Aussie apartment boom: a year on

A year ago, I wrote that “Australia is currently in the middle of a major apartment boom“. Well, the boom is still going – in fact, it’s risen to even higher levels. On a ‘moving annual total’ basis, Australia has gone from approving 86,000 attached units a year to 113,000, an all-time record.* That’s helped push total dwelling approvals to 229,000, also an all-time record.


There are concerns in some quarters that there might be a looming oversupply of apartments in some areas, as noted by the Reserve Bank of Australia. I don’t know enough about the Aussie market to comment, but it’s certainly a reshaping of the market given the amount that’s being built. Speaking of reshaping, Patrick’s post the other day showed how the apartments will change the Melbourne CBD skyline (well, showed how one part will change, I’m not sure if it’s as drastic for other areas).

Back in New Zealand, building consents continue to rise, but not to the same extent. My view is that there’s a lot more growth to come, especially for attached dwellings,** and especially in Auckland. Keep an eye out for this over the next few months.



Lastly for today, here’s an update on the percentage of new dwellings which are attached, for both Australia (which has reached an all-time high, of 49.5%) and New Zealand.



As per last year, I’ll follow up soon with a post looking at the trends in different cities. But I think the trends above for Australia are pretty impressive in their own right.

*Technically, the Australian approvals are for “dwellings excluding houses”. That covers apartments, terraces and so on.

** Statistics New Zealand have changed their categories since last year. I’ve combined the categories for “apartments”, “townhouses, flats, units, and other dwellings”, and “retirement village units”. Note that some of the retirement villages will actually be detached homes, but they’re not split out in the data.

Geography and housing supply dynamics

Last week, I introduced the concept of elasticity of supply with respect to price as a useful measure of housing market dynamics. Supply elasticities measure how responsive builders are to an increase in demand. In other words, when people turn up wanting dwellings, how quickly do the tradies start building more?

Supply elasticity can in turn have a big, long-run effect on prices. If the building sector is consistently slow to respond, it creates the condition for an ongoing shortfall in supply, which means that people will bid up prices more.

My post last week took a look at some of the (limited) international comparisons of planning regulations, which seem to indicate that New Zealand is not an especially poor performer. For example, consent processing time is relatively fast and efficient compared with other OECD countries.

However, regulations are only part of the picture. For example, Patrick wrote a good post a while back looking at Auckland’s geographic constraints:

AKL from space

Intuitively, we’d expect Auckland’s limited supply of developable land to have an effect on housing supply dynamics. But how much of an effect should we expect?

The empirical literature provides us with a reasonable estimate. A 2010 paper by MIT economist Albert Saiz (Massachusetts, not Manukau) measures constraints on land availability in large US cities and uses them to estimate the effect on housing supply.

Saiz finds that there are large differences in land availability between different cities. For example, “flatland” cities like Atlanta or Houston have very little area constrained by lakes, rivers, oceans, or steep slopes. Over 90% of the area around these cities is available for development. Coastal cities like San Francisco, San Diego, or Miami, on the other hand, might be able to develop less than 1/3 of the surrounding area.

Saiz concludes that:

Quantitatively, a movement across the interquartile range in geographic land availability in an average-regulated metropolitan area of 1 million is associated with shifting from a housing supply elasticity of approximately 2.45 to one of 1.25. Moving to the ninetieth percentile of land constraints (as in San Diego, where 60% of the area within its 50-km radius is not developable) pushes average housing supply elasticities down further to 0.91.

Translated from economese, this means that cities with less developable land have housing markets that respond more slowly to increased demand. (Or, as non-economists might say, duh.) For context, an elasticity of 0.91 indicates that a 10% increase in house prices is met by a 9.1% increase in housing supply. Even if regulations are held constant, a “flatland” city is expected to have a more responsive housing market than a coastal city with lots of hills.

In other words, when people compare Houston’s house prices with San Francisco’s or New York’s, they’re not comparing like with like. Geography matters quite a lot!

So what does Auckland’s geography look like? A 2014 NZIER paper modelled the effect of geographic and regulatory barriers on the city’s house prices. The authors conclude that: “relative to even Australian cities Auckland’s twin harbours severely restrict the availability of well-located land close to the city centre.” Overall, they estimate that less than one-third of the area around Auckland is available for development – most of the rest is water:

NZIER Auckland's narrow geography

In other words, Auckland has very severe geographic constraints. In terms of the availability of developable land, it’s similar to hilly coastal cities like San Diego. Saiz estimated that a city of around Auckland’s size with an average level of planning regulations would have a supply elasticity of 0.91. So: does Auckland perform better or worse than this in practice?

A 2010 study by Arthur Grimes and Andrew Aitken provides some relevant data. Using data at a district council level, they looked at how quickly new dwellings were built in response to “shocks” in demand such as increases in net migration. Their key conclusion was that housing supply in New Zealand’s urban areas tends to be a little bit more responsive than supply in rural areas:

If we divide regions into urban and rural, we find faster adjustment in urban areas (average γ1i = 0.0093) than in rural areas (average γ1i = 0.0064). This result is consistent with an active development industry, based principally in cities, facilitating new construction.

In other words, the authors estimate a supply elasticity of around 0.93 for NZ’s urban areas (principally Auckland). This is almost exactly what we would predict based on Auckland’s geography. The implication of this is that Auckland’s housing market functions more or less as expected given its geography – we don’t have to assume unusually restrictive planning regulations to explain the observed outcomes.

There are a couple lessons we can draw from this.

First, Auckland’s geography is a primary driver of the city’s housing supply dynamics. If we have higher house prices than we’d like, it’s partly because we have less land for housing. As I’ve written before, some analyses of Auckland’s high house prices fall prey to omitted variable bias – i.e. ignoring important causal variables and thus over-estimating the impact of specific policies. This can result in flawed policy recommendations.

Second, we shouldn’t compound constrained geography with bad policy. Because Auckland doesn’t have much developable land, there is an even stronger incentive to use land efficiently. (A fact with implications for transport policy, planning policy, tax policy, and publicly-owned land.) Land-hungry policies might not be too bad in a land-abundant place like Houston, but requiring Auckland to follow a similar pattern is economically calamitous.

As most New Zealand cities are also heavily constrained by geography, this challenge isn’t unique to Auckland. But it’s also not all bad: the interplay of mountains, volcanoes, harbours, and oceans is what makes New Zealand such a beautiful place to live. Let’s build cities that enable us to get the best out of it.

Double EMU Orakei Basin

Concepts: Elasticity of housing supply

How should we think through the dynamics of housing markets?

Conceptually, there’s a very simple answer and a very complex one. The simple version is that housing is just another market, shaped by the interaction of demand – i.e. people turning up with money to buy dwellings – and supply – people building new dwellings to meet demand. Policies can affect the supply side (e.g. by making it more costly or difficult to build new dwellings), the demand side (e.g. by subsidising home ownership), or both (e.g. by imposing supply restrictions to produce local amenities like parks).

And then there’s the complex story, in which we have to think about things like:

  • Interactions between owner-occupation, renting, and property investment
  • The impact of mortgage lending practices and asset values on housing
  • The durable nature of housing, which means that prices can overshoot in a declining market
  • The geography of jobs, amenities, and housing supply – not all locations are equally desirable, which means that houses in the wrong place don’t do much good
  • Government provision of housing services (e.g. state homes) and subsidies for property ownership or renting
  • Industrial organisation in the building sector, including firm size and structure and supply of skilled labour
  • A wide range of local and central government regulations covering building materials, performance standards for dwellings, and the bulk, form, and location of dwellings
  • Etc, etc, etc.

So it’s not usually possible to fully explain housing market dynamics with a simple supply and demand story. However, it’s often useful to start with a clear understanding of that story.

So with that in mind, here’s a key concept for analysing housing market dynamics: elasticity of housing supply. In an earlier post on public transport fares, I introduced the idea of elasticity of demand, which measures how responsive people’s demand for a good or service is to higher (or lower) prices. Supply elasticities are much same idea, but on the supply side of the equation.

Elasticity of housing supply is an important concept because it provides an indication of how many new dwellings will be constructed in response to an increase in prices (or demand). For example, an elasticity of less than 1 would indicate that developers are relatively unresponsive to increased demand – i.e. if prices rise by 10%, it will cause new housing construction to increase by less than 10%.

It’s easy to see why this is an important metric. In the aggregate, a relatively “inelastic” supply will mean that the housing stock will struggle to meet demand in a growing city. But aggregate lasticities aren’t everything – if new dwellings can’t be built in areas that are proximate to jobs and amenities, bad things will still happen

Supply elasticities can be measured empirically by looking at how markets have evolved in the past. In fact, a number of people have done just that.

In their 2012 housing affordability inquiry, the Productivity Commission surveyed some of this literature (see pages 33-34 of their final report). They published this chart comparing long-run elasticity of housing supply in 21 OECD countries, including New Zealand. Remember, higher numbers indicate more responsive housing supply:

Productivity Commission elasticity of housing supply chart

New Zealand’s elasticity was around 0.7 – on the inelastic side, but still within the top 1/3 of the countries in the study. In other words, neither terrible nor fantastic. We have historically had a more elastic supply of housing than the UK or Australia, but we’ve lagged behind several Scandinavian countries as well as Japan, Canada, and the US.

Now, elasticity of supply is influenced by a number of factors. Building industry capability and productivity plays an important role. So do geographic constraints – a topic I’ll come back to in a future post. State house construction can also play a role, by ensuring that building activity doesn’t bottom out when prices dip. And, of course, planning regulations and consenting processes play a role. But how much of a role?

Unfortunately, we don’t have any good international comparisons of planning policies. However, the World Bank’s annual Ease of Doing Business report publishes some data on the ease of obtaining building consents, which provides a rough indication of the stringency of countries’ planning processes.

Here’s the upper echelons of their 2015 rankings. As you can see, New Zealand is ranked as the second easiest place to do business. When it comes with dealing with construction permits, we’re ranked 13th – ahead of countries like the United States (46) and United Kingdom (45) but behind Hong Kong (1), Singapore (2), and, oddly, Iraq (9).

World Bank ease of doing business rankings

Here’s a bit more detail on how Auckland’s consenting processes stack up. We have fewer procedures, a shorter consenting timeframe, and a lower consenting cost than the average OECD country:

World Bank NZ ease of dealing with construction permits

So what does all this data mean? I think there are a few lessons we can – and can’t – learn from it.

The first is that perhaps we don’t have as many problems as we think we do. I have to admit that I was surprised by these figures. I was expecting our elasticity of supply to be lower and our consenting processes to be ranked lower. But perhaps – as with Auckland’s congestion – our problems aren’t that bad when put in international perspective. Kiwis do tend to prefer doing things efficiently, and NZ’s not large enough to require overly cumbersome bureaucratic machinery.

The second thing is that there is room to improve. There is almost always room to improve. New Zealand’s housing supply is still inelastic, which suggests that we may have trouble accommodating growth. Although the World Bank’s data on the ease of obtaining building permits seems to suggest that regulatory processes are less onerous here than many other places, who really knows? There are likely to be gremlins in any bureaucratic process.

The third lesson is that there are multiple paths to a well-functioning housing market. The countries with the highest elasticities of housing supply don’t have a lot in common with each other when it comes to policy frameworks. The US has a different set of policies than Japan or the Scandinavian countries. And it’s also the case that some countries have affordable and livable housing even though their elasticity of supply is low – Germany or the Netherlands, for example.

This is, in a way, really good news. We don’t have to go searching for a single “silver bullet” policy framework. There are different paths we could go down to improve the functioning of our housing market.

What do you make of these comparisons?

Briefing Papers 8: “Real Estate Debt and the Balance of Trade”

AUT’s Briefing Papers initiative has kindly allowed us to syndicate their recent series on housing. The eighth paper is by investor and company director John Walley:

Auckland has a housing problem but this is not just a problem for Aucklanders, or new home buyers. Out of control asset inflation – as seen in the Auckland housing market – is toxic to the real economy, destroying our ability to deliver a long-run neutral balance of trade. High asset price inflation misdirects investment and lowers the competitiveness of the tradable sector resulting in lower average wages and falling returns to trade.

Under current conditions investment is largely focused on assets, not productive enterprise. In an effort to check rises in asset prices, interest rates in New Zealand are higher than other countries. Consistently higher comparative interest rates results in a stronger New Zealand dollar than would otherwise be the case, reducing export returns, competitiveness of manufacturers in our domestic market and lowering incentives to invest (key to future innovation, competitiveness and capability). Inequality is worsened, as house and land values contribute to higher living costs; this further damages our economic performance, as recent OECD research has shown higher inequality to be a drag on economic growth. As house prices rise, indebtedness rises in comparison to earnings, increasing vulnerability to economic shocks that can threaten financial stability.

Ever expanding debt, supported by banks and the large monetary stimulus programmes in the U.S, Europe, U.K and Japan, and even by the Reserve Bank of New Zealand (RBNZ rules favour land and buildings on bank balance sheets), fuel ever higher average house prices with respect to average earnings. This process is supported by the notion that prices will always rise and that debt will be paid by the (tax free) capital gain. The risk to stability is, of course, if prices fall. Research by the OECD estimated when household debt rises above trend by 10 percent of GDP there is a 40 percent chance of the economy entering recession in the following year, compared to 10 percent likelihood when household debt is rising at trend.

More generally, recent OECD research looking at the role of finance and growth suggested the following is the case in most OECD countries: more credit to the private sector slows growth; more stock market financing boosts growth; credit becomes a stronger drag on growth when it goes to households rather than businesses; and bank loans slow economic growth more than bonds.

Auckland house prices are high when compared to incomes. The graph below compares housing affordability (the ratio between median house prices and median annual household income) for each countries’ major markets – for New Zealand, this is the Auckland housing market. As of September 2014, the median house sale price in Auckland was 8.2 times median household income – the survey median was 3.8. The New Zealand national median house price-to-income ratio is also high, at 5.2. Demographia defines income multiples of 5.1 and over as ‘severely unaffordable’.

Source: Demographia

Household debt reached a peak of 162.2 percent of disposable income in the first quarter of 2015, after previously peaking close to this at 161.2 percent in the second quarter of 2009. New Zealand’s household debt-to-GDP ratio is at 95 percent, down somewhat on the peak of just over 100 percent in 2009. Research by the Bank of International Settlements (BIS) suggest that household debt over 85% of GDP can damage an economy, though greater sensitivity to economic downturns, and by boosting debt for non-productive assets, pulling resources from the rest of the economy to service it, including skills and investment.


This is the problem – for the whole New Zealand economy. Will building more houses in Auckland fix it?

Under-supply of housing naturally leads to higher prices, particularly with high net migration. Hence the solution to this part is to increase supply, open up new land for development, focus on increasing the number of houses built and responsibly reduce constraints and barriers to new builds. It is also important that such developments target high density development, particularly in larger cities such as Auckland, to reduce the cost of urban sprawl (some commentators have called for a debate on migration).

But supply side activity has a limited pace as the allocation of finite construction resources and labour has a limit, made worse when in catch-up mode, as seen in the large deficit in the cumulative net supply position in the graph below – this is a key area for the Government to do more, especially ensuring affordable housing is built. Low rent inflation suggests investors and speculators are contributing to house price inflation.

Graph Source: MBIE

Supply side efforts take a while to take effect, and the threats to financial stability and the damage to the tradable sector are with us right now. More needs to be done. The supply response in the last two decades has favoured more expensive housing, rather than affordable homes, exasperating the inequality effect.

Source: OECD Economic Survey – New Zealand

Intervention on the demand side, such as a register of foreign buyers, borrowing limits related to asset earnings and/or buyer earnings, higher deposits for landlords and capital gains enforcement can act quickly to reduce the growth in debt, slow price rises and thereby improve financial stability.

Other countries have acted:

  • Last year the Bank of England reintroduced Loan to Income Ratios, where no more than 15% of mortgages issued can exceed a Loan to Income Ratio of 4.5.  If you earn £100,000 a year, your loan would be capped at £450,000.
  • The Central Bank of Ireland introduced Loan to Income Ratios, of 3.5 times of gross income and Loan to Value Ratios set at 80% (a 20% deposit is needed) with a lower ratio of 70% for those buying rental properties. For first home buyers this is set at 90% for properties up to €220,000, with 80% on any value exceeding this. This tougher requirement on rental investors reflects their higher default risk as compared with owner-occupied homes.

Research by the BIS suggests that such macro-prudential tools can be effective in slowing house price inflation and mortgage credit growth if they are introduced at a time when these are both high. In other words, they can be most effective in slowing a boom, and are less invasive at other times, keeping the lid on gently.

Another issue often cited as a factor increasing prices is demand from foreign investors. Unfortunately with no register of such ownership in New Zealand it is hard to judge the extent of this.

  • Singapore introduced stamp duty taxes on non-resident buyers of property. This tax now sits at 15%, increasing from 10% when it was introduced in 2012. They also introduced a cap on debt repayment costs at 60% of the borrowers’ monthly income. These measures have seen prices fall 4% in 2014, and sales volumes falling.
  • Australia: there are proposals to introduce such a register as well as fees on foreign investors: A$5000 fee for property up to A$1m, and investments over A$1m would incur an A$10,000 fee for each additional A$1m purchased. These measures are probably too small to make much difference but are a start. Foreign investors are limited to purchasing new build, and not existing property, and these rules may be strengthened. The state of Victoria is now also planning a 3% tax on foreign buyers of property.
  • England, Ireland and Australia also have some form of Capital Gains Tax.

In a recent speech, the Deputy Governor of the RBNZ suggested New Zealand needs fresh consideration around tax settings for housing, particularly for investors, sayinghousing is the most tax-preferred form of investment, particularly when it is highly leveraged. Indicators point to an increasing presence of investors in the Auckland market and this is no doubt being reinforced by the expectation of high rates of return based on untaxed capital gains.”

While we have seen positive steps forward by both the RBNZ and Government in addressing these issues, wider reform is needed. Limiting the expansion of private debt to both earnings and equity is important not only for those trying to buy a home, but to reduce the impact on competitiveness of the tradable sector through the exchange rate channel and cost of borrowing. More generally, the Government and RBNZ need to stop shying away from strong demand side changes, being sufficiently bold to tackle hard issues around the treatment of asset debt by the RBNZ, and fiscal policy changes by Government around the capital gains incentives.

Transport CBA, housing supply, and the spatial equilibrium

In comments to a recent post I wrote reviewing recommendations from the Australian Productivity Commission’s review of public infrastructure investment, reader Brendon Harre raised an important question about transport cost-benefit analysis (CBA). He commented that:

“the benefits of providing a grid of urban transport options (without mode bias) in advance of development in order to keep land, commercial and residential property affordable is not measured”

This is an important issue that’s worth careful consideration. As a best guess, I think that Brendon’s point isn’t quite true. In a roundabout way, transport CBA does capture benefits associated with enabling development. However, the modelling tools available might over- or under-estimate the magnitude of those benefits in some cases.

Let’s start by reviewing how transport CBA works in New Zealand. Here are the key steps:

  1. A transport agency or council comes up with a land use forecast – i.e. a rough idea of where people are going to live and work in the future.
  2. The transport agency then identifies two (or more) futures scenarios for the transport network in the area. For example, they may consider one scenario in which no new roads were built, and one in which a new highway is built at the edge of town.
  3. The agency then models the transport network under the fixed land use forecast and multiple transport network scenarios.
  4. Based on the modelling, it then calculates how travel times (and vehicle operating costs, emissions, etc) differ between the scenario. It sums up the reductions in travel times (etc), multiplies them by the average value of time, and then uses the resulting dollar value as the numerator in a benefit-cost ratio (BCR).

This procedure obviously bears little relationship to what we observe in practice. In reality, there is significant endogeneity between the availability of infrastructure and land use outcomes. In other words, if you build it, they will come, and vice versa. You can’t assume that land use will remain fixed if transport options change!

Another way of saying this is that rather than “banking” travel time savings from wider or faster roads, people tend to “re-invest” them into other things, such as living in a larger or cheaper house in a different location. (Or re-scheduling trips from off-peak times, shifting modes from PT, walking or cycling, etc.) Public transport is different, as it doesn’t get congested, but the principle is somewhat the same – speeding up journeys allows people to travel more.

Economists call this phenomenon “induced traffic”. I’ve previously discussed this phenomenon from a slightly different angle, focusing on the implications of induced traffic for how we manage and invest in road networks. I’ve argued that we should stop telling ourselves the lie that increased road capacity will ever “fix” congestion and accept that all we can do is give people alternatives to participating in congestion and implement congestion pricing to free up the roads.

However, I think it’s also worth considering what induced traffic means from a housing supply perspective. It’s useful to start by thinking about how individuals might respond to the opportunities created by new transport infrastructure. Let’s use the City Rail Link as an example, as we’ve got a good idea of what it will do for travel times:


Suppose I’m currently living in Morningside (I’m not, but it’s a simpler example) and facing the following costs for transport and housing:

  • Rent of $250 a week, assuming I’m flatting
  • Public transport fares of $30 a week, as a single journey to Britomart costs $3 with a HOP card
  • Travel time costs of around $130 per week, assuming that I value my commute time at around $20 per hour. It currently takes around 40 minutes to travel from Morningside to midtown by train, including the walk at the end.

Now let’s consider what will happen when CRL is done. My travel time will be cut dramatically – after CRL, it will only take 15 minutes to commute from Morningside. This is a big saving in travel time. Under these assumptions, CRL will make me better off by around $80 a week (i.e. ~4 hours saved * $20/hour).

However, I’ve also got the option to live further west in search of cheaper housing. Let’s say I choose to move to Henderson, where I pay a bit more in train fares (around $4.80 per trip) and save a bit of travel time relative to my old location. This only makes sense to do if it enables me to save at least $80 in rents for a similar dwelling. Otherwise, moving further out has made me worse off than simply staying in place and “banking” the travel time savings.

What we learn from this example is that the perceived benefits from relocating following the construction of new transport infrastructure, including lower housing costs or better quality housing, should be roughly equal to the added travel time cost of doing so. Economists describe this concept as the “spatial equilibrium” – i.e. people trade off housing and transport costs. As I found when looking at housing and commute costs in NZ cities, we can observe this trend empirically.

(That being said, there are reasons to think that moving further out in pursuit of cheaper housing is not necessarily a great idea. In The Happy City, Charles Montgomery argues that people overestimate the benefits they get from a bigger house, and underestimate the misery of longer commutes. But let’s set aside the impact of cognitive biases for the moment…)

The upshot of this is that, the standard approach to transport CBA actually seems to capture many of the benefits of new housing supply following transport infrastructure development. This sounds perverse – didn’t I say that transport models didn’t reflect reality very well? – but it makes sense when you think about how individuals make decisions about where to live and how to get around.

However, there are two caveats to this point. The first is that individuals don’t internalise all the costs (or benefits) of their location choices – there are externalities. If one location is better at generating positive spillovers in production or consumption (“agglomeration”), cheaper to serve with publicly-funded infrastructure, or responsible for fewer greenhouse gas emissions, it might be better to build infrastructure that will encourage people to live there. This is captured imperfectly in transport CBA at present – but it doesn’t have much of an impact on housing supply.

A second, more subtle issue is that our capital budget may be too constrained to deliver enough transport capacity to enable a sufficient supply of housing. For example, we may be pursuing a costly and land-intensive approach to supplying peak transport capacity that results in diminishing returns from investments. If that’s the case, we need to ask whether we have cheaper opportunities to add capacity to the transport network. (Or, alternatively, start raising taxes, which is always a popular option.)

What do you think about the spatial equilibrium in our cities?

Briefing Papers 7: “High House Prices: A Blunder of Our Governments”

AUT’s Briefing Papers initiative has kindly allowed us to syndicate their recent series on housing. The seventh briefing paper is by former Reserve Bank economist Michael Reddell:

There has been a strong sense this year that “something must be done” about high house prices, especially those in Auckland. To date, however, the policy responses display little awareness of how previous policy choices have made New Zealand housing increasingly unaffordable over the last couple of decades. Blaming investors or the tax system are largely distractions. And while non-resident Chinese purchasers may be bidding up house prices in Auckland (and Sydney, Vancouver and other cities) right now, these pressures are recent, while housing affordability problems are not. Increased demand for houses, whatever the source, doesn’t create problems if it is easy to bring new houses to market.

In 2013 Anthony King and Ivor Crewe published The Blunders of our Governments, which traced Britain’s experiences with various policy disasters over the previous thirty years. Unaffordable New Zealand house prices, especially in Auckland, are the predictable outcome of a similar blunder: the collision of two sets of perhaps well-intentioned policy choices.

In New Zealand, urban areas cover only around 0.7 per cent of our land. And land used for agriculture is just not that expensive. Prime dairy land at the peak of the boom in 2008/09 was selling for around $50,000 a hectare. Residential sections in Auckland, of less than a tenth of a hectare, are selling for ten times that much. The comparison isn’t precise – subdivisions need streets and footpaths etc, so one hectare of farmland doesn’t generate one hectare of residential land. But in research published in 2007, Arthur Grimes and Andrew Aitken found that land just inside the Auckland Metropolitan Urban Limit was selling for 10 times the price of land just outside the limit. Even if we had a construction industry that was as efficient and productive as any in the world, our house (house plus land) prices would still be very high just because central and local government together have created artificial scarcity. Auckland’s geography is certainly difficult, but that is all the more reason for having as few restrictions as possible on the ability of owners to use and develop land for housing. Land use restrictions appear to have become a much more serious constraint in the last 25 years. By contrast, in the 1950s and 60s, with a much stronger policy emphasis on home-ownership and house-building, planning restrictions (and especially land use restrictions) had a much less serious impact.

Of course, there are land use restrictions in place in local authority areas all over the country. Councils – staff and councillors – seem to feel a need to plan and central government legislation allows them to do so. But house prices in Auckland are four times those in Invercargill. That difference is really down to population growth differences.

In places where there is no population growth, land use restrictions still impose costs, but they don’t have much impact on house and urban land prices. And where land use restrictions aren’t very important, rapid population growth also won’t do much to boost house and urban land prices. An example is the big US city of Houston, where there are few land use restrictions. Over the last 35 years, Houston’s population has more than doubled while real house prices have actually fallen a little.

New Zealand’s land use restrictions are similar, in effect, to those in a range of other Anglo countries. House and land prices are extraordinarily high in places as diverse as Auckland, Sydney, Melbourne, London, Vancouver, and San Francisco. In each of these places, the inability to easily bring new land to market and use it intensively for housing runs into the pressures of rising demand from a growing population. When those two pressures collide, house prices rise. High house prices in these cities are not the result of aggressive and unwise lending by banks. They aren’t the result of speculation. They are just what happens when land use restrictions run head-on into population pressures. And housing demand is, in the jargon, quite inelastic. Existing residents of high-priced cities mostly don’t move somewhere else, partly because the big cities are where the jobs are. Sometimes the resulting high house prices are discussed as some sort of market failure, when it is a sustained failure of governments to allow markets to operate.

Where does the population pressure arise from? In the post-war decades most advanced countries experienced a high birth rate. Demand for housing rose strongly on account of this natural increase in population. Government policy choices didn’t have much to do with that source of demand, and governments in free societies generally don’t attempt to influence the rate of natural increase.

But natural population increase is now quite small in most advanced countries. Even in New Zealand, which has a relatively high birth rate by advanced country standards, the birth rate is only around replacement level. And for the last 40 years or so, New Zealand has had a large net outflow of New Zealanders, pursuing a better life abroad for themselves and their families. This outflow swings around a lot from year to year, but in total around 870,000 New Zealanders (net) have left in the last 40 years.

With little or no natural increase, and a substantial average annual outflow of New Zealanders, New Zealand’s population would now be falling slightly even with the modest rate of inward migration of non-New Zealanders we had in the 1980s. There would be no population pressure on the housing stock in the country as a whole, and probably only modest pressures even in Auckland.

But around 25 years ago, New Zealand immigration policy was reformed to encourage a much larger annual net inflow of non-citizens. The current annual target, reconfirmed by Cabinet only last year, is around 45,000 to 50,000 permanent residence approvals each and every year. That is one of the largest rates of non-citizen immigration (as a share of population) of any advanced economy. As one would expect, a disproportionate share of the migrants settle in our largest and most diverse city.

No one envisaged the impact on house prices when the land use restrictions became progressively more binding, or when the more expansive immigration policy was adopted. With hindsight the contribution of these two directly contradictory sets of policies is pretty clear. Land use restrictions might do little harm in a country with low or no population growth (the situation in many OECD countries today). And rapid rates of non-citizen immigration would have no adverse impact on housing affordability if land could be as freely used for housing as in Houston. As it is, the young and the poor, disproportionately of Māori and Pacific origins, find it almost impossible to purchase a house in our largest city simply because of the choices – blunders – of our governments. It is time for our government to confront that responsibility and to bring about change. If sufficient reform of land use restrictions is not possible – and the overseas precedents are not encouraging – the case for a significant reduction in the target rate of non-citizen immigration is pretty clear.

Briefing Papers 6: “The Problem With Migration”

AUT’s Briefing Papers initiative has kindly allowed us to syndicate their recent series on housing. The sixth paper is by economic commentator Bernard Hickey:

We’re now having a fractious debate about foreign buying of houses, but the more important and tougher debate we should be having is about migration.

Does it actually generate the right type of long term economic growth, or does it just pump up house prices and interest rates, suppress wages and reduce the incentives for New Zealanders to obtain the necessary skills for a modern economy?

Neither of the three biggest parties, National, Labour or Green, have challenged the consensus of at least the last 15 years that New Zealand needs plenty of skilled and unskilled migrants to juice the economy along.

There are plenty of employers who regularly argue that they need both types of migrants to keep their businesses, hospitals, hotels and farms running and growing. The Government has a target of allowing around 45,000 to 50,000 new permanent residents each year, including around 60% who are skilled migrants, over 32% who are family reunifications and over 7% who are approved for humanitarian reasons.

It may argue that one reason for high net migration is the uncontrollable movements of New Zealanders and Australians (who are often ex-pat New Zealanders), but that’s not the whole truth. The Government does control that Residence Programme and various schemes for international students, working holiday visas and seasonal workers.

Over 300,000 migrants have arrived over the last 15 years encompassing the current National and the last Labour Governments.

Understandably, New Zealanders see themselves as the descendants of migrants in one form or another who have an open and welcoming approach to new migrants. That is all good.

But migration that is too fast can put a strain on the economic system and the key variables of interest rates, the exchange rate, house prices and unemployment show the stresses involved of the latest migration surge. When there are restraints on the supply of houses, schools, motorways and hospitals, as there are in Auckland, then prices and interest rates respond.

Former Reserve Bank economist Michael Reddell pointed last week to Reserve Bank modelling showing a 1% rise in population will lead to a 10% rise in house prices. Last year Reserve Bank and Treasury separately forecast that a surge in net migration to over 45,200 and over 41,500 respectively would increase the Official Cash rate by between 50 to 100 basis points and increase nationwide house price inflation by four percentage points.


Net migration alone is increasing New Zealand’s population by more than 1% per year at the moment and that’s before natural population growth adds to the pressures.

“Rapid population growth and a low responsiveness of supply have led to housing and urban infrastructure constraints,” the OECD concluded in its report on New Zealand earlier this year.

All this creates costs for taxpayers and ratepayers alike because the infrastructure costs and rent subsidies triggered by net migration has to be paid for with higher rates and taxes. Auckland’s ratepayers may blame the Auckland Council for their near-10% rates increase this year, but they could just as easily blame New Zealand’s migration policy makers.

The other costs are borne by the rest of New Zealand’s businesses and exporters through interest rates and the exchange rate being higher than they otherwise would need to be. New Zealand has had strangely high long and short term interest rates over the last 20 years relative to the rest of the world and there’s a strong case that our high migration is at least partly to blame.

The other losers are resident workers and the unemployed because the high net migration has helped suppress wage growth and kept unemployment stubbornly high at over 146,000 or 5.8% of the workforce. This may be as good as it gets.

The latest migration tweaks announced last weekend show how responsive the Government has been to the calls from employers to make it easier to solve their labour shortages by importing workers. The rule change to allow long term migrants on temporary work visas in the South Island to apply for permanent residency is one example.

Wage growth has been much lower than everyone expected in the last two years, which is at least partially due to strong net migration soaking up the pressure that would otherwise have been applied to wages.

It also begs the question: why can’t we train or educate some of those 146,000 unemployed for these jobs? Is the Government and society collectively taking the easy option of migration to avoid the much crunchier problem of ensuring kids graduate from schools and tertiary institutions with the literacy, numeracy and life skills needed for these jobs?

Turning full circle, the migration debate is also inevitably intertwined with the debate about foreign buying of houses. New Zealand may discover after October 1 when the tax residency status of buyers will be recorded that much of the money being pumped in from overseas is going through the accounts of new migrants, students and those on short term work visas, all of which would be recorded as local buying.

Ultimately, taking pressure off house prices, interest rates and unemployment will require lots of hard work to improve the supply of houses and skills, but in the short term a debate about the number of migrants is needed.

The case against publicly owned golf courses, part 2

Last week I started taking a look at publicly-owned golf courses. I argued that they are different from public parks in several important respects. While public parks are freely available to all Aucklanders, golf courses are only open to paying golfers. As a result, we need to treat golf courses differently – not as a tax-funded public good, but as a business that must pay its way.

This week, I will take a look at some of the “opportunity costs” associated with using land for golf courses rather than alternative uses, such as public parks or housing. My central question is this: Do the benefits of using land for golf outweigh the benefits of developing the land for housing? Or is it the other way around?

Let’s start with a look at some broad trends. First, here’s what’s happened to the price of housing over the last two decades: it’s gone up significantly. This is a strong indication that demand for housing (and more intensive urban land uses) is increasing. While predicting the future is difficult, most people expect housing demand (and prices) to continue rising in the future.

Auckland house prices, rents, and CPI

Second, here’s a short-term forecast of revenues for Auckland’s 39 golf clubs from a 2013 report on future prospects for golf facilities. According to the report, golf club membership has been declining by around 1.6% a year. Unless something major changes, this trend will continue and put many golf courses under financial pressure:

Auckland golf club revenue projections chart

Effectively, rising demand for housing and falling demand for golf mean that using large amounts of publicly-owned land for golf courses will become increasingly inefficient. Here’s one way of thinking about the benefits of the status quo (to golfers) versus the benefits of redevelopment (to people who otherwise wouldn’t be able to buy or rent homes in the area).

I’m going use Chamberlain Park as a case study, but the same approach could be generalised to other publicly-owned golf courses. Here’s a picture of the course, which occupies 32 hectares in Mount Albert:

Chamberlain Park Golf Course

According to the local board, Chamberlain Park currently hosts over 50,000 rounds of golf a year. Let’s be generous and call it 55,000 rounds. According to the club’s website, green fees are $30 on weekends. This means that the total annual value of golf rounds played at Chamberlain Park is $1.65 million. In present value terms (i.e. extending this forward 40 years into the future and applying a 6% discount rate), this equates to $26.2 million.

Now, let’s consider alternative uses for the land. Let’s assume that we would develop it for housing and commercial uses, with a substantial amount of land reserved for public parks. We don’t have to look too far to find a good example of this kind of development. It’s exactly what’s happening at Wynyard Quarter, which will have a mix of medium-density residential and commercial buildings, a substantial waterfront park, and a linear park running the length of Daldy St:

Wynyard Quarter 2012 master plan

The important thing is that if development is master-planned appropriately, it can lead to more housing and better public spaces. That’s certainly happening at Wynyard, but it could also happen in Chamberlain Park if redevelopment enabled better connections between new public parks, the Northwestern cycleway, Western Springs, and Mount Albert in general.

So let’s start by assuming that we would reserve one third of Chamberlain Park – 10 hectares – for new parks and playing fields. That’s the same size as Grey Lynn Park, which attracts 100,000 people to the Grey Lynn Festival on a single Sunday – i.e. twice as many people as Chamberlain Park sees in a year.

The remainder – around 22 hectares – could be developed as new neighbourhoods, possibly along the mid-rise, mixed-use lines of Wynyard Quarter. I’m going to assume, further, that around 25% of that space would be devoted to streets, which is pretty typical of new developments. That means that after providing some sizeable public parks and laying out all the streets, we’d have around 16 hectares that could be built on.

Now, current land values in the Mount Albert area are in the range of $1500 per square metre, or possibly higher. That’s a reasonable estimate of the value that people place on the opportunity to live in the area. That means that the total benefit of redeveloping Chamberlain Park for housing is around $240 million (i.e. $1500/m2*16 ha*10,000m2/ha). These benefits would accrue primarily to the people who end up living in the area, but it could also keep housing prices from rising as rapidly and thus have wider benefits.

In short, the benefits of redeveloping Chamberlain Park – even after leaving aside a substantial area for public parks – are nine times larger than the benefits of the status quo for golfers (i.e. $240m/$26.2m = 9.2). Because demand for housing is rising at the same time that demand for golfing is falling, this figure is likely to increase, not fall.

This doesn’t necessarily mean that we have to redevelop Auckland’s publicly-owned golf courses, but it does raise some questions. First, given the fact that redevelopment is likely to be vastly more beneficial than the status quo, why isn’t it being put forward as an option in the Chamberlain Park consultation?

Second, why isn’t the opportunity cost of using lots of land for golf being recognised the prices charged by golf courses? As we’ve seen, people would place a quite high value on being able to live or work on the land occupied by some golf courses. In principle, that should be factored in to green fees, but in practice it isn’t. In the next instalment, I’ll explore this question further – it turns out that publicly-owned golf courses enjoy a large subsidy from ratepayers.

What do you think about the benefits of alternative options for using golf course land?

Briefing Papers 3: “Bubble trouble”

AUT’s Briefing Papers initiative has kindly allowed us to syndicate their recent series on housing. The third paper is by University of Auckland economist Ryan Greenaway-McGrevy:

As of May 2015, the average house price in the greater Auckland region was $828,502. In May 2012, it was only $562,454. That is nearly a 50% increase over only three years. Can anything justify this incredible growth in prices, or is it all a bubble?

Peter C.B. Phillips and I address this question in a recent article to appear in New Zealand Economic Papers: Hot Property in New Zealand: Empirical Evidence of Housing Bubbles in the Metropolitan Centres. One of our key conclusions is that there is an ongoing bubble in the Auckland real estate market.


In Hot Property, we try to restore some objectivity to the difficult task of determining whether or not there is a bubble in New Zealand’s real estate markets. But what exactly is an asset bubble, and how can we spot one? A bubble describes a situation in which an asset price is substantially inflated relative to the asset’s fundamental value, which is the present value of expected income from the asset. But while we can easily observe asset prices, it is harder to observe expected fundamentals. Many arguments over the existence of asset bubbles boil down to whether or not high asset prices can be justified by expected incomes. These arguments sometimes persist long after the prices have come crashing down. For example, see this exchange between Eugene Fama and Ivo Welch from 2002 on the famous NASDAQ bubble: Fama is one of the most frequently-cited financial economists, and is known for the efficient markets hypothesis. Arguments over the existence of bubbles lead to a large experimental literature that has established the existence of asset bubbles in the laboratory setting (see, for example, Smith, Suchanek and Williams, 1988). Outside of the lab, however, it is remains difficult to spot a bubble by focusing only on asset prices, because we never really know what market participants’ expectations are.

It may be more productive to focus on the growth rate in prices, rather than the price level, when trying to spot a bubble. Bubbles occur because sufficient numbers of market participants purchase an asset in anticipation of future price increases. This can generate a self-fulfilling prophecy, in which asset prices spiral upwards simply because market participants think that prices will increase. As more and more buyers enter the market in anticipation of future returns, prices increase, and they increase at an accelerating rate. As I will discuss below in more detail, it is harder to justify this accelerating price growth in terms of changes in expected future income from the asset. We therefore look for accelerating price growth when trying to spot an asset bubble. This general approach to bubble detection was first proposed in the 1980s (See, e.g., Diba and Grossman, 1988).

The statistical bubble detection tests we employ are designed to establish whether prices are growing and at increasing rate. Peter and his other co-authors provide the theory for these statistical methods in a series of papers (Phillips, Shi and Yu, 2015a; 2015b). A key feature of the methods is that acceleration in price growth must occur over a sustained period in order for us to identify it with any acceptable degree of statistical precision: We are not talking about accelerating price growth over a few months, but a few years. The methods provide not only an indicator of whether an asset is currently experiencing a bubble, they also provide date stamping mechanisms for identifying when the bubble begins and ends. In other empirical applications the methods have proved to be very adept at capturing the onset of bubbles in other asset markets, such as stocks and commodities. And importantly, the end of the bubbles always coincides with a fall in the nominal price of the asset in these empirical applications.

Using this method we identify an earlier, broad-based bubble in most of the regional real estate markets of New Zealand. The bubble appears first in Auckland and Wellington in mid- 2003, before spreading to the other main centres. The onset of the bubble suggest that it was part of a broader global bubble in real estate. The bubble burst with the onset of the worldwide recession in 2007, and coincided with about a 10% fall in nominal house prices.

More recently however, the tests show that Auckland once again entered bubble territory in mid 2013. As yet, the bubble in Auckland has not ended, nor has it spread to other parts of the country.

Many readers will disagree with our conclusion and argue that the accelerating price growth in Auckland is entirely justified by the fundamentals. We mitigate these concerns to an extent by normalizing house prices by an indicator of asset income – in the paper we use either rents or incomes – before running our battery of statistical tests. By doing so, we rule out the possibility that asset prices have been growing exponentially because rents and incomes have been growing exponentially. This leaves open the possibility that price growth reflects exponential growth in expected future fundamentals. But while it is easy to generate a fundamentals-based narrative that results in price growth, it is difficult to construct a narrative that can generate accelerating price growth over a prolonged period of time. This is because asset prices incorporate news relatively quickly, and certainly not over a period of several years. Consider, for example, that the Reserve Bank recently cut interest rates and signalled the beginning of monetary easing in the economy. If this cut was a surprise, and all else being equal, this should lead to an increase in house prices, but not an acceleration in house price growth over the next few years. Many of the common rationalizations for high prices in Auckland – such as lower interest rates or high migration rates – fall into this category. An unexpected increase in migration, or an unexpected decrease in mortgage rates, is good news for property owners, and should lead to a relatively quick increase in real estate prices. But in order to generate accelerating price growth over a sustained period, we would need a sequence of good news that persists over several years. No one is that lucky.

Do bubbles always collapse? Nobel Laureate Jean Tirole provided the conditions for a bubble to survive in an economy (Tirole, 1985). These conditions include durability, scarcity, and common beliefs, and housing sure does appear to be scarce right now. Up until this point in time, urban zoning restrictions have tied real estate to land in Auckland: We do not have the same high density planning as many other cities in the world, and so the number of dwellings per unit of land has been more-or-less fixed. Right now, housing is scarce because land is scarce. If this link between land and real estate persists, then we may just be sitting on a rational bubble. Happily however, the current version of the Auckland Unitary Plan allows for a potentially large increase in the number of dwellings within the city limits. If approved, the land restrictions on dwellings will be significantly relaxed, allowing supply to better respond to the price signal.

Where to from here for Auckland? Unfortunately, the empirical bubble detection literature currently offers little in terms of predicting the future. It is apparent, however, that it can be a long time between when the bubble is first diagnosed and when it finally collapses: Periods of five years or longer are not uncommon. It would be foolish for me to make any claims regarding when the best time to buy or sell a house is, or whether prices will increase or decrease next month. But can real estate price growth continue to accelerate indefinitely? I wouldn’t bet the house on it.


Diba, B. and H. Grossman (1988). “Explosive Rational Bubbles in Stock Prices?” American Economic Review 78, pp. 520-30

Greenaway-McGrevy, R., and P.C.B Phillips (2015). Hot Property in New Zealand: Empirical Evidence of Housing Bubbles in the Metropolitan Centres. New Zealand Economic Papers, forthcoming.

Phillips, P. C. B., Shi, S. and J. Yu (2015a). Testing for Multiple Bubbles: Limit Theory of Real Time Detectors, International Economic Review, forthcoming.

Phillips, P. C. B., Shi, S. and J. Yu (2015b). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500, International Economic Review, forthcoming.

Smith, V. L., Suchanek, G. L., and A.W. Williams. (1988) Bubbles, Crashes and Endogenous Expectations in Experimental Spot Asset Markets. Econometrica 56, 1119-1151.

Tirole, J. (1985). Asset Bubbles and Overlapping Generations Econometrica 53, pp. 1499-1528

Briefing papers 2: “Understanding housing affordability”

AUT’s Briefing Papers initiative has kindly allowed us to syndicate their recent series on housing. The second briefing paper is written by Motu Institute economist Arthur Grimes:

Housing affordability is a multi-faceted, complex issue. Concentration on just one aspect of the issue – be it housing supply, land supply, interest rates, construction costs or migration – will miss important aspects of why house prices vary in different locations at different times. In this briefing paper, we illustrate how differing facets of the housing market combine to produce diverse housing outcomes.

Common sense and observation of recent trends indicates that house prices reflect variables such as: population and migration, land availability (which is affected by both geographical and planning constraints), construction costs and financial factors (credit availability and interest rates). Government-funded rent and mortgage subsidies will also affect how much people can afford for housing and so will affect prices. These factors are included here in a simple framework, providing a systematic approach to understand house price outcomes. The approach is based on, and extends, published papers by the author[1] as well as other influential papers on housing markets.

Four important relationships

The framework draws on four simple relationships that are at the core of determining housing market outcomes. These four key relationships combine to give outcomes (at the city level) for: house prices, population, land prices, and the housing stock (i.e. the number of dwellings in the city). These outcomes are driven by developments in other factors such as finance costs, construction costs and natural and civic amenities.

The first key relationship is for house prices. Theoretical and empirical work shows that house prices are determined primarily by the ratio of population to the housing stock and by finance costs. As the population rises relative to the available housing stock, house prices increase since people have to bid more to purchase (or rent) a dwelling. As interest rates (and other costs of servicing a mortgage) decline, people can afford to increase their expenditure on housing, so house prices rise. Another (often overlooked) feature of financing costs may also be very relevant for house prices. The greater are government-funded subsidies such as accommodation supplement, the greater is the amount that most renters and lower-income house buyers can afford to spend on housing, so rents and house prices will increase in price.

The second key relationship is for regional population. People are attracted to regions that have high wages, attractive natural amenities and attractive civic amenities. Their choice of location is also affected by the cost of housing (both rental and owner-occupied). If population is very responsive to housing costs then extra supply of dwellings may have little effect in dampening house prices since demand (through internal and external migration) will increase to fill the extra dwellings at near existing prices.

The third key relationship to consider is the responsiveness of new housing supply to changes in prices and costs. Over time, the supply of houses increases (or stagnates) until such time as the market price of houses equates to the sum of all costs of producing a new house. These costs include the price of land associated with the dwelling (i.e. the “lot price”), construction and other costs (including regulatory costs),[2] plus a normal rate of return on capital. The sum of these costs ultimately equals the house price, with changes in the lot price being the most important factor in equating house prices to costs.

This brings us to the fourth key relationship, which is for lot prices. For a given city, the average lot price rises as the local population rises. As the population increases, the price of existing land close to the city centre (or to town centres) becomes more sought after so increases in price. While the lot price on the urban fringe may stay low – though this will be determined crucially by the strength of planning and geographic constraints – the increased price of land in existing parts of the city will increase the average lot price of the city.

The four relationships described above all relate to long term outcomes. While short term outcomes may diverge temporarily from the long term relationships (e.g. due to “fads” or to short term migration swings), an understanding of these four relationships enables us to trace through how economic shocks (e.g. a change in global interest rates) or policy shifts (e.g. a change in costs levied on developers) eventually affect house prices, land prices, population and the housing stock.


We demonstrate the inter-relationships within the housing market by adopting a systems approach that incorporates all four long term relationships just described. We can use this system to evaluate the effects of various developments on housing outcomes. We base our model on published estimates of the effects of the various factors on New Zealand housing market outcomes.[3] Informed by recent Auckland experience, we allow the lot price to form half of the total house price (e.g. a $700,000 house comprises land worth $350,000 and a building worth $350,000). We do not have strong evidence on the effects of population increase on land prices, but assume initially that a 1% rise in population results in a 1% rise in average land values; we also assume that a 1% rise in house prices results in a 0.2% decline in population as people migrate out of the city.

These parameters give us a baseline estimate of responsiveness of the housing market to specific developments. The development that we will concentrate on here is an increase in the number of people wishing to move to Auckland. The assumed increase in population is equal to 10% of Auckland’s existing population holding all other factors constant (we term this a “population shock”). In fact, all other factors will not be constant and the adjustments to these other factors (such as house prices) will affect the final number of people who end up moving to the city.

The first group of bars in the accompanying figure show the baseline estimate of the impact of a 10% flow of people to Auckland on house prices, land prices, actual population and the number of dwellings. Land prices rise (by an estimated 9.1%) in response to the influx of people and this land price rise pushes up house prices by 4.4%. The rise in house prices has two effects. It leads to greater house-building, though this is constrained somewhat by the higher land prices, so the number of dwellings increases by only 6.9%. Higher house prices also deter some people from moving to Auckland, so the population rises by around 9% rather than the full 10% of people initially wanting to move to Auckland. There are now more people per house than previously since the population rises faster than does the housing stock (i.e. crowding increases).

The second group of bars simulates the same population shock but now we assume that land prices are very responsive to the extra population[4] (e.g. because planning laws are very restrictive in allowing extra land for housing). Now we find that land prices skyrocket by almost 25% in response to the same population pressures. This leads to an 11.6% rise in house prices. These house price rises curtail the population inflow, so that population increases by only 7.6% (rather than the 9.1% in the baseline simulation). The skyrocketing land price restricts new housing development so that the stock of dwellings now increases by only 2.4% and household crowding becomes much more severe than before.

Thirdly, we assume the same responsiveness of land prices to population as in the baseline simulation, but now change the responsiveness of population to house prices. We now assume that every 1% rise in house prices reduces population by 1% (rather than by just 0.2% in the previous two simulations). This yields the third set of bars in the figure, again in response to the initial 10% population shock. The rise in land and house prices following the initial population pressures now deters people from settling in Auckland so that the population increase is just 6.6%. The reduced population inflow means that there is less pressure on house prices which now increase by just over 3%. Crowding pressures are no longer as severe as in the other cases as the housing stock increases by 5%, just short of the population increase.

What do we learn from these examples?

These simulations tell us that each aspect of the housing market interacts with each other aspect as a system. One cannot look just at housing supply, or housing demand or immigration to judge its impact on housing outcomes. All these aspects must be considered together. The same shock (e.g. a sudden rise in the number of people wishing to settle in Auckland) can have very different housing outcomes depending on the responsiveness of some factors to others.

Two facets of responsiveness that we have concentrated on here are: (i) the response of population to house prices, and (ii) the response of land prices to population. If population is very responsive to house prices, then house and land price movements will be more muted than when the responsiveness is low. This factor essentially reflects one aspect of the demand for housing.

The second factor relates to the supply of housing. If land prices are very responsive to population size, then house and land prices will react strongly to an influx of population. That the same shock can lead to either a 6% rise or a 25% rise in land prices depending on just these two factors shows the importance of considering all responses in determining what happens to housing outcomes following economic shocks.

We may have little power to affect how people’s location choice responds to house prices, but we do have some ability to affect how responsive land prices are to population pressures. Planning laws that constrain the amount of greenfields land available for new housing or that limit the ability to intensify in existing areas (i.e. the ability to use less land per dwelling) increase the responsiveness of land prices to population inflows. The increased rise in land prices then induces a larger rise in house prices for the same population shock.

Thus while many demand and supply factors interact with each other to affect house prices, we are able to moderate their final impacts through policy choices. It then becomes a political economy question as to whether or not we wish to implement policies to counteract a situation whereby house prices have become so high as to price many ordinary New Zealanders (and almost all poorer New Zealanders) out of buying a house in Auckland. Our work shows that we do not need to accept this situation.

One avenue to help address it is to increase the availability of land (both through enabling intensification and opening up greenfields land) so as to bring land prices and house prices back down to more affordable levels. Even then, however, we have to consider how all the factors appearing in our four relationships interact with each other to understand the overall effects of such a policy change on the outcomes of policy interest. If population flows are rather unresponsive to house prices, freeing up the land supply should bring down house prices and have little effect on population levels. By contrast, if population flows are very responsive to house prices, then freeing up land supply will be reflected principally in an influx of population with only a secondary effect on land and house prices. The responsiveness of population is an empirical issue, but one that may be affected by some policy settings such as migration policy and housing assistance policies. For instance, if housing assistance does not rise with an increase in housing costs, then a house price or rent rise may deter significant numbers of people from living in Auckland. Again, it is a political economy issue as to how the populace and policy-makers wish to treat these various outcomes.



[1] Arthur Grimes & Andrew Aitken (2010) “Housing Supply, Land Costs and Price Adjustment”, Real Estate Economics, 38(2), 325-353; and Arthur Grimes & Sean Hyland (2015) “Housing Markets and the Global Financial Crisis: The Complex Dynamics of a Credit Shock”, Contemporary Economic Policy, 33(2), 315-333.[2] An analysis of regulatory costs in relation to Auckland housing is reported in: Arthur Grimes & Ian Mitchell (2015) “Impacts of Planning Rules, Regulations, Uncertainty and Delay on Residential Property Development,” Motu Working Paper 15-02,

[3] For instance, based on Grimes and Hyland, op. cit., we assume that house prices rise by 2.2% if the population rises by 1% relative to the housing stock in a city.

[4] Specifically we now assume that a 1% rise in population induces a 3% rise in land prices.