Urban Metro Rail Demand: Evidence from Dynamic Generalized Method of Moments Estimates using Panel Data

This paper estimates elasticities of demand for metro services with respect to fares, income, quality of service, population and network length. Data for 32 world metro systems covering the period from 1996 to 2015 are analyzed within a dynamic panel data specification. Three key contributions are made. First, we collate a database for estimation that is more extensive than that used in previous studies. Second, the quality of the data we have available allows us to more accurately represent quality of service than has been possible previously. Lastly, we estimate and compare two different measures of demand. Our analysis finds a statistically significant negative fare elasticity of -0.25 in the long run for a passenger km specified model and -0.4 in the long run for a passenger journey specified model, and a positive long run income elasticity of 0.17 and 0.18 for the passenger km and passenger journey models respectively. Regarding quality of service, we find positive long run elasticities of 0.56 and 0.47 for the passenger km and passenger journey models respectively. Income levels, population, and the size of the network are also found to be statistically significant and positive in nature. The results suggest passenger km and passenger journeys will increase more in response to changes in service (here represented by increased capacity) than to changes in fares, with the difference in elasticities of service and fares being more pronounced for passenger km.