Joh, Nguyen, and Boarnet on walking, built environment, and attitudes towards neighborhood safety

This manuscript has been out for awhile, but I’ve been too busy to read it with the care it deserved. Here’s the full cite:

Joh, K, M T Nguyen, and M G Boarnet. “Can Built and Social Environmental Factors Encourage Walking Among Individuals with Negative Walking Attitudes?” Journal of Planning Education and Research (2011)doi:10.1177/0739456X11427914

From the abstract:

We investigate whether the design of the built environment encourages walking above and beyond individuals’ attitudes toward walking. With data from a regional travel survey, we use regression analyses to examine differences in neighborhood walking trips among residents with positive and negative attitudes toward walking. The results show that built and social environment factors have a differential impact on walking trips depending on a person’s walking attitudes. Therefore, strategies to promote positive walking attitudes should be pursued in tandem with land use policies to encourage neighborhood walking.

They use data from a travel diary administered by the South Coast Association of Governments. The paper frustrates me somewhat, in that they leave out rather some (to me) important details. They stratify their sample into two groups: people who have a high preference for walking (the high walk group) and some who have a low preference for walking. They explain:

To compare these groups, the sample was stratified into two groups based on attitudinal differences, hereafter referred to as “high-walk” and “low-walk” attitudes. A walking attitude index was constructed based on an additive measure of three attitudinal questions from the South Bay travel survey. For each question, respondents were asked to rate on a 5-point ordinal scale (5 = very important; 4 = important; 3 = neutral; 2 = rather unimportant; 1 = not at all important). The median attitude index value of 10 was used as the threshold for stratifying the sample into high-walk and low-walk groups. Therefore, respondents who scored 10 or higher on the attitude index were included in the high-walk sample, while those who scored 9 or lower on the scale comprised the low-walk sample, with index scores ranging from 5 to 15.

Ok, but nowhere in the paper can I find what these three questions are, precisely. And that matters. Travel diaries tend to drive me crazy because transportation agencies seldom cognitively test their surveys with psychologists before administering them. I don’t know whether SCAG did so, but if they did, it would surprise me. Few people in transport are trained this way. This lack of testing isn’t something the authors of the study can do anything about; it’s not their survey. It’s just a problem that bugs me about agency-administered surveys in general.

But the questions they used to combine for their index should be explained in the article. Am I just missing it?

Splitting the sample means they are going to run into more trouble than otherwise when they begin to bring in their neighborhood level variables–which, for all practical purposes–work like another strata on the data. It’s not really clear what the split sample accomplishes for them that using the preference variables or indexes as controls wouldn’t accomplish just as well. The case for stratifying isn’t made clear to me anyway.

They are trying to figure out if built environment and safety variables produce more of an effect for those with different levels of preference towards walking in the first place. They are also, I suspect, trying to figure out if people sorted themselves by residential preference according to preference towards walking: those who very much prefer walking might be expected to, all things equal, buy houses in neighborhoods with more walking amenities. They don’t seem to see that effect here, which probably just means they can’t control for enough residential neighborhood variables to see an effect, or the effect is simply dominated by preferences for other things, like schools.

Their dependent variable is a count of walking trips.

These glitches notwithstanding, they have some interesting results, but what I find interesting, they don’t seem to find interesting. First, we’ll look at what they find interesting. They find that for those who have a high preference for walking, violent crime rates do not dampen the individuals’ tendency to walk much. And, in turn, a good supply of neighborhood walking destinations–a la the mixed use that planners promote so tirelessly–allows those with the preference towards walking to satisfy that preference. Yay! However, violent crimes seem to really reinforce lack of walking among those who show little preference for it–as we would expect–and no amount of neighborhood design seems to influence them to walk more. In fact, the Jane Jacobs idea–short blocks, lots of intersections thing seems to dissuade them! (I TOLD YOU PEOPLE SO! I’ve been saying it for years. Not everybody loves short blocks with lots of opportunities to get hit by a car!! Did you listen? NOOOO).

As long as I am behaving childishly, let’s look at the finding I think is interesting that they don’t comment on: the biggest factor that dampens the high walking group appears to be having children in the household. Don’t you think that’s interesting? I do. It’s a big effect size, too–bigger even than the effect that violent crime rates has on discouraging walking. The low walk group isn’t affected by having kids in any way. So if you want to stay with active transport, don’t have children. 🙂

It would be interesting to see–which they probably can’t do with these data–whether violent crime rates are informing the negative attitudes about walking to begin with.

Pivo and Fisher on the Walkability Premium for Commercial Properties

Edited thanks to thoughtful commenter Derek Pokora:

The full article in per can be downloaded from Pivo’s academic page at the University of Arizona.

I always follow the work of Gary Pivo, and he and Jeffrey Fisher have a new manuscript in this (excellent) edition of Real Estate Economics. Because this is a scholarly publication, you have to pay for access, unfortunately. I will discuss it extensively here for those who can’t go read it themselves.

Here is the citation:

Pivo, G., & Fisher, J. D. (2010). The walkability premium in commercial real estate investments. Real Estate Economics. doi:10.1111/j.1540-6229.2010.00296.x

From the abstract:

This article examines the effects of walkability on property values and investment returns. Walkability is the degree to which an area within walking distance of a property encourages walking for recreational or functional purposes. We use data from the National Council of Real Estate Investment Fiduciaries and Walk Score to examine the effects of walkability on the market value and investment returns of more than 4,200 office, apartment, retail and industrial properties from 2001 to 2008 in the United States. We found that, all else being equal, the benefits of greater walkability were capitalized into higher office, retail and apartment values. We found no effect on industrial properties. On a 100-point scale, a 10-point increase in walkability increased values by 1–9%, depending on property type. We also found that walkability was associated with lower cap rates and higher incomes, suggesting it has been favored in both the capital asset and building space markets. Walkability had no significant effect on historical total investment returns. All walkable property types have the potential to generate returns as good as or better than less walkable properties, as long as they are priced correctly. Developers should be willing to develop more walkable properties as long as any additional cost for more walkable locations and related development expenses do not exhaust the walkability premium.

The use regional, neighborhood, and building variables in their models. Among their building characteristics include: number of stories, a square of that, the property tax, and whether the property is within a half mile of rail transit station. For neighborhood characteristics, they have property crime rates, population density and Walk Scores. They also use a bunch of regional variables.

One of the nice parts of the paper is their discussion of the Walk Score and what it measures.

Ohhhhhhh how I wish they had had parking availability for this study. A walking premium holds with theory. But theory would also suggest that the sorts of designs that accommodate both parking and walking would be even more productive for the developer and the tenants. The big box world of large surface lots has become uninteresting to a lot of urban consumers. But think about all the urban Trader Joe’s out there that have four stories of parking underneath or above in addition to their street-level storefront. Those are the properties that I bet get a nice value boost, and there’s no way to glean that from their data or model.

The difference is huge for those who argue that walkable developments “take cars off the road.” These developments may do so, but they may also simply generate more trips overall–and that’s certainly not a bad thing from the developer’s viewpoint.

Pivo and Fisher find that apartment properties had little premium value associated with walking–rather, the major boost came to commercial property, and in particular, retail property. They argue that it may be that the Walk Score, reflecting multiple things, is also capturing what may be negative effects from proximity to busy commercial centers (noise, lack of privacy, etc). It could be that–Lord knows, plenty of the people who advocate loudly for urban living completely discount its inconveniences.

But I strongly suspect one of the reasons they don’t see more of an effect for the apartments is that there is just plain more variation in quality and individual building characteristics than they can really capture with the data they’ve got. So it’s not like there is no effect, it’s just really hard to suss here given the data and given, as they point out, the potential conflicting effects from the Walk Score.

They find a 0.18 coefficient for market value with regard to their 1/4 mile buffer, and it’s highly significant, for the rail access variable, but that variable correlates at 0.51 to the Walk Score, and they don’t really present any tests for this problem. The correlation is not the end of the world, but it’s just high enough, and it’s positive, that had I been a reviewer, I would have grouched at them to check on it more. When you are using a combined or index measure like a Walk Score, it’s important to help your reader understand how it may interact or correlate with other measures.

The proximity to transit variable tells an interesting story for urban theory. They have appreciation and income variables for outcomes, and these variables are all logged. They find, just as with the Walk Score, that rail transit access has the highest impact (all effects significant) for retail and commercial property. Retail gets a nice boost in operating income from a higher walk score and rail transit access.

However, the aggregate regressions show a positive value for appreciation and negative for income.

So what does this mean? Their interpretation, if I understand them, means that the value of the additional business you get from walking customers probably gets captured by landlords and property owners rather than businesses renting–that is, they pay higher rents for their location location location. Property owners benefit from walkability, but tenants should think twice if somebody asks them to pony up for walking improvements. It also suggests that the property tax is a good source of funding for walking improvements, given who financially benefits, even though we all know that expecting property owners to pay taxes is the equivalent of spitting on veterans and making cookies for Jane Fonda.

What I learned from Marlon Boarnet about walking in the suburbs

Marlon Boarnet of UCI gave a seminar in our school yesterday on some of his collaborative research on walking in the suburbs. I took the following from the talk:

1. Suburbs have various spatial forms, and some of those may be conducive to walking in polycentric regions.

2. Those spatial forms may be difficult to divine empirically, but business number and–perhaps–service diversity may be one way to define a center/cluster.

3. Centers and clusters in the polycentric city can foster walking and dampen driving, though the latter effect appears weakly significant in this test.

4. There is a potential tradeoff between making retail clusters that serve nearby residents who walk becoming greater draws to the larger region that can generate auto traffic into the neighborhood.

5. Successful scholars experiment with cutting-edge ideas and analogies, some of which work, some of which don’t, but from that experiment new concepts and measures emanate.

Why do parents drive kids to school when they could walk?

UNC’s Noreen MacDonald has a very nice manuscript in the upcoming issue of the Journal of the American Planning Association:

From their abstract:

We found that 75% of parents driving their children less than 2 miles to school said they did this for convenience and to save time. Nearly half of parents driving their children less than 2 miles did not allow their child to walk to school without adult supervision. Accompanying a child on a walk to school greatly increases the time the household devotes to such a trip. Few Safe Routes to School programs effectively address issues of parental convenience and time constraints. [1]

So here we have it. The good thing about Noreen and her co-author is that they won’t allow the interpretation here to turn into some working-mom-blame (you think I kid; I have heard public health people say that moms entering the workforce have contributed to childhood obesity because more meals are prepared away from home and the children are outside walking less. This may be, but nobody’s blaming working fathers for this, now are they? Let’s think about how this problem is framed.)

One of the things about the manuscript that makes me wonder: 2 miles is a long way for a young kid to walk–so yeah, it’s going to take some time. I wonder if they were to go finer-scaled–five blocks or so away from school–whether they would get some new insights on why those parents are or are not walking their kids to school.

[1] N. C. McDonald and A. E. Aalborg. Why parents drive children to school: Implications for safe routes to school programs. Journal of the American Planning Association, 75(3):331–342, 2009.