Subsidy | A Political Economy of Access

We are pleased to make available Chapter 4: Subsidy of A Political Economy of Access. It opens:

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

Should government subsidize transport? If government subsidizes transport, should it subsidize producers or consumers? If a government gave money to consumers, they could spend it on what they want, paying for a service, which if it covers operating costs, could lead to more investment. If it gave money directly to producers, they spend it on more supply. Which leads to a better outcome?


Access Quartet

I am pleased to have now completed my Access Quartet of books. These are artisanally selected from the last decade or so of my popular writings, including for the Transportist blog and elsewhere, along with new words to enhance their completeness.

They are organized so that they can be read independently, though an astute reader will identify several themes that run through them all, most obviously the need to privilege considerations of access when considering behavior, deploying technologies, designing infrastructure and networks, and deciding what to fund.

The books are beautifully laid out in the Tufte-latex template for clear information presentation and ease of reading. All are available in hardcover, paper, and PDF.

I thank my coauthors on the books, Kevin Krizek for The End of Traffic and the Future of Access, Kay Axhausen and Wes Marshall for Elements of Access, and David King for A Political Economy of Access for their contributions and extensive editing of my own writing. Each book also had numerous reviewers, who also made the books better.

You should read them all.


The End of Traffic and the Future of Access: A Roadmap to the New Transport Landscape. By David M. Levinson and Kevin J. Krizek.
The End of Traffic and the Future of Access: A Roadmap to the New Transport Landscape. By David M. Levinson and Kevin J. Krizek.
Spontaneous Access: Reflexions on Designing Cities and Transport by David Levinson
Spontaneous Access: Reflexions on Designing Cities and Transport by David Levinson
Elements of Access: Transport Planning for Engineers, Transport Engineering for Planners. By David M. Levinson, Wes Marshall, Kay Axhausen.
Elements of Access: Transport Planning for Engineers, Transport Engineering for Planners. By David M. Levinson, Wes Marshall, Kay Axhausen.
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

It’s the (political) economy, stupid: when it comes to urban transport, we’re doing it wrong

Political choices, not technological innovations, shape our urban transport systems. As long as governments continue to prize mobility over accessibility, those systems will remain unhealthy and ineffectual.

[This is an edited extract from A Political Economy of Access by David M Levinson and David A King, available now in paper and PDF. It was published in Foreground.]

It is hard to examine the state of transport and land use planning without a large dose of cynicism about motives, and skepticism about claims and priorities.

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

Transport engineering and land use planning are technical fields nominally grounded in rational thought. Yet level-headed analysis and calculations haven’t led to healthy and financially sustainable transport and land use systems. Part of what we see as the problem is a focus on mobility over accessibility. This focus prioritizes vehicular flows and speed over people and proximity. Our shared goals should not be how to maximize how much people and things travel about. Rather, our goals should be about how society can make it as easy as possible to reach opportunities and activities. A second part of the problem is privileging expansion over preservation. In a world where transport is new with few roads and no transit service, expansion is the critical phase of development; but in today’s world of mature networks, preservation is so much more important. We identify numerous problems, but the solutions are difficult to implement. That is not, we believe, because they are not good ideas, but rather because the institutions that make decisions are incapable of implementing them.

Our political economy analysis explains how access is shaped by law, culture, and governance. The issues we raise are not new, either. It was a century ago when Frederick Law Olmstead, Jr. said:

“There has been a decided tendency on the part of official street planning to insist with quite needless and undesirable rigidity upon fixed standards of width and arrangement in regard to purely local streets, leading inevitably in many cases to the formation of blocks and lots of a size and shape ill adapted to the local uses to which they need  to be put.”

This quote introduces many of our concerns. First, streets and road networks are more than just thoroughfares. They actively shape the location and function of the built environment, support or deter alternatives to automobility and substantially affect public safety. Second, in a system where transport networks and land regulations are designed and built separately, there are mismatched incentives. The most efficient road may contradict the needs of great places. Speed is not necessarily a characteristic of great cities – other than maybe Indianapolis, no city brags about being a raceway. Third, rigid roadway design is a hallmark of a focus on mobility.  The road itself is simply a conduit through which one passes, and the quality of destinations is diminished. Lastly, these are just some of the well-known problems that have persisted a century later, yet we have spent far less effort trying to understand why we keep building cities that many consider undesirable.

An additional issue is that transport systems require coordination across actors. The car you own is worthless without roads, and the capital and expertise required to build and maintain cars very much differs from the expertise needed for roads. The question remains how to integrate infrastructure, traffic flow, and land development. We advocate for coordination through prices, so people can account for the full cost of the actions of themselves and others when making decisions, whether as a traveler, developer, planner, or elected official.

The current state of transport and land use systems raises further concerns. New technologies are changing transport in fundamental ways. App-based services offer new taxi-type alternatives, which compete with and complement existing travel modes. These services are backed by deep-pocketed investors and despite their popularity are, as of this writing, not actually profitable. But there is little doubt that such services will persist in some form once the money runs out. If the history of taxicabs is any guide, a new era of regulation will protect Uber, Lyft, and others from their demise.

Private firms have reoriented transport planning priorities, for good and bad. Not long ago long-range transport plans largely set the course for policy and investment decades ahead.  Now everything from streetcars for real estate development to ridesharing through dockless bikesharingand, the flavor of  the week, electric scooters, are undermining the slow predictability of policy. With automated vehicles peeking over the horizon, the conventional approach to transport planning may be obsolete as no one knows what innovations and unintended side effects automation will bring.

The internal combustion engine is likely nearing the end of its century of dominance. These engines use fuel, which is taxed to pay for infrastructure across the US and in some other countries, and taxed for general revenue elsewhere. A shift to electricity affects the core relationship between user fees and public spending. New sources of revenue will have to be developed, including road tolls, road access charges, parking fees, and other sources. Of course, a loss of motor fuel taxes also will affect who pays for infrastructure. The role of central governments will likely diminish as fuel taxes decline. This devolution of authority pushes local and state or provincial governments to raise their own revenues. Voters will be asked to approve new taxes and fees, which introduces many concerns, including whether voters are adequately informed to assess the value of any package of taxes and spending.

Transport referenda are generally popular with the public in the United States, for example, where more than 70 percent usually pass. But voters often don’t know the true details of what they are voting on. California has led the way in voter-led projects, including their high-speed rail (HSR) project that voters passed with 52.6% of the votes in 2008. Despite well-publicized concerns, proponents promised a train that would connect the state, “[C]arrying up to 117 million passengers annually by 2030, with the capacity to also carry high-value, lightweight freight.” Since then, the timeline has been extended, the scope scaled back, forecast recanted, and the costs have increased dramatically – at one point to nearly $100 billion. Stations have been delayed or cancelled, and now the train is promoted as a commuter service to open up housing markets away from the extremely expensive coastal cities. The project is substantially different from what voters were sold, and a very passive aggressive solution to the state’s housing affordability crisis. We expect more projects like this.

Lastly, the political economy of access must address issues of race and social justice. New transit investments tend to favor wealthier, whiter communities. Bicycle advocacy is dominated by young, white men, as are the technology companies developing micromobility, services and microtransit and taxi apps. As once-young, white men ourselves, there is nothing wrong with that, but we have learned it is but one perspective of many.

The value we wish to promote is access. Access is the ability for people and firms to interact, whether through employment, production, consumption or sales. Access is a value that differs from mobility. Where mobility improvements are a hallmark of recent decades of transport policy, our focus on mobility has led to auto dominated infrastructure that offers few other options about how to get around. With a focus on access, we can orient transport policy to connecting people to places they want to be, rather than accommodating driving at the expense of everything else.

The political aspects of transport policy shouldn’t be assumed away or treated as a nuisance. Political choices are the core reasons our cities look and function the way they do. Many of the transport and land use problems we want to solve already have technical solutions. What these problems don’t have, and what we hope to contribute, are political solutions.

This is an edited extract from A Political Economy of Access by David M Levinson and David A King, available now in paper and PDF.

Professor David Levinson joined the School of Civil Engineering at the University of Sydney in 2017. He taught at the University of Minnesota from 1999 to 2016 where he held the Richard P Braun/CTS Chair in Transportation (2006-2016). He was Managing Director of the Accessibility Observatory, and directed the Networks, Economics, and Urban Systems research group.

David A King is an Assistant Professor of Urban Planning at Arizona State University School of Geographical Sciences and Urban Planning. His research explores the impact of local transportation planning on the built environment, public finance, social equity and accessibility.

Now Available: A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions

Now available: A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King, in paper and PDF.

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

About the Book

Why should you read another book about transport and land use? This book differs in that we won’t focus on empirical arguments – we present political arguments. We argue the political aspects of transport policy shouldn’t be assumed away or treated as a nuisance. Political choices are the core reasons our cities look and function the way they do. There is no original sin that we can undo that will lead to utopian visions of urban life.

The book begins by introducing and expanding on the idea of Accessibility. Then we proceed through several major parts: Infrastructure Preservation, Network Expansion, Cities, and Institutions. Infrastructure preservation concerns the relatively short-run issues of how to maintain and operate the existing surface transport system (roads and transit). Network expansion in contrast is a long-run problem, how to enlarge the network, or rather, why enlarging the network is now so difficult. Cities examines how we organize, regulate, and expand our cities to address the failures of transport policy, and falls into the time-frame of the very long-run, as property rights and land uses are often stickier than the concrete of the network is durable. In the part on Institutions we consider things that might at first blush appear to be short-run and malleable, are in fact very long-run. Institutions seem to outlast the infrastructure they manage.

Many of the transport and land use problems we want to solve already have technical solutions. What these problems don’t have, and what we hope to contribute, are political solutions. We expect the audience for this book to be practitioners, planners, engineers, advocates, urbanists, students of transport, and fellow academics.

Table of Contents


1 Accessibility

  • 1.1  The duty of the sovereign
  • 1.2  Access as efficiency
  • 1.3  Access as equity
  • 1.4  Why A Political Economy of Access?

I Infrastructure Preservation

2 Hierarchy of Needs

  • 2.1  The nature of need
  • 2.2  The state of infrastructure
  • 2.3  Infrastructure triage
  • 2.4  Report cards
  • 2.5  Infrastructure heal thyself

3 Road Revenues

  • 3.1  From Snicker’s Gap to funding gap
  • 3.2  How the gas tax may fail
  • 3.3  Fix-it-first

4 Subsidy

  • 4.1  Car subsidies
  • 4.2  Bicycle subsidies
  • 4.3  Transit subsidies
  • 4.4  Subsidize users not systems
  • 4.5  Refactoring subsidies

5 The Solution to Congestion

  • 5.1 Welcome to the club
  • 5.2  Supply-side solutions
  • 5.3  Demand-side solutions

6 Pricing

  • 6.1  Temporal variations
  • 6.2  Spatial variations
  • 6.3  You can toll some of the roads some of the time
  • 6.4  You can toll some of the cars some of the time: Phasing in road pricing one vehicle at a time
  • 6.5  Billing systems
  • 6.6  Road service providers
  • 6.7  What about the revenues?
  • 6.8  Planning with prices
  • 6.9  Congestion is over! If you want it

7 Externalities

  • 7.1  Pecuniary and technical externalities
  • 7.2  Negative externalities
  • 7.3  Positive externalities
  • 7.4  Are reductions of negative externalities positive externalities?
  • 7.5  Pollution ethics
  • 7.6  The art of noise
  • 7.7  Safety vs. speed

8 The Solution to Pollution and Greenhouse Gases

  • 8.1  Global warming
  • 8.2  Supply-side solutions
  • 8.3  Demand-side solutions
  • 8.4  Pollution trust funds
  • 8.5  Domain alignment

II Network Expansion

9 Hierarchy of Wants

  • 9.1 Transport costs too much
  • 9.2 Transport benefits too little
  • 9.3 Transport takes too long to build
  • 9.4 Benefit/cost analysis
  • 9.5 Big infrastructure

10 Macroeconomics: Is Transport Stimulating?

11 The Magic of Streetcars, the Logic of Buses

  • 11.1 Ride quality
  • 11.2 Speed
  • 11.3 Operating costs
  • 11.4 Navigability
  • 11.5 Payment and boarding times
  • 11.6 Nostalgia
  • 11.7 Novelty
  • 11.8 Conspiracy
  • 11.9 Amenity
  • 11.10 Sexuality
  • 11.11 Respect
  • 11.12 Status
  • 11.13 Pedestrian accelerator
  • 11.14 Traffic calming
  • 11.15 Superstructure
  • 11.16 Feedback
  • 11.17 Congestion reduction
  • 11.18 Transportainment
  • 11.19 Permanence and directness
  • 11.20 Development-oriented transit
  • 11.21 Discussion

III Cities

12 Clustering

  • 12.1 Multi-sided markets
  • 12.2 Clustering and economic development
  • 12.3 Constraints drive growth
  • 12.4 Simpli-City
  • 12.5 Beyond density
  • 12.6 Competing centers

13 Zoning

  • 13.1 Zoning tries to solve the externalities problem
  • 13.2 Height limits
  • 13.3 Should the Bay Area have 11 million residents?

14 Fielding Dreams

  • 14.1 Defining induced demand
  • 14.2 Induced demand can be a good thing
  • 14.3 Forgetting faster than we learn

15 Trains, Planes, and Automobiles

  • 15.1 Mapping high-speed rail
  • 15.2 A national high-speed rail network
  • 15.3 Nationalize the rails
  • 15.4 Supercities

16 Value Capture and the Virtuous Cycle

  • 16.1  Infrastructure create saccess
  • 16.2  Access creates value
  • 16.3  Value can be captured
  • 16.4  Captured value can fund infrastructure
  • 16.5  Policy implications

IV Institutions

17 Devolve Responsibility

  • 17.1  Subsidiarity
  • 17.2  Ending the federal surface-transport program .
  • 17.3  Transport finance without the feds: The Canadian model
  • 17.4  Transit federalism
  • 17.5  Whose values?
  • 17.6  ‘Dogfooding’: Ensure managers use the system
  • 17.7  Should voters have full information when voting on transport projects?
  • 17.8  Coordinate local transport and land use policies
  • 17.9  Department of Accessibility
  • 17.10  Metropolitan Department for Transport
  • 17.11  The lump of government mistake

18 Private | Public

  • 18.1  Ownership and network size
  • 18.2  Public-private partnerships
  • 18.3  Tender routes
  • 18.4  Thought experiment: Auctioning green time
  • 18.5  Asset recycling

19 Utility Models for Transit and Roads

  • 19.1  What is a Utility?
  • 19.2  TransLink: organizing transport like a utility
  • 19.3  Transit should focus on core markets
  • 19.4  Think of transit like a club
  • 19.5  Enterprising roads
  • 19.6  Minnesota Mobility: A scenario
  • 19.7  Takeaways

20 Politics and Politicians

  • 20.1 Political parties, three axes, and public transport
  • 20.2  Trust as a positive externality
  • 20.3  Lying as a vicious cycle
  • 20.4  It’s a success
  • 20.5  Mischief in Minnesota
  • 20.6  Taking credit
  • 20.7  Expertise
  • 20.8  Frontiers or values as instruments

21  Transport Poverty

22  Pretexts of Safety and Justice

  • 22.1  Safe Streets for All
  • 22.2  Racial Bias in Traffic Enforcement
  • 22.3  US police interactions are needlessly violent
  • 22.4  Why is traffic safety used as a pretext?
  • 22.5  Not in our name

V Conclusions

23 Jam Today, Access Tomorrow, or Six Impossible Things Before Breakfast


A Goods Framework

  • A.1 Rivalry and excludability
  • A.2 Goods and roads
  • A.3 Goods and transit
  • A.4 Anti-rivalry and anti-excludability

B Network Economies, Supply and Demand

C The Price of Privacy

D Governance and Performance

  • D.1 Introduction
  • D.2 Governance
  • D.3 Performance of state highway systems
  • D.4 Analysis
  • D.5 Conclusions

E Long Range Funding Solutions

Postscript: Homo Gridicus



  • 470 pages.
  • Color Images.
  • ISBN: 9780368349034
  • Publisher: Network Design Lab


How more development can lead to less travel: Examples

Balancing housing and jobs, so that they are located near each other, logically reduces travel compared to a situation where those same jobs are far apart. This has long been understood in the transport planning community (see e.g. Cervero 1989, or my 1998 paper), but is not well grasped among the general public.

However, moving a fixed number of things around is not how cities actually grow. Telling place A you taking away their employment is controversial. More generally new things are added.

Development in Mascot. Photo by author.
Development in Mascot. Photo by author.

It is commonly asserted that more development adds to congestion. And often this is true. But not always, it depends on the type of development. More housing in a housing-rich and job-poor area will result in more total travel. More employment in a job-rich, housing poor area will do similarly. More housing in a job-rich area, and more jobs in a housing-rich area can actually reduce travel.

For our baseline case, imagine a city with two precincts separated by 2 km.

Precinct A: 1000 Jobs, 0 Resident Workers

Precinct B: 0 Jobs, 1000 Resident Workers.

The one-way (morning commute) trip table looks like:

Jobs 1000 0
Workers A B
0 A 0 0
1000 B 1000 0

Total daily travel to work is 2000 person km per day. (Everyone commutes from B to A). Travel on Link BA is 1000 at 2 km per trip, or 2000 person km traveled. (This just analyzes one-way trips. Round trip commutes would double this.)

Case 1. 

There is a proposal to intensify development in Precincts A and B, so each is more locally balanced.

Precinct A: 1000 Jobs, 500 Resident Workers

Precinct B: 500 Jobs, 1000 Resident Workers.

The new one-way (morning commute) trip table looks like (rounded):

Jobs 1000 500
Workers A B
500 A 498 2
1000 B 503 497
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

The Daily Travel on links:

AB = 2 @ 2 km

BA = 503 @ 2 km

within A = 498 @ 0.5 km (walking)

within B = 497 @ 0.5 km

TOTAL = 1507 pkt.

This is considerably less than the baseline case as many more travelers can reach their destinations locally. While there is still some commuting, it is far less than before.

Case 2.

There is a proposal to build a locally-balanced Precinct C halfway between Precincts A and B.

Precinct C has 500 Jobs and 500 Workers

The new one-way (morning commute) trip table looks like:

Jobs 1000 0 500
Workers A B C
0 A 0 0 0
1000 B 666.666667 0 333.333333
500 C 333.333333 0 166.666667
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

The Daily Travel on links:

BC = BA + BC = 1000 @ 1 km

CA = BA + CA = 1000 @ 1 km

within C = 166 trips @ 0.5 km

TOTAL = 2083 pkt.

In this example, the total person kilometers traveled (pkt) on the links connecting inter-city precincts is essentially identical to the base case, despite adding 500 residents and 500 workers halfway between each. There are an additional 167 pkt daily on the intrazonal market (within C), which is likely walking.

The total one-way commute travel per person however drops, from 2 km/person per day to about 1.38 km/person per day. The average trip length is reduced. The experienced travel is thus about one-third lower.

Case 3

Building on Case 1, completely balancing A and B (so each has 1000 jobs and 1000 workers) reduces one-way commutes further (to 1176 pkt)

The new one-way (morning commute) trip table looks like (rounded):

Jobs 1000 1000
Workers A B
1000 A 941 59
1000 B 59 941
  • assuming 0.5 km intrazonal travel distance, using a doubly-constrained gravity model with a d_{ij}(-2) impedance function.

So, it should be clear from this example that adding development can actually reduce total travel, if it is the right kind of development in the right places.

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

An argument in favour of streetcars

I am a noted streetcar skeptic. I have written blog posts about their issues. As an objective analyst, I will however admit an advantage streetcars or trams have over buses.

This is not the ‘permanence’ justification that is often heard and easily disproved (i.e. where are they now if they were so permanent?). But it is related, once laid down, tracks are harder to move than buses, and tracks are more expensive, so it is harder to make routes circuitous. Many bus routes look like they were designed by drunk transit planners. One local bus the 370, which runs near my office and my home is so circuitous it is faster to walk even ignoring schedule delay. (It is not quite faster to walk end-to-end though, walking time is 2:30 vs. 1:14 on the bus, so the effective bus speed, assuming schedule compliance, is about 9.6 km/h vs. 4.8 km/h walking.) I have written about this before in Minneapolis, (and nearby Rosedale) and circuity is hardly an unknown problem.

370 Bus Route on Google Maps
370 Bus Route on Google Maps

Now there are undoubtedly reasons for every indirect deviation that diverts buses from the straight and narrow. However, every circuitous zig also loses passengers, and bus routes in the US are much more circuitous than travel by road. Serve this building, serve that one, cover this street, reduce pedestrian walking time.

In contrast, trams in practice are much more straight-laced, paragons of transit routing virtue. The historic Sydney Tram Map, as this map in wikipedia shows, gives a sense of routes that were pretty much as direct as possible.


Now it can be argued this particular bus provides and east-west service that no tram did, which is true in part. But that doesn’t mean trams could not. It also could be argued that almost no one rides the 370 end-to-end. Though I have not checked the Opal data, this is probably true as well. But a well-structured suburb-to-suburb transit network (my fantasy map is here, Jarrett Walker has done this as well) could avoid this. To be fair as well, the Sydney frequent network is not nearly as circuitous as the 370 bus, which has a roughly 20 minute headway

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

Road Rent – On the Opportunity Cost of Land Used for Roads

There are a number of ways to view the cost of automobile travel. For instance

This post looks at the idea of road rent. At the margins, what is the value of road space, and how might that cost look on a per vehicle-km traveled basis?

Real Estate

Land has value. Land used as roads has value both as a road and potentially for other uses. What if the value for other uses was higher than that for use as a road?

In Greater Sydney land values range from to $AU210,000 per m² in Barangaroo on Darling Harbour to under $AU1000 per m² in Western Sydney [link].  In Minneapolis, we estimated a few years ago that average assessed land value as $144 per m² for roads and $30 per m² for highways. [Junge, Jason and David Levinson (2013) Property Tax on Privatized Roads. Research in Transportation Business and Management. Volume 7. pp. 35-42.] It seems that assessed value is about 2/3 of market value in Minneapolis.

In some places it is much higher, in some places much lower, the examples used herein are simply an illustration.

The idea is that there is land holder (such as a government land agency) that has to decide whether to allocate land to road uses or for other purposes.

Parking Rent

Consider a typical suburban residential neighborhood with `free’ parking in front of houses. The land is valued at $1,000 per m². Each house requires one parking space out front, and parking is permitted 24 h per day. Conservatively, a car takes 10 m² when parked (the road is the access lane, we consider that separately). It would cost $10,000 for the land owner to purchase the land equivalent of the parked car. The annual rent on that would be $400 (at 4% interest).

In this example $400 is how much the car owner should pay annually  to their municipality for a permit to park their car to cover the cost of land (not the cost of infrastructure, or any other costs of roads and mobility, just the cost of land). This is a bit more than $1/day (more precisely $1.095/day). In more expensive neighborhoods, this would be higher, in less expensive neighborhoods, lower.

For Minneapolis, I have previously estimated about 220,000 on-street spaces. At $400/space per year, this would raise $88,000,000 per year, a not inconsiderable share of the city’s $1.3B annual budget. Instead it is mostly given away free.

Consider the implications if property taxes were reduced by up to $88M in total, and parking permits sold at $400/year (payable monthly with the water and trash bill). People would realize the cost of on-street parking, and there would be less of it, and less vehicle ownership at the margins, and fewer trips by car. Space freed up could be re-allocated.

Alternatively, $400 per year is the value of public subsidy from publicly-owned land to private car owners who get `free’ on-street parking. In short from the car-less to the car owners.

Alternative Uses of Road Space

The economic idea of opportunity cost is important here. Opportunity cost is value of the next best alternative. The next best alternative to road space might be renting it out. So for instance an urban US freeway that destroyed blocks of extant development when it was built has an opportunity cost associated with the value of that real estate.

So the question arises as to what other uses  could be made of the road; for if there were no other uses, you might as well store cars for free. Here are several other uses that could be  considered to replacing a parking lane:

  • Park or parklet,
  • Bike lane,
  • Bus lane,
  • Paid parking, via meters,
  • Shared car parking (rented to the car sharing company),
  • Shared bike parking (rented to the station-based or dockless bike sharing company),
  • Taxi or ride-hailing stand,
  • Bus stop,
  • Shared scooter parking (rented to dockless scooter sharing company),
  • Food truck or ice cream vendor,
  • Road for moving motor vehicles (a parking lane could be another moving lane),
  • Sold off for development.

The last item deserves some discussion. Consider that our road with two parking lanes (one on each side) is maybe 10 or 12m wide (~32 to 40ft). This is wider than some houses are long. The city could in principle retain the sidewalks and sell off the roadbed for townhouses or single family homes. Given the houses are already serviced by alleys, and so long as not all roads were sold off, some roads could be. An illustration of this is the Milwaukee Avenue in Seward in Minneapolis, as shown in the figure. You will see there is no paved street in front of the houses. This could be tightened up further or realigned should there be demand.

Milwaukee Avenue, Seward. Source:
Milwaukee Avenue, Seward. Source:

This is not appropriate for every street. However, (1) there are places this can be done, where roads are in excess and housing scarce, and (2) this illustrates that land currently used as asphalt to store and move cars has value, and that houses have value even in the absence of streets for cars in the front.

There are always excuses — utilities may need to be relocated, fire trucks would need to go slower down narrower sidewalks. But these excuses can be overcome, there are numerous examples of narrow paths that function as roads.

Driving Rent 

Note: 1 are = 100 m² and 1 hectare  (ha) = 10,000 m²

Typically each car is in use 1 – 1.5 hours per day, and parked for the remainder. In the previous section, we considered parking, the `remainder,’ in this section we look at the time in motion.

When in use, the car is occupying not simply its area (the 10m² = 2m x 5m), but also is preventing the use of other space around it. On a freeway with a capacity of 1800 vehicles per hour traveling at a freeflow speed of 100 km/h, (i.e. just before the speed and flow drop due to congestion sets in) there is a critical density of 18 vehicles/km.

18 vehicles per km is 55.5 meters per vehicle. Lane width is 3.65 meters, so the area occupied is 202 m². Let’s round to 200 m². Each moment  a car is in use, it is using 200 m², on which it should pay rent. So for an hour a day, this is 720,000 m² s or 72 ha s.  (The meter-squared by second (or hectare second) is a new unit of measurement (a time-volume) that needs a catchier name).

It is the density that is the relevant number here, since vehicles are occupying space that we are charging rent for in this thought experiment. Though they are moving, and so the space they are occupying moves with them, there is always some space being occupied for the duration of their travel. Each of those vehicles per hour is occupying a moving window of space.

Roads are a Time Share

When roads are less congested, cars are consuming more space per vehicle. So uncongested urban are much more expensive per traveler than congested rural roads.  When traffic breaks down, they are consuming less space, but presumably are occupying that space for more time, since they are going slower. Induced demand [link] and travel time budgets [link] negate that to a significant extent.

Illustration of space occupied by cars. Note that most cars do not have 2 occupants. This particular layout is, surprisingly, in somewhat congested conditions. Cars often take up more space at higher speeds. Screen still from a 2002 Saturn car company TV commercial. Image source:  The San Francisco ad agency Goodby, Silverstein & Partners.  Article: Raine, George ‘Goodby, Silverstein agency celebrates 25 years’ SF Chronicle.

George Raine

In this example, the hourly rent on 200 m² is what we are interested in. Though cars move, over the course of 1 hour of travel in these conditions, they are claiming that much space. The specific space they are claiming moves with the vehicles, but this all balances out as other cars claim the space they vacated.

Empty roads still have to be paid for, and paid for by actual road users. Even when a road is not being used, it is available to be used. Travelers have the option of traveling. Pavements cannot be easily be rolled up and allocated to other purposes on the fly, particularly purposes like buildings. (Roads can occasionally be closed for special events, but this is rare during business hours.)



Consider a car trip that uses 3 roads:

  • Road section 1 (suburban residential): l=5 km, w=3.65, v=30 km/h, q=1000 veh/h, k=33.33 veh/km, AADT=10,000 vehicles/day/lane, p= $1000/m².
  • Road section 2 (motorway): l=10 km, w=3.65, v= 100 km/h, q=2000 veh/h, k= 20 veh/km, AADT = 20,000 vehicles/day/lane, p= $5000/m².
  • Road section 3 (downtown): l= 1 km, w=3.65,  v=40 km/h, q=1600, k =40 veh/km , AADT=16,000 vehicles/day/lane, p= $10000/m².

where: l = length (km), w= lane width (m), v=velocity (km/h), q=flow (veh/h), k=density (veh/km), AADT = Average Annual Daily Traffic, p= land value ($/m²), i=interest rate = 0.04, r= land rent ($/year/m²), d = days/year

Consider each road section to be a homogenous pipeline. (With heterogenous traffic, this is obviously far more complicated, and we would make use of the q, k, and v variables to compute an area-time.)

The annual rent (R) for  each road section is the R=p*i*l*w

  • Road 1: R=$1,000/m² y * 0.04 * 5,000 m * 3.65 m  = $730,000/y
  • Road 2: R=$5,000/m² y * 0.04 * 10,000 m * 3.65 m = $7,300,000/y
  • Road 3: R=$10,000/m² y * 0.04 * 1,000 m * 3.65 m = $1,460,000/y

This annual rent is paid by the road agency to the land owner for the use of land as a road. The road agency then wants to recover this cost from its customers, the travelers.

The question of how to allocate always has some subjectiveness to it. Another way of thinking about it is based on elasticity of demand. Peak hour work trips are perhaps the least elastic (least sensitive to price), and so from an economic efficiency perspective should bear the greater cost.

In this example, we take a simpler tack.

The allocation is R/AADT to get cost per year per daily tripmaker, and divide by 365 to get cost per trip, and by section length to get cost per km. In this example:

  • Road 1: $730,000/10000 = $73/y = $0.20/trip = $0.04/km
  • Road 2: $7,300,000/20000 = $365/y = $1/trip = $0.10/km
  • Road 3: $1,460,000/16000 = $91.25/y = $0.25/trip=$0.25/km

The total is thus $529.25/year or  $1.45/trip to cover land rent. `Your mileage may vary,’ as the saying goes.


The implications of this are several.

  • At an additional $1.45/trip, travel by car (and congestion) will diminish.
  • Road rent is essentially additive with annualized infrastructure costs, which generally does not consider the cost of land (rather, land is often implicitly considered `free’ or a sunk cost).
  • If travel by car diminishes sufficiently, road space can be clawed back and redeployed for other public purposes.
  • Narrower lanes impose less road rent. But not necessarily proportionately so, as the throughput on narrower lanes (with human drivers) may be lower as drivers are less keen to be immediately adjacent to nearby high-speed vehicles.
  • Slower moving vehicles take up less space, but take that space for longer.
  • While pedestrians and bicyclists use space as well, they use much less space. (See discussion of flux.) Sidewalks (footpaths) are often considered part of the adjacent private property, and are thus already paid for with property tax.
  • Land used for roads instead of development is not on the books for property taxes.
  • The revenue raised can be used for many transport purposes or redistributed back to taxpayers through some other means.
  • We expect the additional road rent reduces the effective land rent that landowners can charge. If people have to pay more for travel, they will pay less for real estate.
  • Rural areas have much lower, perhaps negligible, road rent. Though the number of users drops significantly (so there are fewer travelers who must pay the burden of road rent), the cost of land drops even more significantly.
  • Were there no (fewer) roads, land would also have very little (less) value, since it would be difficult to access and egress.
  • If roads were fully built on, views would be terrible and the existing buildings would diminish in value. But none of that is to say we have the correct amount of roads now. Clearly urban roads are undercharged in a real estate sense.

Speed vs. Safety

March 21 [Updated with more accurate estimate/figure after fixing an excel bug] How fast should we drive? From a social cost perspective, faster speeds save time, which has a value, but faster speeds cost lives, which also have a value. To illustrate the trade-off I did some back of the envelope calculations, imagining, like a macro-economist, a single road represents the whole t

Speed vs. Safety (updated)
Speed vs. Safety (updated)

ransport system. Annually there are about 30-40,000 people killed in the US, there are an annual Vehicle Miles Traveled of 3,208,517,000,000. The average speed of travel isn’t known directly, but if we assume the average person travels in a car 60 minutes per day (the 1 hour travel time budget) this implies, at approximately 30 miles of travel per day per traveler, about 30 MPH, which seems about right (including 1/4 of travel on freeways at higher speeds and 3/4 on surface streets and roads at lower speeds, and including traffic signals). As the saying goes, Your Mileage May Vary, and this is intended to be indicative — not a universal answer. Some additional assumptions:

  • We take the Value of Life to be $10,000,000, and assume fatalities are the only cost associated with crashes (they are about 78 % of total crash costs according to our analyses, so we should inflate this number to get total crash costs) [US DOT says $9.6 M]
  • We take the Value of Time to be $15/hour [US DOT gives a lot of ranges, but this number is high for all surface travel excluding freight]
  • We assume the number of deaths drops linearly with speed, to zero at zero MPH. The improvement is likely non-linear, as reductions in speeds from high speeds are more valuable than from low speeds.
  • We assume the value of travel time savings is constant, independent of the amount of time saved.

To be clear, these are huge assumptions. Examining the figure we see the lines cross at about 75 MPH, which is the minimum total cost. So why don’t we set the speed limit to  75MPH? Note that:

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
  • Travel time savings are, while still speculative in terms of their valuation, both private and real,
  • The statistical value of life is far more abstract. The value of my life to me is infinite. The value of your life to me is, sadly, not. Yet, I am willing to take risks that increase the probability of my dying in order to save time or earn more money. These are the kinds of factors that allow an estimate of value of a statistical life.
  • Death and crashes are probabilistic affairs, while the time lost is deterministic. People are gamblers.
  • There are some other benefits to faster travel not accounted for, such as more or longer trips (to better destinations, or the ability to get better real estate at the same price), which increase consumer surplus. The analysis here does not consider user response to lower speeds, which would be to travel less (or higher speeds and travel more).  There are also issues like travel time reliability.
  • Since 1988 The Statistical Value of Life has risen 6-fold in US DOT estimates, the value of time has little more than doubled. (If we cut the value of life to $3M, (effectively holding the tradeoff more similar to 1988 levels), the tradeoff is much higher .)
  • Speed limits reflect what travelers will travel at, not what we wish they would travel at.

If you dislike these number, you can roll your own analysis on individual roads. The difficulty is not measuring the speed of those roads, but measuring their safety. There is a Highway Safety Manual for such purposes, but crashes are highly random events.

UPDATE 2: Axel Waleczek made an interactive Tableau, so you can test your own scenarios.

Additional Readings

Fielding Dreams – Hypotheses about Induced Demand and Induced Supply,

In the Kevin Costner film  Field of Dreams, a ghost whispers “Build it and they will come”  ‘it‘ refers to a baseball field; ‘they‘ are the ghosts of past baseball players.  This has been adopted by planners to describe the idea of induced demand, which applied in transport is that if you build a new facility (road, tracks, etc.) demand will respond and use it, making trips that previously would have been unmade.

The Field of Dreams

This has been illustrated using economic supply and demand curves, and to an economist this “induced” or “latent” demand was always there, just unrealized until the cost of travel was lowered by the new capacity. The road (or train) fills up, congestion returns (or at least the expected congestion reduction benefits do not last long, as travelers adapt to the new environment. The consumers’ surplus increases, as people can now do things they want to do at lower cost. In the planner’s telling, only the hapless traffic engineer (or traffic modeler who is as often a planner as engineer), who made the partial equilibrium assumption that demand does not respond to supply, is surprised by this growth.

A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King
A Political Economy of Access: Infrastructure, Networks, Cities, and Institutions by David M. Levinson and David A. King

Of course induced demand is not surprising to anyone who has thought about this, and the idea of induced demand has long been well understood, even if the magnitude of induced demand associated with any given project are hard to estimate, and the models are not used appropriately, and internal consistency between model inputs and outputs is still not standard practice [I did my MS Thesis on this more than 25 years ago, and it wasn’t a new idea then.] A related notion is Say’s Law, from 1803: Supply creates its own demand, or more pedantically as per Wikipedia “that aggregate production necessarily creates an equal quantity of aggregate demand.” Induced demand has been dealt with previously on the blog, here we lay out the hypotheses a bit more formally.

But there are 4 specific hypotheses (and 4 null alternatives) that can be generated here, varying three dimensions: construction (supply), demand response, and sequence:

  • If you build it, will they come? [Induced Demand Question]
    • H1: Build it and [then] they will come. [Because demand responds to supply, or because it was coming regardless] [Compare H2]
    • H1null: Build it and [then] they won’t come [Because demand is independent of supply]. [See H4]
  • If they come, will you build it? [Induced Supply Question]
    • H2: They come and [then] you will build it. [Because supply responds to demand, or because you were building it regardless] [Compare H1]
    • H2null: They come and [then]  you didn’t build it. [Because supply is independent of demand] [See H3]
  • If you don’t build it, will they come? [Exogenous Demand Question]
    • H3: Don’t build it and [then] they will come [anyway]. [Because demand is independent of supply] [See H2null]
    • H3null: Don’t build it and [then] they won’t come [Either because demand is independent of supply, or because you didn’t build it]. [See H4null]
  • If they don’t come, will you build it? [Exogenous Supply Question]
    • H4: They don’t come and [then] you build it. [Because supply is independent of demand] [See H1null]
    • H4null: They don’t come and [then] you didn’t build it. [Either because supply is independent of demand or because they didn’t come.] [See H3null]

Each of these tells us something a bit different. There is both the dependence of the supply-demand question (are they dependent or independent), and there is the sequencing (which comes first, transport or land use).

Of course these are binaries, and we could consider how many of “them” need to come for us to say “they came”. So you built a stadium to seat 10,000 and 5,000 came, is that evidence of induced demand? In short, yes, but not as much as you planned for.

Karl Popper developed the idea of  falsifiability, which a website says: “is the assertion that for any hypothesis to have credence, it must be inherently disprovable before it can become accepted as a scientific hypothesis or theory.”

Sequencing, matters here, and it’s hard to prove a negative. A single sequence of events cannot provide proof for induced demand, maybe everyone was going to show up in Kinsella’s Field anyway, and the field just accommodated them. Just because they never showed up before he built the stadium is not the evidence we require. Instead, we need to compare multiple cases to justify our case, and build the evidence for it.

A sequence of events can however disprove induced demand (or supply), as the list above illustrates, there are several cases where construction does not result in demand (we can conclusively disallow induced demand in that case) or where demand does not create supply (we can conclusively refute induced supply).

There are some other issues, what if they come and you didn’t build it (or you didn’t build and they come)? It is sort of hard to get the sequence correct in the absence of an event, when did the event of non-construction happen (or when did construction not happen)? Always. The related question is when did the absence of demand occur?

In either case, negative externalities ensue, this is the NIMBY fear of growth without supporting infrastructure. NIMBYs may not want the growth with the supporting infrastructure either, but their main complaint, on face value, is growth without it, which realistically may negatively affect their personal quality of life and property value. Whether or not you believe they should prevail, you at least understand their point-of-view.

Policy responses to ensure consistency between supply and demand  include concurrency or adequate public facilities ordinances. Having worked on these before, these are rightly treated skeptically by the public.