Private sector investments in public infrastructure projects have witnessed a tremendous increase over the past decade. The lack of government resources coupled with the need for expanding new and renewing exiting infrastructure has created a viable market for private infrastructure investments. Proper allocation of risks in public private partnership (PPP) projects has been identified as one of the critical success factors of these projects. Revenue risk is a common risk item in most PPP projects due to the long contract duration of these projects. Government Minimum Revenue Guarantees (MRG) is a common risk mitigation strategy whereby the government guarantees that project revenues will not fall below a specified limit during the contract. This guarantee is only redeemable at distinct points in time, so takes the form of either a Bermudan option, or a Simple multiple-exercise real option, depending on the number of exercise rights afforded. In this paper the valuation of this real option is done through the application of the Multi-Least squares Monte, and Multi-Exercise Boundary methods. These methods combine the use of Monte Carlo simulation, and dynamic programming. The quantitative approach offers more flexibility than other prevailing methods, and facilitates the contractual and financial negotiations in such projects. Two case studies of waste water treatment plants are examined. The first considers the construction of the treatment plant in one stage while the second considers the contractual requirement of phasing the construction of the plant in two stages.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.