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INFRISK : a computer simulation approach to risk management in infrastructure project finance transactions

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  • Dailami, Mansoor*Lipkovich, Ilya*Van Dyck, John

Abstract

Few issues in modern finance have inspired the interest of both practitioners and theoreticians more than risk evaluation and management. The basic principle governing risk management in an infrastructure project finance deal is intuitive and well-articulated: allocate project-specific risks to parties best able to bear them (taking into account each party's appetite for, and aversion to, risk); control performance risk through incentives; and use market hedging instruments (derivatives) for covering marketwide risks arising from fluctuations in, for instance, interest and exchange rates, among other things. In practice, however, governments have been asked to provide guarantees for various kinds of projects, often at no charge, because of problems associated with market imperfections: a) Derivative markets (swaps, forwards) for currency and interest-rate risk hedging either do not exist or are inadequately developed in most developing countries. b) Limited contracting possibilities (because of problems with credibility of enforcement). c) Differing methods for risk measurement and evaluation. Two factors distinguish the financing of infrastructure projects from corporate and traditional limited-recourse project finance: 1) a high concentration of project risk early in the project life cycle (pre-completion), and 2) a risk profile that changes as the project comes to fruition, with a relatively stable cash flow subject to market and regulatory risk once the project is completed. The authors introduce INFRISK, a computer-based risk-management approach to infrastructure project transactions that involve the private sector. Developed in-house in the Economic Development Institute of the World Bank, INFRISK is a guide to practitioners in the field and a training tool for raising awareness and improving expertise in the application of modern risk management techniques. INFRISK can analyze a project's exposure to a variety of market, credit, and performance risks form the perspective of key contracting parties (project promoter, creditor, and government). Their model is driven by the concept of the project's economic viability. Drawing on recent developments in the literature on project evaluation under uncertainty, INFRISK generates probability distributions for key decision variables, such as a project's net present value, internal rate of return, or capacity to service its debt on time during the life of the project. Computationally, INFRISK works in conjunction with Microsoft Excel and supports both the construction and the operation phases of a capital investment project. For a particular risk variable of interest (such as the revenue stream, operations and maintenance costs, and construction costs, among others) the program first generates a stream of probability of distributions for each year of a project's life through a Monte Carlo simulation technique. One of the key contributions made by INFRISK is to enable the use of a broader set of probability distributions (uniform, normal, beta, and lognormal) in conducting Monte Carlo simulations rather than relying only on the commonly used normal distribution. A user's guide provides instruction on the use of the package.

Suggested Citation

  • Dailami, Mansoor*Lipkovich, Ilya*Van Dyck, John, 1999. "INFRISK : a computer simulation approach to risk management in infrastructure project finance transactions," Policy Research Working Paper Series 2083, The World Bank.
  • Handle: RePEc:wbk:wbrwps:2083
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    References listed on IDEAS

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    1. Froot, Kenneth A & Scharfstein, David S & Stein, Jeremy C, 1993. "Risk Management: Coordinating Corporate Investment and Financing Policies," Journal of Finance, American Finance Association, vol. 48(5), pages 1629-1658, December.
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    1. Marzouk, Mohamed & Ali, Mohamed, 2018. "Mitigating risks in wastewater treatment plant PPPs using minimum revenue guarantee and real options," Utilities Policy, Elsevier, vol. 53(C), pages 121-133.
    2. Yuri Biondi, 2009. "Capital budgeting under relational contracting: optimal ranking and duration criteria for schemes of concession, project-financing and public-private partnership," Post-Print hal-00442716, HAL.
    3. Wang, Xiangning & Zhao, Xing, 2014. "The invoicing currency choice model of export enterprises assuming joint utility maximization and analysis of the factors influencing selection," Economic Modelling, Elsevier, vol. 42(C), pages 38-42.
    4. Nicola Chiara & Michael Garvin, 2008. "Variance models for project financial risk analysis with applications to greenfield BOT highway projects," Construction Management and Economics, Taylor & Francis Journals, vol. 26(9), pages 925-939.
    5. Guofeng Ma & Qingjuan Du & Kedi Wang, 2018. "A Concession Period and Price Determination Model for PPP Projects: Based on Real Options and Risk Allocation," Sustainability, MDPI, vol. 10(3), pages 1-21, March.
    6. Stefano Gatti & Alvaro Rigamonti & Francesco Saita & Mauro Senati, 2007. "Measuring Value‐at‐Risk in Project Finance Transactions," European Financial Management, European Financial Management Association, vol. 13(1), pages 135-158, January.

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