On the design of public infrastructure systems with elastic demand

This paper considers the optimization of public infrastructure systems, recognizing that these systems serve multiple user classes. Example application domains include: public transportation systems, electricity distribution grids, urban water distribution systems, and maintenance of pavement and bridge systems. Under the guidance of a policy-making body, the analyst chooses both the system design, including its layout and control, and the prices to be charged for the service. The goal of the optimization is to maximize society’s welfare recognizing that the system’s performance will in general depend on the system’s demand, and vice versa.The optimization problem is first formulated in its full complexity, where the prices, the demand and the system design are to be determined. It is then shown that if the user classes recognized in the analysis can be priced independently, and if the policy setting body specifies either the demand levels or the generalized prices experienced by each user group, then the resulting welfare maximization problem decomposes into three sub-problems that can be solved sequentially: demand estimation, system design and pricing. It also turns out that the optimum design can always be obtained by minimizing the generalized cost of the system to society for the known fixed demand, as is conventionally done in practice. The resulting design is independent of how net user benefits are measured and of the pricing scheme.If the policy-making body does not specify cost or demand targets, and instead assesses benefits by means of consumer surplus then the optimum design is still the solution of a conventional design problem with fixed demand. In this case, however, the demand has to be obtained iteratively using a marginal cost pricing rule.The paper finally shows how government can structure payments to a for-profit agency so it will be induced to design and operate the system optimally for society.

► Conditions under which system design, management and pricing decisions can be decoupled are identified.
► In some cases, the systems’ design can be optimized in one step without a demand model.
► The management and pricing decisions to go with the design are also identified.
► The results apply to multi-period, long horizon systems with congestion effects and externalities.