Light Rail Cost Functions and Technical Inefficiency

Abstract

Light rail operating costs vary with a system's scale of operations, traffic density, vehicle and passenger outputs, and input prices. Previous attempts at estimating these cost relationships have been hampered by inadequate data and methodologies that restrict their functional forms, limit their output measures, omit factor prices, and fail to account for technical inefficiencies. With more data now available from an increased number of systems operating during longer time periods, new cost specifications that improve the precision and reduce the bias of cost estimates can be estimated. Here, light rail cost functions are estimated with 1994 to 2005 data for 21 U.S. light rail systems. The cost functions relate operating and maintenance costs to passenger and vehicle outputs, input prices, route densities, vehicle capacities, and latent cost inefficiencies. Four estimation methods are used: (a) iterative seemingly unrelated regression, (b) least-squares dummy variable, (c) maximum likelihood stochastic frontier, and (d) hierarchical Bayesian frontier models. Economies of size and density, input productivities, input substitution elasticities, and transit system inefficiencies are measured.