Fine‐tuning the value and cost of capital of risky PPP infrastructure projects

Abstract

PurposeThe present paper aims to introduce a new methodology taking risk behavior of decision maker into account to fine‐tune the value of a risky public‐private‐partnership (PPP) project and the corresponding cost of capital based on the target rate of return set by the project sponsor and the degree of project risks.Design/methodology/approachThe proposed methodology combines the cumulative prospect theory (CPT) to characterize the risk preference of the project sponsor and the Monte Carlo simulation to assess the project riskiness. The methodology requires a pre‐set target rate of return that will define the relative gains and losses for a prospect theory project sponsor. The application was illustrated using a build/operate/transfer toll road project as a case study.FindingsAs the project sponsor sets a greater target return, the probability of the project not meeting the target is accordingly greater. Given that losses have greater impact than gains on the decision, other things being equal, a higher target return leads to a higher value correction. It has also been demonstrated that the corresponding project's cost of capital can be up‐ or downadjusted depending on the project's riskiness which may result in a reverse preference to favor a higher risk scenario.Research limitations/implicationsThe methodology uses the CPT parameters that need to be further confirmed and validated if applied to value large risky projects like PPP investments.Originality/valueThe proposed methodology offers a different approach to correctly value a risky PPP project by extending the application of the cumulative prospect theory that well explains the irrationality of human decision behavior under risk into a financial decision‐making process. It takes the full benefit of simulation to understand project risks and also assists financial decision‐making.