Frédéric Blanc-Brude (Director, EDHECinfra)
By promoting better standards, methods and benchmarking, development finance institutions can move the mountain that is preventing institutional capital from flowing into infrastructure.
The World Bank’s initiative to maximize finance for development (MFD) aims to “find solutions to crowd in all possible sources of finance, innovation, and expertise” in order to achieve the Sustainable Development Goals (SGDs). In the case of infrastructure investment, a significant contribution to long-term sources of private finance is expected from institutional investors such as pension plans, life insurers or sovereign wealth funds.
These investors have become increasingly interested in infrastructure investment in recent years, in search for new sources of returns, diversification, duration and inflation hedging. However, they cannot be expected to make a substantial and durable contribution to the long-term financing of infrastructure if three important changes do not take place:
- Valuation methodologies need to improve to represent financial performance more accurately.
Current valuation methodologies used in private infrastructure are wrong. 50% of the respondents of the largest survey of asset owners ever undertaken (by EDHEC on behalf of the G20) agree with this statement (1). Discounting 25 years of ‘base case’ cash flows using a single discount rate build from ad hoc risk premia assumptions, with little regard for the term structure of risk that characterizes infrastructure firms contradicts basic corporate finance textbooks. It is easy to do a lot better. Advanced private asset pricing techniques using stochastic DCF that take into account market transactions and systematic sources of risk can make significant improvements to approaches based on ‘forward-looking views’ that often amount to unrealistic guess work about the future of energy prices or the world economy over the next 25 years.
- Credit risk methodologies need to evolve to better capture default risk.
Infrastructure debt seldom defaults. Even if a large number of credit instruments is observable, a representative set of default events may not be at hand, especially if no attempts is made to control for financial structure or business model. If almost no defaults have been reported in project finance ten years after origination, is 10-year old project debt risk-free? is it AAA-rated? Of course not. The so-called “reduced form” models used by credit rating agencies work well when large samples of defaults can be observed. When this is not possible, structural models that look at the risk of crossing certain observable default thresholds (like the debt service cover ratio) perform a lot better. Recent EDHECinfra results show that such an approach accurately predicted default rates as high as 5% in European Merchant infrastructure in 2013, or a cumulative 10-year default rate close to 50% in Spanish infrastructure projects. A far cry from the usual ‘stylized facts’ from credit risk studies but also much more realistic in hindsight. Importantly however, this approach would also have predicted this level of credit risk at the time (2).
- Evaluating infrastructure managers and strategies against “absolute return” benchmarks should be abandoned and proper benchmarks capturing the risks inherent in such investments used instead.
Infrastructure is often described as an absolute return strategy. It is expected to deliver a certain level of performance defined ex ante, typically a few hundred basis points above the risk free rate or inflation. While such return targets can be useful for investors, especially if they have liabilities defined in similar terms, the performance of infrastructure products, strategies and teams should not be compared with “absolute” returns. Benchmarking a strategy against “risk-free-plus-five” implies that it is risk free and has an alpha of five percent! Instead, infrastructure investors are exposed to credit risk, interest rate risk, macro risks and certain systematic risks only found in infrastructure (e.g. the systematic differences between merchant, contracted and regulated investments). They are also likely to be exposed to risk factors found in stocks such as the size (small outperforms large) and momentum (winners tend to keep winning) effects.
Only by insisting on adequate risk-adjusted benchmarks can investors’ disillusionment with performance measurement in private infrastructure investment be counteracted. This, in turns, requires better methods, data and reporting to better understand and measure risk and performance.
The World Bank’s MFD calls for best using all sources of finance but also for innovation. Innovation in the area of performance measurement and reporting, credit risk modeling and scoring and above all benchmarking the risks private investors are expected to take when investing in infrastructure will play a significant role in maximizing private finance for development.
Furthermore, new projects — such as the ones championed by the Global Infrastructure Facility — and new products — like the new co-lending structures adopted by IFC — supported by multilateral organizations are an important channel to support and implement such innovations and create a positive demonstration effect that can spill over in the more private and opaque parts of the infrastructure financing sector.
These changes will take time and will not be easy to achieve. They require an unprecedented paradigm shift in the world of private infrastructure finance and investment. These changes are however necessary and asset owners will increasingly demand them if they are to invest in infrastructure on a large scale. Maximizing this potential today however will require leadership and vision.
(1) More than half of respondents representing USD10Tr of assets under management declared that they did not trust or were not sure if they could trust the valuations reported by infrastructure asset managers. Blanc-Brude F., Chen G. & Whittaker T. 2016. “Towards Better Infrastructure Investment Products?” – EDHEC Infrastructure Institute Publication, with the support of the Global Infrastructure Hub (a G20 initiative)
(2) See Blanc-Brude F., Hasan N., Whittaker T. 2018. “Calibrating Credit Risk Dynamics in Private Infrastructure Debt” – Journal of Fixed Income, 27(4) 54-71, for a detailed discussion based on 20 years of debt service cover ratio data.