Auckland's housing market

A while back I wrote about whether Auckland has a big and growing housing shortage. I looked at building consent numbers and estimates of population growth. I thought there was a plausible explanation for the slow supply of housing that did not rely on the normal calls that poor planning had created the lack of supply. Two factors in this were questions over the make-up of population growth and the responsiveness of the house building industry to sudden surges in population growth.

On the number of building consents issued (supply of dwellings), I thought it was important to take into account a lag between population growth occurring and when a house is actually built. I thought it may take up a year for population growth to result in a house being built, for example. On the demand side, I questioned some of the migration data that feeds into the population growth estimates and in particular how many people staying for more than a year actually create demand for a house.

Since then a couple of sets of numbers have come through that shed some light on the points I was trying to make.

First up is the lag issue - the length of time taken between population growth occurring and houses being built. It is often noted that housing markets cannot react quickly to population shocks. It takes time to find sites, draw up plans and get a builder on board; more so as cities intensify and there is a shift from stand alone houses to terraces and apartments.

The Interest.co.nz website (see note 1) ran an interesting set of numbers recently, comparing building permits for new dwellings and code of compliance certificates (CCCs) issued by the Auckland Council.

CCCs are issued when a building is completed. Comparing the numbers of building permits issued with the number of code of compliance issued suggests that  there is a significant time delay between a new building consent being issued and the building receiving a CCC when it is completed.

The data suggests that the lag is about 2 years, based on the numbers in the table below, which are for the Auckland Region.

Code compliance certificates issued		Building permits for residential units
Apr-14	4,106	4,077	Apr-12
Apr-15	5,269	4,835	Apr-13
Apr-16	6,131	6,796	Apr-14
Apr-17	7,412	8,155	Apr-15
Apr-18	9,030	9,353	Apr-16
Apr-19	10195	10,226	Apr-17
		11,629	Apr-18
		13,754	Apr-19

The data suggests that in 2021, up to 14,000 dwellings may be built in the region. 

Note, the 2 year lag is between the building permit being issued and the building being finished. For the building permit to be issued, a site needs to have been found, if needed resource consents obtained and building plans prepared, checked and consented. This adds further time. So the number of building consents issued in any year is likely to reflect the planning and design work undertaken during the previous year or two. But by the time the building consent is issued, these planning related issues have been addressed. The two year lag between building consent being issued and completion must be because of factors like labour shortages and possibly the growing number of multi-unit developments which take longer to build (where all units are completed at the same time). 

During the period between population growth occurring and a new dwelling being finished - perhaps 3 years at least - then there can be extra demands on the housing stock. These are short term pressures. What is important is the housing market response over the medium term. Many commentators seem to latch onto the short term pressure and use this as support for the view that planning restrictions are creating a structural housing shortfall. But what the data, and most texts on housing markets note, is that there is always a delay between demand and supply. That delay is not necessarily the result of planning. 

Next bit of information relates to whether the (delayed) supply response is sufficient to meet demands.  The question has always been, what is a reasonable estimate of demand?

Here the other interesting bit of information is the revision to the net migration numbers by Stats NZ. Stats NZ have been busy revising how they count inwards and outwards migration. As a result of these revisions the number of long term migrants (people staying for more than 12 months over a 16 month period) is lower than previously estimated. Inward migration has been the biggest source of population growth over the past 5 years or so, so a revision is important. 

The table below lists the old and new net international migration estimates, for NZ as a whole.  

	Old	New	Difference
2014	38,300	32,718	-5,582
2015	58,300	53,079	-5,221
2016	69,100	63,145	-5,955
2017	72,300	59,159	-13,141
2018	65,000	49,903	-15,097

The difference is large in the 2017 and 2018 periods. 

Apart from the obvious point that revisions of this scale drive home the point that it is very hard for the building sector to estimate demand if the numbers keep on moving; the other question is over the make up of these numbers. The numbers are for all types of migrants. A migrant is an overseas resident who arrives in New Zealand and cumulatively spends 12 out of the next 16 months in New Zealand. Migrants may be NZ'ers returning, people who come to work, visit for a long period of time or for study, or to shift permanently. For example, an international student who spends the term-time in New Zealand and holiday time overseas, over successive years, will be counted as a migrant arrival at the time of their initial border crossing if they satisfy the 12/16 month criterion.

Net international migration took off in 2014 and peaked last year. Below is the ‘old’ measure of net migration, and while the numbers have been revised downward, the pattern remains. 

Migration was slowing down or negative in the period 2009 to 2012.  Based on the above data on building consents and completions, the number of house completions in 2015 most likely reflected the conditions prevailing in 2012 (ie a much more bleak picture). 

As for the causes of the lift after 2014, in June 2016 the NZ Herald ran a story that international student numbers from new migrant source countries, like India and the Philippines, are contributing to net migration numbers hitting record highs, according to analysis into arrival and departure card data.

To further complicate things, the revised net migration numbers are national figures, not for the Auckland Region. To work out what they may mean for the Auckland Region, we need to make a few adjustments. 

But before we do that, we need to understand that at the regional level migration is the difference between the number of people who have moved to, and departed from, a given area. Sub national net migration includes both international migration and internal migration gains and losses. 

There is no reliable evidence as to the number of NZ residents leaving Auckland for other regions (ie internal migrants) for the period from 2014. Between 2001 and 2006, Auckland ‘lost’ about 18,000 people to other regions. For the period 2006 to 2013, the census records a net loss of 4,650 people. So this number bounces around a lot. From 2014 to 2019, internal migration out of Auckland could have been very high. Until the census data comes out, we dont really know.  

Then there is the number of international migrants who stay in Auckland. 

Stats NZ, for their yearly population estimates, make a stab at working out how many international migrants head to Auckland, versus how many head to other regions.  Their estimate covers both internal and international migrants for the regions, but at the national level, the migration total must only be for international migrants (for internal migration, a loss from one region is made up by a gain in another region).

The following figures are Stats NZ estimates of migration gain for Auckland and NZ, and Auckland’s share.

	Auckland	NZ	Ak Share
2014	19,600	38,300	51%
2015	29,100	58,300	50%
2016	30,800	69,100	45%
2017	28,900	72,300	40%
2018	25,700	65,000	40%

The Auckland share of total migration gain for the country has dropped. This may be because of more local residents leaving Auckland, or fewer international migrants heading to Auckland. We don’t know.   

If we take the above Auckland region shares and apply them to the revised national migration figures, then we get the following:

New NZ	Ak Share	New AK
32718	51%	16,743
53079	50%	26,494
63145	45%	28,146
59159	40%	23,647
49903	40%	19,731

The revised migration gain can then be added to the estimate of natural increase to get total population growth for the Auckland region. 

	Old	New	Difference
2014	33,800	30,943	-2,857
2015	43,000	40,394	-2,606
2016	44,600	41,946	-2,654
2017	42,700	37,447	-5,253
2018	38,700	32,731	-5,969

Does 6,000 fewer people make that much of a difference? At 3 people per house, this is 2,000 fewer houses. Whether the dwelling demand is 3 people per house is debatable. Many migrants are younger people - the median age of Auckland is dropping. At  2013, the average number of people per occupied dwelling in the Auckland Region was 3, but a younger age profile suggests a higher number of people per dwelling. 

If we stick with 3 people per dwelling, then the revised population estimates result in the following dwelling demand.

	Pop change	Dwelling demand
2014	30,943	10,314
2015	40,394	13,465
2016	41,946	13,982
2017	37,447	12,482
2018	32,731	10,910

We can then compare the dwelling demand with dwelling supply, but with a 2 year lag built in between building consents being issued and houses being built. The table below has the dwelling  'supply' lagged by 2 years. For example dwelling demand from population growth in 2014 is matched to building consents issued in 2012. 

Demand Year	Dwelling demand	Dwelling supply	Based on consents issued in Year
2014	10,314	4,197	2012
2015	13,465	5,343	2013
2016	13,982	6,873	2014
2017	12,482	8,300	2015
2018	10,910	9,651	2016

So there is a demand and supply imbalance, but that imbalance is because of the lag between demand becoming apparent and supply cranking up.  

If we ask “did the rising demand result in a signal that building consents needed to be ramped up”, then we can say yes, but it is not a fast process. If we add a year into the supply chain between population growth and a house being completed, so the whole process takes three years, then we can see the housing market responding in the graph below.  

Taking 2010 as a starting point, the figure below shows three things: 

1. Demand as estimated by population growth (adjusted down based on the revised migration data)

2. Building consents for new dwellings, based on a years gap between demand and the consent being issued. So the 2011 consents are probably based on population demand in the previous year, being,  2010.

3. Completions are delayed by 2 years from the year the building consent was issued, so completions are based on estimated demand three years previous.  

What is apparent is the large step up in population growth between 2013 and 2014. Consents started to rise in response, but completions were low because they were based on what was consented two years previous. By 2018, with population growth dropping back a bit, completions have almost caught up. 

There will still be a shortage of houses built up over the period 2010 to 2018, and the above suggests that the shortfall will take a while to work its way out of the system, unless population growth takes off again, or falls back quickly. 

This analysis reinforces the need for there to be sufficient zone capacity to meet housing demand, but provides some caution as to the presumed role of a lack of capacity due to zoning, and the slow pace of adding more capacity, in fueling land  and house price rises. In particular, the AUP (OP) was made operative in late 2016. By 2016, the housing market was responding to the increase in population growth from a few years back, based on the capacity available in 2013. The AUP (OP) has helpfully added capacity (as any plan review should and would have), but this is capacity for future growth. If a lack of zoned capacity was not the cause of house price growth (or only a small cause), then what is the main driver?

Notes: https://www.interest.co.nz/property/100382/number-new-homes-being-completed-auckland-could-increase-about-third-over-next-two

Urban design effects and the RMA 3

More on urban design effects and the RMA. I'm trying to work may way through some sort of urban design 'effects' rating system.

So far I have tried to understand what a rating system needs to do;  how rating effects contributes to procedural and substantive decisions under the RMA. Now the meaty part – what are urban design effects in terms of the RMA? Lots to work through here.

Looking at how RMA plans 'codify' urban design may not be the best place to start at trying to understand urban design effects. RMA plans tend to pick up on a sub-set of urban design. But equally many urban design texts and guides can be so wide ranging as to their definition of urban design that trying to work out what an effect is, is not easy.

So I need to take a different tack.

Somethings to address are:

• Is urban design normative or positive?
• If positive, then in what way does urban design affect the environment? 
• Are urban design effects a positive or negative externality?
• Urban planning versus urban design?
• Whither the 7cs of the NZ Urban Design protocol?

Normative or positive?

Why start here? Perhaps the most basic assumption to be made is that urban design effects can be reliably, objectively measured in someway. Is urban design  just a bunch of ideas as to how the built environment should be, with those ideas varying from urban designer to urban designer? Positive statements must be able to be tested and proved or disproved. Normative  statements are opinion based, so they cannot be proved or disproved. Normative statements do not really help with constructing a robust rating system.

Having the word 'design' in urban design lends urban design towards the normative end of the spectrum. Design suggests a creative endeavour, perhaps something aimed at making a 'bit of a splash'.  The other interpretation of 'design' is the sense of something of standard form or function that is shaped or moulded to fit specific circumstances.

I think urban design is increasingly grounded in research and observation. It may have started out as a bunch of thoughts and guesses about the interaction of people with built environments, but things have moved on. There is the 2005 MfE report on the value of urban design. This is still a good report. People like the old UK CABE (Commission for Architecture and the Built Environment) referred to the benefits of urban design as providing ‘value’ in terms of things like:

• Exchange value: parts of the built environment can be traded;
• Use value: the built environment impacts on the activities that go on there;
• Image value: the identity and meaning of built environment projects, good or bad;
• Social value: the built environment supports or undermines social relations;
• Environmental value: the built environment supports or undermines environmental resources;
• Cultural value: the built environment has cultural significance.

More recently M Carmona in a paper called: “Place value: place quality and its impact on health, social, economic and environmental outcomes” (note 1) suggests that a different way of thinking about urban design benefits  is more straightforwardly the degree to which the different qualities of the built environment impact, either positively or negatively, on different public policy goals. Things like public health, public safety and promoting social interaction are all basic public  ‘goods’ or services that economies and communities need for them to operate successfully. Urban design and the built environment can and does influence the nature and extent of relationships between people and these public goods. The built environment might get in the way of a positive relationship, it can also accentuate a negative relationship. The built environment can also enhance these relationships.

After reviewing over 200 studies on the links between the built environment and public policy goals Carmona concludes that there are strong links between built environments and health and safety, as well as supporting economic exchange and improving the environment.

Now that is all well and good, but it might be said that urban design is not a proven set of facts or theories about how the built environment affects safety, for example. There is no theory in the sense that we can say with certainty: do x and y will result. It is not possible to be so assured as to the link between cause and effect. The above studies show a correlation between good and bad urban design and many positive and negative outcomes. But is there a causal link?

After all human beings are involved. Someone penned the following thought:

As I walk I react to the scale of a building in relation to the scales of others and to that of my own body. In all their proportionate interrelationships, heightening my awareness of self in space. To make my way toward my destination I draw geographic inferences and impose cognitive maps that orientate myself in, and make sense of, the structures through which I move, Drawn and reassured by the vitality on the street, I come out to join that urban commerce and thereby contribute to my own presence to the city’s life. The landscape features I pass become meaningful to me through their capacity to express cultural references, whether local or foreign. Any my determination to continue walking depends on how well the landscape responds to my flagging strength, my desire for shelter, my need for rest, and my wavering curiosity. 

Carmona contends that it has been found that urban design is at least in part pseudo-scientific. This does not mean that urban design rests on a ‘foundation of nonsense’, but a foundation of untested hypotheses, or individual scientific findings that are not scientifically incorporated into the urban design corpus of knowledge.

That urban design can be classed as ‘pseudo scientific’ is not fatal. Jayne Jacobs ends Death and Life of Great American Cities with a chapter on how cities are systems of organised complexity. As such they cannot be analysed by standard scientific techniques (two variable problems). There are many variables in cities which interact and interrelate, many of which are not subject to proven theories of cause and effect.  It is more a matter of likelihoods and probabilities.

She explains some tactics to analyse organised complexity:

• Detail – identify a specific factor and then painstakingly learn its intricate relationships and interconnections. Then move onto another factor
• Look for leverage – seek ‘unaverage’ clues involving very small quantities which reveal the way larger and more common quantities operate
• Processes – cities are always evolving – there is no equilibrium, so any activity or building or space must be placed in some sort of continuum or timeline. Focus on the catalysts that arrest one phase and start another
• Work inductively – reason from the specific to the general.  This helps to avoid seeing cities in the abstract. 

Urban design does concentrate on details, like where the front door is. It does refer to both the exceptional and the normal. Urban design looks at the urban environment not in the abstract, but in specifics.

But is the lack of a scientific base to the understanding of urban design effects an issue? In a world of evidence driven policy, then maybe and maybe not.

Maybe not because much of resource management is about dealing with predictions and uncertainties as to future effects in the absence of complete knowledge. As we all know there is a huge area of opinion and judgement involved in many areas of urban planning and resource management.  Here, probabilities of claimed effects are important. How certain are the links between cause and effect of many urban amenity concerns?

This has been called post-normal science. This is where people involved in unresolved issues hold strong positions based on their values, and the science is complex, incomplete and uncertain. Diverse meanings and understandings of risks and trade-offs dominate.

In a similar vein, given uncertainties, an Environment Court judge has suggested that the probabilities of effects be considered in terms of:
• Confidence in facts
• Likelihood of predictions.

But maybe the lack of a strong theory that has stood up to scrutiny (not be falsified) is an issue, mostly because of the human behaviour aspect of urban design.  The social aspect of  built environment effects may mean that adverse urban design effects need to get to a ‘significant level’ (whatever that is) before management and mitigation of them can kick in. Should the bar for action be a bit higher than for effects on the natural environment, for example?

Note 1: http://placealliance.org.uk/wp-content/uploads/2019/01/2018-June-12-Journal-of-Urban-Design-Place-value-place-quality-and-its-impact_MC.pdf

Effects, urban design and the RMA: 2

I'm on a (one person) quest to better define urban design effects as part of RMA processes. I have started by looking at how effects might be defined, before looking at urban design effects. I ended my first post on the topic with the following effects 'equation':

The scale of an effect is a combination of:

Persistence of effect * magnitude of effect * extent of the effect * probability of the effect * consequence to receiving environment * possible mitigation (reduction) * plan weighting.

I am not sold on the above equation, but it is a start.

If you think the above is a bit complex, then look at the following. This is from Department of Conservation’s guidance on policy 13 of the New Zealand Coastal Policy Statement (which in turn is drawn from a regional policy statement).

The following guidance aims to help with determining the extent to which an adverse effect is ‘significant’.

Status of resources: The importance of the area—locally and regionally. (Effects on rare or limited resources are usually considered more significant than impacts on common or abundant resources).

Proportion of resource affected/area of influence: The size of the area affected by the activity will often influence the degree of impact (i.e. affecting a large area will generally be significant). Affecting a large proportion of a limited area or resource will tend to be significant.

Persistence of effect: The duration and frequency of effect (for example, longterm or recurring effects as permanent or long-term changes are usually more significant than temporary ones. The ability of the resource to recover after the activities are complete is related to this effect).

Sensitivity of resources: The effect on the area and its sensitivity to change. (Impacts to sensitive resources are usually more significant than impacts to those that are relatively resilient to impacts). Reversibility or irreversibility: Whether the effect is reversible or irreversible.

Irreversibility will generally be more significant (depending also on nature and scale), and reversibility the converse.

Probability of effect: The likelihood of an adverse effect resulting from the activity. Unforeseen effects can be more significant than anticipated effects. (Adopting a precautionary approach may reduce the likelihood of adverse effects occurring).

Cumulative effects: The accumulation of impacts over time and space resulting from the combination of effects from one activity/development or the combination of effects from a number of activities. Cumulative effects can be greater in significance than any individual effect from an activity (for example, loss of multiple important sites).

Degree of change: The character and degree of modification, damage, loss or destruction that will result from the activity. Activities that result in a high degree of change are generally more significant.

Magnitude of effect: The scale and extent of possible effects caused by an activity (for example on the number of sites affected, on spatial distribution etc). Activities that have a large magnitude of effect are generally more significant.


I think this list can be re arranged to match my equation, as follows:

DM rating	DoC
Persistence	Persistence of effect:
Magnitude	Magnitude
Extent	Proportion of resource affected/area of influence
Probability	Probability of effect
Consequence	Degree of change Irreversibility Sensitivity of resource
Possible mitigation
Plan weighting	Status of resources:

The DoC list doesn’t have mitigation in it. It does have cumulative effects in it. More on that below.

As another example, Environmental Impact Assessment (which is where the idea of Assessment of Environmental Effects comes from) can have a fairly complex list of things to look at when considering impacts. For example:

Characteristics of Impact:
• the extent of the impact (geographical area and size of the affected population);
• transfrontier impact;
• magnitude and complexity of impact;
• probability of impact;
• duration, frequency and reversibility of the impact.

Transfrontier impacts refers to whether the impact crosses country borders or other boundaries.

Again some similarities come through in terms of the dimensions of an effect.

Once the components of effects has been considered, how do you express the product of the equation? I wonder if the scale for urban design effects should be related to people’s reactions to or acceptance of change to an urban environment, given that cities are all about people, but also constant flux and change. For example, effects are:

1. Not discernible
2. Negligible
3. Tolerable
4. Undesirable
5. Detrimental
6. Intolerable.

These might be described as follows:

Overall rating	Description
Not discernible	Within the normal range of effects / rate of change as currently experienced, generally not perceptible
Negligible	Effect may be noticed against 'background levels', but would be so small or unimportant as to be not be worth addressing. It would not change day to day activities in any material way
Tolerable	Effect would be noticed and may change behaviour / routines, but within the ability of people to adapt. The effect may be bearable
Undesirable	Effect would be noticeable and negatively  impact on people’s day to day routines. It would be objectionable or unpleasant. The effect might be able to be mitigated or potentially traded off for other much bigger benefits
Detrimental	Effect would be visible and be felt. It would be harmful or damaging. People would need to be take deliberate action to avoid the effect which would reduce the overall utility of the environment to support urban activities
Unbearable	Level of effect is excessive and would negatively impact on a wide range of people and lead onto other spill over effects that cannot be managed. The effect would be calamitous and destructive to an urban environment.

The above categories of effects can be related back to the threshold / procedural tests of the RMA as follows:

Rating	Degree of ‘minorism’	Degree of significance
Not discernible	Less than minor
Negligible	Minor
Tolerable	More than minor
Undesirable		Significant, but maybe 'tradeable'??
Detrimental		Significant, best avoided
Unbearable		Significant, avoid

Having said all that, I am not convinced that the above deals with the issue of small, incremental changes to urban areas. Many urban design matters involve small scale changes to the built environment, and most often are not changes to a highly valued environment. One tall fence on the front boundary of a 'normal' residential site might not seem so bad, a whole street of high fences is a problem, but getting from one to many high front fences usually involves numerous small steps. Is the first tall fence an 'unbearable' effect?

As a different example, the area or number of people affected may be relatively small, with only a minor portion of an urban area subject to the effect. A formula which talks about nature and extent of change might imply that changes that affect 100s of hectares are much more important than changes that affect one or two sites. As a result the small changes should get a low 'relative' impact rating.  But of course only one in twenty cases may affect 100  hectares, but 19 cases may affect 5 sites each.

This is the cumulative effects issue; an issue which goes round and round without resolution.

One guide says that cumulative effects become significant when these impacts on the environment:
• “occur so frequently in time or so densely in space that they cannot be assimilated or
• combine with effects of other activities in a synergistic manner” .

In other words, cumulative effects may be additive (accumulate) or synergistic (amplify other effects). Someone has also pointed out that cumulative effects could also be neutralizing (the effects cancel each other out). The issue with accumulative effects is their frequency.

It is the accumulative form of cumulative effects which are perhaps most relevant to urban design. It is common for assessment guides to note that there are thresholds where additional (small scale) disturbance can result in significant deterioration of resources or ecosystems. Cumulative effects become apparent when such thresholds (tipping points) are breached.

But if the effect is at the start of the sequence of potential repetitions, and no threshold has been reached, then a cumulative effect has not yet technically occurred. Even if there is a clear sequence occurring, identifying the tipping point is not easy, and is often only apparent in retrospect.

Cumulative effects can be related to the concept of the "tyranny of small decisions".  Overtime, big changes can occur as a result  of many steps, each small in their individual size, time perspective, and in relation to their cumulative effect. In economic terms, the tyranny of small decisions means that a series of apparently free, individually welfare-maximizing 'purchase' decisions can so change consumer tastes and the context of subsequent choices that desirable alternatives are cumulatively and irreversibly destroyed.

There is no straight forward antidote to the tyranny of small decisions, except to say that someone needs to keep the bigger picture in mind.  But just saying that cumulative effects should be taken into account in the effects equation doesn't really help much.

Plan weighting maybe one way to address small scale, insignificant in isolation but potentially damaging additive cumulative effects. Another way to address cumulative effects may be to introduce another step into the effects equation, covering the likely prevalence or recurrence of the effect - does the effect come up often, or is a rare or unusual effect? So should the equation be:

Persistence of effect * magnitude of effect * extent of the effect * probability of the effect * likely recurrence of the effect * consequence to receiving environment * possible mitigation (reduction) * plan weighting.