A time-series analysis of gasoline prices and public transportation in US metropolitan areas

This research examines the temporal aspects of the relationship between public transportation and gasoline prices in US cities from January 2002 through March of 2009. Data are collected at monthly intervals for transit ridership, service, gasoline price, and price variability for 33 metropolitan areas. These data are analyzed using time-series regression to estimate the presence of lagged effects of price and service on transit patronage.The results indicate a small but consistently significant amount of transit ridership fluctuation is due to gasoline prices. Repeated lags of gasoline prices of up to 13 months are influential on ridership. Every 10% increase in gasoline prices can lead to ridership increases of up to 4% per significant lag for bus and 8% for rail. There is considerable variability across cities in the magnitude of the effect on transit ridership, the impact by mode, and temporal variability. The results are discussed in light of their implications for transit operations, using cost to influence travel behavior, and transportation sustainability.

► Time-series analysis of 33 cities.
► Lagged gasoline prices and other service characteristics to estimate transit use.
► Every 10% increase in gasoline prices equals up to 4% per significant lag for bus.
► Every 10% increase in gasoline prices equals up to 8% per significant lag for rail.
► Greater response in areas with less transit service and with recent improvements