Infrastructure Credit Risk Research
Debt is an inherent part of infrastructure investment and credit risk modeling and estimation are necessary to understand the risk profile of an investment, even on the equity side, which can be “wiped out” in the event of project default.
Our research on credit risk in infrastructure project finance leverages the unique infraMetrics database to understand cash flow dynamics and the risk of default and losses given default.
This paper examines the drivers and evolution of credit spreads in private infrastructure debt. We ask two main questions: Which factors explain private infrastructure credit spreads (and discount rates) and how do they evolve over time? Are infrastructure project finance spreads and infrastructure corporate spreads driven by common factors?
Recent research has demonstrated that structural credit risk models are capable of explaining the credit risk process for private, illiquid debt. This article extends this literature by proposing a simple and intuitive calibration approach using Bayesian inference to capture the nonlinear dynamics of debt service cover ratios.
We extend the structural credit risk model of illiquid debt developed by Blanc-Brude and Hasan (2016) to incorporate the step-in option of senior creditors in project financing and model its impact on the valuation and risk profile of senior unsecured project debt.
A Structural Credit Risk Model for Illiquid Debt
November 2016
We develop a structural credit risk model relying on cash flow data to derive credit risk metrics that is useful for illiquid assets for which a time series of prices is not observable. Our methodology is designed to require a parsimonious dataset of observable inputs.