How to cite this study
Krizek, K. 2006. “Two approaches to valuing some bicycle facilities’ presumed benefits.” Journal of the American Planning Association 72(3): 309-320.
This study found that those commuting by bicycle are willing to go out of their way to use a safer route, with the largest detour for on-street, designated bicycle lanes, followed by routes without parking and routes with an off-street bicycle lane. The effect of these bicycle facilities on property values is mixed, depending on the type of facility and whether it is in an urban or suburban neighborhood.
This study would be of interest to those interested in how cyclists perceive specific types of cycling infrastructure. The analysis of cyclists’ willingness to incur extra commuting time is a unique approach in the literature, and provides a useful hierarchy of cycling facilities’ appeal to use in deciding which types of facilities to build and where to locate them.
The study is based in the Minneapolis-St. Paul, Minnesota metropolitan area, population 677,914 in 2013. These cities had an extensive off-street bike path system covering 1,696 miles in 2006.
The study covers urban cycling-related pathways including off-street bike paths and on-street designated bike lanes. These are largely commuter and transportation routes.
The purpose of this study is to compare how cycling facilities are valued by users, measured in time tradeoffs cyclists make to use designated facilities and measured in different property values near cycling facilities. The goal of the study is to demonstrate the methods to use in other communities, identify the types of facilities most important to cyclists, and identify where facilities should be located to maximize their effectiveness. The study was funded by the National Cooperative Highway Research Program Guidelines for Analysis of Investments in Bicycle Facilities.
Cyclists were most likely to go out of their way on their commute to use an on-street bicycle lane (an extra 16 minutes on a 20-minute commute), although they were also willing to go out of their way to use a route with no parking (an extra 9 minutes) or an off-road route (an extra 5 minutes). Women and those with higher incomes were more likely to choose longer, safer routes.
Cycling facilities had different effects on property values in urban versus suburban settings. In the city, prices were $510 higher for every 400 meters closer the house was to an off-road bicycle path. However, in the suburbs, home prices were $240 less for every 400 meters closer the house was to an off-road path. In both the city and suburbs, house prices were lower when they were closer to a roadside bike path: $2,272 lower in the city and $1,059 lower in the suburbs.
These results differ from findings in other studies (e.g., 22, 23, 26, 43) that found proximity to off-road bike paths to be generally associated with higher house prices. The author suggests that this result may be due to lower rates of bicycle use in suburban neighborhoods, or perhaps because houses near bicycle facilities are also near undesirable features such as railroad right-of-ways. Results from this analysis suggest that siting criteria should differ between urban and suburban areas.
To understand cyclist perceptions of different types of cycling facilities, the author presented respondents with images of five types of facilities: off-street facilities, on-street facilities without parking, on-street facilities with parking, a roadway without a designated bike lane but no parking, and a roadway without a bike lane and with parking. Each facility type was associated with different travel times to use them, and respondents were asked to pick which one they would use. After aggregating responses from 181 participants out of 2,500 recruited (7% response rate), the author estimated a statistical model to understand the time-tradeoffs respondents were willing to make to use a preferred cycling facility.
Although the response rate is very low, because respondents were asked to participate in a survey about their commute and not specifically cycling-related issues, the responses to this survey are not necessarily biased in one direction.
To understand how proximity to cycling facilities affects property values, the author used a statistical model to compare sale prices of homes that were identical in terms of structural attributes (e.g., number of bedrooms and bathrooms), environmental amenities (e.g., distance to open space), location (e.g., distance to central business district), and neighborhood attributes (e.g., school district test scores), differing only in their proximity to different types of bicycle facilities. The difference in prices between these otherwise-identical homes is the implicit value of the bicycle facility. This approach is known as a “hedonic model.” The author used a database including 35,002 residential house sales in the metro area for 2001.
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