Dynamic Estimates of Fare Elasticity for U.S. Public Transit

Abstract

Transit agencies frequently need to estimate the revenue and ridership impacts of proposed changes in fares. These agencies may rely on the decades-old rule of thumb that the elasticity of transit ridership with respect to fare is 20.3. Studies using European data have found that the relationship is more elastic, particularly in the long run. This paper estimates fare and service elasticities with panel data for 198 U.S. transit agencies from 1991 to 2012. Although the short-run fare elasticity was found to be 20.34, the long-run fare elasticity was 20.66. Moreover, the long run was not very far in the future: 90% of the adjustment to the long-run equilibrium occurred within 18 to 36 months. Separate models were estimated for transit agencies in large urban areas (1 million or more population) and smaller ones (less than 1 million). Transit demand in large areas was less sensitive to fare (long-run elasticity of 20.48 compared with 20.73 for small areas) and much more sensitive to service (long-run elasticity of 1.12 compared with 0.67). Furthermore, where fares are initially low, an increase in fare will lead to a greater decline in ridership than in places where fares are initially higher. Use of the 20.3 rule of thumb for forecasting will significantly understate ridership losses caused by fare increases even in the cases in which fare elasticity is lowest (larger urban area or high initial fare). There is no single fare or service elasticity that best fits all cases. At a minimum, both urban area size and initial fare level should be considered when selecting appropriate fare elasticity.

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