The National Infrastructure Commission has been consulting on a number of questions, including how  the Government could best replace fuel duty in a way that is fair.

 The prospect of a complete switch to electric propulsion for cars and vans will lead to loss of most revenue from fuel duty, currently about £28 billion a year (HGVs might still require taxable fuel), offset to a small degree by VAT of 5 per cent on electricity. Vehicle Excise Duty raises some £6 billion a year, rather less than the annual capital and current expenditure on national and local roads of £8 billion in total. So VED could be raised to cover the full cost of the road system. But that would leave a major gap in public revenues and would, in the long run, imply much cheaper motoring – welcome to motorists but problematic in respect of the detrimental impacts of the car.

To fill the revenue gap it would be logical to levy a charge on the use of electric vehicles (EVs). This would be a charge related to distance, weight of vehicle (which determines damage to carriageway), location and (possibly) time of day (reflecting congestion which imposes costs on other road users). It would also be possible to relate charges to the cost of the vehicle when new, so that the better off road users paid more than those who could only afford a reasonably priced family car.

The public rationale for such a charge would be that it is right that EVs should contribute their fair share of the revenues raised from road users, both to cover the costs of operating, maintaining and developing the road network, and to meet the wider needs of society.

EVs could only be charged for road use once their costs permitted this. At present, the lower cost of electricity goes part way to offsetting the higher capital cost of EVs. However, capital costs are expected to fall as battery technology advances, so that over time cost headroom will develop that will allow EVs to be charged for road use while maintaining their economic attractiveness in relation to conventional vehicles.


Road user charging would allow devolution of revenue raising to fund the road system. One tranche of revenue would be taken by the Treasury to support general government expenditure. The remainder would be retained by road authorities to fund their expenditure on roads and other transport provision. The Department for Transport would decide charges for the Strategic Road Network, while local authorities with responsibility for roads would set charges for their networks. There would need to be some coordination of approach to minimise diversion of traffic onto unsuitable roads, perhaps a responsibility for the Office of Rail and Road.

Road authorities would set charges according to their revenue and investment needs: problems with potholes would justify raising charges, as would plans for additional capacity. The income stream from charges could be used to raise finance for capital projects. Devolution of revenue raising to road authorities would largely obviate the need for grants from central government, other than perhaps for regional ‘rebalancing’. If, like London, local authorities chose to manage demand by means of a congestion charge, the revenue could be used to fund public transport. This would provide an important tool to influence the pattern of urban transport.

The London congestion charge is well accepted by the public, is technically reliable and raises useful revenue. It is, however, based on a daily charge for entering the charging zone within the charging hours, regardless of level of traffic or distance travelled. The Mayor’s draft Transport Strategy indicates that consideration will be given to the next generation of road user charging systems, to help achieve policies for mode share, road danger reduction, environmental objectives, congestion reduction and efficient traffic movement. It would be sensible for consideration of technology options to be a joint effort between TfL and DfT, so that London could act as a test-bed for arrangements that are capable for national use in due course.

The technology for road user charging would comprise a digital platform with a vehicle-based device displaying an app. Other facilities could be offered on the device including route guidance to avoid congestion, journey time information, indication of available parking, facilities for sharing trips with those travelling in the same direction, and information about non-car modes of travel where these are practicable alternatives. The menu of options would trade off speed, quality and cost. This technology would allow the operation of the road network to be optimised, reliability to road users to be improved, and the costs of maintenance, operation and development to be recovered through charges that reflect costs.

Uber’s buccaneering entry into regulated taxi markets in many cities prompts questions about the purpose of regulation and who benefits. While there is little academic literature on the topic, a 2016 paper* by Harding, Kandlikar and Gulati, focused on North American taxi markets, is illuminating. It is argued that the case for regulation is based on the view that the taxi market suffers from three problems: ‘credence good’, open access and thin market:

  • A credence good is a good or service whose quality cannot be determined by the consumer until after it has been consumed. Questions about reliability of a taxi service may deter users who may be concerned about excess charges or a poor quality vehicle. Regulation that sets standards for quality and price overcomes such market failure.
  • Open access to the market may attract large numbers of new entrants on account of low costs of entry. Given limited demand in the locality, earnings of drivers would fall, increasing the incentive to illegitimate charging and poor vehicle maintenance.
  • A thin market has a small number of buyers and sellers, which reduces the chances of matching supply and demand. The taxi market is thin in that it is geographically dispersed. Regulation of fares prevents exploitation of users when demand exceeds supply.

The entry of Uber and similar ride hailing platforms impacts the taxi market in a number of ways:

  • Barriers to entry for drivers are lowered, and users are attracted, shifting a thin market to a thick one.
  • Fares flex according to demand but are specified before the trip is undertaken. Surge pricing attracts drivers to meet peaks of demand.
  • Quality rating of both drivers and passengers, plus predictable fares, helps ensure consistent standards of service.

Thus the platforms address the shortcomings of traditional taxi markets that have justified regulation, effectively removing two of the rationales for taxi regulation, and largely mitigating the third (open access), Nevertheless, the implications of competition between platforms are as yet unclear. Competition could lead to instability on both supply and demand sides, which could result in collusion by platforms, to the disadvantage of drivers and passengers; while lack of competition may result in monopolistic pricing.

The paper concludes that regulators should allow the ride hailing market to grow and focus on the possibilities of future monopoly and of collusion between platforms.

*Taxi apps, regulation, and the market for taxi journeys. Transportation Research Part A: Policy and Practice, 88, 15-25, 2016.



I blogged recently about the economics of Uber and other ride hailing services. Further light has been shed by the excellent new book from Andrew McAfee and Erik Brynjolfsson of the Massachusetts Institute of Technology: Machine, Platform, Crowd. From this I gleaned the thoughts below.

Network effects have long been recognised: some services become more valuable to each user as more people use them. The telephone is the historic example, WhatsApp a recent instance. Network effects reflect demand-side economies of scale, where benefits to users, the source of demand, grow as the scale increases (contrasted with supply-side economies of scale where costs fall as scale increases).

Two-sided digital platforms serve to match supply with demand. The most successful take advantage of network effects to become powerful aggregators of both supply and demand. They are early to the business space and pay a great deal of attention to user interfaces and experience, since users may be unwilling to employ more than one or two competing platforms.

In the transport sector, we are concerned with platforms that function ‘online to offline’ – digital access to physical mobility. Examples: Uber, Lyft, Gett and other taxi services, BlaBlaCar and Liftshare for ride sharing, car clubs, dockless bike hire by app, online rail ticketing. As well as matching users with services, the platforms optimise operations, for instance selecting the fastest routes and predicting the location of future demand. The negligible cost of digital scaling means that these platforms can handle huge volumes of information – about user preferences, availability and price of services, payments etc.

In the past such data handling would have been limited to large organisations. Now, the availability of cloud computing with unlimited amounts of capacity helps innovators enter the market, scale rapidly and compete aggressively.

Demand side economies of scale can grow much faster than costs. However, the main challenge for digital platforms arises because the supply side involves physical plant and infrastructure whose capacity is finite, hence capacity, a perishable commodity, must be carefully managed. An important tool is revenue management, pioneered by the budget airlines, where varying price is used to match supply with demand – which needs lots of data and lots of supply and demand to run well.

As well as benefiting from network effects, digital platforms can reduce information asymmetries that inhibit transactions, such as whether you can trust your taxi driver, particularly in an unfamiliar city. Uber asks both customers and drivers to rate each other after each transaction, which allows poor performers to be dropped and increases confidence in quality of service.

Operators of two-sided platforms typically prefer lower prices than their providers of service. The maximum revenue of a taxi service arises at low fares, given the price elasticity of demand. However, two-sided platforms have to satisfy both providers and users. Lower fares increase demand, which will attract more providers onto the system, a benefit to providers. But lower fares also mean less income to drivers.

There is a belief that two-sided platforms for taxis offer network demand side economies of scale such that the biggest platform will dominate each local market. Patient capital to support growth of the market will reduce the marginal costs of arranging a ride, to yield attractive returns to investors.


Analysis of the economics of transport digital platforms is at an early stage.  A key question is whether scale economies would tend to result in monopoly, or whether competition would arise on account of low barriers to entry and a gig workforce open to recruitment by the offer of better terms.











Check refs

An interesting article by Len Sherman in Forbes magazine argues that unregulated taxi services are characterised by bounded demand, abundant supply given low barriers to entry, relatively undifferentiated service quality, low customer switching costs, high variable costs and virtually no economies of scale. Historically, this led to regulation, for example the set fares and ‘Knowledge’ requirement for drivers of London’s black cabs, which allowed profitable operation and acceptable remuneration, at the expense of consumers who paid higher fares.

Uber’s buccaneering approach bypassed taxi regulation, and allowed rapid market penetration of a service that is superior in many respects to existing taxi and private hire services and hence very popular. The question is whether Uber can be profitable, which Sherman doubts.

The economics of ride hailing, or demand-responsive transport (amongst the variety of terms in use), is not straightforward. These businesses compete for both customers and drivers. Low fares attract customers but deter drivers who have other choices for getting clients. Reducing the commission taken (20-25% for Uber) could benefit drivers and customers but would reduce profitability and disappoint investors. Raising fares could benefit both drivers and profitability but would encourage competitors to enter the market.

Much depends on whether the market for ride hailing tends to monopoly, so that the dominant incumbent is able to deter new entrants by short-term fare reductions; or whether sufficient competition would naturally arise because barriers to entry are not high (digital platforms being replicable). Lyft, Uber’s main US competitor has been gaining market share, which suggests a competitive market may be possible.

For governments, there are a number of challenging questions about the future regulation of taxis and private hire vehicles:

  • Create barriers to entry that result in effective monopoly supply, with improved driver remuneration but higher fares (the situation with regulated fares)?
  • Or aim for a level playing field for competing suppliers, to encourage innovation and benefit consumers?
  • Segment the market with distinct classes of providers, or allow new entrants with novel offerings, such as demand-responsive minibuses?
  • Protect remuneration of drivers in a competitive market by application of the ‘minimum wage’ concept?
  • Regulate overall numbers of ride hailing vehicles to mitigate congestion and to limit diversion of passengers from buses, or regard such services as helpful in reducing individual car ownership?

One approach to the problems experienced by Uber drivers in London is being developed by the New Economics Foundation – a driver-owned alternative that is just as convenient and competitive on price, but treats its passengers and drivers with respect. However, the question is whether the economics of ride hailing allow better rewards for drivers, over and above ‘respect’, particularly since a driver-owned cooperative would be constrained by limited capital in the face of competition from well-capitalised commercial enterprises able to sustain short-term losses while seeking market dominance.

Perhaps a better approach to improve the position of drivers would be to devise an app that allowed them to achieve improved outcomes while continuing to work for Uber and other ride hailing businesses. The key point is that transport services are very time sensitive and therefore vulnerable to interruption. It is noteworthy that Ryanair, which had long declined to recognise the pilot unions, has recently agreed to do so when faced with a strike in the run up to Christmas.

Organising collective action by drivers by means of an app might be one approach to securing better terms. But it might also be possible to take advantage of Uber’s surge pricing system in which prices rise when demand exceeds supply, thus deterring some customers and attracting additional drivers. An app that allowed drivers collectively to constrain additional supply could prolong the duration of surge pricing to their benefit.

The operation of such driver-organising apps in an already complex industry would need careful analysis, based on game theory concepts. It is possible that the outcomes for drivers would be better than head-on competition by a driver cooperative.

A kind of precedent is the Vegas Kickback app, which rewards drivers, over and above the fares earned, who take customers to commission-paying destinations in Las Vegas – nightclubs, massage parlors, gun ranges etc.

Transport for London has refused to renew Uber’s licence as a private hire operator after expiry of its current licence on 30 September, on the grounds that Uber lacks corporate responsibility in relation to a number of issues that have potential public safety and security implications (more detail available). Uber is appealing against this decision. Thus far more than 700,000 people have signed an online petition in support of Uber.

The Mayor, Sadiq Khan, has endorsed TfL’s decision, but has recognised the popularity of Uber and has said that there is a place in London for all private hire companies that play by the rules and that he wants to help support innovative businesses in London and to create a vibrant and safe taxi and private hire market. The Mayor is consulting on his draft Transport Strategy, which has the ambition to reduce car use to 20% of all trips by 2040. One reason why car ownership and use in London is on a downward trend is that there are alternatives to the private car, Uber and the like as well as buses and trains.

3.5m Londoners use Uber via its smartphone app and more than 40,000 licensed drivers work for the company. While there have been criticisms of a number aspects of aspects of Uber’s operations, it is evident that this innovative service meets a real mobility need. Its virtues include the clear location and timing of the arriving vehicle with a named driver, the ability to rate the driver after the trip, no need to pay by cash or card, and applicability of the same app throughout London and to all cities that Uber serves. These attractions, together with relatively low fares, account for the success of Uber in competition with black cabs and local minicabs.

TfL’s refusal to renew Uber’s licence on grounds of safety and security seems at odds with the popularity of the service amongst Londoners. Uber must have a fair chance of modifying the decision on appeal to the court or in negotiation. But if not, others will seize the opportunity to step in. The drivers and their cars are there, as are the smartphones waiting to be loaded with new apps. There are other platforms in London such as Gett and mytaxi, (both for black cabs at present), and it is reported that Uber’s main competitor in the US, Lyft, is thinking about coming to London.

An important question is whether a single platform would tend to be dominant on account of economies of scale and scope – spreading the overhead costs across the greatest number of users and providing the fastest response times. Or whether stable competition between a number of providers could be achieved, as they compete for both clients and drivers by offering attractive terms to both. Lyft has been growing market share in New York at Uber’s expense. The New Economics Foundation has proposed ‘Khan’s Cars’, a mutually-owned, publicly-regulated alternative to Uber.

Another question is the sustainable level of fares for services provided by these platforms, which would need to be sufficiently high to attract drivers but low enough to be competitive with conventional taxis and minicabs. The app-based platforms such as UberPool allow customers to share journeys with other going in the same direction at lower fares – a source of competitive advantage as well as a means of increasing vehicle occupancy, which is helpful for efficient use of the road network.

For the longer term, the possibility of driverless vehicles offers scope for substantial cost reduction for robotic taxis. This could allow population of the vacant space between high capacity, low fare public transport offering stop-to-stop or station-to-station service, and low capacity, high fare taxis offering door-to-door journeys.








The Department for Transport publishes passenger numbers for the English light rail systems, shown in the Figure. What is striking is the very different growth rates: buoyant for London’s Docklands Light Rail and Tramlink, and for the systems in Manchester and Nottingham; but relatively static elsewhere – West Midlands, Sheffield and Tyne & Wear.

Urban light rail offers speedy and reliable travel compared to cars and buses on congested roads. In a growing economy, we expect its popularity to grow, as we see in London and Manchester.

The light rail passenger number trends bear upon the general question of whether transport investment can foster economic growth, or whether it follows it. The different patterns observed tends to suggest that urban rail investment can contribute to existing economic growth but may not in itself stimuate lift-off.

It is conventional to value transport investments by estimating the time savings to users, which are multiplied by a value of time derived from Stated Preference studies, essentially survey questions that ask people to trade off time against money. A major re-estimation of the value of travel time commissioned by the Department for Transport prompted me to review the appropriateness of this methodology.

I have long been concerned with the use of travel times savings. The National Travel Survey shows that average travel time has not changed over the past 40 years, during which period many £billions have been invested in the transport system, based on the supposed value of time savings. The NTS findings show that there are no time savings in the long run, the relevant perspective for investment in long-lived infrastructure. The real benefit of such investment is to improve access to land that can be developed to accommodate a growing population and boost the economy. A good example is the regeneration of London’s Docklands made possible by rail investments. So we need an approach to investment appraisal that focuses on the spatial impact, given that the outcome is additional movement of people and goods through space.

I have a paper just published on this topic. Get in touch if you have difficulty in accessing the full paper

I have for some time taken issue with the way the UK Department for Transport (DfT) plays down the economic benefits of land and property development that result when new transport investment makes land more accessible. While DfT recognises that housing developments may be dependent on provision of new transport services, the associated economic benefit is not included in the estimation of the benefit:cost ratio that determines the value for money of the transport investment.

The Department for Communities and Local Government (DCLG) recently published its Appraisal Guide.  This states (para 3.9):

‘….changes in land values as a result of a change in land-use for a development reflect the economic efficiency benefits of converting land into a more productive use. Land value data should be the primary means of assessing the benefits of a development. Land value data is a rich source of information because it is actual market data on individuals’/firms’ willingness to pay for a piece of land. Assuming individuals and firms are rational in their decision-making, market prices should reveal the ‘true’ private benefit of a development. This information can be used to undertake cost benefit analysis to quantify the potential welfare implications of a development.’
So there is a marked difference in the way two government departments treat land value uplift in economic appraisal, which is pretty odd. My view is that DCLG has the right idea. DfT is wedded to a theoretical framework that focuses on benefits to users of the transport system, and assumes that land use is unchanged. But this flies in the face of extensive evidence that transport investment that makes land more accessible can trigger development – London’s Docklands is a prime example of rail investment making land accessible for development. DfT should adopt an evidence-based approach, using evidence of outcomes from completed investments to inform the case for prospective investments.

The current main method of adding capacity to UK motorways is known as Smart Motorway All Lane Running. This involves allowing traffic to use the hard shoulder (previously reserved for breakdowns), with speed controls to respond to accidents and congested conditions. This approach has been applied to a section of the M25, London’s orbital motorway, increasing running lanes from 3 to 4. A monitoring report after two years of operation has been published. The main findings, compared with before the scheme was introduced: traffic flows up by as much as 17%, well above the regional trend (5%); some journey times increased by up to 8%; and only a slight improvement in reliability. Significantly, the biggest increases in traffic occurred at weekends (as much as 26%).


The intention of investment to increase the capacity of the Strategic Road Network, of which the M25 forms an important part, is to improve connectivity between cities and reduce congestion. However, roads like the M25, that are located in densely populated areas, are also used by local users for their daily travel. Any increase in capacity offers opportunities for more or longer local trips.The resulting extra traffic restore congestion to that it had been prior the the investment in capacity. The findings of the present study are consistent with this general experience. Regrettably, there is no data on the composition of the traffic, by journey purpose or distance travelled. However, the finding of a big increase in weekend traffic is consistent with leisure users taking advantage of initially faster travel to reach more distant destinations.

The findings of this report confirm the phenomenon of ‘induced traffic’ – the traffic that results from additional road capacity – as I discussed recently in connection with the CPRE study. Such traffic adds to congestion and so reduces the time savings expected from such investment, time savings that constitute the main economic benefits presumed to justify the investment.


An excellent report on the impact of road investments has been commissioned by the Campaign to Protect Rural England from Lynn Sloman and colleagues. This report re-examines the outcomes of a number of Highways England road schemes, finding average increased traffic above control levels in the short run (3-7 years) of 7% and in the longer run (8-20 years) of 47%. This is clear evidence for substantial ‘induced traffic’ generated by new capacity. The CPRE study also find very limited evidence for benefits to the local economy from road investments.

These findings pose problems for the  Department for Transport’s WebTAG approach to the economic appraisal of road schemes, in which time savings to users is the dominant benefit. However, induced traffic tends to restore congestion to what it had been, lessening time savings. If induced traffic were properly taken into account, the apparent value of the investment would be substantially less. Moreover, the orthodox approach assumes unchanged land use, yet the CPRE report documents extensive land use change in four detailed case studies. Such changes have implications for local economies, not necessarily wholly advantageous if these take the form of low-wage employment in warehouses or car-dependent residential development.


The main policy objective of the current UK national road investment programme is to boost economic growth by improving inter-urban connectivity and reducing congestion. Each scheme of the programme must offer acceptable value for money on the orthodox approach to appraisal, yet this approach overstates benefits by underestimating induced traffic and disregards changes in land use made possible by improved access. We need an evidence-based approach to investment appraisal, in which careful evaluation of completed schemes of the kind commissioned by the CPRE informs appraisal of prospective investments.