A Request for Readers

1. I’ve been writing for Market Urbanism for about a year now and have thoroughly enjoyed it. Getting your comments and hearing from readers is so rewarding. To provide more of what you’re interested in, I would really appreciate any comments about what topics or types of posts you would like to see covered here.

2. This summer I’m hoping to read two urbanist staples that I’ve read a lot about but am ashamed to say I’ve never actually read: The Economics of Zoning Laws: A Property Rights Approach to American Land Use Controls by William Fischel and Donald Shoup’s The High Cost of Free Parking. If anyone else would like to tackle these in the next few months or has already read them and would like to contribute to some discussion on them, I’d be happy to set up a Google Group for that.

Walk Score Regression Results

Thanks for the comments on my Walk Score model! Per a few reader requests, here are the full results. I should have thought to provide them initially but didn’t realize there would be interest. Also, I don’t know a good way to put STATA or Excel charts here, so apologies for the screenshots.

Here are the results from the OLS model. The 259 datapoints represent all cities with population greater than 100,000 for which there is Walk Score data, except for two or three for which I couldn’t find the MSA data The unemployment is the 5-year January moving average at  2010.

 

And here are the results of the IV regression, where the instrument is the year that the city was founded. First stage:

And the second stage:

 

Some Empirical Evidence on Preference for Cities

This semester I took an econometrics class because I got an MA with the bare minimum of quantitative classes. For the class, I wrote a paper asking the question, “Are consumers willing to pay a premium to live in dense urban areas?” It’s easy to see that urban density is correlated with higher housing prices, but this could come from many factors such as people having to live in dense cities to find jobs or to earn higher salaries or from supply restrictions that impact dense cities more than suburbs.

As a proxy for cities’ urban qualities, I used Walk Score. Walk Score is based on residential distance to amenities, block length, and road connectivity and ranks cities on a scales of 100. It is designed to test the feasibility of living in a city without a car, but it excludes some factors that are often considered relevant to facilitating pedestrianism, including street width, sidewalk width, and population density. Still, I think Walk Score provides a pretty good measure of a city’s urbanist quality. The correlation between Walk Score and median house price is pretty striking:

To test demand for urban living, I wanted to control for the economic factors that drive demand to live in a given city. I tested the impact of Walk Score on median house prices controlling for household income, unemployment, and cost of living. The sample includes 259 cities for which I had Walk Score data and house price data from Kiplinger. The results suggest that for a one-point increase in Walk Score, we can expect a .5% increase in a cities’ median house price, and this result is statistically significant.

In another way of measuring the same question (an IV regression using the year the city was founded as the instrument), I found that a one-point increase in Walk Score can be expected to increase home prices by 3%. This result is also statistically significant, but I have less faith in this model.

For the most part, the other studies that I’ve seen of Walk Score’s relationship to house prices look at one city or a few cities and control for variables like a neighborhood’s crime rate and housing quality. While there are obvious advantages to these more detailed, local studies, I think the national view gets around the sample selection problems that make other results ungeneralizable.

I’d be happy to hear your criticisms of this model — what important variable are omitted, etc. I think there is a lot of room to study people’s preferences for urban form. As Stephen has said previously, looking at where people live without controlling for other factors gives us a better sense of allowable land use than free market revealed preferences, but looking at home prices while controlling for important variables can remove some of this bias.

Thanks to Eli Dourado for helping me think through this model, but of course its problems are my fault.

[Note: I had originally said that the house price data came from the Census. I realized that Kiplinger does not get this data from the Census as their Statistical Abstract only covers select MSAs. The data was collected by Clear Capital, but I haven’t seen it publicly available from them.]

Bike Shares and Public Goods

Yesterday, Maryland Governor Martin O’Malley announced that seven jurisdictions in Maryland will be receiving grants to start bike share programs. The money for these grants comes from the Maryland Department of Transportation’s Federal Congestion Mitigation and Air Quality, so these bike shares will be federally subsidized. O’Malley says of the program:

“As we celebrate Bike Month, these grants will help bring Bikeshare stations to Maryland,” said Governor O’Malley.  “Bikesharing allows Marylanders an affordable option for short-distance trips as an alternative to public transportation, driving or walking.  By getting out and taking a bike ride, we also learn to enjoy more of Maryland’s natural treasures, help reduce the impact on the land, improve our fitness and well-being, and enhance our quality of life.”

The program would be of a similar model to DC’s Capital Bikeshare with capital costs covered primarily with federal grants and some local contributions. I am not much of a bicyclist myself, but I can clearly see the appeal of bike share systems. They provide the convenience of riding a bike to a destination without having to ride it back again, introducing additional flexibility to this mode of transportation. Also, the bikes are better-quality than what many cyclists would buy for themselves.

The problem with the politics surrounding bikeshares is that bicycles are not public goods, but elected officials such as O’Malley like to paint them as such. As Adam has previously pointed out, no transportation investment is a public good. The two characteristics that define public goods are nonexcludability and nonrivalrous consumption. Bike shares are perfectly rivalrous and excludable. Because no more than one  person (maybe two people) can ride a bike at a time, bicycles are lower on the public good scale than transit or roads.

Greater Greater Washington cites a study that publicly-supported bicycle shares are, shockingly, not making money, but GGW says this doesn’t matter since bicycles provide so many benefits to their riders. In a system of better incentives, though, both a private company and cities with bikeshare programs could make money if the private company leased public space for docking stations.

TBD points to a study that analyzes the demographics of Capital Bikeshare users, unveiling the regressive nature of this program. About 80% of CaBi annual members are white, over 80% have college degrees, and 43% have graduate degrees. But from a politician’s perspective programs don’t get much better than this. The capital costs are spread across all US taxpayers through CMAQ grants while the benefits are narrowly concentrated on a population of likely voters.

Lydia DePyllis reports on a pilot program that would bring CaBi access to 10 homeless people who are willing to jump through major hoops, and new proposals to require developers, rather than federal taxpayers to pay for new docking stations. Both of these programs could make CaBi somewhat more equitable. We could provide targeted benefits to low-income bicyclists though with a voucher system for a privately run bike share and achieve greater benefits at a lower cost.

By leasing sidewalk space to private companies to have bikeshare docking stations, these programs could easily become an all-around win for customers, companies, and cities, but as it stands, they hurt everyone except for their users, a government contractor, and vote-seeking politicians.

Compared to other transit modes, CaBi is doing very well, nearly covering its operating costs, but none of its capital costs, with membership fees. I’m picking on this program, because it is currently so regressive and because perhaps it’s new enough to turn over to the market. The private bikeshare system proposed in Los Angeles demonstrates that some investors think there are profits to be made in this industry in an arguably less-bikeable city without imposing the costs of bike sharing on those who don’t use it.