A few weeks ago, I took a look at property taxation in the US, Canada, and New Zealand. I found that Auckland homes are taxed lightly by comparison – rates average 0.39% of house value. Property tax rates are twice as high in most of the other cities I looked at. In some cases – e.g. Houston, where property taxes average 2.31% of home value – they are much, much higher.
This should come as no surprise to anyone who’s read the literature. For example, Grimes and Coleman (2009) find that New Zealand under-taxes property:
McLeod et al (2001; p.26) showed that the proportion of taxation raised through property taxes was lower in New Zealand than in Australia or the United States. Taking into account all levels of government (federal, state and local), Grimes (2003) found New Zealand’s share of property taxes in government revenue was relatively low, at 5.7%, compared with a (20 country) OECD average of 8.3%. As a share of GDP, New Zealand’s property tax share was also relatively low at 1.8% compared with the average rate of 2.4%.
They go on to suggest that introducing even a relatively small land tax could result in fairly large changes to land prices. It’s intuitively sensible that higher property taxes would discourage people from bidding up prices – the more they pay for land, the more they pay in taxes!
Stu recently took a look at the same research, and some of the broader trends, and concluded that higher property taxes could take some heat off the housing market. But how much does property tax really matter for housing affordability?
To get a rough sense of the relationship, I’ve put together a chart showing the relationship between property tax rates (x axis) and Demographia’s “median multiple” measure of house prices relative to incomes (y axis). It includes data on all 59 US, Canadian, and New Zealand cities with a population over 1 million.
Notice the substantial negative correlation between property taxes and median multiples. There is a strong tendency for places with lower property taxes to have higher house prices, and vice versa. The least “affordable” places all have relatively low property taxes.
Overall, this chart suggests two things: First, New Zealand’s relatively low property taxes may contribute to our relatively high house prices. Notice how Auckland’s house prices seem to fit the overall trend in the data.
Second, as I’ve previously argued, Demographia’s analysis is largely meaningless as they have failed to account for the full range of explanatory variables, from interest rates to tax policies to economic fortunes.
Here’s another view on the same data. I’ve taken the natural logarithm of both variables to smooth out the relationship, and put a trend-line through the data points. This simple bit of analysis suggests that:
- About 44% of the variations in median multiple can be “explained” by differences in property tax rates. For a bivariate regression, this is quite high.
- The slope of the regression line suggests that, within this sample of cities, a 10% increase in the property tax rate is associated with a 4.6% reduction in the median multiple. Again, that’s a quite strong relationship.
I don’t think we can draw any firm policy conclusions from this data, but it certainly suggests that our low property taxes are worth investigating as a cause of our high house prices. In the words of xkcd, “Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there’.”
Finally, it’s worth taking a closer look at the four US cities with the highest median multiples – the top data points on the left hand side of the first chart. They are all large cities in California – San Francisco, Los Angeles, San Jose (i.e. Silicon Valley), and Sacramento (the state capitol). They provide a great illustration of why failing to account for multiple, correlated explanatory variables can undermine an analysis of house prices.
But first, a California-themed music break:
In California, state-level legislation establishes a common planning framework. There are local variations, but if one city is constrained by regulations – as San Francisco and Silicon Valley are – the rest are likely to have similar problems. To give an example, the California Environmental Quality Act, which is the state’s equivalent of the Resource Management Act, has traditionally required all new developments to assess their impact on traffic congestion and mitigate it. As a 2011 Citylab article explains, this requirement has prevented the development of space-efficient forms of housing and transport:
There’s also a great irony underlying the use of LOS [traffic Level of Service] as part of CEQA’s environmental impact checklist. It seems self-evident that bike projects are favorable to the environment, but the use of LOS to evaluate them can sometimes imply quite the opposite. The person who filed the 2005 lawsuit against the San Francisco master bike plan, for instance, suggested that because bike lanes raise LOS they also raise congestion and car idling, and thereby cause pollution.
That’s not the only contradictory aspect of LOS. Case in point: a developer whose building fails an LOS threshold can mitigate the environmental impact by widening the street, which of course would attract more cars and pollution. So instead of encouraging dense development and lower vehicle mileage — the hallmarks of a transit-first city — San Francisco’s use of LOS as part of CEQA actually discourages livable design. In a three-part series on LOS at Streetsblog, one transportation consultant called LOS the “single greatest promoter of sprawl and the single greatest obstacle to transit oriented development” in California.
However, CEQA and its absurd requirements for traffic assessments (etc) aren’t the only thing going on in California. State-level laws have also constrained local governments’ ability to raise property taxes. Proposition 13, a citizen-initiated referendum passed in 1978, caps property tax rates at 1% and fixes them to the value of the house at the time it was purchased, plus a 2% annual increment for inflation.
This has had a number of perverse effects, including stripping away funding from California’s formerly excellent primary and secondary education and setting it on a path of decline. (Prop 13 is basically exhibit A in the case against binding referenda.) It has also distorted the housing market. Because home-owners know their property taxes won’t increase if the value of their house increases, they may be more willing to speculate on capital gains.
A 1982 paper by economist Kenneth Rosen offers empirical support for this hypothesis – he found that reductions in property tax rates were almost immediately followed by proportional increases in house prices.
Consequently, it would be foolish to analyse the Californian housing market without attempting to control for both taxation and planning policy. If you only looked at one policy, your conclusions would be biased by mis-attributing the effects of the other policy. (That’s precisely what Demographia seems to have done, by the way.)
What’s true for California is also true for New Zealand. I find it hard to take seriously the claims of people who attribute housing affordability solely to regulatory policy and fail to consider the potential impact of our low property taxes.
What do you make of the data on property taxes and house prices?