Chris Bradford has recently run an excellent series of posts featuring the Census Bureau's newly-released data covering population-weighted density. Chris has been an advocate of this density measure (also referred to as "perceived" density) for much longer, though, and has promoted it as a more useful alternative to both standard density and the somewhat more helpful urbanized area density.
At The Atlantic Cities, Richard Florida picked up on the story, noting its significance of these new figures in exploring the relationship between density and productivity. The topic has been addressed at least once before: a 2010 report from the Federal Reserve Bank of New York, updated last year, used weighted population density to find that:
- In general, productivity increases by 2 to 4 percent as weighted density doubles.
- Productivity increases are correlated with human capital (e.g. skills and education), such that cities with a human capital one standard deviation below the mean have no productivity gains from increased density, while those with high human capital have twice the average gain.
- The benefits of density are especially pronounced for certain industries, including professional services, arts, entertainment, information and finance.
Along the same lines, I've drawn up a correlation chart showing the population-weighted density for all metropolitan statistical areas as compared to several other factors, including total metro area population, population change during 2000-2010 both in net and as a percentage, urbanized area density, median home values, median personal income (a stand-in for productivity in many studies), and finally income-to-home value ratio (an indicator of relative housing affordability). Each factor has been compared against every other (raw data is available here).
A few of the things that jumped out at me from the chart:
- Income is more strongly correlated with weighted density than total population, although not dramatically so. However, median home values were even more strongly correlated with weighted density. The result is that, for cities of equivalent size, the city with the higher weighted density will generally be less affordable in relative terms, even if incomes are higher (for instance, Sacramento is almost twice as dense as similarly-sized and lower-income Kansas City, but is only two-thirds as affordable).
- Although high weighted-density metros have generally higher incomes than low-density cities, they grew more slowly than these cities, perhaps indicating the push and pull forces of housing affordability.
- Nonetheless, relative housing value was negatively correlated with population growth, although not strongly. This suggests a tension between low housing values being a product of low demand, and the attraction of low housing costs in otherwise prosperous cities that have presumably kept prices low through adequate supply. Looking at only large cities bears this out (see below).
Here is the same chart showing only MSAs with more than one million inhabitants as of the 2010 Census:
The sign for affordability relative to population gain has flipped, and more affordable markets are here associated with higher population growth.
Another factor I would have liked to include, had it been available for all MSAs, would have been median transportation cost, since to some extent that would offset the poor affordability of certain high-density cities.
I am skeptical, though, that these figures would make much difference for most cities. Although recent studies have pointed to the transit savings of living in high density areas well-served by mass transit, most American metro areas remain overwhelmingly car dependent. Moreover, while high housing costs cannot be easily avoided, households have more direct control over transportation spending even in low-density cities.
Beyond these points, I'll leave the numbers out there to speak for themselves.