations

Though this analysis presents strong evidence that transit systems play an important role in reducing peak-hour congestion, several limitations are worth noting. First, it is difficult to fully anticipate what types of long-term changes in travel behavior might occur if the transit system were shut down permanently. Fundamentally, rail lines and busways transport passengers at high capacity. During their peak hours, the Metro Red and Blue lines carry as many passengers as congested 12- and eight-lane freeways respectively, at substantially lower capital costs. In the long run, this high capacity affects urban densities, employment locations, and even work hours. Valuing the economic gains of coordination in space or time is beyond the scope of this study.

A second limitation to this study is that, because the entire transit system shut down, the results do not reveal the effects of marginal changes in the transit network, such as a subway line extension. Likewise, they cannot reveal the optimal mix of service (e.g., whether a particular route should be served by light rail or bus rapid transit).

A final caveat is that the “optimal” solution of congestion pricing is assumed to be politically infeasible. With optimal congestion pricing, there would be no congestion and thus no congestion-relief externality, and the benefits of transit service could be evaluated on more conventional grounds.

Does Transit Make Economic Sense?

I would argue that in many cases, yes. The median urban voter clearly believes that transit delivers significant benefits, as evidenced by the continued funding of most transit systems. Nevertheless, it has proven surprisingly difficult to establish transit’s benefits using conventional transportation models. In this study I reconcile this paradox by noting that many commuters who choose to ride transit are not distributed at random, but instead come from the most congested roads at the most congested times. Removing them from the road thus generates a large reduction in congestion. Detailed freeway speed data during a five-week shutdown of the LA transit system confirms this prediction.

At a minimum, these results establish the importance of transit in Los Angeles, which many consider the quintessential car-centric city. They also suggest that public transit greatly reduces congestion in other large cities. The per-capita transit ridership and congestion levels in Los Angeles are roughly equivalent to those in other large urban areas, such as Chicago, San Francisco, Houston, and Washington, DC. Nationwide, public transit surely provides many billions of dollars worth of congestion relief.

The article is adapted from “Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion,” American Economic Review (2014)104: 2763-2796.

Further Reading

Yihsu Chen and Alexander Whalley. 2012. “Green Infrastructure: The Effects of Urban Rail Transit on Air Quality,” American Economic Journal: Economic Policy 3(4): 58–97.

Pierre-Philippe Combes, Gilles Duranton, Laurent Gobillon, and Sébastien. 2010. “Estimating Agglomeration Economies with History, Geology, and Worker Effects,” Agglomeration Economics, Edited by Glaeser, Edward. University of Chicago Press, 15–65.

Gilles Duranton and Matthew A. Turner. 2011. “The Fundamental Law of Road Congestion: Evidence from US Cities,” American Economic Review 101(6): 2616–52.

Ian W.H. Parry and Kenneth A. Small. 2009. “Should Urban Transit Subsidies Be Reduced?” The American Economic Review 99(3): 700–724.

David Schrank, Tim Lomax, and Bill Eisele. 2012. 2012 Urban Mobility Report, Texas Transportation Institute. http://mobility.tamu.edu.

Clifford Winston and Vikram Maheshri. 2007. “On the Social Desirability of Urban Rail Transit Systems,” Journal of Urban Economics 62(2): 362–82.

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C.J. Gabbe, Santa Clara University and Greg Pierce, University of California, Los Angeles

Urban renters in the US face fast-rising housing prices, especially in coastal metropolitan areas. Price increases are in part due to restrictive land-use regulations. Minimum off-street parking requirements, a central component of land-use regulation in the US, warrant detailed study and policy reform. In most cities today, municipal regulation requires developers to provide on-site parking. Renters or buyers then pay for this parking as part of their monthly rent or purchase price; the price of parking is thus “bundled” with the price of the housing unit. While many households might have chosen to pay for on-site parking in a free market, this proportion is surely lower than what has been mandated. Moreover, the historical effect of minimums and bundled parking hides a transportation cost burden in housing prices, leaving households unable to choose. Minimum parking requirements force developers to build costly parking spaces that drive up the price of housing. Urban policymakers have recently taken an interest in reforming parking regulations and allowing unbundled parking based on social equity and environmental sustainability rationales.

In our research, we ask: What are the effects of parking provision on residential rents in America’s cities? We find that the cost of bundled garage parking for renters is approximately $1,700 per year, and the bundling of a garage space adds about 17 percent to a unit’s rent. There are about 708,000 households without a car who have a garage parking space. We estimate that these households’ payments for parking represent a direct deadweight loss to society (a measure of the large-scale inefficiency associated with minimum parking requirements) of approximately $440 million per year. We argue that this figure represents just the tip of the iceberg when considering the indirect cost of minimum parking requirements. We conclude by suggesting two types of local land-use regulatory changes to reduce the high cost burden of parking: (1) cities should reduce or eliminate minimum parking requirements, and (2) cities should allow or encourage developers and landlords to offer unbundled parking options.

Parking Regulation and Housing Prices

Parking regulations limit housing supply, and increase housing prices, by (1) reducing density, and (2) imposing costly standards on developers. Minimum parking standards reduce density when land that would otherwise be devoted to buildings is instead used for car storage. This makes some infill development physically and/or financially infeasible. Minimum parking requirements can also be very costly to real estate developers. Along with the opportunity cost of devoting space to parking rather than another use, there is a high direct cost of building new parking. Nationally, in 2012, the average cost to build one underground parking space was $34,000 and to build an aboveground parking space was $24,000. These costs are ultimately passed on to the consumer whether they have a car or not.

Several city-specific studies estimate the effect of parking provision on housing costs. In a 1999 study, Jia and Wachs found the average single-family unit in San Francisco with off-street parking sold for 12 percent more and the average condo unit with off-street parking sold for 13 percent more than the price of comparable units without parking. In a 2013 study, Manville analyzed a sample of buildings in downtown Los Angeles that had been converted to housing after the city passed its Adaptive Reuse Ordinance. He found that bundled parking raised the rent for an apartment by about $200 per month and raised the price of a condo by about $43,000. These articles provide preliminary evidence regarding the effect of bundled parking on housing prices, but are limited to select neighborhoods within California cities. Building on these studies, we assess how parking affects housing prices among a national sample of housing units.

Using the American Housing Survey to Study the Cost Of Parking               

We use data from the 2011 American Housing Survey (AHS), conducted biennially by the US Census Bureau. We concentrate on renters in urban areas because these households are experiencing the worst — and worsening — housing cost burdens. We focus specifically on garage parking because it is the most expensive type of parking to construct and the most prevalent form of parking in central, transit-oriented neighborhoods. Our modeling approach — called hedonic regression — is based on the idea that the price of a house or apartment is a function of its attributes, including building, neighborhood, and locational characteristics. The availability of on-site garage parking is one factor in a household’s housing purchase or rental decision, and is the focus on our study.

Bundled Parking and Renters Without Vehicles        

A large majority (83 percent) of rental housing units in American metropolitan areas included some kind of parking on site. About 38 percent of rental units had garage parking, while 45 percent had surface or other non-garage parking spaces. About 17 percent did not have a parking space, but this varied dramatically by metropolitan area. The New York City area had the highest prevalence of units without parking (73 percent), contrasting sharply with Orange County, California at the other extreme (1 percent). Across metros, approximately 3.5 million rental units did not include parking. These units tended to be smaller, older, and with fewer in-unit amenities than units with bundled parking.

Most American households have at least one automobile; census data show that nationwide only about 7 percent of rental households do not have a car. As with bundled parking, there is considerable variation in the share of households without a vehicle across metros, from 26 percent in metropolitan New York City to 1.5 percent in the St. George, Utah, metropolitan area. Across the entire 2011 AHS sample — which includes renter and owner-occupied units — more than 71 percent of carless households live in a housing unit with a bundled parking space, as opposed to more than 96 percent of households with a vehicle. Within our sample of renter-occupied units, these percentages are 73 percent and 93 percent, respectively. Quantifying the relationship between vehicle ownership and parking is important because carless households are paying for something that they most likely do not need or want.

Isolating the Price of a Parking Space

We use a hedonic regression modeling approach and find that a bundled parking garage spot costs about $1,700 per year, or $142 per month. Thought of another way, including garage parking increases the rent of a housing unit by around 17 percent. While these figures were averages for all rental households, we hypothesized that carless renters might place a lower value on parking availability. The data support this hypothesis. For carless renters, bundled garage parking costs an average of $621 a year — a 13 percent premium on their rental price. We calculate the deadweight loss to society stemming from garage parking provided by landlords to residents of 708,000 housing units who do not own a car. At a national level, this deadweight loss amounts to $440 million paid for garage parking spaces unused by residents for parking annually. This amount represents only the direct cost of parking requirements on low-income renters and does not account for the many indirect costs of parking provision.

Discussion

Our results support the economic logic that an apartment with garage parking, with other conditions remaining the same, will be more expensive than one with surface parking or no parking. On the demand side, garage parking spaces are an important amenity for many urban renters. Garage parking is particularly valuable in higher-density urban neighborhoods where on-street parking is metered or difficult to procure. Carless households and households who do not use their garage for automobile parking may still gain some utility from a garage by using it for storage or even additional living space. This would be more likely for households with a private one- or two-car garage, rather than a household with a designated space in a shared parking structure or underground parking garage.

On the supply side, the direct and indirect costs of parking provision are high, and these costs are passed on to renters. Garage parking is expensive to build and its provision often represents a substantial opportunity cost for a real estate developer, particularly when land area is devoted to parking rather than leasable residential or commercial space. We show that these direct and indirect costs are passed on to consumers in the form of higher rents.

The provision of parking supply without associated demand can only be characterized as wasteful. Minimum parking requirements create a major equity problem for carless households, illustrated by the large deadweight loss ($440 million per year) associated with renters paying for garage parking that they do not use for car storage. Given that the carless population in the US is generally made up of lower-income households, many of the households involuntarily paying for garage parking are the ones that can least afford to do so. In fact, we find the average income of households with a garage space but no car ($24,000) is only slightly more than half the income of other households ($44,000). In the absence of paying for an unused parking space, these rent outlays could be applied to renting a larger or better-located unit, other consumer spending, or saving for a home purchase.

Minimum parking requirements create a major equity problem for carless households, illustrated by the large deadweight loss ($440 million per year) associated with renters paying for garage parking that they do not use for car storage.

We recommend that cities should reduce or eliminate minimum parking requirements in urban areas. Even if cities reduce parking requirements, as some have recently done, the housing supply takes years to adjust. It would likely be a decade or two before consumers could choose from many housing options with unbundled parking. Reducing or eliminating minimum parking requirements would have the biggest benefits to renters in higher-density, centrally located neighborhoods where garage parking is prevalent.

We also recommend that cities allow or encourage real estate developers to unbundle parking from new housing. This recommendation depends on reform of minimum parking standards. If minimum parking standards are not reduced or eliminated, a developer would have little or no incentive to unbundle parking because there would be an oversupply of parking that could not be rented, and a developer would essentially pay for this. A combination of these policies will allow developers to build housing with less parking and then to use pricing to allocate the parking spaces they construct as they see fit.

Conclusion

Our findings provide the first nationally representative evidence that urban garage parking provision is costly to renters. We provide further evidence that minimum parking requirements are burdensome to renters and lead to societal waste. Carless households, many of whom have low incomes, are disproportionately affected in neighborhoods and cities where garage parking is the norm. Eliminating minimum parking requirements in these locations will allow the market to gradually meet the latent demand for housing options with unbundled parking. Additionally, it will reduce the annual $440 million deadweight loss directly experienced by urban renters without cars. In short, the elimination of minimum parking requirements will help remedy the perverse incentive for driving and discourage the sprawling urban form that these requirements have encouraged over the past 75 years.

This article is adapted from “Hidden Costs and Deadweight Losses: Bundled Parking and Residential Rents in the Metropolitan United States,” Housing Policy Debate (2017) 27: 219-229.

References And Further Reading

Wenyu Jia and Martin Wachs. 1999. “Parking Requirements and Housing Affordability: A Case Study of San Francisco.” Transportation Research Record 1685: 156–60.

Manville, Michael. 2013. “Parking Requirements and Housing Development.” Journal of the American Planning Association 79 (1): 49–66.

Donald Shoup. 2014. “The High Cost of Minimum Parking Requirements,” in Parking Issues and Policies, edited by Stephen Ison and Corinne Mulley. Bingley, UK: Emerald Group Publishing, 87–113.

Donald Shoup. 2011. The High Cost of Free Parking. Revised edition. Chicago: Planners Press.

Suggested citation for this article

Gabbe, C. J., & Pierce, G. (2017). The hidden cost of bundled parking. Access, 51(Spring). Retrieved from http://www.accessmagazine.org/spring-2017/the-hidden-cost-of-bundled-parking/

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Okay, the title of this article is a bit tongue-in-cheek, but travel does involve considerable costs. The average household spends about $8,500 per year on transportation, making it one of our biggest expenditures. Time is another cost of travel, because the roughly hour and ten minutes American adults spend traveling each day might be better spent on things like work, family, and even sleep. Travel can also be tiring, stressful, dangerous, and more.

So why do we travel so much? Transportation academics have made the obvious assumption that we travel to reach destinations. They view travel as a “derived demand;” we don’t do it for the love of travel itself, but because of the benefits we reap at our destinations. Thus, it is commonly assumed that individuals minimize their travel, so long as they get to the places they need to go.

But is traveling really so bad? Some researchers have concluded that travel might have benefits excluding the obvious one of getting you to places. At least in some ways, travel can be fun. Travel can involve adventure and novelty; it can give your life a refreshing breath of air. Travel may give us a satisfying sense of autonomy and the enjoyable feeling of mastering our surroundings, and can even promote feelings of social status. Operating a vehicle can make us feel like we are in control and accomplishing a challenging task. It can be a thrill to move at high speeds. Looking at the passing scenery can be aesthetically enjoyable. Many people report that travel is a valued “down time” when they are free from the stresses of work, school, and family life. We can also multitask and do enjoyable things when we travel, like listening to music and talking on the phone.

Many people report that travel is a valued “down time” when they are free from the stresses of work, school, and family life.

And there are many forms of travel that people devote lots of time and money to do purely for fun — from skiing to riding roller coasters to sailing, hiking, and biking. Surely traveling to the grocery store isn’t as fun as kayaking down rapids, but maybe there are at least some aspects of recreational travel that we also experience during more mundane, day-to-day trips.

Surveys confirm that travel might not be all bad. Thirty-two percent of respondents in one survey reported they enjoy travel (Ory and Mokhtarian), with only 13 percent saying they dislike it (the rest were neutral). Nearly 70 percent disagreed with the statement that “the only good thing about traveling is arriving at your destination.” Only 20 percent disagreed with the statement that “getting there is half the fun.”

The same survey found that trip purpose matters. Trips to pleasant destinations such as entertainment, social activities, and recreation seem more pleasant than trips to mundane places like work or school.

Mode of Travel

The mode of travel is also important. Two-thirds of respondents said they enjoy biking and walking, and most people said they wished they traveled more by these modes. Auto travel is also generally well-regarded, with 58 percent liking it and less than 12 percent disliking it. Transit, however, fared less well. Only 31 percent said they liked train/subway/light rail travel, with an almost equal number saying they dislike it. And only 8 percent expressed a positive opinion about taking the bus, with a whopping 63 percent responding negatively. Granted, this simple survey data doesn’t take personal characteristics into account or involve any math, but simple descriptive statistics can tell us a lot, particularly with results as striking as these.

To explore this further, Erick Guerra of the University of Pennsylvania and I examined people’s moods while they travel. We used data from the American Time Use Survey (ATUS), which studies what activities people do in a day, how long they do them for, whom they do them with, and where they do them. Travel is one such activity, which is further broken down by mode and trip purpose. Moreover, in 2011 the ATUS selected three activities per person and asked respondents about the intensity with which they felt certain emotions during them. The emotions the survey asked about were happiness, sadness, stress, fatigue, pain, and whether they found the activity meaningful.

We examined these emotions individually, and also used two different techniques to construct a composite “mood” variable to reflect people’s overall frame of mind. We had more than 13,000 people in our sample who reported on over 39,000 activities. The sample is representative of the entire US adult population.

We used two different modeling techniques. One was ordinary least squares (OLS) regression. Broadly, this tells us if travelers as a group are in a good mood compared to those doing other activities, while holding basic demographic characteristics constant. The other technique was fixed-effects panel regression. This takes advantage of the fact that we have three observations per individual, so for each person who traveled we can see how they were feeling while they were traveling compared with how they were feeling while doing two other things. This is very useful because some people tend to be in better moods in general than others, and a fixed-effects panel allowed us to control for innate mood as well as other individual traits.

The results indicated that the activities people do, like traveling, influence their mood to a perhaps-surprisingly small extent. Our OLS models, which contain all of the demographic variables typically found in social science models (like gender, age, race and income), as well as activity type, only explain about 14 percent of respondents’ moods. Other factors, like people’s basic tendency to feel a certain way, or things that could have affected them during their day, explained much more.

That said, we find that travel is not associated with complete misery. In fact, according to our results, it is a roughly “medium-mood” activity. Travel is associated with a less-positive mood than socializing, volunteering, eating and drinking, or participating in religious activities. But it is associated with more happiness than “poor-mood” activities such as work or household chores. So, there must be some benefits of travel that offset its admitted costs.

Our OLS model shows that travelers are in a somewhat better mood than people who aren’t traveling, but the panel model shows that people are in about the same mood when they are traveling as when they are participating in other activities. This suggests that intrinsically happier people are more likely to travel than others.

The fact that travel must, at least in some ways, be fun has some interesting implications. Perhaps getting to a destination is not the sole reason we undertake many trips. It may be that travel is motivated, at least in part, by a desire to travel for travel’s own sake. In some cases it may be possible that the out-of-home activity is motivated by the desire to travel rather than vice versa. Haven’t you found yourself on some Saturday nights deciding you wanted to go somewhere, and then figuring out where that somewhere will be?

Bicycling

The happiest mode of travel appears to be bicycling. Even after excluding those who bike purely for recreational purposes, bicyclists are in a significantly more positive mood than other travelers such as bus riders or walkers. Given that biking is healthy, eco-friendly, inexpensive, and enjoyable, it makes sense to consider measures like bike lanes to encourage bike riding.

Even after excluding those who bike purely for recreational purposes, bicyclists are in a significantly more positive mood than other travelers such as bus riders or walkers. Given that biking is healthy, eco-friendly, inexpensive, and enjoyable, it makes sense to consider measures like bike lanes to encourage bike riding.

Walking

Walkers, however, are not in a particularly good mood. (Again, we excluded people who walk for recreation or exercise.) We suspect our finding masks the fact that there are many types of walking trips, some more pleasant than others. For those who lack access to an automobile and walk from necessity, long distances, inclement weather, heavy burdens, or unsafe neighborhoods might make walking trips an unhappy experience. Those who do have choices, and walk only when they prefer it to other modes, may enjoy it more.

Transit

Broadly speaking, our findings suggest that transit is not a particularly happy travel mode. Train/subway/light rail travel fared the most poorly in our OLS models, and bus travel was associated with the worst mood in our panel regression. Why is this the case? Prior scholars and commonsense suggest two major sets of reasons.

First is the feeling that transit travel involves surrendering control. Not only is the rider at the mercy of the transit schedule, but the vehicle’s route might also be indirect and circuitous, and the stops might not be close to the traveler’s destination. Furthermore, the traveler has no control over whether the vehicle is on time or whether a seat will be available. Transit travelers have to cede some control over their personal space, and may not particularly like the people sitting or standing close to them.

The other major set of reasons might be grouped as “discomfort.” In addition to sometimes having to stand on a crowded vehicle, transit travelers might be exposed to bad weather walking to or waiting at stops. The climate control in the vehicle might not be satisfactory, or other passengers’ cell phone conversations might be a nuisance. Discomfort may be psychological as well. Transit travelers might be stressed about when their vehicle might arrive and whether they will get to their destination on time. Also, they might feel stigma and shame about taking modes that are generally associated with lower social status than traveling by private car.

All of this doesn’t necessarily mean we should give up on transit, which, in the right places and at the right times, has the potential to reduce auto congestion, help the environment, and allow the dense concentrations of people that make cities thrive. But these findings do help explain why few Americans choose to ride transit, and suggest that we may need to adopt new strategies to attract more riders.

Typically, we think about improving transit by adding service, building new infrastructure, increasing vehicle frequencies, and increasing travel speeds to make service more convenient and competitive with cars. Without a doubt, these are key pieces of the puzzle. But we also need to focus on what makes transit travel, at least for many people, not fun.

We also need to focus on what makes transit travel, at least for many people, not fun.

There are cost-effective measures that can address transit’s psychological burdens. Examples include electronic signage indicating arrival times, or mobile applications that show where the vehicles are and when they will arrive. In most cases, these aids will not change travel plans, or get people to destinations any faster, but at least they will reduce the stress and uncertainty of waiting for a vehicle.

Cars

Finally, we find that auto travel is associated with being in a relatively good mood; the American “love affair” with the car seems to be going strong. One noteworthy finding is that, when we control for the fact that car passengers are more likely to be interacting with another person and that such interactions are quite pleasant, car drivers and passengers are in roughly similar moods. This suggests that driving might not be the chore it is commonly assumed to be, and people might not be as happy to adopt autonomous vehicles as many enthusiasts believe.

Duration and Life Satisfaction

In other research, Eric Guerra and I examined the association between trip duration and mode. We reached the conclusion that longer trips are associated with a significantly worse mood than shorter trips, which might seem self-evident to anybody who has ever been stuck in traffic or taken a long road trip with antsy children in the back seat shouting “Are we there yet!?” Heightened fatigue, pain, and stress account for this drop in mood. These findings imply that efforts to fight congestion may have emotional merits. Another implication is that changing land uses to move origins and destinations closer together might have emotional benefits. Some, however, argue that such strategies might actually increase travel times, because even though distances may be shorter, higher densities might concentrate traffic and produce more congestion.

In other research I have looked for associations between time spent traveling and life satisfaction. On the day of the study, those who traveled more reported being significantly more satisfied with their lives, if only modestly so. This holds true even when people spent the same amount of time at their destinations. This means if two people spend the same amount of time at destinations outside their homes, the one who spends more time getting to that destination is predicted to be somewhat happier. Given my finding that longer trips are associated with worse mood, this is somewhat counterintuitive. Perhaps spending more time traveling pays off because, despite the fact that long trips aren’t pleasurable, they get us to better activities.

Mode choice is also associated with life satisfaction. Bicycling is again the mode most strongly associated with happiness; each minute of biking is associated with 13 times more additional life satisfaction compared to the amount of additional life satisfaction associated with each minute spent in a car. In addition, time spent walking is strongly associated with life satisfaction. Interestingly, travel time is more strongly associated with life satisfaction in small cities rather than in very large cities, perhaps because the latter are more likely to feature heavy traffic congestion and/or greater distances between activity sites.

Conclusion

The problem is that I can only show associations between life satisfaction and travel; showing causation is a lot more complex. The link between travel and happiness almost certainly comes in part because travel enables us to reach destinations — life can’t possibly be good if a lack of transportation prevents us from working or getting to the grocery store. But the link may also come because travel itself is fun, or because people who are happier in the first place may be more likely to travel. My research suggests that all three of these explanations are true; future research should focus on untangling just how strong each of these effects might be.

It’s easy to get depressed about transportation given all of its social costs: congestion, pollution, crash injuries, and more. But we often forget about travel’s private benefits. It’s hard to explain why people are spending so much time and money on something if it’s not doing them a lot of good. No, travel isn’t so bad — though that’s no reason we should stop trying to make it better.

No, travel isn’t so bad — though that’s no reason we should stop trying to make it better.

References and Further Reading

Eric A. Morris. 2015. “Should We All Just Stay Home? Travel, Out-of-home Activities, and Life Satisfaction. Transportation Research Part A: Policy and Practice, 78: 519-536.

Eric A. Morris and Erick Guerra. 2015. “Are We There Yet? Trip Duration and Mood During Travel. Transportation Research Part F: Traffic Psychology and Behavior, 33: 38-47.

Eric A. Morris and Erick Guerra. 2015. “Mood and Mode: Does How We Travel Influence How We Feel? Transportation, 42(1): 25-43.

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App-based, on-demand ride services—also known as Transportation Network Companies (TNCs)—have grown rapidly in recent years and caused debate in the passenger transportation industry. Advances in information and communication technology have enabled these services to provide a wide variety of real-time and demand-responsive trips. Companies such as Lyft, Uber, and Sidecar (now defunct) have developed smartphone apps whereby passengers can “source” a ride from a private passenger vehicle driven by a non-commercially licensed driver (usually). These apps communicate the passenger’s location to the driver via GPS and charge a distance-based fare. The driver is paid approximately 80 percent of the fare; the company keeps the rest. Many of these apps maintain a rating system that allows drivers and passengers to rate each other after the trip is completed. A passenger’s credit card information can be saved within the system to facilitate future trips.

Many terms have been used to characterize these app-based, on-demand ride services, but there has been little consensus on terminology. The California Public Utilities Commission (CPUC) was among the first to name these services Transportation Network Companies. CPUC has regulatory authority over TNCs to protect public safety in the State. Other names include ride-booking or ride-hailing and even ridesharing. Although ridesharing is used colloquially, the term has sparked controversy and confusion. The emerging app-based services have fundamental differences from traditional ridesharing (the grouping of travelers into common trips by car or van, whereby the driver has a common origin and/or destination with the passengers). To dispel this misunderstanding, we use the term ridesourcing to convey the essential technology—a platform used to “source” rides from a driver pool. Thus, we refer to these services as ridesourcing.

The Debate Over Ridesourcing

Ridesourcing has its roots in ridesharing and exhibits traits of traditional taxis. In some ways, ridesourcing may become more similar to ridesharing by allowing unrelated passengers to share a ride. However, in comparison to ridesharing, ridesourcing drivers typically do not share a destination with passengers. Instead, the driver’s motivation is income. To some, ridesourcing more closely resembles a taxi in that a driver offers a ride in exchange for a fare. Further blurring definitions, taxi companies are increasingly adopting app-based dispatch services known as e-Hail, and ridesourcing companies are launching services that more closely resemble ridesharing or microtransit (privately owned and operated shared transportation services with fixed, on-demand schedules, or both). Thus, complete characterization of ridesourcing is difficult because the services are quickly evolving.

Supporters view ridesourcing as an alternative to driving alone and as part of a suite of shared mobility options that serve previously unmet demand for fast, flexible, and convenient mobility in urban areas. Ridesourcing services have directly challenged existing regulations and practices that have over the years shaped the taxi industry, raising questions about appropriate regulatory and public policy responses. Moreover, critics argue that ridesourcing services compete with public transit, increase congestion during peak periods, mislead consumers through opaque pricing practices, and endanger public safety. As city leaders revise policies on ridesourcing services, there is an urgent need for independent analysis of their mobility and environmental impacts.

We studied ridesourcing’s role in urban transportation through an intercept survey of users in San Francisco. The findings provide an initial picture of the ridesourcing market.

Policy Developments 

Innovations in shared mobility have begun to outpace policy, particularly since ridesourcing services launched in San Francisco, California in Summer 2012. With murky definitions and limited understanding of public safety and transportation-related impacts, policymakers were compelled to consider whether these new services, which called themselves “ridesharing,” fell under the classical definitions of ridesharing or for-hire vehicle services.

The California Public Utilities Commission established a new category of motor vehicle carriers, known as Transportation Network Companies, in September 2013. A TNC was defined as an operator that “provides prearranged transportation services for compensation using an online-enabled application or platform (such as smartphone applications) to connect drivers using their personal vehicles with passengers.” Under the new rules, TNCs in California were required to obtain a license from the CPUC, conduct criminal background checks on all drivers, provide a driver training program, maintain a “zero tolerance” policy on drugs and alcohol, and secure adequate insurance coverage for drivers when the app is on. In 2014, California passed Assembly Bill (AB) 2293, which supplants the CPUC decision and incorporates many of CPUC’s rulemaking statewide.

The emergence of ridesourcing companies draws attention to gaps in the transportation ecosystem not quite met by the taxi and ridesharing market. Ridesourcing shares many characteristics with taxis, but it also has the potential to realize some ridesharing benefits. Since the initial CPUC decision, almost every US state has enacted legislation either to allow or limit ridesourcing, yet ridesourcing continues to pose a challenge for regulators.

The emergence of ridesourcing companies draws attention to gaps in the transportation ecosystem not quite met by the taxi and ridesharing market. Ridesourcing shares many characteristics with taxis, but it also has the potential to realize some ridesharing benefits. 

Key Findings from Survey of San Francisco Ridesourcing Users

In partnership with several researchers at the University of California, Berkeley, we conducted an exploratory study of ridesourcing users in San Francisco to begin answering policy questions. In May and June 2014, 380 complete surveys were collected from three ridesourcing “hot spots” in the city, including the Mission District, Marina District, and North Beach. To obtain an adequate response rate, intercept surveys were conducted between 6:30 pm and 9:30 pm from Wednesday to Saturday for approximately two months. Surveyors targeted two types of potential respondents: those who had just completed a ridesourcing trip (“intercept trips”) and those who had used ridesourcing within the last two weeks (“previous trips”). Both types responded to identical surveys. The survey asked 18 questions regarding trip origin and destination, trip purpose, previous and alternative modal choice, car ownership, and basic demographics. After survey completion, respondents received a $5 gift card to a local coffee vendor. The study compared ridesourcing survey data with three other datasets: (1) the American Community Survey (ACS) 2012 one-year estimates, (2) a survey of taxi users conducted for the San Francisco Municipal Transportation Agency (SFMTA) in early 2013, and (3) trip logs from a medium-sized taxi company in San Francisco from October 2013.

Market Share and Demographics

UberX provided over half of surveyed trips (53 percent), while Lyft provided 30 percent of trips, Sidecar provided 7 percent, and the remainder were other services. Respondents were 60 percent male and 40 percent female. Ridesourcing respondents were generally younger than frequent taxi users from the 2013 SFMTA survey. Respondents were also more highly educated relative to the citywide average; 84 percent had a bachelor’s degree or higher.

Wait Times

While ridesourcing services and taxis serve a similar market demographic and demand, ridesourcing users experience shorter wait times than typical taxi dispatch and hail times. Two thirds of ridesourcing respondents waited five minutes or less, and nearly 90 percent waited ten minutes or less, regardless of the time of day. In the corresponding San Francisco taxi survey, only 35 percent of respondents stated they waited less than ten minutes on a weekday, and only 16 percent reported waiting less than ten minutes on weeknights and weekends.

Modal Shift and Induced Travel

It is difficult to determine whether ridesourcing services induce travel. Table 1 displays results to the question: “How would you have made this trip if Uber/Lyft/Sidecar were not available?” Ninety-two percent stated they still would have made the trip, which suggests an induced travel effect of 8 percent. About one third would have made the trip by public transit (bus or rail). Four percent of all respondents named a specific public transit station as their origin or destination, which suggests that some individuals use ridesourcing to access public transportation.

In terms of modal shift and safety, it is important to note that a small number of respondents (3 percent) said they used ridesourcing services to avoid driving after drinking alcohol, when they otherwise would have driven themselves.

Vehicle Ownership and Driving Frequency

Ridesourcing serves many residents who do not own a car, as those surveyed reported owning fewer vehicles than taxi users. Forty-three percent stated they did not own a vehicle at home, while 35 percent of taxi users reported being carless. Given that ridesourcing is still a new option to the urban transportation system, it is not surprising that 90 percent of vehicle owners reported they have not changed their ownership levels due to ridesourcing. Yet ridesourcing may allow users to drive less frequently—40 percent stated they drive less since starting to use ridesourcing. Thus, ridesourcing has the potential to impact vehicle miles traveled and vehicle ownership.

Study Limitations

This study is not completely representative of ridesourcing trips and users, as it focused on three “hot spots” in San Francisco during evening timeframes. The majority of trips reported were for social/leisure purposes and under-represent other trip types (e.g., commutes, airport trips, errands). Given these limitations, this research is exploratory in nature. Nevertheless, it can help to guide future research.

Key Takeaways 

This research presents ridesourcing in the context of classic ridesharing and taxi services in urban transportation and delineates the differences between each. At present, the policy discussion continues to evolve across the US at local and state levels, addressing issues of insurance coverage, driver and vehicle safety checks, and taxi competition. There were several key findings from our Spring 2014 survey of ridesourcing users in San Francisco: users tend to be younger, own fewer vehicles, and more frequently travel with companions than taxi users. Forty percent stated that they drive less due to ridesourcing. Notably, only 10 percent of ridesourcing respondents waited more than 10 minutes for a ridesourcing vehicle, while 65 percent of taxi uses waited more than 10 minutes on weekdays, and 84 percent waited more than 10 minutes on weekends. While ridesourcing competes with taxis (40 percent), it also competes with other modes (60 percent), including public transit, walking, private auto, cycling, and carpooling. It can also complement modes, such as public transit, as a first- and last-mile service and fill gaps in public transit networks. Furthermore, 8 percent of the trips reported were new trips that would not have been taken previously without ridesourcing.

As a relatively new transportation option with little publicly available data, ridesourcing is not yet well understood by policymakers, regulatory agencies, or academics. Future research should investigate ridesourcing with more representative data, such as ridesourcing trip and user data obtained directly from or with the help of ridesourcing companies. Future research could attempt to measure the induced travel effect or the longer-term impacts on other modes and vehicle ownership (including impacts on energy use and emissions), as well as equity. A study of ridesourcing driver motivations, behaviors, and travel patterns would be beneficial for expanding knowledge of the industry. Finally, researchers could begin to explore the impacts of enacted policies on insurance and safety to guide future policies as ridesourcing continues to evolve.

This article is adapted from “Just a Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco,” originally published in Transport Policy.

Acknowledgments

The University of California Transportation Center and the Transportation Sustainability Research Center (TSRC) at the University of California, Berkeley generously funded this work. Thanks also go to our survey respondents and to the San Francisco Municipal Transportation Agency for providing us with taxi data. We are grateful for the many contributions made by our co-authors Professor Robert Cervero and Danielle Dai, as well as numerous students including Dylan Baker, Apaar Bansal, Shuchen Gong, Lindsay Lewis, Brandon Harrell, An-Yu Liu, Rebecca Lopez, Kevin Otis, Samuel Penny, Diwen Shen, Christine Vandevoorde, and Isabel Viegas. Ian Johnson helped with the taxi data analysis. The authors are responsible for the accuracy of the data presented herein.

Further Reading

Chan, N. and Shaheen, S. (2012). Ridesharing in North America: Past, Present, and Future. Transport Reviews, Vol. 32, No. 1, pp. 93-112.

Henderson, J. (2013). Street Fight: The Politics of Mobility in San Francisco. University of Massachusetts Press, Amherst.

Dewey, O. F and L. Rayle. (2016). How Ridesourcing Went from ‘Rogue’ to Mainstream in San Francisco, Harvard University Graduate School of Design, 41 pages. Available at http://research.gsd.harvard.edu/tut/files/2016/06/San-Francisco-Case-2016.pdf

Rayle, L., Dai, D., Chan, N., Cervero, R., and Shaheen, S. (2016). Just a Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco. Transport Policy, Vol. 45, pp. 168-178.

Shaheen, S., Cohen, A., and Zohdy, I. (2016). Shared Mobility: Current Practices and Guiding Principles. Report No. FHWA-HOP-16-022, Federal Highway Administration, US Department of Transportation, April 2016. http://ops.fhwa.dot.gov/publications/fhwahop16022/fhwahop16022.pdf

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Many low-income neighborhoods have two serious problems: overcrowded on-street parking and undersupplied public services. One policy can address both problems: charge for on-street parking to manage demand and use the resulting revenue to finance local public services.

Charging the right price for on-street parking is the best way to manage demand, and the right price is the lowest price that will produce one or two open parking spaces on every block. This is the Goldilocks Principle of parking prices: the price is too high if many spaces are open, and the price is too low if no spaces are open. If one or two spaces are open on each block, drivers can reliably find a curb space at their destination, and the price is just right. Everyone will see that curb parking is both well used (most spaces are occupied) and yet readily available (new arrivals always see a convenient place to park).

New technology has solved the practical problems of charging market prices for curb parking. Meters can charge different prices for parking at different times of day, and occupancy sensors can report the availability of curb spaces in real time. The remaining problems of charging market prices for curb parking are political.

Parking Benefit Districts

To solve the political problems of charging for curb parking, some US cities have formed Parking Benefit Districts (PBDs) that spend the meter revenue to pay for public services in the metered areas. If all the meter revenue disappears into a city’s general fund, few businesses or residents will want to charge for on-street parking. Dedicating the revenue to pay for neighborhood public services, however, can create local support for priced parking. Prices manage the parking and the public services improve the neighborhood. Everyone who lives, works, visits, or owns property in the district can then see the benefits paid for by parking.

Old Pasadena, a historic business district in Pasadena, California, illustrates the potential of PBDs. Parking meter revenue in Old Pasadena helped convert a former commercial skid row into a popular destination. In 1993, the city installed parking meters in Old Pasadena and committed the resulting revenue of more than $1 million a year to rebuild the sidewalks, plant street trees, add historic street furniture, increase police patrols, and provide other public services. Following the example of Pasadena, several other US cities, including Austin, Houston, and San Diego, have committed parking revenue to finance public services on the metered streets.

Will PBDs work in other countries? To help answer this question, we examine the case of a historic neighborhood in Beijing, China. Although our case study focuses on one neighborhood, the findings should be relevant for any neighborhood where: (1) on-street parking is overcrowded; (2) public services are undersupplied; (3) most residents park off-street or do not own a car; and (4) residents who do own a car have higher incomes. Many cities, especially in Asia, Africa, and Latin America, have neighborhoods that fit these four criteria.

Parking Spaces and Public Services in Hutongs

The Chinese word hutong refers to narrow alleys in historic neighborhoods in Beijing, and they are similar to streets in low-income parts of many older cities around the world. Figure 1 shows a hutong before cars arrived.

Regularized Parking

Hutongs are typically between three meters (10 feet) and nine meters (30 feet) wide. Beijing prohibits parking in alleys that are narrower than six meters, and allows parking in wider alleys only in legal spaces that are marked by lines painted on the roadway. Nevertheless, because drivers have nowhere else to park, illegal parking has become a widespread practice tolerated by the authorities (Figure 2).

Many drivers avoid using their cars because parking will be difficult when they return. Some drivers have devised ingenious tricks to preserve their parking spaces when they leave, such as erecting temporary sheds to prevent anyone else from parking. In effect, car owners privatize public land by encroaching on the streets.

The share of cars parked illegally in Beijing has been estimated to be as high as 45 percent. Cars often block traffic and occupy much of the space planned for cyclists and pedestrians. Because so many drivers now park illegally, enforcing the regulations is politically difficult. The best solution may therefore be to regularize and charge for this illegal parking, taking into account urban design, the competing needs of different road users (pedestrians, cyclists, delivery vans, emergency services), and the residents’ demand for parking spaces.

Regularizing informal on-street parking implies marking the boundaries of spaces and assigning rights to their use. This process has two main benefits. First, it makes parking more convenient and reduces the traffic chaos caused by illegal parking. Second, it creates the opportunity to charge for on-street parking and thus produce revenue to improve public services.

Better Public Services

If cities spend the revenue from on-street parking to pay for desired public services, many residents, especially those who park off street or do not own a car, may support charging for parking in their neighborhoods. While most hutongs in Beijing have running water, electricity, and even internet access, many do not have sanitary sewer connections. The residents must therefore use public toilets. Because many alleys have overcrowded parking and unsanitary public toilets, we examine whether charging for on-street parking can yield enough revenue to provide clean public toilets. More convenient parking for drivers and better toilets for everyone may create the popular support necessary to regularize and charge for on-street parking.

If cities spend the revenue from on-street parking to pay for desired public services, many residents, especially those who park off street or do not own a car, may support charging for parking in their neighborhoods.

A Pilot Program

Fortunately, we have an example where Beijing piloted a program to regularize parking and provide public services. Xisi North 7th Alley is a typical hutong with 247 households and about 660 residents. The regularization part of the program aims to prevent illegal parking, remove obstacles used to secure vacant parking spaces, and reserve parking spaces for alley residents (Figure 3).

The pilot program also improves public services. Government employees clean the public toilets (Figure 4). Surveillance cameras and 24-hour patrol officers increase security. Private firms provide other services, including street cleaning, trash collection, and landscape maintenance.

Financial Analysis

Capital and Operating Costs

Parking is free in the pilot program and a subsidy from the subdistrict government pays to provide the public services. We can, however, estimate whether parking charges could replace the subsidy for the pilot program. The capital costs for 7th Alley, which were mainly for sanitation, landscaping, and parking regularization, totaled about $62,000 (¥380,000). The operating costs, which are mainly for the salaries of toilet cleaners, trash collectors, and patrol officers, are about $24,600 (¥150,000) a year.

Other neighborhoods with chaotic parking and poor public services would like to see similar improvements, but government subsidies are not available to replicate the pilot program everywhere. Can charging market prices for on-street parking yield enough revenue to finance the capital and operating costs of similar programs in other neighborhoods? To answer this question, we examine the potential parking revenue in 7th Alley.

Revenue from On-Street Parking

Cities can use several non-price ways to distribute parking permits among residents (for example, by lottery), but charging for the permits is the only way to produce revenue to pay for public services. Auctioning the permits is the simplest way to discover the price that will equate the supply and demand for parking in a neighborhood. Beijing auctions land for residential, commercial, and office uses, and Shanghai auctions license plates. Therefore, auctions for parking permits have well-established precedents.

Uniform-price auctions are often used when selling a large number of identical items. Consider how a uniform-price auction could allocate the permits in 7th Alley, which has 52 parking spaces. Suppose each resident can submit a bid for one permit. After the bids are ranked in descending order, the highest 52 bidders receive permits. All the winning bidders then pay the same price: the lowest accepted bid. All but the lowest winning bidder thus pay less than what they actually bid. Uniform-price auctions encourage people to bid the highest price they are willing to pay because the high bidders do not risk paying more than the lowest accepted bid. Your bid determines whether you receive a permit but not what you pay for it.

The auction prices for on-street parking will presumably relate to the market price of nearby off-street parking. For example, if residents can rent parking in a nearby garage, that price could put a ceiling on what residents are willing to bid for a permit to park in the alley. Because the prices in the nearest garages are around $80 a month, this seems a reasonable estimate for the auction value of the 52 parking spaces in 7th Alley. If the auction price is $80 a month, the 52 permits will yield total annual revenue of about $50,000 ($80 x 52 permits x 12 months) to pay for added public services.

Although $80 a month may seem a lot to charge for a permit to park on the street, car owners will receive guaranteed parking spaces, which are valuable assets where parking had previously been a big problem. Because the parking revenue will pay for public services, the combination of guaranteed parking and the new public services may entice even residents who park on the street to support market-priced parking. If most residents park off street or do not own a car, they can provide strong political support for PBDs.

The Payback Period

At a price of $80 per space per month, the potential parking revenue in 7th Alley is about $50,000 a year, which is double the program’s operating cost of $25,000 a year. Because the net operating revenue is about $25,000 a year ($50,000 ̶ $25,000) and the capital cost was about $62,000, the payback period for the capital investment is 2.5 years ($62,000 ÷ $25,000). In this case, the parking revenue should more than cover the operating costs and quickly repay the capital costs of the alley improvements. This result suggests that the program can be self-financing and is replicable in other neighborhoods.

Political Prospects of Residential Parking Benefit Districts

Residential parking permits are usually free or cheap because influential car owners resist paying a market price to park in front of their own homes. Residential Parking Benefit Districts resemble conventional Residential Parking Permit Districts but differ in three key ways. First, drivers pay market prices for the permits. Second, the number of permits is limited to the number of curb spaces. Third, the permit revenue pays for neighborhood public services. In neighborhoods where most residents park off street or do not own a car, the desire for better public services can outweigh the desire to park free on the street.

Residential Parking Benefit Districts resemble conventional Residential Parking Permit Districts but differ in three key ways. First, drivers pay market prices for the permits. Second, the number of permits is limited to the number of curb spaces. Third, the permit revenue pays for neighborhood public services.

To examine the political feasibility of charging for parking to finance public services, we examined the demographics of people and cars in 7th Alley (Table 1). Only 35 percent of households own a car. The other 65 percent who are carless will receive better public services without paying anything, and they outnumber the car owners almost 2-to-1. If the carless majority prefers public services to free parking, a PBD may be politically feasible.

Equity in Residential Parking Benefit Districts

A lottery that gives every household an equal chance to win a parking space might seem fairer than an auction. A lottery, however, would not provide any revenue to pay for public services. A lottery would instead give valuable land to a few lucky car owners and nothing to everyone else. Randomly giving free parking to a few car owners and nothing to many more people who cannot afford a car is hardly fair.

If charging for parking can earn $50,000 a year to pay for public services, free parking subsidizes car ownership by $50,000 a year. Is providing free parking for 52 cars more important than providing better public services for the 660 people living in the alley? If the city were already charging market prices for parking and spending $50,000 a year to provide extra public services, few would argue that the city should remove the public services to provide free parking.

Parking Benefit Districts are bottom-up governance, not top-down regulation. But will charging for parking place an unfair burden on lower-income residents? In Beijing, car-owning households have more than twice the income of carless households (Table 2). In 7th Alley, they have almost three times the income of carless households. Charging for parking and spending the revenue for public services will therefore transfer income from richer to poorer households. Because richer households who park their private cars on public land will finance public services not only for themselves but also for many poorer people, it is hard to argue that charging market prices for on-street parking will be unfair.

When both equity and efficiency are considered, PBDs should be most appropriate where car owners have higher incomes and most residents do not own a car, so the poorer, carless majority will receive public benefits at no personal cost.

Parking Benefit Districts can efficiently manage on-street parking and equitably financed public services, but do they privatize public land? The government owns the land, charges market prices for parking on it, and spends the revenue to provide public services. Parking Benefit Districts thus resemble market socialism, not privatization.

Conclusion: Turning Problems into Opportunities

Streets belong to the community and PBDs can monetize on-street parking to pay for community benefits. Our case study of a pilot program in Beijing found that on-street parking can finance important public investments with a payback period of fewer than three years. Most households do not own a car, and the car-owning households’ average income is almost three times that of carless households. PBDs will therefore transfer income from richer drivers to poorer nondrivers, while rich and poor alike will benefit from regulated parking and better public services.

Parking Benefit Districts are most appropriate in dense neighborhoods where: 1) on-street parking is overcrowded; 2) public services are undersupplied; 3) most residents park off street or do not own a car; and 4) residents who do own a car have higher incomes. Where these criteria are met, any city should be able to offer a pilot program to charge for parking and use the revenue to finance public services. If residents don’t like the results, the city can cancel the program. If residents do like the results, however, the city can offer this self-financing program to other neighborhoods. Because neighborhoods will have money to spend and decisions to make, residents will gain a new voice in governing their communities. Residential Parking Benefit Districts may turn out to be a fair, efficient, and politically feasible way to improve cities, transportation, the economy, and the environment, one parking space at a time.

This article adapted from  “Charging for Parking to Finance Public Services,”  published in Journal of Planning Education and Research, 37(2), June, 136–149.

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To live in Los Angeles is to endure chronic traffic congestion. Cities are places where people cluster together to create and enjoy the benefits of economic wealth, cultural vibrancy, intellectual exchange, and more. But with clustering comes traffic — often lots of it. While nearly everyone agrees that traffic is a problem, opinions diverge widely on what to do about it.

There are five major views on how to best manage traffic congestion. One view focuses on adding road capacity: wider streets, new traffic lanes, left- and right-turn lanes, more parking, and even new freeways — all of which cost a lot of money. A second view favors putting roads on “diets” and adding capacity elsewhere: improved bus service, more bike lanes, increased building densities to encourage walking, and new rail transit lines — the last of which also costs a lot of money. A third and more cost-conscious view focuses on better management of our existing transportation systems: coordinated signal timing for cars, signal pre-emption for buses, remote coordination of bus and train operations, and freeway service patrols all aim to make our transportation systems operate more effectively. A fourth view is that technology will save the day: traffic-sensitive navigation systems, increasing use of services like Lyft and Uber, and, eventually, fully autonomous vehicles that reduce the need for parking and use road capacity more efficiently. The fifth view is perhaps most favored by transportation experts, but is also generally reviled by the traveling public and the officials they elect: using prices to balance the supply of and demand for travel.

Why are experts so enamored of pricing? To answer that question, you need to know two things about congestion. First, when traffic is crawling along at rush hour, fewer vehicles are getting through than at other times, not more. A typical freeway lane can handle up to 2,000 vehicles per lane per hour, but in really bad traffic that throughput can be cut in half; just when we need the most out of our road system, it performs at its worst. So heavy traffic is not only irritating, it’s also really inefficient. Second, traffic delays are non-linear, which means that when traffic rises to certain levels it becomes unstable. Add just a few too many cars at the wrong time and fast-moving traffic suddenly slows to a crawl; take just a few cars off of the road at the right time and traffic speeds and throughput can both increase dramatically. If we can find a way to keep some cars from crowding onto already congested roads at certain times and places, many more people will get through the system overall, and at higher speeds to boot.

Keeping drivers from crowding onto roads at the wrong times and places is not easy, and could entail a heavy-handed role for government. This is where pricing comes in. Road space is scarce and valuable, so why not use prices to allocate it like we do for almost everything else, including food, housing, and utilities? Objections to this question are typically of three sorts.

Road space is scarce and valuable, so why not use prices to allocate it like we do for almost everything else, including food, housing, and utilities?

First, roads are owned by the public, like parks, libraries, and schools; some argue that charging people to drive would be like charging kids to play in the park. But one thing that defines public goods (in the economic sense of the term) is that use by one person does not significantly affect use by others. With congested roads, however, use by one person can strongly affect use by others and can slow everyone else upstream. Thus, charging for roads is qualitatively different from charging for public parks or libraries.

Second, say the skeptics, most people have no choice but to drive to work, school, or shopping, so pricing will impose fees on those with no alternative means of transportation and thus do little to reduce traffic. But research shows that many drivers do respond to prices by shifting the mode, time, and/or route of their travel. And since traffic is non-linear, only a few people have to change their behavior to get traffic flowing again so that many more travelers can get through — a crucial but often disbelieved aspect of road pricing. Rather than simply punishing drivers, well-tailored fees have been shown to buy travelers substantial time savings, with the added benefit of reduced vehicle emissions as well.

Rather than simply punishing drivers, well-tailored fees have been shown to buy travelers substantial time savings, with the added benefit of reduced vehicle emissions as well.

Third, many people fear that pricing would unduly burden low-income households by pushing them off of the roads so that the rich can travel at high speeds. Burdens on the poor are an important consideration, which is why we have programs that assist low-income households by subsidizing the cost of food, housing, and utilities. However, we don’t provide food, housing, and utilities to both low- and high-income households for free. Yet, that is what we’ve done with our roads. Furthermore, transportation systems are currently financed by a combination of property, gas, and sales taxes, the latter of which have raised virtually no objections on equity grounds. Sales taxes are the most popular new way to increase revenues for transportation, but they disproportionately burden the poor who tend to pay a higher share of their incomes on purchases subject to sales taxes. Research suggests that the poorest travelers would be better off with road pricing than with the current trend toward increasing reliance on transportation sales tax finance.

Road pricing is expanding around the globe. In the US, Los Angeles, Orange County, San Diego, Houston, Minneapolis, and a growing list of other cities have high-occupancy toll (HOT) lanes. The prices on these lanes vary based on congestion levels in the parallel “free” lanes in order to keep traffic flowing smoothly in the toll lanes. The Orange County 91 Express Lanes celebrated their 20^th anniversary in 2016, and over 600,000 travelers in Los Angeles have accounts to use the I-110 and I-10 ExpressLanes. The revenues generated have helped to pay for improved public transit service in the ExpressLanes corridors.

Outside the US, London, Milan, Singapore, Stockholm, and several other cities now charge drivers who enter their congested central areas. Chronic bumper-to-bumper traffic disappeared virtually overnight after the charges were introduced in each of these places. Buses now travel much faster and more reliably, the streets are more pleasant for walking and biking, and those who want to pay to drive can do so with few delays. In Stockholm, public support for the central area (or cordon) pricing increased after people saw how well it worked. Today, the Southern California Association of Governments is looking into experimenting with central area pricing in some chronically congested districts to see if the sorts of improvements seen in London and Stockholm can be realized here. While sure to meet with resistance among motorists, the experience elsewhere suggests that area pricing, when properly designed and implemented, can drastically reduce traffic and make formerly congested districts more appealing places to live, work, and play.

Politics ain’t worrying this country one-tenth as much as where to find a parking space.

 —Will Rogers

This issue of ACCESS considers the most controversial topic in transportation: parking. When it comes to parking, rational people quickly become emotional, and staunch conservatives turn into ardent communists. Critical and analytic faculties seem to shift to a lower level when people think about parking. Some people strongly support market prices—except for parking. Some vehemently oppose subsidies—except for parking. Some abhor planning regulations—except for parking. Some insist on rigorous data collection and statistical tests—except for parking. This parking exceptionalism has impoverished discussions about parking policies. The authors in this issue have taken a more rational and rigorous approach.

Andrew Fraser, Mikhail Chester, Juan Matute, and Ram Pendyala found that, as of 2010, Los Angeles County had 18.6 million parking spaces, including 15 million off-street parking spaces and 3.6 million on-street spaces. This amounts to more than 200 square miles of parking, equivalent to 14 percent of the county’s incorporated land area. Even though Los Angeles has one of the densest road networks of any metropolitan area in the US, the area dedicated to parking is 43 percent larger than the area dedicated to roads.

Zhan Guo examines what happened when London switched from minimum parking requirements to maximum parking limits. With the previous minimum but no maximum, most developments did not provide more than the minimum required, whereas with the maximum but no minimum, most developments provided less than the maximum allowed. The supply of parking in new developments is only 52 percent of the previous minimum required and only 68 percent of the currently allowed maximum.

Michael Manville and Daniel Chatman examine the results of SFpark, San Francisco’s pilot program that adjusts on-street parking prices to ensure parking availability. They find that the average parking occupancy rate is not the best way to measure parking availability. Instead, they argue that cities should aim for a high share of each time period with one or two vacant spaces on every block because drivers search for vacancies, not average occupancies.

Adam Millard-Ball, Rachel Weinberger, and Robert Hampshire also examine the results of SFpark.  They find that extending meter hours into high-demand times in the evenings and on Sundays, or pricing parking on unmetered residential streets, can provide higher benefits than simply adjusting rates where meters already exist.

Richard Willson explains why getting the prices right for parking are necessary but not sufficient for parking management. He shows how cities can both shrink the demand for parking and better manage all the parking they have.

And in the final article, I argue that charging market prices for on-street parking and spending the revenue for local public services can be a cheap, fast, and simple way to improve cities and create a more just society, one parking space at a time.

Donald Shoup

Editor of ACCESS