Cash flow forecasts made by infrastructure investors and developers are notoriously inaccurate. The base case of infrastructure projects is often found to be overoptimistic and demand or traffic risk is the primary reason why infrastructure projects experience significant problems , including default and therefore equity losses.
A well documented ‘optimism biases’ leads to the overestimation of future demand or traffic. Numerous papers and book report that demand forecasts and construction cost schedules are usually over-optimistic in both publicly and privately financed projects with this optimism bias averaging 25% and deviations from the base case sometimes reaching 200 or 300% .
The standard approach taken by valuers and investors to predict future dividends consists of mimicking the cash flow waterfall in a static manner: from future revenues to future operating and maintenance costs, given any reserve accounts or senior debt covenant in force (e.g., dividend lockup, cash sweep, etc.), the remaining free cash flow can be used to repay future outstanding senior debt and, when possible, pay back shareholder loans or make distributions to shareholders.
This approach underpins the initial business case upon which investment decisions in unlisted infrastructure are taken.
In the best case, such models represent the best information available at the time and provide investors and valuers with an approximation of what cash flows can be expected, conditional on the assumptions made for each model input. This base case however is typically not a statistical model and thus may not represent the expected value of future cash flows.
Moreover, beyond the initial investment date, updating such models presents numerous challenges:
In short, the standard static waterfall approach requires a lot of inputs and is fundamentally ad hoc: it is not a model of the expected value of cash flows in the statistical sense.