The Auckland Transport Alignment Project (ATAP) report, which was released last week, identified the need to spend more money on transport infrastructure in Auckland. ATAP estimates that we need to spend $24 billion on new transport infrastructure over the next decade, around $4 billion of which would not be funded by current transport budgets.
While $4 billion is a sizeable gap, it’s smaller than previously assumed, due in part to ATAP’s recommendation to defer costly projects like the Additional Waitemata Harbour Crossing. But meeting it will mean raising fuel taxes, fares, rates, general taxes, or implementing congestion pricing to manage demands until funding is available.
ATAP’s obviously identified a need to spend more money on transport infrastructure in the Auckland context. But is spending more money on infrastructure in general a good idea? In other words, should any additional spending in Auckland be balanced by proportionately higher spending everywhere else in the country?
Two prominent American economists, Larry Summers and Ed Glaeser, recently took contrasting views on this question. Summers is most well-known as a policy advisor to Democratic administrations and (in recent years) an advocate of fiscal policy as a cure for long post-GFC recession. Glaeser, on the other hand, is best known for his work on urban economics, including his great book Triumph of the City.
Summers lays out the case for spending more (in the Financial Times). His key argument is that low interest rates signal an underemployed economy where the “opportunity cost” of paying people to build more stuff is relatively low, and that infrastructure spending is a good way to do this as it can enhance a country’s long-run productive potential:
There is a consensus that the US should substantially raise its level of infrastructure investment. Economists and politicians of all persuasions recognise that this can create quality jobs and provide economic stimulus without posing the risks of easy-money policies in the short run. They also see that such investment can expand the economy’s capacity in the medium term and mitigate the huge maintenance burden we would otherwise pass on to the next generation.
The case for infrastructure investment has been strong for a long time, but it gets stronger with each passing year, as government borrowing costs decline and ongoing neglect raises the return on incremental spending increases. As it becomes clearer that growth will not return to pre-financial-crisis levels on its own, the urgency of policy action rises. Just as the infrastructure failure at Chernobyl was a sign of malaise in the Soviet Union’s last years, profound questions about America’s future are raised by collapsing bridges, children losing IQ points because of lead in water and an air traffic control system that does not use GPS technology.
In particular, Summers argues that priority should be placed on funding deferred maintenance, which is a major problem in the US:
What is the highest priority? The fastest, highest and safest returns are likely to be found where maintenance has been deferred. Maintenance outlays do not require extensive planning or regulatory approvals, so they can take place quickly. And they tend naturally to take place in areas where infrastructure is most heavily used.
Glaeser sets out a considerably more skeptical perspective in the City Journal. Contra Summers, he argues that infrastructure spending isn’t a particularly efficient way of getting unemployed people back to work, and that the political incentives facing decision-makers tend to mean that additional funding is misspent in declining areas like Detroit or on projects that don’t do much good:
While infrastructure investment is often needed when cities or regions are already expanding, too often it goes to declining areas that don’t require it and winds up having little long-term economic benefit. As for fighting recessions, which require rapid response, it’s dauntingly hard in today’s regulatory environment to get infrastructure projects under way quickly and wisely. Centralized federal tax funding of these projects makes inefficiencies and waste even likelier, as Washington, driven by political calculations, gives the green light to bridges to nowhere, ill-considered high-speed rail projects, and other boondoggles. America needs an infrastructure renaissance, but we won’t get it by the federal government simply writing big checks. A far better model would be for infrastructure to be managed by independent but focused local public and private entities and funded primarily by user fees, not federal tax dollars.
Glaeser takes more specific aim at the notion that infrastructure investment inevitably generates broader economic returns:
Infrastructure spending is a form of investment: just as building a new factory can boost productivity, laying down a new highway or opening a new airport runway can, at least in principle, generate future economic returns. But the relevant question is: How do those future returns compare with the costs? Just because infrastructure is a form of capital doesn’t mean that spending a lot on it is always smart. When a firm estimates the rate of return for a new factory, it can calculate the expected net profits and compare those with the expense. The analog for, say, new or improved roads is to estimate the benefits to users from reduced travel times, add the likely modest spillover benefits to nonusers, and then subtract the spending needed to construct and maintain the infrastructure. The results can differ significantly across projects. A well-known 1988 Congressional Budget Office survey found that spending to maintain current highways in good shape produces returns of 30 percent to 40 percent—but that new highway construction in rural areas showed a much lower return. A clever study that used firm inventories estimated that the rate of return to new highways was sizable during the 1970s but sank below 5 percent during the 1980s and 1990s.
The existence of plausible transportation alternatives and the law of diminishing returns have also tended to reduce the benefits of infrastructure investment over the past two centuries. The opening of the Erie Canal in 1821 brought enormous value because the inland transportation options at the time were dismal. In the early nineteenth century, it cost as much to ship goods 30 miles over land as to send them across the entire Atlantic Ocean. Yet the very existence of canals, as much of a breakthrough as they represented, reduced the benefits of the later rail system, as Nobel economist Robert Fogel has shown. The returns for new transportation infrastructure in places with terrible roads, such as much of Africa and India, will be much higher than in the United States, which already enjoys an impressive, if under-maintained, array of mobility options.
While Summers and Glaeser take different views on the value of spending more money on infrastructure, there are some important points of agreement, such as:
- Prioritising maintenance spending to replace or upgrade run-down infrastructure
- Better cost benefit analysis to ensure that money is being spent in more beneficial ways
- Where appropriate, funding new infrastructure more from user charges and fees, rather than general taxes.
Lastly, it’s worth asking whether these issues look different in New Zealand than in the United States. I don’t have a complete answer to this, but in previous posts I have looked at the issue of infrastructure spending from a variety of perspectives. For instance, I’ve asked:
On balance, I’d say that those posts present a moderately skeptical view of the case for significantly ramping up transport investment – ie more in line with Glaeser’s view than Summers’. That’s not to say that we shouldn’t spend a bit more, but any additional spending should be backed by robust analysis.
What do you think about infrastructure spending? More or less?
This is the second post in an ongoing series on the politics and economic of zoning reform. The first part looked at the costs, benefits, and distributional impacts of reforming urban planning rules to enable more development. This part takes a more specific look at the most recent reform to Auckland’s planning system: the Unitary Plan.
Now that the hearings are over, the submitters have been heard, and the politicians have voted, it’s worth asking: What have we gotten from the Unitary Plan? Does it take us in a useful direction, and to what degree?
In order to give a coherent answer to this question, I’m going to have to simplify matters. The UP does a lot to regulate development and local environmental issues – addressing everything from air quality to zoning for factors. But it has the strongest effects are on the city’s housing market. The UP shapes how much housing can be built, where it can be built, and how easy it is to get permission to build it.
Consequently, I’m going to focus on the impact of the Unitary Plan on people’s ability to build more homes in the city. Zoning capacity isn’t the only thing that matters, but it’s important. Cities that have “downzoned” severely, like Los Angeles in the 1970s and 80s, typically experience rising housing prices, while cities that “upzone” significantly, like Tokyo in the 1990s, tend to have an easier time keeping prices under control.
The great down-zoning of LA (Morrow, 2013)
In order to estimate the UP’s impact on Auckland’s capacity to build more homes, I’m going to draw upon “capacity for growth” modelling produced by Auckland Council and subsequently updated throughout the hearings process. As changes to the modelling methodology make a like-for-like comparison a bit difficult, I’m going to have to piece together the overall results.
The 2012 Capacity for Growth Study estimated the number of homes that could be built under the legacy zoning rules that were put in place prior to Auckland Council amalgamation. The modellers estimated a measure of “plan-enabled capacity” – i.e. the total quantity of housing that could be built within the city if everyone (re)developed their site to the maximum permitted under the zoning rules.
This is obviously an implausible scenario, as many people won’t choose to redevelop, at least for a while. So the results are best thought of as a theoretical upper bound rather than a realistic estimate of what would happen in practice. As we’ll see, this was addressed in subsequent modelling undertaken during the hearings.
With that caveat in mind, the modellers found that the legacy zoning rules allowed between 250,000 and 345,000 additional dwellings to be built in Auckland. The lower number reflects the maximum capacity for infill development, while the higher number reflects the maximum capacity for redeveloping residential sites.
The 2013 Capacity for Growth Study used the same methodology to assess the version of the UP that was notified by Auckland Council after consultation on the plan. This showed that the notified UP had only made incremental increases to infill and redevelopment capacity within the city.
The modellers found that the legacy zoning rules allowed between 258,000 and 417,000 additional dwellings to be built in Auckland. The lower number reflects infill capacity, while the higher figure reflects redevelopment capacity. However, it also noted future greenfield areas with capacity for around 90,000 additional dwellings.
Taking the greenfield areas into account, the notified UP would have delivered a 39-47% increase in capacity for housing, relative to the legacy zoning. That difference is shown in the following diagram. Essentially, the Unitary Plan as originally conceived would have been at most an incremental improvement.
Things get a bit more complex when comparing between the notified UP and the final version of the UP that was recommended by the Independent Hearings Panel and approved (with minor tweaks) by Auckland Council. The modelling methodology changed in the course of the hearings, with the focus shifting from “plan-enabled” capacity to “commercially feasible” capacity. In effect, a new model was built to filter out sites that wouldn’t be profitable to develop.
The result was the final numbers presented in the Independent Hearings Panel’s report (and covered, somewhat hyperbolically, by the Spinoff) are lower – but considerably more realistic – than the figures reported in the Capacity for Growth Studies.
You can see that in the following chart. The commercially feasible capacity enabled by the notified UP is 213,000 additional dwellings – only 42% of the full plan-enabled capacity.
The key thing in this chart is the change between the notified UP and the final UP. Feasible capacity has increased from 213,000 to 422,000 dwellings, or a 98% increase. Most of the increase in capacity comes from within existing residential zones, thanks to rezoning and changes to zoning rules to allow people to build more dwellings on the same amount of land.
So if we squint a bit, we can put these estimates together to get a rough picture of the overall outcome:
- The notified UP increased plan-enabled capacity by 39-47% relative to the legacy plans
- The final UP increased feasible capacity by 98% relative to the notified UP
- This implies that the final UP has increased the zoning envelope by around 175-190%, relative to the legacy plans (i.e. 1.98*1.39 to 1.98*1.47).
Equivalently, if we assume that only around 42% of the plan-enabled capacity under the legacy zoning plans would be commercially feasible (a similar ratio to the notified UP), we can put together the following chart:
Is this sufficient? Time will tell. Getting housing, transport, and place-making right for Auckland doesn’t end with a planning rulebook. But the final UP is undoubtedly a large step away from the broken status quo.
As this is a series on the economics and politics of zoning reform, I want to close with a few simple observations that arise from the quantitative analysis in this post.
- The incremental changes observed between the legacy plans and the notified UP reflect the outcome of a political process. Council put out a draft plan for consultation, and then pulled back a lot of the changes in response to criticism.
- The considerably larger changes between the notified UP and the final UP arose from a technical process – the independent hearings.
- Although the IHP recommended, councillors decided. The final UP was voted up by many of the same councillors who had pulled back to a more conservative position three years before.
This in turn raises two questions that I will revisit in future posts in this series. First, why did the political process deliver a more conservative outcome than the technical process? And second, what changed between 2013 and 2016 to obtain a different outcome from the council votes on the plan?
What do you make of these figures?
This is the first part in an open-ended series on the economics and politics of zoning reform. The Unitary Plan decision means that Auckland’s urban planning framework is set for the short to medium term – albeit with inevitable appeals and changes. But the issues we’ve been grappling with over the past few years – i.e. how, where, and why to adjust the rulebook – will keep coming back. A growing city must also be a continually changing city, and zoning decisions can either help or hinder that.
A good starting point for thinking about the economics and politics of zoning reform is to ask: What are the costs and benefits of allowing more housing to be developed? And how are these costs and benefits distributed?
I investigated these questions in a conference paper at this year’s New Zealand Association of Economists. Without getting into the numbers, we can identify three main effects:
First, the benefits of new housing primarily accrue to people who are newly entering the housing market. For instance, young people trying to buy or rent a home benefit from there being more homes, as it means they can get better housing or cheaper housing. Equivalently, restrictions on new housing development mainly impose costs on people who don’t already own homes. When the supply of housing is restricted, then they face a choice between paying more for housing that meets their needs, living in substandard or crowded housing, or leaving the city entirely.
Second, the costs – adverse effects – of new development are location- and context-dependent. The distributional impacts – who is affected? – can also vary quite a lot. For instance, a new subdivision on the city fringe probably wouldn’t shade anyone’s home or block its view, but it might worsen water quality or biodiversity. And, given the dysfunctional way we build new suburbs, it will definitely increase traffic congestion.
By contrast, redevelopment and infill within the city will tend to have fewer environmental impacts – it’s already a city! – but there are more neighbours who may be affected by the various nuisances associated with development, like having new buildings casting shade on adjacent properties or more people parking on “their” street. People don’t like change very much… but they can easily adjust to different “status quo” scenarios.
For instance, consider Ponsonby. It would all be horribly illegal under today’s zoning codes. Lot sizes too small, buildings too close to each other and taking up too much of the lot, no parking, etc, etc. If you tried to get houses like these consented today, especially in an existing suburb, you’d be refused in about three seconds flat. But because they’ve been there for decades, people see them as something that should be protected – present-day zoning code be damned!
Third, enabling housing development can allow cities to grow larger and in a more economically efficient pattern – leading to enhanced agglomeration economies. The benefits of increased productivity and greater consumer choice accrue broadly to most people in the city, or potentially even to the entire country. (Taxes paid in Auckland pay for retirements in Tauranga!)
Conversely, evidence from overseas cities suggests that restricting housing supply can result in large economic costs as a result of the misallocation of workers throughout space. For instance:
- In the US, Chang-Tai Hsieh and Enrico Moretti found that high housing costs have discouraged people from getting jobs in high-productivity cities – in particular New York, San Francisco, and San Jose. If those cities had allowed more homes to be built over the past three decades – which would have entailed more intensive development – the US economy would now be 9.7% larger than it actually is, with commensurate gains in income.
- In the Netherlands, Wouter Vermeulen and Jos van Ommeren found that housing supply, not productivity or availability of jobs, has driven cities’ growth. Rather than moving to locations with abundant high-income jobs, people move to places with more homes – again, with a cost to overall economic outcomes.
As Matt Yglesias observed, agglomeration economies benefit workers with different skills… provided that they can afford to locate in high-productivity cities:
…just as factories served as economic anchors for regions, today’s big industries produce broader local prosperity.
Here are some examples from the San Francisco area:
The problem is that for most residents of these places, the higher cost of living erodes the benefits of higher pay.
So how does all this add up? There are two answers. The first is that the benefits of urban development tend to outweigh the costs… provided that it isn’t happening in a totally dysfunctional way, like paving over the habits of endangered birds or building astonishingly unredeemable eyesores. In other words, the benefits for people who are getting housed, plus increased agglomeration economies, outweigh the costs from negative social or environmental impacts. So from the perspective of long-run social wellbeing, zoning that enables more development seems like a good idea.
The second answer is that the distributional impacts tend to determine the politics of zoning. As economist William Fischel observed, local governments tend to be dominated by “homevoters” who are mainly worried about risks to their property values and quality of life. In this context, the fact that enabling urban development mostly has benefits for new entrants to the housing market – i.e. young people and people moving into the city from elsewhere – is pretty important.
As economists like to say, the incentives facing local government voters aren’t well aligned with long-run social wellbeing. To current voters, zoning reform isn’t necessarily an appealing proposition. It appears to create uncertainty for their neighbourhood and property values, while principally benefitting other people.
This is a very understandable view for individuals to hold, but it’s not awesome for society as a whole. If cities and economies don’t change, they wither and die, creating vast human misery in the process. In order to prevent that from happening – i.e. to keep people from crowding into unsanitary accommodation or going homeless – we need to be willing to reform our zoning policies.
In the subsequent posts in this series, I’m going to take a look at what that might look like. In the first instance, I want to focus on the institutional arrangements that enable reform, considering issues like:
- The trade-off between localised and centralised decision-making
- The good and bad in New Zealand’s legislative framework
- The role of analysis and evidence in planning decisions
- The role of social norms in encouraging (or discouraging) people to plan for future generations.
As always, leave your views in the comments.
Is Auckland abnormally congested?
I occasionally hear people bemoaning that Auckland is one of the most congested cities in the world, or at least one of the most congested cities for its size.
I’ve previously taken a look at this from a few angles – looking at trends in traffic delay in Auckland and average commuting time in large cities around the world. Auckland looks pretty good on the latter measure, which kind of belies the “most congested city” rhetoric:
For another look at the same issue, we can take a look at data on traffic delay in cities across New Zealand and Australia.
Helpfully, the Australian Bureau of Infrastructure, Transport and Regional Economics (BITRE) publishes data on the cost of congestion in large Australian cities. They measure congestion as the amount of traffic delay that could feasibly be avoided without reducing the overall value that people get out of travelling.
Unfortunately, comparable figures aren’t available for New Zealand cities. The Ministry of Transport tracks delays in traffic, but doesn’t make monetised estimates of avoidable congestion costs. However, it isn’t that hard to make a reasonable estimate, if you combine MoT’s traffic delay statistics (average delay of 0.52 minutes per kilometre in March 2014, but less in the November survey) with their data on the total amount of vehicle travel in Auckland (12.7 billion vehicle-kilometres driven in 2014).
Following BITRE’s approach, I’ve assumed that avoidable congestion is about 55% of total delay – reflecting the fact that many people prefer to travel even on congested roads. I then monetised the total delay-hours using NZTA’s standard figures for the value of travel time (around $23.40 in 2015 dollars) and converted between Australian and New Zealand money. After mixing in some data on city population in Australia and New Zealand, I got the following chart:
Each individual point is an observation from a single city in a single year – so it’s possible to see how congestion has evolved over time in each city. We can immediately see three important things from this chart.
The first is that Auckland is right on the trend-line. We have the congestion levels that you’d expect to see in an Australasian city with 1.5 million residents – right between Adelaide and Perth. So once again, there are no signs that Auckland is particularly exceptional in the traffic congestion area.
The second is that congestion is a nonlinear phenomenon – it increases faster than city size. You can see that in the upward-sloping trendline fitted through the points on the graph. On average, in this sample of cities, a 10% increase in population is associated with around a 13% increase in congestion levels.
What that means is that new residents entering the city experience the average congestion levels in the city – 10% of that 13% increase – and also have a (relatively small) negative impact on congestion for existing residents – the remaining 3% increase.
The third is that, setting aside the average relationships across all of the cities, individual cities appear to follow slightly different trends. For instance, while Perth and Melbourne have followed the trend-line pretty closely, there seems to be a steeper relationship between congestion and population size in Adelaide and Brisbane.
That suggests that urban policies – land use, transport investments, etc – can enable some cities to grow in more or less efficient ways. Which specific urban policies are better or worse is a bit of a vexing question – but there does appear to be something there.
What do you make of the data on congestion costs in Australasian cities?
Who benefits from enabling housing development? And who bears the costs of restricting it?
One common refrain is that reducing regulations to enable housing will deliver higher profits to developers, while disadvantaging existing homeowners, who must contend with more people living in the neighbourhood. Another view is that restricting housing supply primarily benefits existing homeowners, who earn (untaxed) capital gains, while disadvantaging people who don’t own homes.
Along with Fran O’Sullivan, Arthur Grimes, Bernard Hickey, and many other commentators, I tend to agree with the second viewpoint: The primary distributional impact of restrictions on housing supply is to benefit existing homeowners at the expense of future homeowners. In this post I will argue that 1) we face a choice between existing and future home owners and 2) profits from development pale in comparison to untaxed capital gains on property.
So if you’re concerned about rampant profiteering, then you should be in favour of enabling more housing development.
Profit, homeowners, and false dichotomies
Developers undoubtedly set out to make a profit. They are after all putting their own time and money into building something, which in the process exposes them to risks. In this context it seems reasonable that they get something in return, otherwise, why would they develop housing at all? Whether developers earn a reasonable profit then effectively comes down to competition, and the best way to encourage competition is to enable lots of people to be developers.
In general, the more we restrict and regulate the supply of housing, then we will get less supply and less competition.
Those who rally against developers making profits seem to ignore that most of Auckland’s existing housing stock resulted from profit-seeking developers. This includes many houses that are now protected for heritage reasons. So it’s not clear to me that simply because developers are look to make a profit today, that the resulting developments will not be valued.
It is certainly fair to say that developers will only able to make a profit from development if they build something that people are prepared to pay for today. This is another way of saying that developers must consider their customers , i.e. people who want somewhere to live. So it strikes me as a false dichotomy for people to argue that developers “put profit before people”: If developers didn’t meet the needs of at least ***some*** people, then they wouldn’t make a profit.
Instead, the main trade-off seems to be between existing and future homeowners. I think Arthur Grimes described the trade-off best when he said (source):
My call for policies to drive a house price collapse is driven by my personal value judgement that it’s great for young families and families on lower incomes, to be able to afford to buy a house if they wish to do so. My concern is not for older, richer families, couples or individuals who already own their own (highly appreciated) house.
In this quote Arthur observes that we primarily have a choice between existing homeowners and future homeowners. He doesn’t mention developers at all. So when councillors vote for regulations that restrict housing supply, they are effectively voting in favour of existing homeowners. This is fine, provided they are comfortable with adopting what I consider to be a typically conservative position. These councillors are, in effect, behaving like Tories; they are protecting those who already have wealth.
The effects of restricting supply: Dislocation and rampant profits
However, building new homes isn’t the only – or even the main – way to make a profit in Auckland’s current housing market. Due to restricted housing supply, we aren’t building enough homes to meet demand. As a result, prices have risen.
Rising prices has two primary effects. First, it squeezes low-income people out of the market. This is a well-documented phenomenon. As the California Legislative Analyst’s Office found in an analysis of the San Francisco Bay Area, suburbs that developed less housing experienced more displacement. Without new housing development, every new resident must displace an existing resident – a vicious dynamic that hits low-income households hardest:
A lack of housing supply is compounded by distortionary tax policies – principally our unwillingness to tax unearned capital gains on housing – with the result that house prices are going up at a fast clip. This provides an unearned, untaxed capital gains windfall for people who are lucky enough to own property.
Unearned capital gains, unlike developer profits, are a win-lose scenario. People who own houses win, as the value of their assets rise. But people who are renting or trying to buy a home lose to an equal extent, as they face higher and higher prices.
So how large are capital gains compared to developer profits, anyway?
In recent years, untaxed capital gains on residential property have been very large relative to developer profits. According to data from the Reserve Bank, untaxed capital gains on residential property exceeded $100 billion last year:
- In the first quarter of 2016, the total value of residential property in New Zealand was $905 billion
- One year earlier, the value of residential property was only $791 billion.
By comparison, according to Statistics NZ’s most recent (2014) Annual Enterprise Survey, which tracks industry performance, residential housing construction firms (ANZSIC E301) made gross, before-tax profits of a mere $570 million. Even if we add in “other construction services” (ANZSIC E321, E322, E323, E324, and E329), which includes land development firms as well as a whole bunch of other stuff, total residential development profits add up to no more than $2 billion a year, before tax. And developers pay taxes on those profits! For the visual learners out there, here’s the data in a chart:
In other words, the profits that developers earn are relatively insignificant compared to the unearned, untaxed capital gains that have accrued to property owners. I would argue that the latter are largely the result of regulations that restrict housing supply, and hence represent a transfer from future homeowners, and to a lesser degree developers, to existing homeowners.
So what’s the takeaway message from all this? Well, if Councillors like Mike Lee and Cathy Casey are concerned about profiteering in New Zealand society (and they say they are), then they should start pushing to enable more housing development in Auckland. Yes, developers may make slightly more money in the process, but this increase pales in comparison to the reduction in untaxed capital gains that would accrue to existing home-owners. If you’re concerned about people making unearned profits, then regulations that restrict housing supply and which drive up the prices of existing dwellings should be your primary target.
The inclusion of congestion pricing in the recent Auckland Transport Alignment Project interim report has (helpfully) reignited the public debate on the topic. Transportblog’s authors have been pretty enthusiastic about the idea – see e.g. Stu Donovan’s posts on the topic.
But the announcement also raises some questions. For example, congestion pricing is certainly a good idea in principle, but could we put it into practice in Auckland without unintended consequences? And would people in Auckland get on board with it?
So I thought I’d open this up to readers: What do you think the preconditions are for congestion pricing in Auckland? In other words, what would we have to do in order to make the scheme work?
I have my own thoughts on the matter, but rather than putting them forward I thought I’d summarise some of the main things that come up in discussions. I’ve left aside the exact design and technical feasibility of congestion pricing – for now, let’s just assume that it’s going to be possible to implement a GPS-based pricing system that allows for variable tolls between different roads and time periods.
1. We don’t need to do anything else.
Some people argue that congestion pricing will work without any further changes to transport infrastructure or services. Stu, for example, put forward this case the other week.
The argument in favour of this view is that congestion is typically very concentrated in peak periods due to bottleneck delay, and that encouraging people to take some trips a bit earlier or a bit later will benefit the overall transport network without imposing large costs on people who re-time journeys to avoid tolls.
2. We need to provide more public transport infrastructure and/or walking and cycling options before implementing congestion pricing.
A second common view is that we need alternative, non-driving transport options in place prior to congestion pricing. Reasonable people could disagree on what would represent enough alternatives, but I’d suggest that a reasonable aspiration would be:
- Bus routes that cover most of the city, with reasonable frequency
- Spare rapid transit capacity through key pinch points such as the Auckland Harbour Bridge and Panmure Bridge
- Cycle lanes running on or parallel to many urban arterials.
The argument in favour of this view is that it is unfair to ask people to pay a toll without giving them options for avoiding it. In that respect, it conflicts a bit with the first view, which holds that people will have the option of re-timing trips to avoid tolls.
3. We need to use the revenue from congestion pricing to improve transport infrastructure and services on busy corridors.
A third view is that we should spend any additional revenues from congestion pricing to build additional transport infrastructure. Some people argue that this should be more roads, while others argue for public transport.
It seems a bit perverse to implement a demand management measure (congestion pricing) and then turn around and spend more building infrastructure. However, the argument in favour of this view is that congestion pricing will give us a better indication of which corridors have high economic value – as evidenced by higher tolls – and hence that investment is needed to allow more people to use them.
4. We should “recycle” additional revenue from congestion pricing into lower taxes or rates.
Another view on what to do with the revenue from congestion pricing is that it should be returned to households. In other words, the scheme should be “revenue neutral” on the whole.
There are two main ways to do this:
- Lowering income taxes, which will (all else equal) enhance incentives to work while discouraging car commuting at peak times
- Distributing money equally to households, through lower uniform charges in the rates bill or AECT-style dividends.
The argument in favour of the first approach is that it will tax “bads” (i.e. excess congestion) while rewarding the “goods” (i.e. working). The second approach doesn’t improve incentives to work – people would get the money regardless of whether they are working or not – but it would ensure that every household had an additional chunk of money that they could choose to save, spend, or use to offset the cost of tolls.
5. We should liberalise residential and business zoning rules alongside implementing congestion pricing.
Separate from what to do with the revenues, another view is that it would be necessary to change our approach to land use planning in order to get the best result from congestion pricing.
The argument in favour of this view is that congestion pricing would influence people’s decisions about where to live and work. In other words, some people may choose to move closer to work to avoid paying tolls, while others would prefer to move further out of town to take advantage of faster drive times. However, zoning rules that, for example, held up intensification around employment centres may prevent this from happening.
6. We don’t need congestion pricing in the first place.
Finally, some people argue that congestion pricing is unnecessary. There seem to be two main reasons why someone may hold this view:
- Contrary to popular perceptions, Auckland’s not really congested enough to need congestion pricing
- If we just got on and built a lot of roads, like, immediately, traffic would flow smoothly and there would never be any congestion ever again.
The first reason seems to have at least some evidence supporting it, but the second evinces an insane disregard for basic economics (induced demand), financial realities, and the laws of geometry.
Leave your views in the comments, or answer the following poll:
More commentary on this later on, but for now I’m just going to drop in some data.
Former Reserve Bank chair Arthur Grimes commented last week in The Spinoff:
In March 2016, the REINZ Auckland median house price reached $820,000. Four years previously, it was $495,000 – that’s a 66% increase in 4 years. What’s more alarming is that in 2012, many people considered that house prices were already getting out of reach for most people. That was particularly the case for young people and low income earners.
That extraordinary increase – coupled with the already high level in 2012 – was behind my call to a recent Auckland Conversations event that policy-makers should strive to cause a 40% collapse in house prices to bring the median back to around $500,000.
This sounds like a bit of a crazy idea. But the even crazier thing is that it’s happened before.
In the early 1970s, New Zealand experienced a rapid increase in house prices caused by, among other things, a swift run-up in immigration and a shortage of builders and building materials. Between 1971 and 1974 real house prices increased by 60%. This caused alarm, and the government responded by loosening planning controls to allow more flats to be built in cities. Then the 1973 oil shock hit, net migration turned negative, and the economy entered into a prolonged slide. (Thanks Muldoon!)
From 1974 to 1980, house prices fell by around 40% in real terms. By the end of the decade houses were no more valuable than they had been at the start. That’s shown in the following graph, which I’ve compiled from Reserve Bank data on long-run house prices and consumer price inflation.
In principle, the same thing could happen today, given the right confluence of supply and demand shocks. But there’s an important difference between the 1970s and the 2010s: consumer price inflation.
Back then, overall price levels were inflating at double-digit rates. As a result, all that it took to get house prices back in line with wages (and prices for everything else) was for them to stand still for a few years. In dollar terms, house prices actually held constant from 1974 to 1980, while prices for everything else increased around them.
Today, consumer price inflation has dropped to almost zero. This means that getting real house prices back in line with incomes, at least in the short term, will require prices to fall in dollar terms. That is, understandably, a scary prospect for politicians, bankers, and homeowners. But it could happen.
Congestion pricing has once again hit the political radar, with the news that the Auckland Transport Alignment Project has recommended it as an option to more efficiently manage the transport network. They find that variable road tolls – highest during peak periods on busy roads and low (or even zero) at off-peak times – are the single most effective intervention to improve traffic flow.
On the whole, it looks like support for the idea is on the rise, which is positive. That suggests that the work that Auckland Council’s consensus building group did a few years back has contributed towards a better public conversation on the issue. That’s good, as it’s a challenging idea to sell to people.
The NZ Herald’s editorial on the topic was tentatively supportive and showed a reasonable understanding of the core principles of congestion pricing:
Transport Minister Simon Bridges conceded this week, “we can’t keep building new lanes on highways. We will need a combination of demand-side interventions if we are going to deal with congestion over the next couple of decades”. He prefers the term “demand-side interventions” to taxes, tolls or charges but those are what it means.
Unlike the council, the Government does not advance these for revenue raising but for reducing traffic on the roads. It clearly thinks road rationing is more politically acceptable than revenue raising and the AA agrees. Feedback from members, it says, showed support for tolls as long as people could be convinced it was for congestion benefits, not simply revenue.
However, the Herald’s editorial also exhibits a common misunderstanding about congestion pricing, arguing that free routes must be available as an alternative to tolled routes:
The joint report for the council and the Government this week did not suggest how road travel might be charged. Mr Bridges said one option was to track all traffic with GPS technology which is being trialled in Singapore and Japan. But that implies no roads would be free at times the charge applied. Travel is a basic freedom. We could welcome the chance to pay to use a fast lane when we need one, so long as free lanes remain.
The Herald’s position is basically in line with NZTA’s existing tolling policy, which states that:
…a road tolling scheme may be established to provide funds for the purposes of one of more of the following activities, namely, the planning, design, supervision, construction, maintenance, or operation of a new road, if the Minister of Transport is satisfied that:
- the relevant public road controlling authorities (including the Transport Agency) have carried out adequate consultation on the proposed tolling scheme;
- the level of community support for the proposed tolling scheme is sufficient;
- if an existing road is included in the scope of the tolling scheme, it is physically and operationally integral to the new road in respect of which the tolling scheme will be applied;
- a feasible, untolled, alternative route, is available; and
- the proposed tolling scheme is efficient and effective.
However, I think that both NZTA and the Herald are being too hasty in assuming that the untolled alternative route has to run parallel to existing roads. Alternatives can exist in time as well as in space.
Stu Donovan described the maths behind this last week. Transportblog reader Bryce Pearce also dug up a good practical example: apparently Singapore’s road pricing scheme allows people to travel for free most of the day. For example, if you are trying to drive on Lorong 6 Toa Payoh at 8:30am, you’ll have to pay $1. But if you leave an hour earlier or an hour later, you won’t pay anything:
ATAP took a similar approach when choosing how to model congestion charges. As the following diagram shows, the ATAP scheme would increase peak and inter-peak pricing, relative to current fuel taxes, but decrease charges in evening periods. Consequently, people would have options to save money for certain types of trips, for example, by shifting supermarket trips from the afternoon to the evening:
Arguably, being able to travel for free on the same road, at a slightly different time, is even better than being able to travel for free on a different, more circuitous road at the same time.
There are obvious user benefits to the approach of varying tolls by time of day. It allows people to make better choices that respect their individual preferences for time, timeliness, and money.
But there are also important system-wide benefits from variable tolls between different time periods. Because congestion can be quite sensitive to changes in the number of cars on the road at a given time, encouraging even a relatively small number of people to shift the time at which they travel can lead to large benefits.
That’s nicely illustrated in the following graph of Auckland Harbour Bridge traffic volumes. The AHB is essentially free-flowing during the middle of the day, when there are around 1300 vehicles per lane per hour. But it is considerably slower during the evening and morning peaks, when the bridge carries more like 1500-1700 vehicles per lane per hour.
Because the peakiest bits of the peak are relatively short – perhaps 2.5 hours in total across an average weekday – you could improve the performance of the bridge by charging tolls during a few short windows. People could still travel for free (or at any rate a lower price) during the remaining 21.5 hours of the day.
From my perspective, that’s a pretty good alternative for drivers! But what do you think about the issue?
In the 1990s, in the early years of the information technology revolution, economist Robert Solow famously commented that “you can see the computer age everywhere but in the productivity statistics.” Two decades on, that still rings true. Social life has been profoundly transformed by new technology: It has altered the way we communicate with friends and family, how we entertain ourselves, and even how we date.
When I read Douglas Adams’ Hitchhiker’s Guide to the Galaxy in the early 2000s, the titular device still seemed like a fantastical idea: a handheld device you could use to access information (much of it inaccurate or incomplete) on anything, from anywhere.
Now, we all have smartphones. But productivity growth has stubbornly failed to take off over this period. Does this mean that technological progress has failed to deliver?
Journalist Ezra Klein (Vox) recently reviewed the current debate over technological progress. One perspective he discusses is that the benefits of information and communication technologies (ICTs) have largely accrued to consumers rather than producers:
Measures of productivity are based on the sum total of goods and services the economy produces for sale. But many digital-era products are given away for free, and so never have an opportunity to show themselves in GDP statistics.
Take Google Maps. I have a crap sense of direction, so it’s no exaggeration to say Google Maps has changed my life. I would pay hundreds of dollars a year for the product. In practice, I pay nothing. In terms of its direct contribution to GDP, Google Maps boosts Google’s advertising business by feeding my data back to the company so they can target ads more effectively, and it probably boosts the amount of money I fork over to Verizon for my data plan. But that’s not worth hundreds of dollars to Google, or to the economy as a whole. The result is that GDP data might undercount the value of Google Maps in a way it didn’t undercount the value of, say, Garmin GPS devices.
As Klein goes on to observe, ICTs have transformed our leisure time more than our work time – in large part, by giving us many more choices about where to dine, what television shows to watch, and who to talk to.
Interestingly, what’s true for technology might also be true for cities. The conventional narrative about agglomeration economies – the economic benefits of scale and density – is that their main effect is to lift productivity. But, as Stu and I have discussed in the past, there’s an increasing body of evidence that suggests that agglomeration also has significant benefits for consumers.
In recent years, economists have used micro-data on household consumption patterns to build a much richer picture of the impact of city size and structure on consumption choices. In short, larger cities don’t always offer lower prices – as you’d expect if higher productivity made it cheaper to produce goods and services. But they do offer a much greater variety of goods and services, which in turn translates into higher wellbeing for households.
A 2015 paper by Jessie Handbury and David Weinstein uses barcode data on retail sales in 49 large US cities to analyse prices and product varieties. They find that:
There are approximately four times more types of grocery products available in New York [metro population 21 million] than in Des Moines [population 456,000].
Because people in larger cities tend to buy a wider range of goods, including more expensive products, a naïve comparison of average retail prices would suggest that larger cities are more expensive. But Handbury and Weinstein’s analysis shows that, after accounting for product variety, prices in large cities are no more expensive than smaller cities. If anything, they tend to be lower:
When we use the data to construct a theoretically rigorous price index that corrects for product, purchaser, and retailer heterogeneity and accounts for variety differences across locations, we find that the price level is actually lower in larger cities. Consumers spend less, on average, to get the same amount of consumption utility in larger cities.
Moreover, what’s true in grocery stores is also true in restaurants. In a 2012 paper, Nathan Schiff took a look at the impact of city size and population density on restaurant markets in 726 urban places in the US. His key finding is that:
For the 182 cities in the top quartile by land area of my data (mean population 331,000), a one standard deviation increase in log population is associated with a 57% increase in the count of unique cuisines. A one standard deviation decrease in log land area–which increases population density without changing the size of the population–is associated with a 10% increase in cuisine count, equivalent to increasing the percentage of the population with a college degree by one standard deviation and larger than the effect of increasing the ethnic population associated with each cuisine by one standard deviation.
In other words, cities that are larger or denser offer people more choices about where and what to eat. Density is especially crucial in large cities, as people generally don’t travel long distances to dine. (Incidentally, relatively open migration policies are also an important enabler of restaurant choice in cities, as migrants bring new cuisines with them.)
What does this mean for urban policy? I think there are two main lessons.
The first is that although agglomeration economies in production are important to long-run economic outcomes, we might be looking for the benefits of cities in the wrong places. They might not always appear in productivity statistics or price indices, but in the consumption choices that cities offer people. Measuring variety – and how people respond to it – is therefore crucial to understanding agglomeration economies.
The second is that conventional urban policy might be based on false premises. Ever since the “dark Satanic mills” of the Industrial Revolution, policymakers have assumed that cities are good for businesses but bad for people. Accordingly, they designed transport systems and planning policies that aimed to disperse the city and to separate people from their workplaces and from each other.
That made sense when cholera was a major cause of death, but it’s increasingly illogical in today’s world. Urban disamenities such as air quality, crime rates, and infectious diseases are all improving, and the evidence increasingly shows that the consumer choices offered by cities (and dense urban places) have benefits for households. In this context, policies that enable urbanisation are likely to have larger benefits than commonly assumed.
What do you think about the role of consumer choice in cities?
Housing is a normal good. That is, it’s something that people tend to want more of as their incomes increase.
“More” doesn’t necessarily mean “larger”. People do tend to prefer larger homes as they get wealthier, but that’s not the only thing that matters. They may be willing to compromise on space in exchange for a higher-quality living space – bring on the granite countertops! – or a home in a better location. A “better location” could in turn mean anything from proximity to jobs (resulting in efficient use of valuable time), proximity to shops or cultural amenities, location in a good school zone, or access to parks or beaches.
One interesting phenomenon is that people seem to be willing to travel further to work than to consumption amenities (ranging from retail to concerts). In their fantastic book Cities and the Urban Land Premium, Dutch economist Henri de Groot and several co-authors provide some data that shows that people are, on average, willing to travel considerably further to work than to consume. They show that this results in a higher urban land premium for accessible inner-city areas, as vibrant downtown areas have the most varied and interesting consumption opportunities.
Furthermore, you’d expect this premium to rise as incomes rise, as people with more disposable income will have an increasing preference for close proximity to consumption and cultural amenities.
Is the same thing likely to be true in Auckland? Nobody’s done a survey, but we’ve got some data on the distance that people actually travel to access jobs and retail.
In a paper two years ago, I analysed Census data on commuting distances in order to understand what Auckland households spend on housing and transport. I went back and re-analysed that data to get an estimate of the distribution of commuting distances in Auckland. This data suggests that 50% of Aucklanders commute less than 9km, while less than 2% are super-commuters travelling longer than 50km.
As a point of comparison, I used data on retail spending patterns compiled by economist Susan Fairgray in a 2013 report on the Auckland retail sector. Based on electronic card spending data, Fairgray estimates that 50% of Auckland retail spending is done within 5km of people’s homes. (See Table 3 on page 58 of her report.)
Here’s the chart. As in the Netherlands, distances travelled to consume drop off more rapidly than distances travelled to produce.
There are several implications for how we build cities. The first is that we should expect retail, personal services, and recreation to be widely distributed throughout the city. Large tracts of houses without good access to shops and recreation are not likely to be awesome in the future. There are various ways to cater to these needs, ranging from mixed-use zoning that allows retail and housing to colocate to distributing small retail centres throughout suburbs (a la Auckland’s tramway suburbs).
The second thing is that we should think more carefully about how preferences for centrality are changing. The consumption amenities that cities offer play an increasing role in their success or failure. Some important consumer amenities tend to be located centrally. For example, nightlife and entertainment districts are almost always located near the city centre – think of Ponsonby or K Road in Auckland. Likewise, museums and public art galleries are usually located downtown – e.g. Te Papa in Wellington or the Auckland Art Gallery – to maximise the number of people that can access them.
Auckland Art Gallery
As demand for consumer amenities will tend to increase with rising incomes, we’d expect demand to live close to them to increase in the future. Meeting this demand in a growing city will, in turn, mean building more apartments.
But wait! If people also want more living area as they get wealthier, doesn’t that mean that they’ll reject apartment living? Won’t apartments simply be too small to meet their needs, even after taking location into account?
It is the case that new apartments tend to be smaller than new standalone houses in New Zealand. Over the last five years, the average standalone house consented in Auckland was about twice as large as the average apartment consented in Auckland.
However, there’s no universal law that says that apartments have to be small. Policy can play a big role in keeping apartment sizes down, or enabling them to be more spacious. As LSE economist Paul Cheshire observes, planning policies (and other things like tax policies) can have the unintended consequence of discouraging adequately-sized housing:
If you really want to plan to protect and provide better access to green space and open countryside without artificially constraining land supply and forcing up house prices, then Green Fingers (or Green Wedges) would seem to be the best solution. That is what more egalitarian Scandinavians have. Copenhagen has its Green Fingers – really brown urbanisation along the radial routes out of the city with protected countryside each side. Denmark has not just got cheaper housing: according to the Dallas Fed’s data, the real house price has increased by a factor of 1.6 in Denmark compared to 3.4 in the UK since 1975 but new houses in Denmark are a lot bigger: 80% bigger in fact.
As Cheshire’s example of Copenhagen shows, it’s possible to build dwellings that meet people’s needs for living space and preserve usable open space around cities. You just need to be willing to build intensively where you do build – and integrate it with rapid transit.
For a less anecdotal look at the issue, I used Eurostat data to measure the relationship between dwelling size and dwelling type in 29 European countries. Here’s a scatterplot showing the relationship between the share of dwellings that are detached houses (X axis) and average dwelling size (Y axis). Observe how there is almost no relationship whatsoever. If anything, there’s a slight negative relationship – countries with more standalone houses may have slightly smaller dwellings, on average. (There’s probably an income effect in there that I haven’t controlled for – richer countries tend to be more urbanised, which will tend to mean more apartments, and also have larger dwellings.)
But basically, there doesn’t seem to be an inescapable trade-off between dwelling type and size. Apartments can be small… but they can also be large. And cities that are willing to let people more apartments get built will, in addition to being more affordable, give people more opportunities to realise their demands for both space and proximity.
What do you think of this data?