Using Probabilistic Methods to Estimate the Public Sector Comparator

Abstract

Abstract: The use of the public sector comparator (PSC) is gaining momentum as a tool to ensure value for money in public–private partnership (PPP) projects. Several countries have been engaging in the calculation of the PSC, but the methodologies are excessively dependent on deterministic models, as referred to by the existing literature. Alternatives to accommodate uncertainty and forecast bias are required to improve the robustness of the calculations. This article proposes new developments in existing methodologies able to accommodate dynamic analysis to cope with uncertainty in the assumptions. A simulation model was used to compute the variability in the PSC, but the research went a step further in developing a Bayesian network approach. The output of both models is a probability distribution for the PSC, instead of just a single value, therefore, the authors have developed a methodology for comparing the PSC distribution with the PPP value.

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