Large intersections

Last week, I took a high-level look at the opportunity cost associated with Auckland’s car-centric transport system. Simply put, cars use up lots of land, and public transport, walking, and cycling don’t. At a time when we’re struggling to find space to accommodate the city’s residential and economic growth, this is likely to be increasingly inefficient.

For example, here’s a graph that shows, roughly speaking, the last 50 years of trends in traffic volumes (using the Auckland Harbour Bridge as a proxy) and land values (using national house prices as a proxy). In the last decade or two, demand for intensive land use has far outstripped demand for driving:

AHB traffic volumes and real house prices, 1961-2014

However, this isn’t always acknowledged in the activities of transport agencies. As Matt highlighted two weeks ago, Auckland Transport is currently proceeding with a plan to knock down a house (on the bottom left corner of the intersection, shaded in magenta) for an intersection widening project:

Chivalry Rd Intersection Future

A bit earlier, Stu also pointed out an intersection design down in Hamilton that seems quite hazardous to people on foot. Now, there are certainly reasons to redesign – and even widen – intersections. But what worries me is that intersection layout sometimes seem to be on auto-pilot, without any deep consideration of the conflicting values at play or the opportunity costs associated with particular designs.

Take, for example, this intersection at the junction of St Johns Road and College Road in Remuera. It’s large. Very large. Although there’s only a single lane in each direction on the roads in and out of the intersection, it widens to implausible dimensions in the intersection itself. I can only imagine what it’s like to try to cross the intersection on foot.

st johns and college road

I asked my friend Lennart, who originally spotted this intersection, to show me how things could be done differently. He quickly sketched up a simplified design – shown in the green and magenta lines – that eliminated the big islands and the split lanes but still left enough room for buses to turn smoothly.

(Caveats: This is not necessarily a better design from a traffic engineering perspective – just a more space-efficient one. As we haven’t looked at traffic volumes, it’s difficult to say whether a signalised intersection or other safety treatments would be required if the slip-lanes were taken out.)

Overall, we found that there would be up to 2,000 square metres of space left over if the intersection was downsized. That’s enough space for three or four reasonably-sized houses on reasonably-sized lots.

Is this expenditure of space worth it? Would it be better to narrow the intersection and sell off the residual land for housing? Possibly. Possibly not. But no matter what the answer is, I hope that those questions are being asked of Auckland’s road designs.

What do you think of the space occupied by our intersections? Good, bad, indifferent?

The cost of space (for cars)

Earlier this month, urban policy researcher Todd Litman published a useful summary of some of his new research into the cost of sprawl:

Our analysis indicates that by increasing the distances between homes, businesses, services and jobs, sprawl raises the cost of providing infrastructure and public services by 10-40 percent. Using real world data about these costs, we calculate that the most sprawled quintile cities spend on average $750 annually per capita on public infrastructure, 50 percent more than the $500 in the smartest growth quintile cities. Similarly, sprawl typically increases per capita automobile ownership and use by 20-50 percent, and reduces walking, cycling and public transit use by 40-80 percent, compared with smart growth communities. The increased automobile travel increases direct transportation costs to users, such as vehicle and fuel expenditures, and external costs, such as the costs of building and maintaining roads and parking facilities, congestion, accident risk and pollution emissions.

[…]

We estimate that in total, sprawl costs the American economy more than $1 trillion annually, or more than $3,000 per capita, and that Americans living in sprawled communities directly bear $625 billion in extra costs, and impose more than $400 billion in additional external costs. This is economically inefficient and unfair: it wastes valuable resources and imposes costs on people who do not benefit from sprawl.

These findings should not be particularly surprising to regular readers of Transportblog – or, indeed, to anyone with an elementary understanding of geometry. (Serving dispersed suburbs with network infrastructure is more expensive.) But the magnitude of the costs is impressive.

I was particularly struck by the following chart, which illustrates the amount of space required for various different transport modes. Litman estimates that each automobile requires a total of 80 to 240 square metres, mostly for parking. By comparison, walking, cycling, and public transport require less than 20 square metres per passenger:

Litman-space-required-by-mode

As I’ve written before, space is expensive in cities, which means that we must use it efficiently. Moreover, the cost of space for cars is rising rapidly, while demand for driving is levelling off. In this situation, devoting more space to roads and parking – or preventing the re-use of road space and parking lots for other purposes – may represent a significant misallocation of resources:

AHB traffic volumes and real house prices, 1961-2014

So, we might ask: How much space have we misallocated as a result of our bias towards building roads rather than public transport and cycling options? And what else could we be doing with this space instead?

First, some data. As we tend to build road networks for peak demands, they tend to have spare capacity during the middle of the day and evenings. Consequently, I’m going to focus on trips taken in the morning peak. This is a conservative view on the space required for a car-based transport system, as cars used during off-peak times still require lots of parking.

According to modelling results reported by Wallis and Lupton (2013), in 2006 there were around 450,000 vehicle trips taken during the morning peak. (See Table 4.1 in their report.) Most of these are trips in single-occupant vehicles. How much space do we need to accommodate all these vehicles?

Based on Litman’s figures, travelling by car requires an average of 150 square metres of space – around 40 square metres of roads per car when moving and 110 square metres for parking. This implies that the 450,000 vehicles moving around during the morning peak occupy 67.5 square kilometres of space, including (at minimum) 18 square kilometres of roads.

That’s a lot of land. Urban Auckland covers a total area of around 544 square kilometres, which suggests that we’re using up around 12.4% of the city’s land area simply to move single-occupant vehicles during the morning peak and warehouse them during the day.

If anything, this is probably an under-estimate of the spatial cost of Auckland’s car-based transport system. A 2013 UN-Habitat report on streets as public spaces and drivers of urban prosperity found that Auckland devotes 14% of its land area to roads alone. Parking is likely to cost us even more space, as this map of Manukau central shows. Everything that’s not coloured in red or green is a carpark or a road:

mcc-coloured

But regardless of whether we’re dealing with 12% of the city’s land area or 30%, we’re talking about a lot of expensive space devoted to moving or storing cars. Even a modest reduction in the share of people travelling by car in the morning peak would save us a large amount of land.

Let’s say, for example, that we’d invested in better transport choices that enabled 10% of the people in cars to shift to public transport or cycling, which require around 10 square metres of space per person. If we had done so, we would have had an extra 6.3 square kilometres of land that didn’t need to be used for roads and carparks. [6.3km2=45,000 vehicles*(150m2-10m2)]

This is valuable land. Assuming an average land price of around $500 per square metre, it’s worth $3.2 billion. And it could be used for so many more things – housing, businesses, public parks, schools, etc – if it hadn’t been gobbled up by our space-hungry transport system. If it had been developed to the same density as Auckland’s average neighbourhood – around 43 residents per hectare – instead, it could have housed 27,000 people.

In a city that’s struggling to find enough space to house it’s growing population, this amounts to a minor scandal. Since the 1950s, local and central governments have spent lavishly on roads and neglected public transport, walking, and cycling. Those decisions have inadvertently contributed to our housing woes today, as they’ve saddled us with a space-inefficient transport system and a shortage of developable land.

At the moment, local and central governments are looking at ways to get best us out of their own properties. Auckland Council’s setting up Development Auckland to manage and develop its substantial land-ownings. At this year’s Budget, the Government announced a more hastily-developed plan to sell off a significant chunk of the land that it owns in Auckland for development.

Given their interest in the subject, they should also be thinking hard about how to minimise the “opportunity cost” of Auckland’s space-hungry car-based transport system. Investing in public transport and safe walking and cycling can allow us to move more people without gobbling up more valuable land.

What do you think about the spatial cost of our car-based transport system?

If congestion is so bad, we should price it

Last Thursday, the Government shut the door on the idea of road pricing for Auckland, saying that it would prefer to undertake “a year-long negotiation with the council on an agreed 30-year programme focusing on reducing congestion, and boosting public transport where that reduces congestion.”

The following day, the road/infrastructure lobby undertook a bit of a media blitz pushing for more construction. As part of that, we got sent this press release from the Auckland Chamber of Commerce:

Media Release

12 June 2015

Auckland – defined by congestion

The Auckland Chamber of Commerce strongly supports the initiative of Government to seek a negotiation with Auckland Council on an agreed 30-year programme focusing on reducing congestion, and boosting public transport where that reduces congestion.

Michael Barnett, head of the Auckland Chamber was responding to news reports that Transport Minister Simon Bridges and Finance Minister Bill English have sent Auckland Mayor Len Brown a letter proposing a negotiation and ruling out allowing Auckland to bring in motorway charges to help fund transport projects.

“The Auckland business community overwhelmingly agrees that immediate action to address the City’s transport congestion is required,” said Mr Barnett.

In short, congestion is bad. Really bad. It’s a crisis deserving immediate action… in the form of a year-long talk-fest between local and central government.

Of course, it’s difficult to find reliable empirical evidence that Auckland’s congestion levels really are that bad. Average commute times are a cruisy 25 minutes – well below many other cities. NZTA research has found that the actual cost of congestion is neither (a) largely a monetary cost for businesses or (b) anywhere as large as people claim. While people like to claim that congestion costs “billions” annually, a more realistic figure is $250 million. The one source that does claim that Auckland has world-beating congestion, the TomTom index, has serious methodological flaws.

Nevertheless. Even though its empirical basis is shaky, the Auckland Chamber of Commerce’s recommendations for projects are not crazy. In fact, they seem to be on Auckland Transport investment radar already:

A good outcome from Government and Auckland Council working together would be a package of fast-tracked projects aimed at:

  • Improving public transport services’ reliability and frequency
  • Getting as much use as possible out of the transportation system we have
  • Removing parking from major arterial routes to create more usable road space.
  • More high occupancy lanes to encourage a reduction of sole occupancy cars.
  • Strengthened integrated traffic management covering arterials and motorways.
  • Expanding park and ride facilities at main trunk rail and busway stations.

But even if the ideas are sensible, “fast-tracking” them will be expensive. We simply can’t build everything at once. Even if Government was willing to give Auckland Council more tools to raise revenue – which is unlikely given its refusal to consider road tolls – capacity constraints in the civil engineering business would make it hard to do much more.

To its credit, the Chamber seems to recognise this and agree that we need to prioritise use of our scarce resources:

“Good leadership is about partnership,” said Mr Barnett. “It is about understanding that we have limited resources, so we must learn to prioritise correctly,” he concluded.

Which leads me to my point. If congestion is such a big problem, why don’t we use congestion pricing to make sure that we’re prioritising use of our road network efficiently?

I find it very strange that business groups aren’t more enthusiastic about this idea. If congestion is really as bad as they say it is, why aren’t they loudly advocating a policy solution that would actually address it? (Road-building doesn’t work.) Surely freight companies and construction firms would benefit from the resulting reductions in traffic, even if they had to pay a bit for them.

In my experience, congestion pricing is one of those ideas that virtually all economists agree on. It’s like free trade in that regard – there might be some disagreement about the fine details, but most agree that it’s a good idea. But it hasn’t gotten as much attention in other quarters.

So here, for example, is William Vickrey, who won the Nobel Memorial Prize in Economics for his pioneering work on the topic:

Known among economists as “the father of congestion pricing,” Professor Vickrey sees time-of-day pricing as a classic application of market forces to balance supply and demand. Those who are able can shift their schedules to cheaper hours, reducing congestion, air pollution and energy use — and increasing use of roads or other utilities. “You’re not reducing traffic flow, you’re increasing it, because traffic is spread more evenly over time,” he has said. “Even some proponents of congestion pricing don’t understand that.”

He has admitted that his ideas have sometimes not been well received by those who set public policy because, “People see it as a tax increase, which I think is a gut reaction. When motorists’ time is considered, it’s really a savings.”

And here’s urban economist Edward Glaeser commenting that more megaprojects aren’t the best fix for transport issues:

Infrastructure investment only makes sense when there is a clear problem that needs solving and when benefits exceed costs. U.S. transportation does have problems — traffic delays in airports and on city streets, decaying older structures, excessive dependence on imported oil — but none of these challenges requires the heroics of a 21st century Erie Canal. Instead, they need smart, incremental changes that will demonstrate more wisdom than brute strength…

IMPLEMENT CONGESTION PRICING: We should expect drivers to pay for more than just the physical costs of their travel. We should also expect them to pay for the congestion that they impose on other road users. If you have a scarce commodity, whether groceries or roads, and you insist on charging prices below market rates, the result will be long lines and stock outs, like those that bedeviled the Soviet Union decades ago. Yet U.S. roads are still running a Soviet-style transport policy, where we charge too little for valuable city streets. Traffic congestion is the urban equivalent of a stock out.

And here’s economist Matthew Turner, who co-authored one of the most comprehensive studies of “induced traffic”, which I discussed here:

So what can be done about all this? How could we actually reduce traffic congestion? Turner explained that the way we use roads right now is a bit like the Soviet Union’s method of distributing bread. Under the communist government, goods were given equally to all, with a central authority setting the price for each commodity. Because that price was often far less than what people were willing to pay for that good, comrades would rush to purchase it, forming lines around the block.

The U.S. government is also in the business of providing people with a good they really want: roads. And just like the old Soviets, Uncle Sam is giving this commodity away for next to nothing. Is the solution then to privatize all roads? Not unless you’re living in some libertarian fantasyland. What Turner and Duranton (and many others who’d like to see more rational transportation policy) actually advocate is known as congestion pricing.

And here’s the OECD in its latest country report on New Zealand:

A just-released OECD economic survey blames years of under-investment in infrastructure for the city’s roading problems. It calls for a mix of tolls and congestion charges to alleviate peak-hour traffic pressure and help fund new roads and more public transport.

“Placing a cost on travel during peak periods could incentivise drivers to travel at different times (off-peak), if they are not required to be on the roads, or could encourage more carpooling and use of public transportation,” the report says.

In short, if you’re worried about congestion, you need to take congestion pricing seriously. There are undoubtedly reasons why we may not want to implement congestion pricing, ranging from technical feasibility to equity concerns. But in my view it’s ridiculous for business groups and politicians to get all up in arms about the issue – and promptly rule out one of the few realistic solutions.

What do you think about congestion pricing?

More on AT’s Light Rail Proposal

We have been sent more LRT details from AT. Light Rail is undergoing investigation at this point, but slowly more of their thinking is emerging:

LRT Stage 1.0

Clearly access to Wynyard is the most difficult part of this route. Queen St is so LRT ready and at last a use for that hitherto hopeless little bypass: Ian Mackinnion Drive. The intersection of New North and Dom Rd will need sorting for this too- Is there nothing that LRT doesn’t fix!

LRT Stage 1.1

They are planning for big machines, 450 pax is at the top end of LRVs around the world.

LRT Stage 1.2

At 66m, these are either the biggest ever made, or I guess more likely 2 x 33m units. 33m is a standard dimension, and enables flexibility of vehicle size.

LRT Stage 2.1

The contested road space of Dominion Rd. Light Rail will create the economic conditions for up-zonning the buildings here; apartments and offices above retail along the strip. But the city will have to make sure that the planning regulations support this. Otherwise it will be difficult to justify the investment. Something for those in the area who reflexively oppose any increase in height limits, reduction of mandated parking, or increases in density and site coverage rules to ponder. If they prefer to keep the current restrictions they need to be aware they are also choosing to reject this upgrade. More buses will be as good as it gets, and AT’s investment will have to go elsewhere. I’m not referring to the the large swathes of houses back from the arterials, no need to change these; it’s the properties along the main routes themselves that need to intensify; anyway these are the places that add the new amenity for those in the houses. And not just shops and cafes, also offices with services and employment for locals, and apartments for a variety of dwelling size and price. Real mixed-use like the world that grew up all along they original tram system city wide, before zoning laws enforced separation of all these aspects of life.

LRT Stage 2.2

Are we measuring housing affordability correctly?

As someone who uses statistics (and statistical methods) on a regular basis, I often find that the “headline figures” that get all the attention obscure as much as they reveal. For example, reporting a single benefit-cost ratio (BCR) for a project may conceal uncertainty about potential outcomes.

When talking about data, there’s a strong tendency to focus on the average value, without considering the variation in outcomes. So, for example, we get news articles like this:

Auckland house prices climbed to a fresh record last month, while the number of sales dropped from March’s peak, according to Barfoot & Thompson.

The average sale price rose to $804,282 in April, from March’s previous record $776,729, the city’s largest realtor said.

Averages are certainly useful, but it would also be helpful to know more about how the distribution of house values has changed. For example: perhaps the average is being dragged up by the sale of a small number of really expensive homes? It’s hard to know.

In fairness, the article does provide this data suggesting that there is a fair range of prices. But we don’t know whether the number of homes sold for under $500,000 is increasing, decreasing, or staying the same:

“157 homes sold during the month went for under $500,000, which represents one in seven of all homes sold. There is a good choice of homes in this price category but LVRs often mean potential buyers cannot meet the home deposit requirements.”

As an illustration of why we can’t rely solely upon measures of central tendency, such as the mean or median value, consider two hypothetical cities:

  • City A has an average house price of $500,000, and a standard deviation in house prices of $50,000. (As a rule of thumb, if your data follows a normal distribution, 95% of values will be found within two standard deviations of the average. In other words, in city A, 95% of houses are sold for between $400,000 and $600,000.)
  • City B, by contrast, has an average house price of $600,000 and a standard deviation in house prices of $150,000. (Implying that 95% of houses are sold for between $300,000 and $900,000.)

I’ve graphed the distribution of house prices in these two cities below. City A is in blue, while city B is in red.

housing price distribution chart

We can immediately see two things. First, the average house in A – found at the peak of the bell curve – is cheaper than the average house in B.

A second key fact, however, is that B actually offers more affordable houses overall, in spite of its higher average prices. This can be seen pretty easily on the chart – B has a much fatter “tail” of low-priced houses than A does.

Let’s think about what these two cities offer for households on lower incomes. Consider what house-hunting looks like for a household earning $50,000 a year.

If these people were basing their decisions on where to live on average house prices alone, they’d clearly prefer to live in city A, where average prices are $100,000 lower. But once they got there, they’d have a lot of trouble finding a home that they could afford.

Because city A has such little variation in house prices, it’s hard to find any houses that sell for less than $400,000. Assuming a 10% down-payment and a 6% mortgage rate, our household would have to pay $26,000 in mortgage repayments every year for the cheapest house on the market. Over 50% of their annual income!

By contrast, if they’d looked behind the headline figures on average house prices, they would find that city B offers many more affordable homes. Around 5% of homes in city B sell for less than $350,000, and it’s possible to find homes for $300,000 or less.

Under the same mortgage assumptions, our household would have to pay around $19-22,000 in mortgage repayments every year to live in a cheaper house in city B. This still isn’t great – it’s around 40% of household income – but it’s better.

In other words, although the first city seems more affordable based on its average house prices, it is actually likely to be considerably less affordable for many of the real human beings that are trying to live in it.

How do you think we should measure and report on house prices?

Isolated in the quarter-acre pavlova paradise?

The other week, the NZ Herald reported on some new research into Kiwis’ sense of social connectedness. The results, unfortunately, are fairly dismal:

New research has found that New Zealanders are losing touch with their neighbours – and it’s affecting our wellbeing.

In the recently released results of the Sovereign Wellness Index, New Zealand trailed behind other countries when it came social connections and community, with our neighbourly relations particularly lacking.

“We came last when compared to 29 European countries that deployed the same survey, which is not only a disappointing result but, when compared to the first Sovereign Wellbeing Index in 2013, it shows no improvement,” said Grant Schofield professor of public health at AUT University, who led the research.

Interestingly, the study’s authors identified urban form as a principal cause of our weak social bonds:

The survey found that only four per cent of New Zealanders agreed they felt close to people in their local area – which Mr Schofield said was a symptom of sprawling, car-centric cities such as Auckland.

“Community design has a role to play in fostering connections and I don’t believe we are seeing the benefit of this in New Zealand,” he said.

“Work, play and home are often on opposite sides of the city and the commute is killing our neighbourly interaction and our community integration,” Mr Schofield said.

The survey also found that almost 40 per cent of Kiwis only meet with others socially once a month or less.

There are probably some other factors at work here. As I discussed in a post last October, Auckland’s commute times really aren’t that bad – the average Aucklander doesn’t seem to spend enough time on the road to explain our lack of social engagement.

Avg commute times in large cities

On the other hand, New Zealanders do work quite long hours when compared with Europeans. The average employed Kiwi worked 1760 hours a year in 2013 – around 27% more than the productive Dutch and Germans. Long hours spent at low-income jobs is probably worse than commuting for most people.

Nonetheless, we do need to take social connectivity seriously when we think about what we’re trying to accomplish in urban and transport policy. If you think about it, social connection is why we have cities in the first place. Urban economist Edward Glaeser is fond of describing cities as “the absence of physical space between people and companies.” They allow us to be close to each other, which offers all sorts of fantastic opportunities for efficiency and innovation and enjoyment.

Cities, in Glaeser’s view, emerge from our deep evolutionary biology. We are social animals – we like being around others and become unwell when we’re isolated. Hence cities.

Growth in world incomes over the past two centuries has not coincided with a great dispersal of human population. We have not sought to retreat into our own isolated estates. Instead, we have invested our newfound wealth into making our cities healthier, more attractive, and larger: steel framed buildings, elevators, trams, subways, public health and education, reticulated water systems…

World Bank GDP per capita and urbanisation

In short, humans have a preference for proximity, and we come to cities to satisfy it. If our cities are in fact isolating us, we need to re-think how we’re building them. Plonking down new houses in a paddock and calling it a solution to housing affordability is dangerously short-sighted. We’ve got to be thinking a few steps beyond that, and asking:

  • Will complementary land uses be integrated? Are we going to build places that pass the “five minute pint test” of having a place to get a pint of beer or a pint of milk within walking distance? Or will people have to get in the car to run even the simplest errands?
  • Will people have good access to the places they want to go? Will the housing choices we offer people respect their time, energy, and money, or will they lock people into long commutes on congested roads?
  • Will we offer people good transport choices that give them freedom to opt out of congestion by taking rapid transit or cycling?

Do you think Auckland (and other NZ cities) are socially disconnected? If so, what do you think we should do about it?

Trade over distance and the Auckland export paradox

What, exactly, does Auckland do to pay its way?

Last year, I took a look at the geography of the New Zealand economy, finding that New Zealand’s three main cities accounted for at least 56% of GDP. Auckland alone accounted for at least 34% of economic activity – considerably more than the entirety of rural New Zealand:

City share of NZ GDP map v2

(By the way, these figures are likely to under-estimate the size and productivity of the Auckland economy. Dave Maré’s 2008 paper on the Auckland productivity premium used firm micro-data to get a more accurate estimate, finding that Auckland accounts for around 40% of New Zealand’s market economy. See page 15 for figures.)

So Auckland’s economy is large. But are Aucklanders doing anything especially productive, or are we just selling houses to each other? (Or worse, to Johnny Foreigner!)

As New Zealand is a small, open economy, we have a tendency to focus on exports as a key measure of economic success. This makes sense – we can’t make everything locally, so we need to earn foreign exchange to pay for all the cars and oil and smartphones and bicycles that we want to buy.

At a national level, we export around 30% of GDP, which is low by the standard of other small open economies and worrisomely concentrated in a few undifferentiated primary commodities:

Source: World Bank

Source: World Bank

By comparison, a 2010 study commissioned by Auckland Council found that exports of goods and services accounted for around 14-16% of Auckland’s GDP:

The value of Auckland region’s exports has increased relatively steadily over recent years, with an average annual growth rate of around 2 percent recorded for both commodity and services exports for the period 2001-2008. The economic impact undertaken as part of this study suggests, however, that there has been a small decline in the relative importance of export sales to the Auckland region economy over this period. First in terms of commodities, it is estimated that the direct and indirect value added impact produced by commodity exports as a percentage of Auckland’s GDP has fallen slightly from 9 percent in 2001, to 8 percent in 2008…

Measured in value added terms, the direct and indirect contribution of service exports to the regional economy has remained fairly constant over the last decade at around 6-7 percent of GDP.

So Auckland’s not exactly an export powerhouse. What, then, are we doing to afford the food that we’re buying from rural New Zealand and the manufactured goods we’re buying from offshore?

Last year, the Productivity Commission published some new research that points towards an answer. Their report, which has the attention-grabbing title of “Trade over distance for New Zealand firms: measurement and implications“, looks at the degree to which firms in different industries are co-located with their domestic customers. They put together some nifty measures showing how likely different industries are to “trade” across New Zealand regions.

The Productivity Commission researchers concluded that:

In New Zealand, firms producing highly tradable services tend to locate in the main urban centres (Figure 8a). Wellington has the highest employment share in high and medium tradable service industries, reflecting the concentration of government in the capital. Market-based services that are tradable over distance tend to concentrate in Auckland – there is a positive and significant correlation between tradability in market-based service industries and their Auckland-based employment share (Figure 9). As such, around 40% of total employment in market-based service industries in the medium to high tradability category is Auckland-based (Figure 10). For services in the low-tradability category, the share of employment based in Auckland is 32%.

In other words, Auckland has a comparative advantage in producing services that it can “export” to other New Zealand regions. Here’s a key chart from the report, which compares tradability (y axis) with Auckland employment share (x axis) across high-level industries:

PC tradability and Auckland share chart

If you look at the service industries (orange dots), excluding public administration, you can see the clear correlation between tradability and Auckland share of employment. Industries that have to be very close to their customers, like retail and health, aren’t concentrated in Auckland.

On the other hand, four especially tradable service industries – finance and insurance; information, media and communications; professional, scientific, and technical services; and wholesale trade – are highly concentrated in Auckland. (Interestingly, these industries span both blue-collar and white-collar work.)

So perhaps the story is that Auckland “pays its way” by producing services that the rest of New Zealand buys. The work that Auckland does for the rest of the country isn’t always visible – we’re not trucking boxes of it south from Auckland to the Waikato – but it is very real.

Furthermore, Auckland’s “exports” of services to other New Zealand regions have implications for the national trade balance. If Auckland wasn’t doing the banking, engineering, accounting, and wholesaling, we’d probably have to purchase those services from Australian cities instead. (Jane Jacobs would observe that Auckland is following the typical path to urban success – “import-competing” economic growth.)

By way of illustration, consider where Fonterra, New Zealand’s largest exporter of dairy products, chooses to locate its headquarters. They’re not based in Hamilton or Christchurch, closest to the cows and dairy factories. No: Fonterra is in Auckland, which doesn’t produce much milk but does offer the best access to skilled labour, professional services (accounting, legal advice, advertising, etc), and international connections (i.e. the country’s main international airport). They value those services, and recognise that they can’t get as many of them outside of Auckland.

What do you make of Auckland’s role in the New Zealand economy?

The urban planning conundrum

Since I moved to Auckland, I’ve been trying to make sense of local trends in house prices. Why have they risen over the last decade? Will they keep going up, or crash back down to earth? What’s driving all this?

Over the last few years, a lot of the focus has been put on the role of planning regulations in pushing up prices. I’m sympathetic to this focus, as it looks like there may be a few barriers to building the kind of city I’d like to live in. But I also suspect that the causes are a bit more complex than planning alone. After all, housing markets are big, confusing (and confused) things.

Others are more confident that planning was what done it. For example, the annual Demographia Housing Affordability Survey states, quite confidently, that planning regulations – an “institutional failure at the local level” – are the main cause of high house prices:

The purpose of the Demographia Surveys is to alert the public and policy-makers if housing exceeds 3.0 times annual household incomes, that there is institutional failure at the local level. The political and regulatory impediments with respect to land supply and infrastructure provision must be dealt with.

Former Reserve Bank governor (and former leader of both National and ACT) Don Brash made matters even clearer in his foreword to the 2008 edition:

The affordability of housing is overwhelmingly a function of just one thing, the extent to which governments place artificial restrictions on the supply of residential land.

In short, planning rules – especially metropolitan urban limits – are bad. Very bad. They are the main reason that houses in some places are unaffordable, which Demographia defines, somewhat arbitrarily, as median house prices that are more than three times the median household income:

Demographia affordability categories

Now, according to Demographia, Auckland currently has a “median multiple” of 8.2: “severely unaffordable”. Based on their figures, the median house price in the city at the end of 2014 was $613,000. (This actually seems low – perhaps they’ve converted it to USD?)

In order for Auckland to meet Demographia’s definition of an “affordable” market, house prices would have to fall by $390,000, or 63%. Given that they think that urban planning/metropolitan urban limit policy is the main cause of high house prices, we can take this as their estimate of the cost of those policies. $390,000, per house.

This is obviously a very large number. If house prices fell back to the “affordable” level, it would have ruinous effects on NZ’s financial system and household wealth. (Frankly, this does not seem like a very good outcome.)

So that’s Demographia’s estimate. Recently, several New Zealand economists have taken a more detailed look at the costs of planning regulations in Auckland. For the most part, they analyse the impact of planning rules that were put in place by previous councils:

  • Motu’s paper on the costs of planning regulations concludes that they add between $32,500-$60,000 to the cost of a new standalone house and $65,000-$110,000 to the cost of a new apartment. These figures were sourced from a survey of developers and accounted for the impact of a number of individual rules ranging from balcony rules to section size controls.
  • NZIER’s paper models the impact of urban limits and height/density limits. (This paper uses a similar approach to the one I discussed here.) It concludes that these two rules cost households the equivalent of $1800 per annum. In present value terms, this is somewhere on the order of $30-40,000 per household (depending upon what discount rate you use).

[Disclaimer: I know the authors of both studies and have a great deal of respect for their work. In a professional capacity, I provided comments on earlier drafts of both papers. This is somewhat unavoidable given the size of New Zealand…]

Here’s a chart comparing Motu and NZIER’s estimates of the cost of planning regulations with Demographia’s estimate:

costs of planning regulation chart

In other words, these estimates suggest that Auckland’s planning regulations explain only 10-30% of the difference between Auckland house prices and a median multiple of 3. Even if we add together the estimates from the two papers, we don’t get anywhere near explaining the gap.

So: whose estimates of the cost of planning should we believe?

Personally, I trust Motu and NZIER’s analysis, as it’s backed up by empirical research and/or economic modelling, whereas Demographia’s is mainly justified by rather repetitive and self-referential haranguing. Consequently, I don’t think we can conclude that planning regulations are a sufficient explanation for Auckland’s relatively high house prices.

That doesn’t necessarily mean that we should be sanguine about planning regulations. While things will change under the Unitary Plan, the costs associated with existing rules are reasonably large. And, in contradiction to Demographia’s claims that constraints on greenfield land supply are the biggest problem, both papers find that existing regulations place higher costs on higher-density developments.

The Motu paper finds that existing planning rules add twice as much cost to apartment developments as to standalone houses. Similarly, the NZIER paper finds that height limits (and other controls on density) are slightly more costly than urban limits. (This is partly because Auckland is mostly surrounded by water, meaning that preventing land from being used efficiently is much more deleterious than it would be in a city with more land.)

If these issues aren’t addressed, it may be more difficult to get the Auckland that we want: a city that gives people better housing choices, that lets them live in places that are accessible to jobs and amenities, and which efficiently accommodates the next Aucklander.

What do you think about the cost of planning?

The moral case for immigration

In a post several weeks back, I talked about the economic case for immigration and population growth. In it, I hypothesised that:

New Zealand has a strong feedback loop between net migration and economic growth. When growth prospects get worse – as they did in the 1970 and 1980s – it dissuades people from coming here and encourages Kiwis to leave for greener pastures. This in turn worsens growth prospects by sucking consumer demand out of the economy and reducing perceived household wealth (i.e. lowering house prices).

By contrast, good growth prospects tend to attract migrants to New Zealand’s cities and encourage potential emigrants to stay. This in turn leads to a virtuous cycle between higher growth and increased migration.

In my view, building good cities that attract and efficiently accommodate population growth can make us better off by strengthening the agglomeration economies at work in New Zealand’s economy. It can also make us better off in non-economic ways: consider romantic relationships, for example. If you’re young and single (or old and single), you should absolutely prefer more people to be arriving than leaving. The more young, mobile people are staying or arriving in New Zealand cities, the better your odds are of ending up in a good relationship.

However, I don’t think the economic case for immigration is as strong as the “moral” case for immigration. That’s because immigration is one of the most powerful mechanisms for enabling people to lift their incomes and social status. Migration can offer individuals opportunities that they never would have had in their home countries.

I’m going to discuss some economic research on the topic, but first I want to explain why it’s important to me.

Basically, in the 200-400 years in which reasonable data on my ancestors is available, migration has been just about the only thing that has enabled us to have any significant social or income mobility. Ever.

Migration has worked out well for me. Moving back to New Zealand has given me opportunities that I might not have had in the United States. Thus far, I’ve had a more interesting and fulfilling career and I’ve been surrounded by interesting and friendly people while doing it.

Migration also worked out well for my parents and several of their siblings, who left New Zealand in the 1970s and 1980s during the wave of economic destruction caused by collapsing commodity prices and Muldoonist Think Big initiatives. Like many other New Zealanders, they’ve done well overseas.

And, back in the 1840s-1890s, migration to New Zealand opened up opportunities for social mobility and independence to my great-grandparents and great-great-grandparents. In fact, those were just about the first opportunities anyone in my family had to get ahead. If it weren’t for migration, we’d still be lower-middle class in some grim former mill town in northern England.

I’m grateful for the opportunities that migration has offered me and the opportunities that it’s offered to my family. Furthermore, I feel strongly that more people should have similar opportunities. I don’t believe in pulling up the ladder. If some hard-working folks from Nigeria, Guatemala, Bangladesh, Samoa, or wherever want to try their luck moving to an unknown country, I’m all for it. Give them a fair go.

Several recent papers by University of Otago economist Steven Stillman (another immigrant!) and several co-authors help quantify how valuable giving people the opportunity to immigrate can be. Stillman uses evidence from two “migration lotteries” operated by the New Zealand government. Under a programme started in 2002, a small number of Tongans and Samoans randomly selected from a pool of applicants are offered residency in New Zealand.

Evidence from the Tongan migration lottery shows significant improvements in well-being for migrants. Stillman and his co-authors found evidence of:

  • “Very large gains in objective well-being result from migrating to New Zealand (Table 2). The weekly wage of principal applicants rose by NZ$321 (US$200) within a year of first moving which is almost three times the weekly wages of the control group in Tonga (NZ$117).”
  • “More subtle and complex effects on subjective well-being…” After four years, they observed a “very substantial rise in the other components of mental health, of about three points, which is equivalent to one quarter of the wave 2 scores for the control group in Tonga.”

Evidence from the Samoan migration lottery shows that migration can also improve wellbeing for migrants’ families in the old country, at least in the short term. Stillman and his co-authors found that migration increased household consumption and reduced poverty in households that sent migrants to New Zealand, although these effects faded away over time.

In short, even after controlling for self-selection bias (i.e. the fact that migrants tend to have both motivation and resources to migrate), migration seems to make people better off. It doesn’t necessarily work for everyone, but it certainly works for most people.

In my view, the evidence suggests there are good economic and moral arguments for enabling migration, rather than cutting it off in the good times. If we want to manage house price inflation, it would be fairer and more sensible to pursue other policies instead. This could include (but certainly isn’t limited to):

  • Changes to tax policy to harmonise our property taxes with major trading and investment partners – as Stu highlighted, our unusually low property taxes distort people’s investment decisions and push cash into housing
  • Supply-side policies like a revitalised programme of state house construction or urban planning policies that enable people to build more housing in areas that are accessible to jobs and amenities.

What’s your experience with immigration? Remember, you or your ancestors came here relatively recently by boat or by airplane!

Do property taxes affect housing affordability?

A few weeks ago, I took a look at property taxation in the US, Canada, and New Zealand. I found that Auckland homes are taxed lightly by comparison – rates average 0.39% of house value. Property tax rates are twice as high in most of the other cities I looked at. In some cases – e.g. Houston, where property taxes average 2.31% of home value – they are much, much higher.

This should come as no surprise to anyone who’s read the literature. For example, Grimes and Coleman (2009) find that New Zealand under-taxes property:

McLeod et al (2001; p.26) showed that the proportion of taxation raised through property taxes was lower in New Zealand than in Australia or the United States. Taking into account all levels of government (federal, state and local), Grimes (2003) found New Zealand’s share of property taxes in government revenue was relatively low, at 5.7%, compared with a (20 country) OECD average of 8.3%. As a share of GDP, New Zealand’s property tax share was also relatively low at 1.8% compared with the average rate of 2.4%.

They go on to suggest that introducing even a relatively small land tax could result in fairly large changes to land prices. It’s intuitively sensible that higher property taxes would discourage people from bidding up prices – the more they pay for land, the more they pay in taxes!

Stu recently took a look at the same research, and some of the broader trends, and concluded that higher property taxes could take some heat off the housing market. But how much does property tax really matter for housing affordability?

To get a rough sense of the relationship, I’ve put together a chart showing the relationship between property tax rates (x axis) and Demographia’s “median multiple” measure of house prices relative to incomes (y axis). It includes data on all 59 US, Canadian, and New Zealand cities with a population over 1 million.

Notice the substantial negative correlation between property taxes and median multiples. There is a strong tendency for places with lower property taxes to have higher house prices, and vice versa. The least “affordable” places all have relatively low property taxes.

property taxes and median multiples chart 1

Overall, this chart suggests two things: First, New Zealand’s relatively low property taxes may contribute to our relatively high house prices. Notice how Auckland’s house prices seem to fit the overall trend in the data.

Second, as I’ve previously argued, Demographia’s analysis is largely meaningless as they have failed to account for the full range of explanatory variables, from interest rates to tax policies to economic fortunes.

Here’s another view on the same data. I’ve taken the natural logarithm of both variables to smooth out the relationship, and put a trend-line through the data points. This simple bit of analysis suggests that:

  • About 44% of the variations in median multiple can be “explained” by differences in property tax rates. For a bivariate regression, this is quite high.
  • The slope of the regression line suggests that, within this sample of cities, a 10% increase in the property tax rate is associated with a 4.6% reduction in the median multiple. Again, that’s a quite strong relationship.

property taxes and median multiples chart 2

I don’t think we can draw any firm policy conclusions from this data, but it certainly suggests that our low property taxes are worth investigating as a cause of our high house prices. In the words of xkcd, “Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’.”

Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'.

Finally, it’s worth taking a closer look at the four US cities with the highest median multiples – the top data points on the left hand side of the first chart. They are all large cities in California – San Francisco, Los Angeles, San Jose (i.e. Silicon Valley), and Sacramento (the state capitol). They provide a great illustration of why failing to account for multiple, correlated explanatory variables can undermine an analysis of house prices.

But first, a California-themed music break:

In California, state-level legislation establishes a common planning framework. There are local variations, but if one city is constrained by regulations – as San Francisco and Silicon Valley are – the rest are likely to have similar problems. To give an example, the California Environmental Quality Act, which is the state’s equivalent of the Resource Management Act, has traditionally required all new developments to assess their impact on traffic congestion and mitigate it. As a 2011 Citylab article explains, this requirement has prevented the development of space-efficient forms of housing and transport:

There’s also a great irony underlying the use of LOS [traffic Level of Service] as part of CEQA’s environmental impact checklist. It seems self-evident that bike projects are favorable to the environment, but the use of LOS to evaluate them can sometimes imply quite the opposite. The person who filed the 2005 lawsuit against the San Francisco master bike plan, for instance, suggested that because bike lanes raise LOS they also raise congestion and car idling, and thereby cause pollution.

That’s not the only contradictory aspect of LOS. Case in point: a developer whose building fails an LOS threshold can mitigate the environmental impact by widening the street, which of course would attract more cars and pollution. So instead of encouraging dense development and lower vehicle mileage — the hallmarks of a transit-first city — San Francisco’s use of LOS as part of CEQA actually discourages livable design. In a three-part series on LOS at Streetsblog, one transportation consultant called LOS the “single greatest promoter of sprawl and the single greatest obstacle to transit oriented development” in California.

However, CEQA and its absurd requirements for traffic assessments (etc) aren’t the only thing going on in California. State-level laws have also constrained local governments’ ability to raise property taxes. Proposition 13, a citizen-initiated referendum passed in 1978, caps property tax rates at 1% and fixes them to the value of the house at the time it was purchased, plus a 2% annual increment for inflation.

This has had a number of perverse effects, including stripping away funding from California’s formerly excellent primary and secondary education and setting it on a path of decline. (Prop 13 is basically exhibit A in the case against binding referenda.) It has also distorted the housing market. Because home-owners know their property taxes won’t increase if the value of their house increases, they may be more willing to speculate on capital gains.

A 1982 paper by economist Kenneth Rosen offers empirical support for this hypothesis – he found that reductions in property tax rates were almost immediately followed by proportional increases in house prices.

Consequently, it would be foolish to analyse the Californian housing market without attempting to control for both taxation and planning policy. If you only looked at one policy, your conclusions would be biased by mis-attributing the effects of the other policy. (That’s precisely what Demographia seems to have done, by the way.)

What’s true for California is also true for New Zealand. I find it hard to take seriously the claims of people who attribute housing affordability solely to regulatory policy and fail to consider the potential impact of our low property taxes.

What do you make of the data on property taxes and house prices?