Simulation of investment returns for toll projects

Public-private partnership (PPP) is an innovative funding mechanism for state Departments of Transportation (DOTs) to utilize private capital and expertise in transportation infrastructure projects, so as to increase funding options to bridge the budget gap of DOTs. In this thesis research, a literature synthesis was conducted to clarify key concepts including reviews on the literature of PPP and toll projects, investigation of the state-of-art financial models, presentation of problems in toll revenue estimation and summarization of the significance of conducting risk management in PPP investments. Financial models can provide public sectors and private partners with an analysis tool to evaluate the potential returns of investments and financial feasibility of the projects. This research develops a methodological framework to illustrate key stages in applying the simulation of investment returns of toll projects. This methodological framework of risk analysis for financing toll projects acts as an example process of helping agencies conduct numerical risk analysis by taking certain uncertainties associated with toll projects into consideration. The numerical financial model provides a deterministic financial evaluation for the project. Next, there are four risk sources identified in this research, including project-based risks, cost-based risks, toll-based risks and finance-based risks. For each risk source, critical variables are recognized. Furthermore, probability distributions of identified variables are suggested. The deterministic financial evaluation result is obtained through the projected single-value estimates of these variables. By considering the variability associated with the components of a project, the Monte Carlo simulation technique is used to estimate the overall project risks. Risk simulation results are interpreted through various numerical measures of project’s risks, which further provide agencies with quantitative information to set investment decision criteria. For risk optimization, there are two main functions. One is to explore the optimal value-combination of variables so as to help set risk control benchmarks. The other is to utilize the single-variable control method to investigate the optimal total revenue considering the impact of toll prices on the traffic demand, which could assist agencies in setting threshold toll prices in order to achieve the goal revenue and maximize potential returns on the investment. The risk analysis, consisting of risk simulation and risk optimization, can give the statistical distribution of investment returns for a project under analysis, providing decision makers with a direct approach to the evaluation of the projects’ financial risks and the development of recommendations for risk control measures.