Improving Demand Modeling in California\u27s Rail Transit System

This paper analyzes urban rail-fare elasticity and compares the results across four California transit systems. A method of Internet search is adopted to collect monthly transit-fare records from 2002 to 2013. This paper contributes towards improving demand modeling for public transit using more precise and monthly data and applies econometric techniques involving autoregressive integrated moving average (ARIMA) and panel data models. Results show that demand for public transit in California is very inelastic. Any ridership promotion policy may have a heterogeneous impact across transit systems