Article ID: | iaor2012949 |
Volume: | 39 |
Issue: | 2 |
Start Page Number: | 409 |
End Page Number: | 432 |
Publication Date: | Mar 2012 |
Journal: | Transportation |
Authors: | Pucher John, Buehler Ralph |
Keywords: | statistics: inference, statistics: regression |
This article analyzes the variation in bike commuting in large American cities, with a focus on assessing the influence of bike paths and lanes, which have been the main approach to increasing cycling in the USA. To examine the role of cycling facilities, we used a newly assembled dataset on the length of bike lanes and paths in 2008 collected directly from 90 of the 100 largest U.S. cities. Pearson’s correlation, bivariate quartile analysis, and two different types of regressions were used to measure the relationship between cycling levels and bikeways, as well as other explanatory and control variables. Ordinary Least Squares and Binary Logit Proportions regressions confirm that cities with a greater supply of bike paths and lanes have significantly higher bike commute rates–even when controlling for land use, climate, socioeconomic factors, gasoline prices, public transport supply, and cycling safety. Standard tests indicate that the models are a good fit, with