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.
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?
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:
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:
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…