Real estate giant Redfin (which owns WalkScore) has a study about how transit quality correlates with property values. And yes, there’s a correlation:
On average, across the 14 metros analyzed, one Transit Score point can increase the price of a home by $2,040. But the price premium varies widely from metro to metro.
That variance is a problem, though. For example, a Transit Score point gains you 1.13% on property values in Atlanta but counts for nothing in Orange County, California. When you see this kind of variance, you should suspect that other factors are more significant than the one being studied. So this supposedly pro-transit Redfin piece can actually be used to argue that transit isn’t all that important, or at least that when transit is important, it’s because it echoes something else that matters more.
But we should explore a simpler explanation: Maybe transit is relevant, but Transit Score isn’t.
I explain what’s wrong with Transit Score here, but the bottom line is that Transit Score has nothing to do with where you can get to on transit. Transit Score is about how much transit is nearby, and whether it’s cute or sexy, but not at all about whether it’s useful. In this it’s much like the way the real estate industry evaluates static civic amenities, like schools and parks, whereas it should be more like the way the same industry evaluates road access, i.e. by caring how fast you can get to places. More here.
This is important because when you publish results with such huge variability, you tip off smart people that you may not be looking at the right explanatory variable. It’s easy to look at these results and assume that transit isn’t what matters. But maybe it’s Transit Score, not transit, that’s the distraction.
So a useful Transit score would need to provide a value that represents how many places the closest transit portals could get you to in some amount of time?
A fast approach might be to pre-calculate the walk-score for each train/bus stop. Save in a database. Then add up the values reachable in say an half hour.
The pre-calculation could include dwellings and jobs in the walk score if they don’t already.
Are we getting close enough and fast enough to calculate on the fly from any address?
I wonder what the correlation is between rents and proximity to transit? It strikes me that a higher proportion of renters would be transit users who would value living closer to good service and be willing to pay for it.
This might explain why it’s Atlanta’s shitty transit that sees a transit score effect while Orange County’s frequent grid doesn’t.
When I checked, Atlanta’s only frequent bus routes were suburban feeders to rail, and never intersected each other outside a rail station or went downtown, and the rail lines themselves formed a simple cross shape, with some branching of the northern leg in the far suburbs. Orange County, by contrast, has a grid of frequent bus routes, albeit no rail. So it seems that less useful, perfunctory transit is more beneficial to property values than transit that meets all the criteria you regularly lay out.
It’s impossible to fully assess their analysis without seeing more detail on their methodology and results, including standard errors on their coefficient estimates of the impact of TransitScore on sale prices.
However, I wouldn’t be so quick to dismiss the results. They’re roughly what I’d expect: A consistently positive effect, but coefficients that vary between cities and are sometimes negative. The variation in effects between cities is as likely to reflect imprecision in the coefficient estimates as it is to reflect variation in the *actual* effect.
One potential reason for an imprecise estimate is that there may be relatively little variation in TransitScore in some cities. Hence Atlanta, which has sharp differences between the quality of PT provision in different neighbourhoods, will tend to have a more precise estimate than Orange County, where there may be less variation in PT provision.
My suspicion is that the confidence interval for the Orange County estimate includes both positive and negative values – ie it’s not conclusive evidence of a negative impact of better PT access.
It’s more than just the measurement method.
At least in Melbourne Australia (which has large variations in transit service provision across the city) the correlation between property prices and transit is limited. Areas with little or no transit seem to be clustered at the extremes in property prices and average incomes. Eg Rosebud West, Campbellfield, Hastings are low income with limited transit. They are often 1970s-1980s housing commission or low income type estates not walkable to very much.
Portsea, Patterson Lakes, Sandhurst estate, Eynesbury (and until recently Sanctuary Lakes and Waterways) are often exclusive golf club or marina-based estates with some of the highest SIEFA scores (a measure of socio-economic advantage) in the city due to their paucity of low income earners. They have (or had) no or very limited public transit and often nothing within walking distance. In some cases they were ‘green wedge’ developments that breached rules of locating ‘on the way’.
Take those away and there’s more a relationship between proximity to the CBD and house prices. And the better proximity to the CBD the better the transit service (especially rail modes which in Melbourne is strongly correlated with good frequency and especially long operating hours).
But if we zoom into the micro level within suburbs, areas around stations are often shabby and the ‘best’ housing may be 1 or 2 km from the station – ie a bit beyond walking distance (although this is changing with urban infill). The latter is even more so true in slow growing cities such as Adelaide where the rail corridors are often underused with declining marginal industry at less than even standard suburban density and there is less demand for urban infill.