Last week the NZTA posted this video on their YouTube channel as part of a series talking about motorway works in Christchurch.
Not sure I could have said it better myself.
Last week the NZTA posted this video on their YouTube channel as part of a series talking about motorway works in Christchurch.
Not sure I could have said it better myself.
Last week the Upper Harbour Local Board passed a resolution (below) to try and get Auckland Transport to rip out recently installed cycle lanes near the intersection of Upper Harbour Dr (UHD) and Albany Highway. It’s a section of road that I am very familiar with as I use it regularly when I ride to work.
The cycle lanes along UHD were installed last year and I’ve previously written about how AT removed the existing broken yellow lines (BYLs) when installing the cycle lanes resulting in locals parking in the cycle lanes. This issue wasn’t unique to UHD but something good came from it with AT agreeing to change their policy and mark BYLs on all cycle lanes.
So what’s the problem this time?
This year UHD has been noticeably more congested this year than it has in the past. On the worst day I’ve seen the slow moving queue was over 2km long* although that’s an extreme – I’ve definitely been thankful to have been on my bike and not caught up in that.
Drivers and residents have been complaining to the local board about the congestion and all have taken a correlation equals causation position on the matter. In their view the problems all stem from the creation of the cycle lanes. You can see the old layout on the Google Maps image below where for about 200m prior to the intersection there were two lanes, one for each direction.
And here’s what it looks like now from Streetview. The cycleway extends to the intersection. You can still see the old lane markings.
Here’s what the local board chair told our friends at Bike Auckland:
Even the local Community Constable is blaming the cycle lanes and pushing for the cycle lane to be removed or able to be used by cars.
Below are some observations I’ve made from travelling through here:
By now you might be asking, “but didn’t we just build a parallel motorway, why aren’t people using that?” The image below is from Tauhinu Rd which crosses over SH18 at the southern end of UHD. Like UHD it only seems to have become so congested this year.
This changes the question to “why are both of these routes suddenly seem so much more congested than they were last year?”
The answer to that is actually quite simple, and is one of the oldest reasons in the book – roadworks. For some time now Auckland Transport have been working on Albany Highway and since about the middle of last year that work has focused on the southern section which is the one that most affects traffic to and from the commercial area. Those road works are due to finish later this year. That needs to be completed before any assessment is even considered.
It’s also worth pointing out that traffic isn’t always bad. This was taken last week at the same time and day of the week as the first photos. It was also taken the same day as the image above. The road was empty all the way to the intersection. Perhaps the congestion on UHD was being exacerbated by people trying to use UHD as a rat run to avoid the motorway?
I’ll obviously be watching closely to see how Auckland Transport respond to this request from the local board. It seems to me a case of correlation does not equal causation and if it is decided that the only way to get bike infrastructure is only if it never impacts drivers then it will be a very much longer and more expensive to make any meaningful progress.
* the 2km long queue appeared to be the result of the drivers rubbernecking at the police stopping drivers who travelled through the intersection illegally.
This is a repost from 2013 in the issues with the TomTom congestion report of which the latest version has been released today.
TomTom have once again released their meaningless congestion index.
It’s meaningless for a number of reasons including:
1. It measures the difference in speed between free flow and congested periods. That means cities with lots of all day congestion there isn’t as much of a difference between peak and off peak times and therefore they get recorded as having less congestion.
2. It doesn’t take into account the speeds at which roads most efficiently move traffic – which is not in free flow conditions. This is something picked up on in research conducted for the NZTA by Ian Wallis and Associates
The graph below shows the engineering definition mentioned above.
3. It doesn’t represent all trips on the transport network. We know that even though only about 10% of all trips to work (which excludes trips for education) are made via PT, it still represents a lot of people. For trips to the City Centre more than half of the people arrive by means other than a private vehicle and many of the PT users arrive via the train, ferry or a bus that has travelled along bus lanes. The people on those services or walking/cycling are doing so often completely free of congestion and so their experience isn’t counted.
4. The data only comes from people with a TomTom device and who have obviously had it on. Many people making the same trip on a daily basis or running a regular errand like going to a supermarket are likely to simply leave their GPS systems off. That is likely to distort the overall figures as they may use routes that have less congestion on them than the route the GPS would select.
5. It can disproportionately impact on smaller cities. As an example if you’re in a larger city and have a 45 minute commute however congestion delays you by 30 minutes that equates to a 67% congestion rate however if you are in a smaller city and you’re commute is only 15 minutes and you get delayed by 15 minutes that’s a 100% delay despite the hold up being half of what the bigger city experienced.
It’s starting to get a bit old now however there’s a good piece on the issues with the methodology in this piece from Reuters, some of which is covered above.
Lastly in the email I received about it they also mentioned this
So we have worse congestion than New York, a city where the majority get around by methods other than a car and who in recent years has been reclaiming road space for pedestrians, cyclists and buses. Perhaps we should do more of that.
Lastly if we really want to move people around then then the Congestion Free Network would allow people to do that completely free of congestion giving some real choice.
This is the first half of a two-part series of posts. It summarises a few ideas that have been banging around the back of my head for a while – basically, an attempt to answer the question: “What can economics do for cities?” In this part, I discuss a couple of important concepts: agglomeration economies, which underpin cities’ existence and ongoing success, and the potential role of pricing mechanisms for managing urban ills.
What do cities do?
Cities mean different things to different people. They are places to work, places to play, places to invest, places to consume, places to conduct politics, places to realise one’s individuality, places to blend into the crowd. (And many, many more things beside.)
In fact, one of the features of a successful city is that it can mean different things to different people, and attract and retain them for different reasons. Cities exist because they are efficient and diverse.
Economists use the term agglomeration economies to describe the advantages of urban scale and density. If you operate a business, locating in a city will allow you to access more workers, more customers, and more new ideas. But even if not, an urban location still offers advantages – more restaurants and retailers, a larger dating pool, better access to education and healthcare, and more choices about how to work, live, and get around.
New research from the Netherlands finds that agglomeration economies in both production and consumption are important, albeit to a different extent in different cities. Furthermore, ignoring agglomeration economies is a risky proposition for cities:
In other words, urban success is a dynamic process. Cities can’t stand still – they must be capable of attracting new people and generating new ideas and opportunities. Simply identifying some things that people like about a city and then freezing them in amber is a recipe for long-term urban failure.
1. Incentives and prices matter, so it’s important to get them right
We need change, but we don’t necessarily need change at all cost. Most development is good, but some has deleterious side-effects. A new factory may contaminate local air and water quality. A coal-fired power plant will damage our climate. A new subdivision may pump traffic onto congested roads. A new retailer may attract more people to park on already-crowded streets.
Policy responses to these challenges can heavy-handed and inefficient. While negative (and positive!) spillovers are abundant in cities, some cures may be worse than the disease. A good example is minimum parking requirements, or MPRs, which require new developments to provide a defined minimum amount of parking. The aim of this policy is to prevent parking from spilling over onto neighbouring streets and properties.
Unfortunately, MPRs tend to be both inefficient and ineffective. They are inefficient because (a) there is usually poor evidence for choosing minimum ratios, meaning that many businesses and households are compelled to purchase more parking than they need and (b) they tend to be more costly than alternative approaches to parking management. Furthermore, they are often ineffective, as people continue to complain about a lack of parking even in places where MPRs have led to a major oversupply.
Better pricing is often a better alternative to blunt policy instruments. As any economist will tell you, if you want less of something, put up the price! This approach is applicable to a wide range of policy areas, especially in cities. For example:
There are several important advantages to using prices, rather than regulations or construction, to discourage negative spillovers. First, pricing respects people’s ability to make good choices. If we had a carbon tax, it wouldn’t prevent someone from burning petrol or farming cows. But it would make them pay the full social cost of those choices.
Second, prices can change in response to new information. AT’s new parking policy is a good example of this – they will monitor demand for on-street parking and tweak the prices up if occupancy is too high. This reduces the risk of screwing things up due to forecasting errors.
Third, and most importantly, prices provide governments, businesses, and households better information, which can enable them to make better decisions. Over time, this will result in significant dynamic efficiencies. For example, congestion pricing will help transport agencies plan infrastructure upgrades. Rather than having to guess whether people will value expanded roads – which frequently leads to errors – they will be able to measure the actual value that people place on travel.
Tomorrow: Part 2.
Think Auckland has a congestion problem, take a look at these images from China a few days ago on the Beijing-Hong Kong-Macao Expressway. It’s the result of people heading home at the end of a week long national holiday.
The bottleneck kind of reminds me of this image from Sydney – and which is equally appropriate for another road based harbour crossing
In comments to a recent post I wrote reviewing recommendations from the Australian Productivity Commission’s review of public infrastructure investment, reader Brendon Harre raised an important question about transport cost-benefit analysis (CBA). He commented that:
This is an important issue that’s worth careful consideration. As a best guess, I think that Brendon’s point isn’t quite true. In a roundabout way, transport CBA does capture benefits associated with enabling development. However, the modelling tools available might over- or under-estimate the magnitude of those benefits in some cases.
Let’s start by reviewing how transport CBA works in New Zealand. Here are the key steps:
This procedure obviously bears little relationship to what we observe in practice. In reality, there is significant endogeneity between the availability of infrastructure and land use outcomes. In other words, if you build it, they will come, and vice versa. You can’t assume that land use will remain fixed if transport options change!
Another way of saying this is that rather than “banking” travel time savings from wider or faster roads, people tend to “re-invest” them into other things, such as living in a larger or cheaper house in a different location. (Or re-scheduling trips from off-peak times, shifting modes from PT, walking or cycling, etc.) Public transport is different, as it doesn’t get congested, but the principle is somewhat the same – speeding up journeys allows people to travel more.
Economists call this phenomenon “induced traffic”. I’ve previously discussed this phenomenon from a slightly different angle, focusing on the implications of induced traffic for how we manage and invest in road networks. I’ve argued that we should stop telling ourselves the lie that increased road capacity will ever “fix” congestion and accept that all we can do is give people alternatives to participating in congestion and implement congestion pricing to free up the roads.
However, I think it’s also worth considering what induced traffic means from a housing supply perspective. It’s useful to start by thinking about how individuals might respond to the opportunities created by new transport infrastructure. Let’s use the City Rail Link as an example, as we’ve got a good idea of what it will do for travel times:
Suppose I’m currently living in Morningside (I’m not, but it’s a simpler example) and facing the following costs for transport and housing:
Now let’s consider what will happen when CRL is done. My travel time will be cut dramatically – after CRL, it will only take 15 minutes to commute from Morningside. This is a big saving in travel time. Under these assumptions, CRL will make me better off by around $80 a week (i.e. ~4 hours saved * $20/hour).
However, I’ve also got the option to live further west in search of cheaper housing. Let’s say I choose to move to Henderson, where I pay a bit more in train fares (around $4.80 per trip) and save a bit of travel time relative to my old location. This only makes sense to do if it enables me to save at least $80 in rents for a similar dwelling. Otherwise, moving further out has made me worse off than simply staying in place and “banking” the travel time savings.
What we learn from this example is that the perceived benefits from relocating following the construction of new transport infrastructure, including lower housing costs or better quality housing, should be roughly equal to the added travel time cost of doing so. Economists describe this concept as the “spatial equilibrium” – i.e. people trade off housing and transport costs. As I found when looking at housing and commute costs in NZ cities, we can observe this trend empirically.
(That being said, there are reasons to think that moving further out in pursuit of cheaper housing is not necessarily a great idea. In The Happy City, Charles Montgomery argues that people overestimate the benefits they get from a bigger house, and underestimate the misery of longer commutes. But let’s set aside the impact of cognitive biases for the moment…)
The upshot of this is that, the standard approach to transport CBA actually seems to capture many of the benefits of new housing supply following transport infrastructure development. This sounds perverse – didn’t I say that transport models didn’t reflect reality very well? – but it makes sense when you think about how individuals make decisions about where to live and how to get around.
However, there are two caveats to this point. The first is that individuals don’t internalise all the costs (or benefits) of their location choices – there are externalities. If one location is better at generating positive spillovers in production or consumption (“agglomeration”), cheaper to serve with publicly-funded infrastructure, or responsible for fewer greenhouse gas emissions, it might be better to build infrastructure that will encourage people to live there. This is captured imperfectly in transport CBA at present – but it doesn’t have much of an impact on housing supply.
A second, more subtle issue is that our capital budget may be too constrained to deliver enough transport capacity to enable a sufficient supply of housing. For example, we may be pursuing a costly and land-intensive approach to supplying peak transport capacity that results in diminishing returns from investments. If that’s the case, we need to ask whether we have cheaper opportunities to add capacity to the transport network. (Or, alternatively, start raising taxes, which is always a popular option.)
What do you think about the spatial equilibrium in our cities?
Last week, I took a look at some new research from the Netherlands that estimated the benefits of public transport for car travel times based on data from 13 “natural experiments” – public transport strikes. The Dutch researchers found that PT provided significant congestion reduction benefits – around €95 million per annum, equal to 47% of PT fare subsidies.
While the data was specific to Rotterdam, I’d expect to find similar results in most other cities with half-decent public transport networks. The whole thing got me wondering: Is there any similar evidence from New Zealand?
Fortunately for PT users and drivers, but unfortunately for researchers, potential PT strikes have mostly been averted over the last few years. However, Wellington did experience a “natural experiment” of sorts back in June 2013, when a major storm washed out the Hutt Valley railway line:
The Hutt Valley rail line was out for six days, including four working days. During that period, things got pretty ugly on the roads, as the motorway into downtown Wellington didn’t have enough capacity to accommodate people who ordinarily commuted in by train.
The Ministry of Transport (among others) very cleverly observed that this was a great opportunity to learn something about the impact of PT networks on road congestion. During the rail outage, they surveyed around 1,000 Wellington commuters about their travel experiences. According to their report, they found that:
Essentially, what happened was that a bunch of people who ordinarily caught the train from the Hutt Valley couldn’t do that due to the storm damage. A quick eyeballing of MoT’s graph of daily rail patronage suggests that around 4,000 people had to make other travel arrangements:
Almost half of the rail commuters from the Hutt Valley opted to drive instead, while the remainder chose to take replacement buses or to stay at home instead. This had a serious impact on motorway traffic, as shown on this graph of hourly southbound traffic volumes. On a normal day (the green or blue lines), traffic volumes peak at around 7-8am, and fall off sharply after that.
By contrast, on Monday 24 June, when the rail line was out, people were still travelling in (slowly) until almost 11am. That’s some serious congestion:
Based on survey data, MoT estimated that the storm damage increased average travel times during the morning peak by 0.329 hours (20 minutes) on Friday 21 June, 0.309 hours (18.5 minutes) on Monday 24 June, and 0.230 hours (14 minutes) on Wednesday 26 June. It then used those estimates of average delay for people travelling at peak time to estimate the added cost of congestion that arose as a result of the Hutt Valley rail line outage:
In short, a four-day breakdown in part of Wellington’s public transport network cost morning peak travellers around $2.66 million in lost time. If we assume that there was a similar level of delay during the afternoon peak, when people are commuting out of downtown Wellington, the total cost would be roughly double that – $5.32 million.
This can give us a rough estimate of the value of public transport for congestion relief in Wellington. Extrapolated out over a full year (i.e. 250 working days), these results suggest that the Hutt Valley rail line saves drivers the equivalent of around $330 million in travel time (i.e. $5.32m / 4 days * 250 working days).
That is a very large number. According to an Auckland Transport report comparing Auckland and Wellington rail performance, Wellington’s overall rail network only cost $81.2 million to operate in 2013. 56% of operating costs were covered by fares, meaning that the total public subsidy for the network is around $36 million per annum.
On the back of these figures, it looks like Wellington’s drivers are getting a fantastic return from using some fuel taxes to pay for PT rather than more roads. The travel time savings associated with the Hutt Valley line alone are nine times as large as the operating subsidy for the entire Wellington rail network.
There are two caveats worth applying to these figures, one practical and one methodological.
First, it’s likely that the value of rail for congestion relief is unusually high in Wellington due to the shape of the city. Here’s a map of Wellington’s population density and infrastructure in 2001 and 2013 (from my analysis of urban population density). Dormitory suburbs extend linearly up the Hutt Valley and towards Porirua and the Kapiti Coast. Everyone travelling from those places to downtown Wellington are funnelled through a single transport corridor running along the shoreline of the harbour:
In Wellington, losing the rail line means pushing everyone onto a single road. (Unlike Rotterdam, cycling isn’t especially viable due to the lack of safe infrastructure on this route.) In other cities, there tend to be a greater range of alternative routes, which spreads around the traffic impacts.
Second, these results aren’t as robust as the Rotterdam study, due to their use of survey data rather than quantitative measures of traffic flow and speed. They’re not likely to be totally wrong, but it’s likely that people over- or under-estimated commute times, or that the survey wasn’t representative of all travellers (which could invalidate MoT’s extrapolation to all morning peak travellers).
However, the increasing availability of real-time data on traffic speeds from GPS devices means that the next time this happens, it will be possible to measure the impacts in much greater detail and with greater precision. The Rotterdam study offers some good methodological insight into how best to do that – it looks at transport outcomes at specific locations over a long period of time, and controls for seasonal and weekday effects that may influence transport outcomes.
Lastly, it would be really interesting to see some similar analysis done for Auckland. I’m sure that there have been a number of full or partial rail network outages, either due to bad weather or scheduled track upgrades. Perhaps it would be worth taking a look at congestion on those days.
Auckland may be the most prominent voice when it comes to discussing congestion charging in New Zealand but it appears other cities are keen to join in. Last week it emerged that Wellington are also wanting to look at congestion charging however unlike Auckland where it is being talked about primarily as another revenue source, Wellington say they need it to deal with the after effects of building new motorways.
A couple of thoughts immediately spring to mind.
The last point is displayed very well at the start of this interview on Radio NZ with Paul Swain, the chairman of the Regional Transport Committee who seemed aghast at the slight possibility of not building some new roads. It is also appears to be the attitude that is taken by Wellington City Councillor Andy Foster later in the piece who appeared quite annoyed that the Basin Reserve Flyover was cancelled – and as per this excellent op-ed from Dave Armstrong it appears both were quite keen on it.
I also found Foster’s comments on public transport interesting. He’s obviously correct that Wellington has the highest use of public transport in the country however I’m not sure I would go as far as him in saying that Wellington has a good system. There certainly seems to be a lot more that could be done to make the system better and therefore increase patronage. Many of those are things that Auckland has done or are on the agenda such as integrated ticketing and fares and a better bus network and greater bus priority. I kind of get the feeling that Wellington won’t really wake up and realise how far behind it’s falling until in a few years (at current rates) when Auckland passes them.
Coming back to congestion charging, I was also amused by this press release yesterday by the Property Council which claims that reducing cars in to Wellington would have catastrophic effects.
Perhaps someone needs to tell them that it’s people that buy stuff, not cars. Flooding the CBD with cars will only make it a less attractive place for people to be and therefore they will be less inclined to work and shop there.
Who knows what the outcome will be on congestion charging in either Auckland or Wellington but it’s certainly interesting that both cities are now starting to talk about it much more openly. As has long been the case my personal position is that any form of congestion charging should be designed at least initially to be revenue neutral – substituting rates or fuel taxes. That would give the public a greater level of comfort that it isn’t just a revenue gathering exercise but rather a traffic demand tool. I also think it is something that should be implemented in advance of another wave of road building so we can see the real impact it has before committing billions to construction.
In July, I started taking a look at the economics of public transport fare policies. In the first part of the series, I took a look at how traffic congestion can be a rationale for public transport fare subsidies. (Parts 2 and 3 dealt with different issues.) I observed that:
But how much congestion reduction can we attribute to public transport? How much slower would car commutes be if some people weren’t travelling by PT instead of clogging up the roads? And how much is that worth to us?
It’s not possible to test this experimentally – we can’t exactly build a bunch of cities that are identical except for their PT systems and see what happens. (Transport research budgets are not nearly large enough.) However, we can observe the outcomes from various “natural experiments” that disrupt public transport systems while leaving everything else unchanged, such as natural disasters and public transport strikes.
Stu Donovan pointed me towards a recent research paper that analysed traffic speeds during public transport strikes in the Dutch city of Rotterdam. The authors, Martin Adler and Jos van Ommeren, use detailed traffic flow and speed data to model how 13 PT strikes that occurred from 2001 to 2011 affected traffic speeds. Because strikes prevent people from using PT without impeding road traffic, the outcomes observed during strikes give us some indication of what would happen to congestion in the absence of PT.
If you’re interested in knowing a bit more about the topic or the methodology, I highly recommend you read the paper. (It’s an excellent paper!) Here, I’d like to focus on a few key findings from the analysis.
First, the authors found that PT helps to speed up car journeys by reducing the number of people driving:
Intuitively, these results make sense. The benefits of PT for drivers are much higher in busier areas, such as Rotterdam’s inner city roads. However, Rotterdam’s ring road highways still derive some benefits.
The second interesting finding is that the popularity and ease of cycling in Rotterdam – even though it’s not exactly leading by Dutch standards – cushioned against some of the negative impacts of PT strikes:
In other words, the availability of multiple congestion-free networks – public transport and cycling – meant that the roads didn’t have to accommodate all of the people who couldn’t get on the bus on strike days. In other words, the availability of multiple transport choices enhanced network resilience.
Third, the authors calculated the value of congestion reduction benefits attributable to public transport in Rotterdam. Based on some plausible assumptions about journey lengths and the value of time, they estimate that:
This is a really interesting finding! It puts a monetary figure on the congestion relief delivered by PT. (For Rotterdam, at least.) And, interestingly, it’s a large enough figure to justify a good proportion of PT fare subsidies. There are also other rationales for fare subsidies that I haven’t discussed here, such as social equity for people without cars and various types of network effects in PT provision.
But even if we leave those aside, this finding suggests that drivers should be happy to spend some fuel tax revenues to subsidise public transport.
What do you think about congestion and public transport?
Back in June, Stuff published a report on regional airfares, focusing on the way that prices are affected by major events such as concerts and sports competitions. Now, I’m no airline economist, but I’ve got a general interest in transport pricing so I figured that it would be worth taking a look at the topic.
The point of the article seems to be that airplane tickets are higher during periods of high demand. That doesn’t seem too weird, but this guy in Nelson is absolutely ropeable at the thought:
The man quoted in the article seems to argue that these jumps up in fares are due to uncompetitive or discriminatory practices by Air NZ. By contrast, the airline says that the price increases are just due to cheaper tickets selling out faster:
Now, as an economist I’m always wary of the potential for companies with few immediate competitors to exercise market power over their customers. But in this particular case, I don’t think that’s happening. What we are seeing is the normal, and in fact beneficial, working of supply and demand.
Let’s start with the supply side. Air NZ doesn’t have an infinite budget for airplanes and staff. It faces constraints. If it wanted to run more services between Nelson and Auckland on particular weekends of high demand, it would have to either:
So that’s the supply side. What about demand?
Air NZ has observed, correctly, that demand for flights is not constant over time. Simply put, more people want to fly at some time periods than during others. Airlines can respond to this in a few different ways. The first would be to keep prices constant, regardless of demand. This would turn air travel into a first-come-first served game, which is great if you always buy tickets months in advance but terrible if you have to take a last-minute trip for work or a medical emergency.
The second approach, which Air NZ may be using, is to charge higher prices during periods of higher demand. This may seem less fair, but it’s actually better for (almost) everyone. It means that airlines aren’t constantly booking out flights well in advance or misallocating resources in a futile attempt to give everyone a cheap flight. Travellers also benefit – they get a choice between paying more to travel at their preferred time or finding a cheaper fare at an off-peak time.
I fly for work on a semi-regular basis so I’ve noticed some of the patterns over time. Between 4-6pm, departure gates fill up with suit-wearing men and women headed home from their meetings in time for dinner. Not surprisingly, prices are highest at this time. Later on, prices drop, planes get a bit emptier, and the suits get replaced with casual clothes. By the end of the night, most of the people who want to get home have gotten there, and for a price that they’re willing to pay.
Occasionally, this means that somebody decides not to go to a Madonna concert. But that’s not a flaw with supply and demand – that’s how it’s supposed to work! If the man quoted in the Stuff article didn’t go, it’s only because someone who valued being there more bought the ticket instead.
Finally, I have to ask: Why are people outraged when the principles of supply and demand are applied to airfares? Perhaps it’s because we routinely ignore those principles everywhere else in our transport system.
As numerous economists have observed, we manage our roads like a Soviet supermarket. The price to use roads is set at a single, low value – i.e. NZ’s comparatively low petrol taxes – and thus people queue up for ages to drive on them every morning and evening. The same thing happens with parking, where we have regulated to make it abundant and free and ended up in a situation where people can never get enough parking.
In economic terms, there is no difference between this:
They are both situations in which scarce resources, including people’s time, are misallocated due to poorly-functioning price signals. So rather than asking “why don’t we price air travel as inefficiently as roads?”, we should ask “why don’t we price roads as efficiently as we price airfares?”
A failure to price roads efficiently badly distorts our supply decisions. We are forever pouring more asphalt and concrete that accommodates a few more slowly-moving cars at peak times and sits idle much of the rest of the time. By contrast, congestion pricing would allow us to avoid many of these expenditures by giving people an incentive to travel differently.
What do you think about airfares – and transport pricing in general?