Rolling stock purchase cost for rail and road public transportation: random-parameter modelling and marginal effect analysis. Issue 5 (27th May 2016) - Murillo-Hoyos, Jackeline; Volovski, Matthew; Labi, Samuel
ABSTRACT: Public transportation rolling stock is a major item of capital expenditure associated with transit facility construction, expansion, or revitalisation. As such, reliable estimates of the expected purchase costs of rolling stock are critical for analysing the financial feasibility of proposed public transportation systems and financial planning for existing systems. Such cost data are often characterised by heterogeneity of observations that often plagues fixed parameter (FP) model estimation. Therefore, in modelling transit rolling stock costs, it is needed to address such limitations of past studies. Using data from the National Transit Database, this paper addresses the issue through the random parameter (RP) estimation modelling technique, where parameter estimates are allowed to vary across observations according to the most appropriate distribution. The paper demonstrates that the RP modelling technique yields superior estimates compared to the FP model. This is because the former can account for unobserved heterogeneity in transit rolling stock purchase cost data due to unobserved factors that otherwise severely impair the reliability or intuitiveness of the model. The paper also carries out marginal effect and sensitivity analyses on the developed model to acquire a deeper insight into the influence of the cost factors. The RP rolling stock cost models developed in this paper can be applied by public transportation agencies to carry out strategic tasks associated with the development or management of new or existing transit systems, respectively. These tasks include analyses of financial feasibility of proposed transit systems, development of budgets, and projections of cash outflows as part of long-range plans, financial planning, and short- and long-term funding needs assessment for existing or proposed transit systems. Moreover, the findings regarding the influential cost factors can be used to guide purchasing policies for transit rolling stock.