Every weekend we dig into the archives. This post by Peter was originally published in March 2015.

Every year since 2005, pro-sprawl think-tank Demographia has published a new edition of its “International Housing Affordability Survey“. They report a “median multiple” measure of housing affordability that compares median house prices to median household incomes within a number of cities, mostly in the English-speaking world.

Demographia’s aim, in publishing this data, is to argue that “if housing exceeds 3.0 times annual household incomes, that there is institutional failure at the local level. The political and regulatory impediments with respect to land supply and infrastructure provision must be dealt with.” By this, they mean building car-dependent suburbs on the urban fringe – and nothing else.

Another Demographia-approved urban paradise.

A number of people, including Todd Litman and Stu Donovan (on Transportblog), have taken aim at Demographia’s empirical analysis and choice of metrics. Unfortunately, Demographia is unwilling to open up its analysis and methodology for an independent peer reviewed, so it’s difficult to referee those claims.

Here, I want to take a look at the issue from a different perspective. Basically, the urban economics literature suggests that Demographia’s chosen measures do not mean what they think they mean. And they almost certainly do not prove the case they’re trying to make.Before I explain why, let’s start out with a quick look at the data. According to Demographia’s 2015 report:

  • The most “affordable” cities included the likes of Detroit (median multiple of 2.1), Cleveland (2.6), and Houston (3.5)
  • The “unaffordable” cities included most large Australian cities, including Sydney (9.8) and Melbourne (8.7), many “coastal” North American cities, such as Los Angeles (8.0), San Francisco (9.2), Vancouver (10.6), New York (6.1), and Boston (5.4)
  • All New Zealand cities were on the “unaffordable” end of the spectrum, ranging from Palmerston North (4.1) and Dunedin (4.6) to Christchurch (6.1), Tauranga (6.8) and Auckland (8.2).

In other words, there’s a quite large range of median multiples. This raises a quite obvious question: Why are people willing to pay so much more to live in some places? Why live in “unaffordable” San Francisco when “affordable” Houston is just down the road? Why live in Auckland when housing is relatively cheaper in Dunedin?

Why would anyone want to live in a large, multicultural city located between two beautiful harbours in a subtropical climate? Sheer madness.

Urban economists have studied this phenomenon in detail, and observed that there is an omitted variable in Demographia’s equation: the differing amenities offered by different cities. If a city offers good natural amenities or consumer amenities, people will be willing to pay more to live there. Conversely, if a place isn’t particularly nice, people won’t be willing to pay much for houses there. (Common sense, really.)

In his fantastic survey of the urban economics literature, Harvard economist Ed Glaeser goes so far as to say that ratio measures, such the median multiple popularised by Demographia, are useless for analysis:

It is quite common in discussions of housing affordability to focus on the share of income being spent on housing, as if this is a natural measure of the degree to which housing affordability is a problem within an area. The spatial equilibrium assumption suggests that this measure is not particularly meaningful or helpful.

In short, urban economics suggests that we should interpret a high median multiple as an indication that a city offers great amenity for its residents, rather than an indication of bad policies. I tested this hypothesis by looking at the correlation between the (2012) Demographia median multiple figures and two international quality of living rankings. I found that there was a positive correlation between median multiples and livability.

Here’s the correlation between the median multiple (X axis) and the Economist Intelligence Unit’s 2012 Best Cities Ranking (Y axis). I was only able to match up 12 cities, but there’s a fairly strong positive trend:

Demographia median multiple vs EIU livability index

Here’s the correlation between the median multiple (X axis) and Mercer’s 2012 Quality of Living Survey (Y axis; lower numbers indicate higher rankings). Once again, a positive correlation, with 31 data points:

Demographia median multiple vs Mercer livability ranking

In other words, high house prices relative to incomes are a good indicator that a city is a nice place to live. Rather than proving that Metropolitan Urban Limits inevitably push up house prices, Demographia’s median multiple seems to simply measure cities’ relative levels of amenity. When they argue that all cities should have a median multiple of under three, they are arguing for an absurdity: that all cities should offer the exact same level of amenity to their residents.

If we wanted to accomplish that, we’d have to destroy most of the things that make great cities great. This might make housing cheaper, but it wouldn’t make us any better off in a broader sense. That’s because it would require us to:

  • Bulldoze the Waitakere Ranges and use the spoil to fill in the Hauraki Gulf – to ensure that Auckland didn’t have any natural advantages over a flat, inland city like Hamilton
  • Dynamite the historic boulevards of Paris and replace them with American-style subdivisions and malls – to ensure that Paris didn’t offer anything that Houston doesn’t
  • Ban any venture capital or startup activity in San Francisco, to ensure that it doesn’t offer any agglomeration economies that don’t exist in Detroit
  • Build large screens over sunny cities like Tauranga and Brisbane – to ensure that they don’t have nicer weather than Moscow or Toronto.

But Demographia’s not aware of this. Their analysis is overly simplistic. The only thing it reveals is the authors’ grievous failure to understand the basics of urban economics. It’s no wonder that Demographia has never tried to have its studies peer reviewed or published in academic journals. Their claims aren’t supported by any valid conceptual model. But I guess that’s what happens when you get an urban planner and a former property developer to do an economist’s job…

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  1. Great post, thanks. I suppose people understand this if they think about holidays. Of course people are willing to pay more to have a holiday in a place that’s gorgeous – beaches, parks, good recreational facilities, good natural beauty. Whereas not many people would pay to have a holiday in a heavily paved carmaggedon where there are no cultural activities or recreational activities. Choosing where to live is similar.

  2. I think multiples are a stupid measure anyway. According to multiples you would be worse off in San Fran earning 100k and paying 50k mortgage than in detroit earning 50k and paying 20k mortgage. Yet in San Fran you have 50k to spend but in Detroit only 30k.

  3. These median multiples are meaningless for comparisons.

    They are like comparing and contrasting BCR’s between completely independent sorts of projects (say comparing BCRs for: a roading project, a hospital construction project and a types of aircraft Air NZ should buy next).

    Each number is meaningful, but only within a very narrow context. Taking them and comparing them outside of those contexts is useless at best, extremely dangerous at worst.

    Who defines what a “home” is anyway and thus the dollar figure to which the median income is compared to via the multiple? In most place a “home” is defined as something quite different from here in NZ.

    In San Francisco a “home” may commonly be taken to mean a 1 bedroom apartment in the city area, in Detroit a 2 or 3 bedroom apartment in the “projects”, in Houston a stand alone McMansion house way out in the ‘burbs.

    Each is hardly comparable to others within its own market, let alone between those 3 markets as Demographia do here.

    This is nothing but statistical snake oil of the first order.

  4. That’s fine, but land prices are actually a legitimate problem; and amenity has little to do with it. A city can be expensive but it can be the only place people can find work. That doesn’t mean it’s a ‘nice’ place to live. If other areas had the same job opportunities then it’s unlikely there’d be so much internal migration towards Auckland, but that doesn’t make the lifestyle in Auckland any more enjoyable as a result.

    1. Isn’t the ability to find work part of the amenity? If that work didn’t exist in Auckland, house prices would be lower. Which is the essence of this article – house prices aren’t just based on housing supply.

      1. Ask people struggling to meet rent or save a house deposit how great Auckland is. It’s one thing to rip into people for not acknowledging basic economics, but another to ignore that the approach they advocate loads costs onto people, whether they can afford it or not.

  5. This is a very poor article from someone who prides themselves on being an economist. The pay the man not the ball comments at the end indicate the preconceived bias of the author and undermine the argument that they are trying to make. In term of the critique of the demographics approach it many or many not be correct. The correlation between a limited set of data points from 2 surveys and the housing affordability metric does not prove causation. Price is a function of not only demand but also supply. In the case of a city the amenity of the city could be argued to be very high because of the very strong and continued migration to that city (quite possibly a better measure of the desirability than the surveys who are biased towards the views of certain cosmopolitan demographics). Houston is a good example. demand is clearly very high however it is offset by liberal urban planning guidelines and efficient constuction. Looking back of the key drivers of the increase in median house price to income the cause is at least as likely to be restrictive planning and a greater availability of relatively low cost finance as compared to increased desirability. It is not possible to make a clear conclusion without a far more sophisticated analysis, which is definitely not econ 101. The author should think again before jumping to a conclusion that support the type of city that they would like as opposed to the complicated realities of the multinational housing market

    1. “surveys who are biased towards the views of certain cosmopolitan demographics”

      I’ve also been sceptical of quality of life surveys. To me, teen emotional health is probably the best measure. Feelings of optimism, self-determination, opportunity, belonging and freedom of teenagers seems to reflect lifestyles, respect for others, tolerance, connection with nature, and opportunities of the population at large. Hard to measure, I suppose, except in the negative (teen suicide rate, and even that probably measures gun availability to a large extent).

      I wouldn’t have thought continued immigration to be a particularly good measure, as that will be influenced by immigration policies and relative job availability to a large degree, and has very little relevance to the majority of people who stay put.

      I quickly checked Demographia’s Best Three US Cities (ie with the lowest median multiples, all below the magical 3) against their suicide rates [not teen suicide – I couldn’t find that by state]. They were in the 15th, 31st and 34th worst states by suicide. Similarly Demographia’s Worst Three US Cities (with highest median multiples) were in their 45th and 49th worst states by suicide (ie amongst the best). I chose US states because I imagined the methods of measurement would be closer, state to state, than between countries.

      Utterly rough analysis, I realise, ignoring demographics and city / rural balance, and much more besides. But it’s enough to convince me that Demographia’s measure of a quality city is upside down. I’ll stick with the quality of life surveys that Peter has used until someone presents something more convincing.

      That the Demographia work then recommends throwing urban containment policies away speaks volumes: What kind of bias blinds one to how fundamentally wrong it is to cover more farmland with urban sprawl, ruining our soil, water and ecological base, and committing the many people who don’t drive to dependency on others, and those who do drive, to dependency on their cars? What kind of bias would blind them to the very real lower GHG gas emissions from dense, contained cities?

    2. I think demand is high in Houston because it’s cheap, not because it’s great. If the price were to go up, the demand would come down. But I get the feeling that in the popular cities, demand actually increases as prices increase.

  6. Demand is likely to be high in Houston because of the nature of the lifestyle (big and affordable housing, sunny climate) and job opportunities relative to the cost. This includes taking into account the potential down sides of this urban model like long commute times. The relevant question here is what is likely to be the best demand and supply side variables that predict the ultimate price of housing. The desirability of a city undoubtably has an impact however as stated previously I would be very skepitical using liveability surveys that are based of the preferences of a small elite. The definition of what is desirable is likely to vary significantly across different groups of people, across geographies and time periods. People vote with their feet, this is arguably a better predictor of the true preferences of different cohorts than a dubious survey or two.

    1. Shall we try to reclaim the word ‘elite’ from the ideologues, Mintaro, or shall we be blind to its misuse?

      Car dependent cities create elites: those who drive and who are wrecking the climate through their squandering of the planet’s capital as if it is income. They don’t feel like elites because the car dependency isn’t pleasant. But it’s a whole lot nicer than being someone who doesn’t drive in these sorts of cities.

      Compact cities that give access to the whole population – whether too young, poor, elderly or disabled to drive or be driven – are proposed by people who care about earth care, people care and fair share.

      Calling these thinkers ‘elites’ is playing the man, not the ball.

      1. Your comment is a good example of why I responded to this article in the first place. You start with a desired outcome based on you own beliefs and biases and then retro fit data and argument to justify it. The article’s author clearly prefers the compact city model, didn’t like the conclusions of some of the Demographia work and the used some poorly thought through analysis to justify a position that confirms what he believed in the first place. This didn’t meet basic standards of the Economics profession and would get a poor grade in a beginners Econometric class.

        I suggest that you google logical fallacies to see where your argument and the authors are weak (confirmation bias, shifting the goal posts, cherry picking, attacking the person not the argument). I would also look up the dictionary on the definition of elite as well

        Note at no stage did I say what urban model I prefer. Otheriwse I have no doubt that the Demographia work has its own biases (possibly designed to purposely to generate publicity to drive subscription or consulting revenue). The Article linked to below by Brendan is a far more nuanced and sophisticated analysis…

  7. “Why live in Auckland when housing is relatively cheaper in Dunedin?”

    Demographia’s analysis is broadly right. Tight land use restrictions drive up land prices (& thus house prices as well) [there are other things like tax treatment & low interest rates as well]

    However the key issue is that current housing prices only affect those that are considering moving to a city or moving houses (or those renting).

    1) If you already live in Auckland and already own a house then your existing house is also overvalued & you only have to pay the marginal difference if moving houses.

    2) Everyone doesn’t suddenly move to Dunedin from Auckland because of 1) & because you have to get a job in Dunedin & there are only enough jobs there to cater for the 100,000 odd population. (So even those renting in Auckland (in totality, given some individuals may be able to move) are stuck there.)

    Driving up land prices for no reason other than tight land use restrictions does nothing more than add an unnecessary unproductive cost to the NZ economy.

    We’d be far more productive with effects based planning (rather than zone based), no/limited density controls, a capital gains tax, congestion tolling and a sustainable immigration rate.

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