In a new article in The Journal of Alternative Investments, three EDHEC-affiliated scholars, led by Frédéric Blanc-Brude, the director of the EDHEC Infrastructure, Singapore, look at recent improvements in the understanding of the financial performance of privately held infrastructure investments, debt or equity, with respect to benchmarking thereof. They conclude there is a lot of work yet to be done in this field.
Along with Blanc-Brude, Majad Hasan and Tim Whittaker are the authors of the new paper, “Benchmarking Infrastructure Project Finance.” Whittaker is the Singapore team’s senior research engineer, and Hasan is a PhD candidate.
Why the Demand for Benchmarks?
In considering a way forward for benchmarking, Blanc-Brude et al. classify the reasons that infrastructure investment benchmarks are in demand. They identify three. First, long-term investors have to “evaluate their infrastructure investment managers or strategies” and may also want to look ahead at the social and environmental significance of their investments. Second, regulators have to understand how infrastructure investments fit within risk based frameworks; in particular, within Solvency II, an insurance industry regulation in the European Union that came into effect on January 1, 2016. Third, policy makers in much of the world are concerned with the quantity of long-term savings as a factor in economic growth.
This understanding of the demand leads Blanc-Brude et al back to the question of supply, that is, to an understanding of the key questions that such benchmarks have to be expected to help answer.
The questions concern “risk-adjusted performance, extreme risks, and liability friendliness.” Performance breaks down into component parts: current value of a portfolio, Sharpe ratio, and correlations. Likewise the question of extreme risk can be seen in a number of ways: value at risk; conditional value at risk; maximum drawdown of a reference portfolio; measures of dependence including non-linear correlations relevant to crises. Finally, how friendly is this sort of investment, and how friendly are particular examples of it, under particular managers, to liability-driven investors? Unfortunately, these questions remain very difficult to answer today, for lack of relevant information.
Lack of Information
A big part of the problem is that there are very few stocks or bonds that precisely correspond to the performance of the underlying infrastructure projects.
The background of this article is what Blanc-Brude in particular has elsewhere called the “infrastructure investment narrative”: that is, the idea that infrastructure investing is unique in the way it combines certain features. It offers returns with a low correlation with the ups and downs of the business cycle, monopoly pricing power, attractive risk-adjusted cash flow, etc…
This narrative implies that a portfolio with some infrastructure in it does a better job of hedging against liability and inflation than one without. The problem, though, is that the narrative and the intuitively plausible implications remain just that … the compound of a story and some intuitions. Social scientists (not to mention investors, regulators, and policy makers) want something more solid and empirical.
Hence, the authors draw a roadmap designed to get us to a place where the questions can be answered. One key is to know exactly what should count as “infrastructure” for purposes of this discussion.
The definitional effort at issue should be neither essentialist (no point looking for some Platonic Form of infrastructurehood) nor Wittgensteinian (that is, we shouldn’t resign ourselves to simply treating the word as a pointer toward some family resemblances.) The definitional effort should be pragmatic – oriented by purpose. Specifically: what does infrastructure have to mean in order that we may have a chance to validate the investment “narrative” at issue?
The answer, and one that may push scholars in the right direction down this road, is that we should come to understand infrastructure on the basis of the business model and the life-cycle characteristics of the firms in the field, and we should treat such matters as sector categorizations as, well … accidental.