The Productivity Commission has released a draft report called Using Land for Housing which looks at options for how more land can be made available for development. At first blush that may sound like code for “open up lots of greenfield land for development” however the report appears to actually look at many of the issues in a holistic way giving a fairly balanced outcome. On a first skim through I agree with most of the changes the commission has suggested.
Before I go into the recommendations I think it’s useful to highlight that the commission start off by showing a good understanding of why cities are important. This is from a short summary document however there is a more detailed discussion in the draft paper. I think this is important as far too often if feels like many see and treat cities – particularly Auckland – like some kind of unnatural aberration sucking the value out of the rural areas.
Cities are national assets. They provide a wide range of jobs, higher incomes, generate higher productivity and raise the prosperity of surrounding regions. Cities also offer access to amenities not available elsewhere, such as specialised health and education services. Allowing cities to grow and accommodate new residents can help improve the wellbeing not just of the people who live there, but also those elsewhere in the country.
The main recommendations revolve around a few key categories, namely: planning/regulation, infrastructure and overcoming existing barriers/behaviour.
The recommendation that’s probably gained probably the most attention so far falls into that last category and is the suggestion of setting up Urban Development Authorities (UDA) – much like Auckland Council is already doing by merging Waterfront Auckland and their property CCO. They say a UDA could assemble, rezone and prepare for development large parcels of greenfield or brownfield and then partnering with private developers to build at scale. This seems pretty much identical to what’s being going on at Wynyard Quarter.
What’s gaining attention though is a suggestion that these UDAs could have powers of compulsory acquisition which would help in assembling suitable land and address issues such as land banking. It’s worth noting that compulsory acquisition was possible in the past and I believe is partly how the former Waitakere City Council was able to buy up large amounts of the town centre – although the government has currently removed the ability to do so in future.
They also suggest these UDA’s could help capture some of the increased value that occurs from the development. Overall I think the idea of a UDA is a good one although I can certainly understand the concerns about giving so much power to them.
Looking at the other parts of the report, they say that one of the current issues is that existing homeowners have a disproportionate influence on local political processes as they are the ones who benefit the most from restricting supply in their area – thereby inflating the value of their own property/s. This then gives those homeowners greater incentive to be more politically active and push for regulations that restrict development opportunities. This is of course exactly what we saw happen in the Unitary Plan discussions.
To counter this the commission suggest that councils engage in more sophisticated consultation processes and giving the government more say in planning processes. I do agree with the first point but the second I’m not so sure about given the past comments from the likes of Nick Smith.
The commission specifically call out a number of planning regulations that have been imposed – often by the processes above – that have made it much more difficult and costly to develop urban land thereby reducing density. They make the following recommendations in this regard saying we should:
remove District Plan balcony / private open space requirements for apartments;
review minimum apartment size rules in their District Plans, with a view to removing them (once the MBIE has completed planned work on updating Building Code rules and guidance related to air quality, lighting, acoustics and access in multi-unit dwellings);
remove District Plan minimum parking requirements and make more use of techniques for managing traffic demand;
lift current building height limits where it cannot be demonstrated that the benefits outweigh the costs; and
undertake robust cost-benefit analyses before considering the introduction of building height limits.
We have addressed all of these points in the past, especially the minimum parking requirement issue so it’s great to see the commission pick up on these points.
There is quite an extensive amount of discussion on the issue of the provision of infrastructure and how it is funded. In short they suggest funding constraints – often from the political processes mentioned earlier – makes it difficult for core infrastructure such as water and roads to be built in advance so it is done piecemeal which adds extra costs to the process.
They suggest that councils need additional tools to both help manage demand on existing infrastructure and to help fund new infrastructure that supports growth. They particularly point out that the government need to allow for road pricing on existing roads where it can be justified.
They also want to see more variable pricing in things like water connections. The example of Watercare is used which charges a flat fee for any new connection however they say that distorts costs and reduces transparency. Instead they think the charge should be influenced by local conditions i.e. if connecting a new dwelling an area has excess capacity in the network then that could be cheaper to connect to the network than a house on the edge of town in a new subdivision that needs new pipes installed.
Interestingly the specifically call out as not practical a few finance methods often suggested by those pushing greenfield growth such as Tax increment financing (TIF) and Municipal utility districts (MUDs). They do call for greater use of targeted rates to pay for local infrastructure though, for example the costs of the core infrastructure to new developments mentioned above could perhaps be paid off by a targeted rate levied against that area so it doesn’t impact on the rates of the rest of the city.
A few other recommendations around rates are made. This includes that council rates should be based on land values not capital values as it would encourage “land to flow to its highest value use”. It also suggests that the government should pay rates on core crown land including hospitals and schools. This is for the same reason as having rates based on land values, to encourage the best use of it. It’s one recommendation that I’m sure won’t be implemented. I would like to see rates paid by other organisations too such as churches. An example I highlighted the other day on twitter was this one up around Oteha with huge amounts of land dedicated to parking that pays almost nothing in rates due to being a church. Note: this is not a debate about or an attack on religion.
There are a number of other recommendations and in the interests of space and time I won’t cover them all. All up it seems like a fairly well balanced report that importantly recognises that cities and density are important. If you want to make a submission, you need to do so by 4 August.
I was a bit surprised to hear the Property Institute of New Zealand warn of an “apartment bubble” in Auckland earlier this week. I was even more surprised when I read their press release. The CEO, Ashley Church, is predicting a bubble as a response to 1) banks being likely to decrease their deposit thresholds on apartments from 20% to 15%, and 2) the Reserve Bank potentially bringing in “loan-to-income restrictions”, where mortgagees would then only be able to borrow X times their income.
The press release then gives a hypothetical chain of events:
1. The Reserve Bank restricts mortgage loans to a percentage of household income – effectively making the purchase of freestanding residential homes almost impossible to all but the very wealthy.
2. With median household incomes of just $76,500 – home buyers flock to the apartment market to find properties which comply with the new rules.
3. The relaxed deposit rules, by the major banks, allow buyers to borrow a little more if the apartment is new – (on average, a little over $400,000 if we adopt the Brit formula) – and this combination fuels a new wave of apartment building and streamlined marketing programs designed to entice buyers.
4. Property Investors – many of whom have also been caught by the new rules – also start buying apartments in large numbers.
5. The combined effect of this new wave of buyers quickly pushes up the price of apartments – fuelling an ‘apartment bubble’.
6. Perversely – the quality of new apartments suffers as developers focus on the ‘low-end’ of the market so as to appeal to as wide a range of potential buyers, within the Reserve Bank rules, as possible.
7. Meanwhile, the cost of renting free-standing homes in Auckland also increases as demand outstrips supply due to the absence of traditional property investors buying these types of properties.
8. Within 7 to 10 years Auckland becomes a highly ‘intensified’ city with large numbers of low quality apartments dotting the landscape and free-standing residential homes becoming the preserve of the well-off and wealthy renters.
However, this chain of events misses out half of what defines a bubble. He’s postulated a rise in prices, sure. But where does the subsequent decrease happen? To me, this sounds like a recipe for a one-off, permanent increase in apartment prices. A permanent shift in the demand curve, as it were. I’m not making any predictions on apartment prices, I’m just pointing out that the chain of events here doesn’t actually include a drop in prices, and therefore isn’t a bubble.
Moving on from that (rather important) point, there are a lot of other strange things in this press release. Firstly, it seems a bit far-fetched that the Reserve Bank would impose harsh restrictions to the extent that only “the very wealthy” could afford freestanding homes, and the press release also ignores the price response (i.e. prices would drop, and many people would still end up in those homes – there aren’t enough “very wealthy” people to fill them all up).
Secondly, if the Reserve Bank is going to clamp down on Auckland home loans, it’ll be because they’re worried about a city-wide bubble. I’d say this is a much bigger concern than an apartment bubble – it’d affect a lot more people.
Point 7 is one I’ve been reading a few variations of recently, which doesn’t follow from economic intuition. If landlords drop out of the market, do rents to rise? Given that each landlord dropping out of the market means there’s an owner-occupier there instead – and therefore a smaller rental market on both sides – the effect on rents might go either way.
Points 6 and 8 in the chain of events are odd too, essentially scaremongering about large numbers of low-quality apartments. The press release continues in a similar vein:
Mr Church says that he is aware that a focus on ‘intensification’ through building more apartments is consistent with the Auckland Unitary Plan and that some might see this outcome as a good thing – but he notes that this provision is also strongly rejected by a large number of Aucklanders and shouldn’t be forced on the city by the Reserve Bank.
“The drive for Intensification is based on a political ideology and is rejected by a large number of Aucklanders. It should only happen if Aucklanders want it”.
It’s a strangely political statement itself, coming from an organisation which began as the professional body for valuers. The PINZ’s statement in March that “the Reserve Bank Governor needs to “stop chasing shadows and stick to his knitting” seems a bit ironic.
As an aside, I think it’s great that the banks reviewing their lending policies on apartments; after all, it’s a more established market now than it was ten years ago, and there’s (hopefully) a lot less speculation going in that market than there was in the mid-2000s boom-bust. The banks will still be cautious about lending for leaky or leasehold buildings, and perhaps shoeboxes, and once those are taken out of the equation the apartments that are left should have a manageable level of risk.
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.
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?
On the Weekend TV3’s The Nation discussed what could end up being one of the defining issues of the next few decades, generational inequality. At its most basic it’s the idea that through various policy decisions older generations have effectively pulled up the ladder behind them on issues such as housing and infrastructure thereby making it much more difficult for younger generations. This is also something that’s not unique to New Zealand and the same issues are also being grappled with in many western countries.
First up on The Nation was Shamubeel Eaqub from the NZ Institute of Economic Research (NZIER) talking primarily about housing and how that it’s not just about home ownership but that it is likely to have other impacts throughout society such as pushing out poorer people further away from the city and the opportunities it can offer while saddling them with higher transport costs.
Following this The Nation hosted a debate (two segments) between a Baby boomers represented by former National MP Tau Henare, Former National Party President Michelle Boag and Otago University Economist Simon Chapple and ‘Team Gen X and Y’ represented by Morgan Foundation Economist Geoff Simmons, Green MP Julie Anne Genter and former Salient Editor Asher Emanuel.
In my view the contrast between the two groups was stark. The younger were much more calm and composed, they seemed to have come prepared with facts and were able to (or at least attempted to) use them. By comparison the boomers (with perhaps the exception of Simon) where shouty and arrogant and best summed up by Michelle Boag’s closing comment of “Don’t give me evidence”. Another thing I noticed was that quite often when trying to say that they had it tough the boomers were actually referring to the experiences of their parents struggling to get by which in many ways is one of the core points of the generational debate. Older generations worked hard to give their boomer kids a better future but those boomers are increasingly putting in place polices that make it difficult for younger generations to do the same.
The debate primarily focused on housing. As expected there were of the typical old chestnuts that often get trotted out in this kind of debate. These include:
That parents help out their children to get in to homes. This was quite well addressed by Shamubeel in the first section who noted that it’s only good if you happen to be born to parents who own a house.
That “Back in the 70’s/80’s we paid higher interest rates” came up fairly quickly but the reality is a high interest rate on a cheap house is still probably better off than a low interest rate on a very expensive house. It would be interesting if anyone has worked out the differences however a quick google search did find this from Stats NZ showing that we’re now spending over 2.5 times more on housing than we did in the past and given this is at a national level it’s probably even higher in Auckland
Our (our parents) generation used to move further out and buy a small bach and live in it for a couple years while saving up money to buy or build something larger. One of the issues with this is that we appear to be seeing a correction in land prices back to more historical trends where land prices closer to town are much higher, that means buying a house further out and saving money can still be a futile effort. Regardless, if anything this generations version of it is buying a small apartment or town house. The problem is if we want people to have starter homes we need to enable the construction of small and cheaper dwellings.
That also raises another issue that was highlighted in that there is an element of regulatory capture in urban planning. Existing home owners in desirable areas have used the planning process to prevent any new housing to be developed in their neighbourhoods, thus driving up the value of their houses. Any moves to change that are met with strong opposition come election time so politicians are too scared to do anything.
There were a few other related issues too such as education, employment and superannuation.
Demographia state that planning regulations – or, more precisely, metropolitan urban limits – cause houses to be unaffordable. Without planning, they claim that the median house would cost no more than 3 times the median household income.
Is this claim actually true? Last week, I took a look at some recent research by New Zealand economists that found that Auckland’s planning regulations had a much lower cost than Demographia think. (But still a substantial cost, especially for apartments.) So that’s evidence against Demographia’s claims.
But to really test the robustness of their analysis, I’m going to attempt what mathematicians call a proof by contradiction. My aim is to show that it cannot be the case that planning is the only factor that is pushing the median multiple above three for standalone houses. In order to prove that I will have to show that Demographia’s claims are mathematically impossible.
Somewhat to my surprise, this is not particularly difficult.
The first step in the proof is to consider the channels through which planning regulations can impact the cost of housing. They can:
Constrain the supply of bare land for development, which will tend to drive up the price of land
Limit the number or size of dwellings that you can build on a site
Impose cost, delay, and uncertainty in the regulatory process, which may scare some people off entirely.
Consequently, I’m going to look at what houses would cost if only construction costs mattered. No land costs, no consenting requirements, or anything else. That way, we can be certain that we’re not accidentally including any costs that arise as a result of planning regulations.
If the cost to physically build an average house is greater than three times the median household income, then planning regulations cannot possibly explain all of the difference between observed prices and Demographia’s preferred median multiple of three. For Demographia to be correct, land costs would have to be negative in the absence of planning regulations. As this is a logical impossibility, this would be sufficient to prove that Demographia’s estimates of the cost of planning regulations in New Zealand cities are too high.
Without further ado, here are my calculations. I’ve drawn this data from several reliable sources:
Construction cost data for different cities from a recent edition of Rawlinsons Construction Cost Handbook, a reliable source on building costs. I’ve used the midrange of their estimated costs for a single-storey weatherboard home – the most common, cheapest option on the market.
Statistics NZ’s building consents data, which shows that over the last 10 years the average size of new residential dwellings has been around 190 m2. (This is actually likely to under-state the size of new houses, as it also includes apartments. Also, note that it’s necessary to go into Infoshare to actually access the data.)
Median household income (2013)
Average build cost ($/m2)
House size (m2)
Total build cost ($/house)
Median multiple of build costs
Fairly remarkable results. The costs of physically building an average-sized house in four New Zealand cities ranges from 3.5 times the median household income (Wellington) to 5.7 times (Dunedin). The “median multiple of build costs” seems to always be above three.
We have just shown that planning regulations cannot fully explain the difference between house prices in New Zealand cities and the prices that would be implied by a median multiple of three. That is, in fact, a logical impossibility. Demographia seems to be over-stating their case, probably substantially. Quod erat demonstrandum.
However, it does look like construction sector productivity might be a bit of an issue. Different sources disagree on whether New Zealand faces higher construction costs than Australia and other countries. In its 2012 Housing Affordability Inquiry, the Productivity Commission suggested that pay more for construction. On the other hand, a rather excellent NZIER report that benchmarked construction costs against Australia found that we don’t.
So who knows what to think? Economists, eh?
That being said, it’s clear that productivity trends in the building industry are not flash. Here, for example, is the Productivity Commission’s graph of growth in construction industry productivity since 1978. In short, there hasn’t been much:
To summarise, there are many factors driving New Zealand’s house prices. Planning regulations are part of the picture, but as I’ve shown here they cannot possibly explain everything about our high housing costs. We’ve got to also consider other supply-side factors, such as construction productivity and the availability of building tradesmen, and myriad demand-side factors ranging from urban amenities to tax policy to interest rates. And, of course, we might want to ask why people aren’t choosing to respond to high building costs by building smaller houses. (Perhaps it’s an income effect – wealthier people spending more on big houses? Or perhaps there are some rules that make it difficult to build small, efficient dwellings?)
What do you make of the data on residential construction costs?
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?
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:
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:
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.)
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.
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 previouslyargued, 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.
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’.”
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.
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?
Accommodating a growing population can certainly be challenging. It means having to find more money to invest in transport and water infrastructure to enable new residents to live and travel in the city. As Auckland Council’s recent consultation on the Long Term Plan shows, asking people to pay more is never a very popular proposition – even if they like how the money’s being spent.
And, as Stu pointed out in his post on Auckland house prices this Monday, population growth can also put pressure on housing markets. Multiple researchpapers from the Reserve Bank have shown that increases in net migration tend to be followed by increases in house prices – shown in this chart. Obviously, homeowners do quite well out of this, but others face added costs:
In short, it’s not surprising that some people feel trepidatious about population growth and migration. And it’s not surprising that those anxieties are especially present in Auckland, which is projected to continue growing rapidly over the next three decades.
While unease about population growth is understandable, I’d argue that it’s misplaced. In my view, the benefits of urban population growth in New Zealand far outweigh the costs. While large urban areas can become dysfunctional – think of Beijing’s astonishing smog problems or the high cost of infrastructure in sprawling American cities – New Zealand’s cities are nowhere near large enough for the diseconomies of scale to triumph over the economies of scale.
This is easy to see if we look at the periods when Auckland hasn’t been attracting migrants. Here’s a chart from a presentation on Auckland’s demographics by Auckland Council social researcher Alison Reid. It displays the composition of Auckland’s population growth since 1922. In recent decades, natural population increase – i.e. people having babies – has been the biggest source of growth. Net migration is important, but it can be quite volatile – surging up and then crashing back.
What stood out to me from this chart was that the years with little or no net migration to Auckland have not been good times for the city. Net migration slowed to a trickle during the Great Depression, and turned negative during the constrained years during and after World War Two. More recently, quite a few people fled Auckland during the economically calamitous Muldoon years. Net migration remained low during the painful adjustments imposed by the following two governments.
I wasn’t living in Auckland during the 1990s – my parents had joined the queues leaving via Auckland airport – but friends who were say that the city was turning into a ghost-town. History shows that shutting off the migration tap has never led to a better, more vibrant city or more opportunity for residents. It’s simply been a sign of failure.
My hypothesis is 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.
We can’t fully control this process, as it depends in part on what’s happening in Australia and the rest of the world (not to mention macroeconomic variables that we don’t fully understand). But we can make sure that our cities are in a good position to take advantage of population growth.
The first, and most important thing we can do is to build better cities that are able to attract and efficiently accommodate more people. In Auckland, for example, we’ve got some challenges, including transport investment that’s been heavily skewed towards cars (and only cars) and rising house prices. But the flip-side of those is that we’ve got great opportunities to:
Improve transport choice by investing in Auckland’s “missing modes” – a frequent bus network throughout the city, rapid transit infrastructure, and safe walking and cycling infrastructure
Invest in great public spaces, such as Auckland’s waterfront and increasing numbers of shared spaces.
Second, as we attract more people to our cities, we need to accommodate them in an efficient and environmentally responsible way. This means enabling people to live in areas that are accessible to jobs, shops, and other amenities. As I found when I looked at carbon emissions from commutes in New Zealand cities, people in inner-city areas are considerably more environmentally friendly than their co-workers from the urban fringe.
Moreover, the data shows that increasing density can be a positive-sum game for existing communities as well as for the environment. At the city level, we can’t observe any relationship between rising population densities and congestion – fears of traffic-choked streets just don’t seem to have materialised in practice. (So much for diseconomies of scale!)
Which suggests that there is also a third important thing that we need to do, which is to tell good stories about the opportunities that urban growth will offer us. New Zealand’s used to thinking of itself as a rural economy with some cities sprinkled around as afterthoughts. That’s a dated and inaccurate self-image when over half the economy is located in our three largest cities.
Bayleys calculated the first-year mortgage repayment costs for different suburbs based on median house prices from the Real Estate Institute of New Zealand (REINZ) and the ANZ variable rate of 6.74 per cent.
It found the annual cost of servicing a mortgage for a median priced Orakei or Remuera home ($1.35 million) was $84,060 in the first year.
In Pukekohe, where the median price of a home is $500,000, the annual mortgage repayment in the first year would be $31,128.
Even factoring in the $4032 annual cost of commuting from Pukekohe to the CBD by train on the At Hop card system – as well as the $768 public transport cost from Orakei to the city – living in the southern suburb was about $50,000 cheaper.
First, they’ve chosen a misleading measure of housing costs. House prices aren’t a realistic measure of the true cost of living at a point in time, as they are influenced by a range of short-term and long-term factors. In particular, when you buy a home, you are actually buying three very different things:
A place to live right now
A place to live later, when you have paid off the mortgage
In other words, looking only at house prices is like arbitrarily including the cost of Kiwisaver into your housing costs.
My intuition is that rental costs are a better indicator of housing costs. They’re certainly less volatile, as I found in a recent paper that I co-authored on the relationship between rents and prices in Auckland. One of the key findings in that paper was that rents were quite low relative to prices in inner-city and coastal suburbs. As the following maps shows, median rents are only around 1/3 to 1/2 of median mortgage repayments in Remuera:
It’s not as though data on rents isn’t available. The Ministry of Business, Innovation and Employment publishes quarterly data on average rents for new tenancies, broken down by suburb, dwelling type, and number of bedrooms. So let’s take a look at that data instead. According to MBIE’s data, the average weekly rent for a three-bedroom house was:
$754 in Remuera (or $39,000 per annum)
$406 in Pukekohe (or $21,000 per annum)
However, there were a number of cheaper options available in Remuera, and the inner suburbs in general. Going down to two bedrooms would reduce your rent by $9,000 per annum – a viable and attractive option for many households – and looking for flats or apartments would save even more money.
But basically, looking at the rental data shows that most of the cost of buying in Remuera is not related to housing costs per se – you’re actually buying the expectation of capital gains. The rent data shows that it’s still possible to save money on housing costs by living further out, but the magnitude of savings is far lower.
Which brings me to a second major flaw in the Herald’s analysis: They have only accounted for the monetary costs of commuting further into the city centre and completely excluded the value of people’s time. A quick look at AT’s journey planner shows that the train trip from Pukekohe to Britomart takes about 70 minutes, while a public transport trip from Remuera to Britomart takes 20-30 minutes depending upon whether you’re closer to the train station or a bus route.
In other words, the Herald has assumed that people don’t mind spending an extra 80-100 minutes commuting every day. They haven’t even tried to account for the cost of wasted time. Most researchers and transport economists disagree with this approach. Here, for example, is a discussion of the subject from Charles Montgomery’s great book The Happy City:
[University of Zurich economists] Stutzer and Frey found that a person with a one-hour commute has to earn 40 percent more money to be satisfied with life as someone who walks to the office. On the other hand, for a single person, exchanging a long commute for a short walk to work has the same effect on happiness as finding a new love…
Daniel Gilbert, Harvard psychologist and author of Stumbling on Happiness, explained the commuting paradox to me this way:
“Most good things and bad things become less good and bad over time as we adapt to them. However, it is much easier to adapt to things that stay constant than things that change. So we adapt quickly to the joy of a larger house because the house is exactly the same size every time we come in the front door. But we find it difficult to adapt to commuting by car, because every day is a slightly new form of misery, with different people honking at us, different intersections jammed with accidents, different problems with weather, and so on.”
In short, the Herald’s analysis has:
Overstated the real magnitude of financial savings from living in Pukekohe vs Remuera by a factor of three – a comparison of rental data suggest that the financial savings are actually $16,000 per annum or less
Ignored the non-monetary costs of commuting extremely long distances, which makes people miserable. All else being equal, people should be willing to pay more to live in the areas which have the best job accessibility.
My advice, if you are choosing where to live in Auckland, is to disregard the advice of real estate spruikers such as Bayleys and the Herald, and take a more objective and comprehensive look at the topic using the affordability.org.nz app developed by my co-worker Alex Raichev. The app provides information on a much broader range of factors, including the rents, the monetary and time cost of commuting, and the costs of car ownership. Here’s a sample:
And, as always, my advice to the Herald is to check the facts more comprehensively before committing this sort of thing to print.
My lasttwo posts about Demographia’s analysis of house prices prompted quite a bit of discussion. I thought that it may be worth expanding on my points and clarifying why they mean that we should take Demographia’s conclusions with a large grain of salt.
Economists (and statisticians) have a term for what Demographia has done: “omitted variable bias”. This can occur when there are multiple variables that have a causal impact on an outcome. If we attempt to understand that outcome without considering all explanatory variables, we run the risk of biasing our conclusions.
Economists are trained to identify and address issues arising from omitted variable bias. Here, for example, is a comment on the topic from a widely used undergraduate econometrics textbook:
Now suppose that, rather than including an irrelevant variable, we omit a variable that actually belongs in the true (or population) model. This is often called the problem of excluding a relevant variable or underspecifying the model. We claimed in Chapter 2 and earlier in this chapter that this problem generally causes the OLS [ordinary least squares regression] estimators to be biased.
Now, I realise that’s a bit obscure, so let me be more specific. Here’s a list of (some) factors that can influence house prices, with a view on their expected impact:
Expectations for future population and economic growth
Future expectations tend to be capitalised into house prices – i.e. prices will tend to be higher in areas with better growth prospects
Consumer and natural amenities
People are willing to pay more to live in nicer places
Interest rates (and availability of finance)
Lower interest rates enable people to afford a larger mortgage on a given level of income
Construction sector productivity
Lower productivity will increase the cost of supplying new dwellings
Tax policies, including capital gains taxes and mortgage interest deductions
Taxation of capital gains will reduce willingness to invest in housing for capital gains
Tax subsidies for mortgage-holders will tend to push prices up
Other housing market policies, such as rent subsidies or public housing provision
Rent subsidies tend to be captured by landlords and thus will tend to push up prices
Ongoing construction of state housing will add supply to the low end of the market and thus constrain price increases
Urban planning policies
Policies that constrain the development of new housing in desirable areas, or make it more costly or uncertain to develop, will reduce supply and push up prices
Demographia only addresses one of those seven variables. Because they fail to account for the other six potentially explanatory variables, their estimates of the welfare impact of urban planning policies are not likely to be reliable. Without controlling for other potential explanations for high housing prices, it’s impossible to say whether their conclusions about any individual city are correct or not.
Consequently, my recommendation to people seeking to understand the impact of urban planning policies on housing costs is simple: Ignore Demographia and go read the relevant economics literature instead. For those who are interested in doing so, here are a few papers that I have learned a lot from. They apply a range of modelling approaches, but what they have in common is that they undertake a detailed analysis of rules, rather than making sweeping and unsupported generalisations:
Glaeser, Gyourko and Saks (2005) studied the impact of building height limits in Manhattan by looking at the gap between observed sale prices and the marginal cost to add another floor to high-rise buildings. They find that constraining the supply of high-rise apartments imposed a significant “regulatory tax” on residents.
Grimes and Liang (2007) took at look at land prices around Auckland’s Metropolitan Urban Limit, finding evidence of a “boundary discontinuity”. They interpreted this as evidence that the the MUL is overly restrictive.
Kulish et al (2011) developed a hypothetical model of the impact of several factors on housing and transport costs. They modelled density restrictions as well as increased transport costs and lower building productivity, finding that building height limits raise housing costs and increase sprawl. I have previously discussed their findings.
MRCagney (2013) examined the impact of minimum parking requirements in Auckland, finding that they impose a loss on developers and businesses by forcing them to over-supply parking. They also cause worse congestion, meaning that not even drivers benefit. Luke C briefly discussed this study in a post on the Unitary Plan parking rules.
My favourite economics paper on planning regulations is Cheshire and Sheppard’s 2002 study on the impact of greenbelt rules in Reading, UK. The authors observed that greenbelts have both positive and negative effects. On one hand, they limit the supply of land for new housing, which drives up costs. On the other hand, they give residents access to public open spaces, which people like. Rather than ignoring this trade-off, they used house price data to model it.
Overall, Cheshire and Sheppard did find that allowing development in Reading’s greenbelt would make people better off. However, they also found that a failure to consider the amenities produced by planning rules would have resulted in too high an estimate of the gains in wellbeing. In other words: right direction, wrong magnitude.
In light of the evidence, my view is that failing to account for urban amenities and other explanatory variables in an analysis of the impact of supply restrictions can result in two errors:
First, it can make us over-optimistic about the degree to which loosening rules will affect housing prices. That’s not to say that less restrictive planning regulations couldn’t make us better off – just that we should not expect house prices to fall by 60-75% as Demographia implies when it says that Auckland should have a median multiple of 3.
Second, it can lead to perverse outcomes, by encouraging us to eliminate rules that are serving a useful purpose. Often (although not always) planning rules are managing the external social or environmental costs associated with some developments. A proper cost-benefit analysis – which Demographia has not done – will consider both the pluses and minuses of rules.
In short, housing markets are complex, and any analysis needs to consider that fact. To reiterate my point from last week: Demographia takes an inappropriate, overly simplistic view of house prices. This may be good for grabbing headlines, but it’s not good economics.