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Valuing infrastructure projects

From time to time an infrastructure project or its [potential future] shareholders may need to know the value of the project’s equity. Generally this will be for the purposes of a sale or purchase, or possibly for a listing.

It is most common to use a discounted cash flow methodology when conducting such a valuation. Most of the time this is fairly easy, as the project is likely to have a project model which produces distributions to shareholders at the bottom of the cash flow waterfall.

However, there are a few considerations to take into account when conducting a valuation:

Starting balances

Unless you are conducting the valuation as at financial close, the project will have built up certain actual balances during the construction period and any operations period that has elapsed. These will include the likes of cash in bank, debtors, creditors and plant and equipment. It is best to source these from the most recent set of financial accounts or management accounts available, as these will be the most accurate figures available. These balances will need to be incorporated into the project model such that in due course they feed through to the cash flow waterfall accurately. For example, a debtor balance will, via the model’s working capital assumptions, feed through into the cash flow waterfall and ultimately to distributions.

Starting balances, even cash balances, should not be included as stand-alone sums in the valuation. This is because the timing of distributions creates a material difference to the valuation, and generally any balance lacks this information unless it feeds through the waterfall. For example, a cash balance may result from a debt covenant lock up, which may only be cured in several months’ time.

More information about incorporating balances into the project model is available here: Operationalising Project Models.

Input assumptions

There are three main sources of assumptions available to the valuer:

  • The Project Documents and the Finance Documents. Good examples of such assumptions are base tariffs prior to inflation and interest margins. These assumptions will, all things being equal, hold for the life of the project, and consequently the valuer should leave them unchanged in the base case project model.

 

  • Expert information. Certain technical and macroeconomic assumptions may have been set by experts at the beginning of the project life or subsequently. An example of such would be future fx or inflation assumptions. These are best sourced from a (reputable and justifiable) expert source. Some technical assumptions may not change considerably over the life of the project, and may therefore be left alone without significantly effecting the valuation. An example of this might be power plant capacity.

Note that some project models may have a lenders’ base case and an equity base case. Typically it is most appropriate to use the equity base case (eg P50 energy yield assumptions) since it is the distributions which are being valued.

 

  • Actual experience. The performance of the project may differ to the original expected performance, in which case, in the absence of a reason to the contrary, the assumptions should be updated to reflect the most recent experience. Experience should be of reasonable duration – 12 months might be a good starting point to incorporate a reasonable sample size and any seasonality effects. Non-contracted opex inputs are a good example here, as is recent technical performance. Obviously when updating assumptions to reflect recent performance, one needs to apply a reasonability filter. Updating opex or technical assumptions to reflect an abnormally good or bad year will create bias in the valuation. One also needs to ensure that the experience is adjusted to account for the model’s inflation from the base date of the assumptions to the present.

A critical valuation assumption which deserves particular mention is the risk discount rate used to discount the distributions back to the valuation date. There are different means of arriving at, and influences upon, the appropriate discount rate for the valuation, and often some judgement will be required. These may include the following:

  • If the valuation is part of a sale negotiation, the risk discount rate may have been negotiated in advance, with the monetary valuation flowing from the risk discount rate as a result;
  • There may be recent sales which provide discount rate market benchmarks;
  • The project may have been structured so as to arrive at a reasonable risk discount rate for the risk profile of the project, as at the date of development;
  • The project may have experienced certain milestones and events which increase or decrease risk. An obvious one of these is the project completing construction and reaching Commercial Operation Date successfully. Another is the acquisition of an operating track record of a statistically significant sample length;
  • For completeness, there are theoretical models for determining an appropriate risk discount rate using the market risk free rate and the project’s beta and leverage – the Capital Asset Pricing Model (CAPM). Such a model is perhaps less relevant for an infrastructure project than for a normal operating company.

If a particular assumption has considerable uncertainty and has a significant effect on the distributions of the project – eg if plant output is very uncertain in the future for some reason – then it may make sense to model that assumption into the project’s future explicitly, rather than by modifying the risk discount rate to reflect the additional uncertainty. This allows greater understanding of the change in the valuation resulting from poor performance relating to the assumption in question. A good example of an assumption like this may be the traffic experience in a toll road project.

 

Valuation date

The date of the valuation may have considerable impact upon the valuation. In particular, moving the valuation date later by a month will have the following effect:

  • The valuation will increase by approximately 1/12th of the discount rate; and
  • The valuation will decrease by any distribution that was in the valuation period before the date change, but is no longer in the date change.

Consequently, if distributions are semi-annual, the valuation can move as much as 41% of the discount rate from a 5-month change in valuation date.

 

Termination amount

If one simply discounts the distributions in the project model, it is possible to miss the residual value of the project at the end of the project term (usually the end of the offtake contract term). This may be completely appropriate, for example in the case of a Build Own Operate Transfer project. However, in other instances it may not be appropriate at all, such as in the case where it may be feasible to enter into another subsequent offtake contract, or dispose of some of the project’s assets for a sum. Conversely, a rehabilitation cost may be applicable at the end of the term. Such an amount may be modeled explicitly by discounting the sales price or rehabilitation cost, or by extending the term of the modeled operations period using a new set of (possibly conservative) assumptions.

 

Sensitivities

The valuer may be asked to provide a single valuation figure, but it is nonetheless good practice to provide sensitivities to those assumptions which either:

  • Have considerable uncertainty;
  • To which the valuation outcome is very sensitive; or
  • Both.

The purpose of the sensitivities is to help the client in any final negotiations or decisions around the final price or valuation. If the final report is a public document, or shared with the other side of the negotiating table, these sensitivities could be removed from the final public version of the valuation report.

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Infrastructure Project Lifecycle

As a project moves through the project lifecycle, it increases in value and new funders are required to invest at lower expected returns because:

  • The risk profile decreases at each stage indicated below;
  • Greater amounts of funding are required at each stage; and
  • Future cash flows are closer to the present, and are consequently discounted for less time.

Note that valuation of infrastructure investments are typically done on a discounted cash flow basis, with risk adjustment either on an explicit basis, such as probability-weighting of cash flows, or implicit in the discount rate.

Project development

A project developer will typically spend considerable time and a up to a few million dollars to develop a project. This entails identifying, arranging, negotiating and obtaining the following (non-exhaustive list):

  • Land usage;
  • Offtake contracts;
  • Regulatory approvals;
  • Environmental Impact Assessments (“EIAs”);
  • Engineering, Procurement and Construction (“EPC”) contracts;
  • Operating contracts; and
  • Equity and debt financing.

Often the developer will prepare and submit a tender proposal which may require bid bonds.

This work is done at risk. If a project fails to win the relevant tender, or cannot successfully obtain all of the project requirements, the project will fail and the developer will lose what funds have been put in. Because of the relatively high probability of failure at this stage in the process, project development is typically funded by equity and external investors could expect to obtain ‘zero-or-hero’ risk/return profiles with extremely high returns on funds used to develop projects.

If a tender has been awarded, the project undergoes a step-change in value, and equity becomes considerably more expensive / projected equity returns for new entrants into the project shareholding are lower. This recognises that the true value of any infrastructure project is in the payment stream which it can generate, which flows from the offtake or concession contracts, and not only the physical assets used to generate that payment stream.

Financing

Financing is a late stage in the development process. Due to the stable and predictable cash flows in infrastructure projects, projects are typically highly geared. Depending upon sector, debt:equity ratios of between 70:30 – 80:20 (typical of most power transactions) are not uncommon, while even 95:5 is not impossible.

The financing process typically requires considerable due diligence on the behalf of the lenders, which will usually be paid for by the project and guaranteed by the developer or project sponsors.

After signature of the finance contracts, it typically takes a few days or weeks until the conditions precedent to the finance contract becoming unconditional are fulfilled, at which stage the project reaches financial close and the project may draw down on the debt facilities. At the same time, the various project contracts, most importantly offtake, EPC and O&M, will be signed and become unconditional.

Project developers usually collect a development fee which may range between 1% – 10% at financial close depending upon the size of the project and the other project counterparties’ leniency. Lenders may require that this fee stays in the project until construction completion, and it is often ploughed back into the project as an equity carry.

Again, the project gains value when it reached financial close.

EPC

The project now enters the engineering, procurement and construction phase, which may be several months up to a few years in length. Typically little or no revenues are earned during construction. Construction ends on successful commissioning, and there is often a warranty or defects liability period (depending upon the asset type) for a period after completion.

The construction phase of the project is considered to be risky, as at this stage significant funds have been advanced by investors, but the ability of the infrastructure asset to generate revenues is as-yet unproven. In addition, any problems during construction which are left unmitigated will impact upon the whole of the revenue-generating operations period.

Operations

The project enters the operations phase, usually operated by a contractually-remote third party who will be financially liable for successful operations. Once the project has been demonstrated to perform successfully, the perceived risk profile of the project drops yet again, and the price of equity increases further. In addition, the project may refinance in order to gear up further (particularly if revenues are greater than originally expected) and / or to decrease debt margins.

Considerable consolidation has occurred during the operations phases of projects. For example, much of the renewable energy industry in Europe has been consolidated into relatively few utility-scale investors who receive a (relatively) low but stable return from the asset, which is boosted by undertaking the operations and maintenance of the infrastructure asset themselves.

Transfer

If the project is predicated upon a concession or government / parastatal offtake contract, the infrastructure asset may be transferred back to the state or offtaker at the end of the concession period. This is referred to as a ‘BOOT’ scheme, standing for ‘Build, Own, Operate, Transfer’. BOO and BOT schemes are also common.

At the end of the asset’s life, the project may incur decommissioning costs.

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Is volatility in a renewable energy yield assessment good or bad for lenders?

BAD! Or, at least, that’s the general view. As always, however, there isn’t a simple answer.

I once made a casual statement that volatility on a renewable energy yield assessment for a debt transaction I was working on was beneficial from a creditworthiness perspective. My client at the time (the lender) was adamantly opposed to the statement. Since it’s generally the case that greater volatility is bad for a transaction, (and the client is always correct!), let’s look at why it’s bad.

Project finance is, inter alia, lending a principal sum against a set of predictable cash flows. Greater volatility of yield implies less predictability and therefore greater risk of being unable to meet payments when they fall due. This means higher probability of default, higher pricing, less debt-bearing capacity and so on. So volatility is generally bad for a transaction, and perhaps especially so for equity, since debt will only ever lend up to a level of risk which it is comfortable with (one assumes!).

On the other hand, there’s the concept of Upside Risk (https://en.wikipedia.org/wiki/Upside_risk). This is the possibility of a gain in the value of an investment. All other things being equal, the greater the (statistical) downside risk in an investment, the greater the (statistical) upside risk. Upside risk is also applicable to a yield assessment, since it is, after all, a statistical assessment.

Moreover, lenders will usually lend up to a maximum amount limited by the P90 yield assessment. (and the debt:equity ratio, debt service cover ratio levels and other metrics imposed by their credit committees). Assuming the yield assessment is reasonable in determining the P50 yield and the standard deviation of the yield, and that a Normal distribution is a reasonable approximation of the actual random distribution of the yield, it’s helpful to examine the downside and upside scenarios in terms of conditional probabilities (https://en.wikipedia.org/wiki/Conditional_probability, for those of you who like numbers!):

  • Downside scenario: All other things being equal, the expected yield given the actual yield is less than the P90 level will be lower for a plant with a higher-volatility energy yield than for the same plant with a lower-volatility energy yield.

Obviously when considering such a scenario, lenders would like a lower volatility energy yield assessment, so as to limit possible downside scenarios to a smaller loss (or failure to repay).

 

  • Upside scenario: All other things being equal, the expected yield given the actual yield is greater than the P90 level will be higher for a plant with a higher-volatility energy yield than for the same plant with a lower-volatility energy yield.

 

In this scenario, higher-volatility implies greater CFADS.

Consequently, it is reasonable to balance the risks and benefits of the two scenarios. Under the downside scenario, the risk is that the yield may be insufficient to ensure debt service, particularly if the cover ratios under the P90 base case were tight to begin with. It is worth noting that (assuming the correctness of the yield assessment) this risk has less than a 10% probability of arising (because we’re using a P90, the base case cover ratios being > 1.0x and because Normal distributions with the standard deviations typical of renewable energy projects are relatively long-tailed).

The upside scenario, on the other hand, encompasses 90% of predicted years’ energy outcomes, assuming we’re using a 1-year P90. This in turn means that the CFADS will be larger than under the P90 base case in most years, and, simply, cash can be used to mitigate many risks. The nature of those risks is, of course, very much dependent on how well they are mitigated through the contractual protections built into the project documents. If all risks other than yield are 100% contracted away to the project’s reliable and creditworthy counterparties, then the protection offered by additional cash is worth less than if only a portion of that risk is dealt with. Similarly, if DSCRs are very healthy using the P90 cash flows, the marginal benefit of yet more cash is smaller.

The question then becomes one of whether the benefit of additional cash in (probably) nine out of ten years to mitigate risks which may arise in those years, is greater than the risk of a greater expected underperformance in the one (probably!) year in ten when yield is lower than the P90 level. This is a slightly more difficult evaluation than an all-encompassing perspective that volatility is bad. However, it also offers benefits which may be proposed to a credit committee, for those transactors with a higher-volatility project!

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Renewable energy yield analysis

The energy yield assessment is a fundamental requirement for any new wind or solar project, with both developers and lenders spending considerable time with their respective advisers to understand the underlying wind or solar regime. The remainder of this article speaks predominantly to wind energy yield assessment, but the same principles can be applied to solar projects.

Before we start, a short discussion around P50 and P90: The P50 energy yield estimate is the estimate of the energy yield which the energy yield modeller estimates will be exceeded with a 50% probability. Similarly, the P90 energy yield estimate is the estimate of the energy yield which the energy yield modeller estimates will be exceeded with a 90% probability. Consequently, the P90 estimate is lower than the P50 estimate. Although P-levels are usually quoted as annualised figures, the application periods can differ: Hence you may see reference to a 1-year P90 or a 10-year P90. This is simply the estimate of the amount of energy which the modeller estimates will be exceeded in a 1-year period or a 10-year period (multiplied by 10, since it is an annualised figure). They differ because the P90 is a function of the median energy yield estimate and the standard deviation of the energy yield estimate. In the case of the 10-year P90, the uncertainty associated with the estimate is spread over 10 years, so that a bad year can be offset by a good year within the period; or statistically speaking, a larger sample size reduces the variance associated with the estimate. As an aside, because the P50 is simply the median of the probability distribution and takes no account of variance, there would be no difference between the 1-year and 10-year P50 estimates. A P90 estimate is typically used for the banker’s base case model, and a P50 for the equity case. Project financiers should consider whether the P90 estimate is a 1-year of 10-year figure in determining their cover ratios – particularly if the numbers are tight.

The process of estimating the energy yield for a wind farm involves the following steps:

  1. Implementation of an on-site wind data measurement campaign
  2. Estimation of the average long-term wind speed at the site
  3. Estimation of the energy yield (which is driven by the characteristics of the particular wind turbine selected for a wind farm)
  4. Uncertainty analysis (further consideration of the uncertainties associated with the particular yield estimation, e.g. short data record representing a long-term wind regime, accuracy of measurement equipment, etc.)

Given the significant number of wind projects implemented over the last 30 years globally, the process of estimating the energy yield for a wind farm is nowadays well understood, with established internationally accepted norms and standards. The above four steps are described in more detail below.

 

Measurement Campaign

Wind projects require on-site measurement campaigns in order generate an energy yield for a potential wind farm. Data is collected using a wind mast and anemometers. Ideally the mast should be at turbine hub height to eliminate uncertainty associated with wind shear (vertical movement of air) and uncertainty associated with different wind speeds at different heights.

Typically one or more wind masts are placed within circa two kilometres of the furthest proposed turbine locations in the future wind farm. Each mast will have a number of cup anemometers (a device for measuring wind speed) at intervals up the mast up to the hub height of the proposed turbines, as well as wind vanes for measuring wind direction, thermometers and possibly barometers for measuring air pressure.

The period over which data should be collected should be greater than one year in order to assess the effects of seasonality on the wind resource. Any additional period in excess of one year is beneficial in that it further reduces the standard deviation of the data sample and allows some or better identification of long-term trends. For this reason, nearby meteorological station data is often correlated with the data derived from the on-site mast and, should the correlation be sufficiently high, used to establish whether wind speeds experienced in the 12-month measurement period are above or below the long-term average.

The topography of the site, and in particular the extent of rough terrain and surfaces such as mountainous terrain, trees, tall buildings and other wind turbines effect the flow of air across the site. In a relatively low-complexity (smooth, few trees or other such features) site, industry experts recommend that measurement masts are placed within one to two kilometers of the turbines.

Data is collected at short intervals, such as every 10 minutes. Before further analysis, the data is usually checked and cleaned for any anomalies (e.g. periods where equipment has failed).

 

Estimation of Long-Term Wind Speed

The collected data is used to fit a Weibull probability distribution function, which represents the statistical distribution of the wind speed. A normal distribution is sometimes used as a tractable approximation to the Weibull function.

If there is a nearby meteorological station with wind measurement data which is sufficiently highly correlated with the on-site data, its data may be used to determine long-term trends in the on-site wind data. For example, it may be possible to determine whether the measured year is abnormally windy or still. If such long-term information is not available (which is the case in most instances), then this is addressed in the uncertainty analysis (see below), i.e. the standard deviation of the energy yield estimate is increased, resulting in a lower P90 estimate.

Once the long-term average wind speed for a mast location has been derived, the wind speed is in turn estimated for each future turbine location, which will then enable an estimation of the overall energy yield for the wind farm, discussed further below.

 

Energy Yield Estimation

For each turbine location, the wind distribution is transformed using either a theoretical or empirical power curve associated with the proposed wind turbine, thereby converting the wind speed distribution into an energy output distribution. The power curve is provided by the turbine manufacturer, and it is noteworthy that the turbine manufacturer will typically provide a power output guarantee supported by performance damages, with the result that the power curves are unlikely to be unduly optimistic. An example of a power curve is displayed below:

(Source: www.wind-power-program.com)

In addition to fitting the probability distribution function for wind speed, the data is used to determine the extent of turbulence (very short duration gusting), changes in wind direction and wind shear (vertical air movement), all of which are incorporated into the yield estimation model for the power output.

While a measurement mast as described may accurately determine the output of a wind turbine on the same spot, wind speeds and other relevant meteorological conditions will change as turbines are sited further away from the measurement location. Consequently, the wind yield modeller will typically build a computational fluid dynamics model which takes account of the topography of the proposed site, including the wake effect of the turbines upon each other. The layout of the wind farm, or micro-siting, is determined by means of optimising the positioning of the turbines with respect to energy yield.

The energy yield modeller deals with additional influences upon the plant and uncertainty in the modelling variables by modifying the expected energy yield. An example of this taken from a wind energy  yield report is shown below:

In this example, the modeller has decreased the expected energy yield, which is the central estimate, or the P50 energy yield. Going back to our discussion about probability distributions, the figure of 134.4 GWh/year is the modeller’s best estimate of the yield, and is therefore the median in the probability distribution.

To obtain the energy yield with a higher certainty (e.g. the P90 yield, or the yield that can be expected to be exceeded 90% of time) an uncertainty analysis is required which is discussed further below. Naturally, the P90 yield will be lower than the P50 yield. Regarding the losses calculated above, these particular loss factors attributed to the plant result in a certain loss (of 21.4GWh/annum in our example) but no change in volatility, and consequently reduce the P50 yield estimate and the P90 yield estimate by the same amount.

 

Uncertainty Analysis

There are a number of sources of uncertainty which feed into the standard deviation of the wind probability distribution function, thereby into the standard deviation of the energy yield probability distribution function, and which therefore decrease the P90 yield estimate, but not the P50 yield estimate. These sources of uncertainty are broadly split into two types, being:

  • The underlying “true” volatility of the wind resource (it could actually blow more this year than next or vice versa); and
  • The uncertainty associated with the calculations made along the way. Included here is the uncertainty introduced by using a short data record (e.g. 12 months’ on site data) , accuracy of the measurement equipment, etc.

Using this final power output probability distribution function, the energy modeller is able to determine confidence limits for the energy output of the plant. In particular:

  • A P50 estimate is the median yield which is typically used for determining the equity case, and
  • A P90 case, being the power output likely to be exceeded with a probability of 90%, is typically used as the power output assumption in the lenders’ base case.

Various P-values are used for debt structuring purposes, with the EU market commonly using a 10-year P90 yield, as alluded to above. The type of financing structure may also determine which P-value is used, e.g. higher gearing (80%+ debt) may need to be structured using a more conservative P-value. In South Africa, some projects have been structured using 1-year, and others 10-year P90 values. Ultimately, each project should be reviewed independently, by reviewing the underlying energy yield assessment (unique for each site) and conducting sensitivity analyses to assess how uncertainty in the energy yield impacts the expected financial performance of a project.

A little more on regional standards: The EU commonly uses a 10-year P90 with a minimum 1.30x DSCR, while the US market commonly uses a P99 with a minimum 1.0x DSCR. Please don’t take these as gospel, though. Rather assess your project and determine the suitability of any given regime (or use more than one!)

Comparing wind with solar projects, the variability in a wind energy resource assessment is typically higher than that in PV, and significantly higher than for CSP (concentrated solar thermal power). For example, the P50 yield typically exceeds the 1-year P90 yield in wind transactions by between 15% and 25% of the P90 yield. A Moody’s research paper for 34 wind farms in the USA provided an average P50/1-year P90 exceedence of 17.6%. This compares to a commensurate difference in PV of circa 8% – 10% (also using 1-year P90).

Breaking it down further, the size of the standard deviation of the energy yield estimate is a function of:

1)  The estimated volatility of the wind regime; and

2) The uncertainty relating the model of the plant. I.e. How that wind regime translates into energy output.

The impact of the volatility of the wind regime can have a significantly different impact for different locations and different turbine choices.  Consider the turbine power output curve:

In particular, for a given volatility of wind speed, a wind regime in which the median wind speed is close to the wind speed required to top out the power curve (14 m/s in the illustrated graph) will have a much power output volatility  than that of a wind regime where the median wind speed is in the middle of the curve (circa 9 m/s). This is simply a function of the relative steepness of the curve at each of these two points – the steeper the curve, the greater the change in energy yield per m/s change in wind speed.

Consequently, although it is obvious that faster average wind speeds are better for a wind farm, there’s also a beneficial second-order effect in that they will probably also reduce the volatility of the energy yield.

It is important to keep in mind that the difference between the P90 and the P50 (for our discussion defined as “yield volatility”, which is not a formal industry term) does not influence the probability that the lenders’ base case will be achieved or exceeded – being, of course, 90%, assuming the competence of the modeller.

 

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Guarantees from counterparties

Different counterparties to the project may be required to provide guarantees that their performance will meet a certain minimum standard. For example, the Engineering, Procurement and Construction contractor may be required to guarantee the date of completion, and the minimum performance levels of the plant. Similarly, the operator may be required to guarantee a certain minimum availability for the plant, or the fuel supplier the calorific value of the fuel.

In assessing guarantees , whether as project or lender, it’s helpful to examine three specific characteristics of the guarantees, being effectiveness, importance and reliance:

Effectiveness:

Is the guarantee effective in covering lost revenues? To do this, compare the rate of accrual of the guarantees per day of delay or per percentage point downside performance with the resulting loss of revenues.

For example, if the delay liquidated damages (LDs) accrue at a rate of USD 0.5m / day, and the project would have generated USD 5.0m on that day had it been operating, then the rate of accrual for the delay LDs is not effective in compensating for the lost revenues.

Similarly, if the project is completed and handed over to the owner underperforming relative to its guaranteed performance level by 2%, the NPV of free cash flows after opex at the guaranteed performance level is USD 1.0 billion (using the WACC as the discount rate, perhaps), and the rate of accrual of performance LDs is USD 25m / percentage point downside performance, then, per percentage point downside performance, the project will lose USD 20m NPV over its lifetime, but will gain USD 25m immediately, and the rate of accrual of the LDs will therefore be effective in replacing the forfeited revenue stream.

To establish effectiveness, one normally needs to refer to the schedules of the construction, operations or supply contract.

In some instances it is not appropriate to use lost revenue as a comparator –  for example where liquidated damages are payable for failure to deliver under a small supply contract. More on this near the bottom of this article.

Importance:

Is the cap on liability sufficiently high so as to make the guarantees meaningful?

Simply put, if the cap on delay LDs means that the delay LDs run out after one week, then the delay LDs are not meaningful. Similarly, if the performance guarantee cap is low such that only very little downside performance revenue loss is covered by the contractor, then the performance LDs are not meaningful. Determining a level of meaningful guarantees is best done with the assistance of a technical advisor and the project model, which, in conjunction can tell the owner or lender what sort of underperformance is possible or likely, and the impact thereof.

To establish importance, look for the limitation of liability clause of the construction, operations or supply contract.

Reliance:

Finally, assuming the rate of accrual and the cap on guarantees are suitable (or sufficient), we should ask ourselves whether we are able to place reliance on the guarantor or security. If an on-demand bank guarantee has been provided as security for the guarantees, then we can most likely place significant reliance on the guarantees, at least until the amount of the bond has been exceeded. Thereafter, we may need to look to the credit quality of the contractor, or, if a Parent Company Guarantee has been provided, to the credit quality of the parent. There is a significant difference between an on-demand guarantee and a PCG, even from a very creditworthy parent. In the former case, the project (and vicariously, the lenders) may simply deliver the bank guarantee to the guarantor and demand the funds, whereas in the second instance, litigation or at least negotiation may be required.

Other considerations:

Note that a rate of accrual or a cap sufficient to transfer all risk of delay or underperformance to the contractor may not be available. In such instances, it is desirable, if only as second prize, to ensure that the guarantees are sufficiently robust so as to significantly incentivise the contractor to meet his performance guarantees.

Situations like this arise for contracts which have a small value relative to project revenues, but which would prevent the operation of the project if the services provided are absent. If the services under such a contract can be replicated, the guarantees may be sized to cover the difference in price between the original contract and the (possibly temporary) replacement. Example of such a contract may be a water supply contract, or a limestone supply contract for a coal power station.

However, projects may have vital contracts with no available replacement and a small contract value, for which guarantees provide very little risk mitigation, other than alignment of incentives. An example of such a contract is a pipeline/transport agreement for a gas powered power plant. In such instances, incentivisation may be all that is possible.

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Political Risk

One of the key risk areas considered by the banks when lending to an infrastructure project is country risk. This has a number of different sub categories, including:

  • Political violence, such as revolution, insurrection, civil unrest, terrorism or war;
  • Governmental expropriation or confiscation of assets;
  • Governmental frustration or repudiation of contracts;
  • Wrongful calling of letters of credit or similar on-demand guarantees;
  • Inconvertibility of foreign currency or the inability to repatriate funds.

Of these risks, currency convertibility and repatriation is perhaps the most prevalent, as most infrastructure capex is paid for in hard currency, while the revenue stream of the project, or if not the project, at least the offtaker, is usually local currency. Consequently care needs to be taken to ensure that the project or offtaker is able to source the currency which the loan is denominated in. Unfortunately fx swaps are typically inadequate to the task of immunising a project against currency convertibility and repatriation risks for a number of reasons, being:

  • Often local currency rate curves, and therefore forward fx curves, do not usually go out to the durations of the debt. If they do, they may be illiquid and expensive;
  • Fx swaps can result in very significant credit exposure, which may nullify the benefit of having done the swap in the first place; and
  • It may be the state which prevents repatriation.

There are a number of different ways to mitigate this risk, some of which may be available only during the structuring stage of the transaction, and some of which can be bolted on afterwards.

 

Political Risk Insurance

It is possible to purchase Political Risk Insurance (“PRI”) to cover one or more of the heads of cover indicated in the list above. Premiums can be paid either up front or periodically (usually annually in advance) and may be payable by the project or the investor. Premiums range in size as well as value for money, as different providers will have different mandates to provide such cover.

 

Commercial PRI

Commercial PRI is available from any number of large commercial insurers and reinsurers, such as Lloyds.

Pricing for commercial PRI is volatile, depending upon current perceptions of the liklihood of the risk being insured against that actually occurring in the specific jurisdiction, as well as market appetite for such risk.

 

MIGA

The Multilateral Investment Guarantee Agency (“MIGA”) is an international financial institution which offers political risk insurance guarantees to help investors protect foreign direct investments made in developing countries against political risk. MIGA is a member of the World Bank Group and is headquartered in Washington, D.C. It was established in 1988 to serve as an investment insurance facility of the World Bank to help investors overcome political and other non-commercial risks and invest confidently in developing countries. Since its inception, MIGA has provided more than USD24 billion in cover for 700 projects in over 100 developing countries. MIGA currently has an outstanding guarantees portfolio of USD 9.2 billion (2012).

MIGA offers partial credit guarantees (“PCGs”) to cover the credit risk of a sovereign government or parastatal entity, and partial risk guarantees (“PRGs”) to private projects to cover a government’s failure to meet its contractual obligations. Heads of terms covered are:

  • Civil unrest, terrorism or war;
  • Governmental expropriation or confiscation of assets;
  • Inconvertibility of foreign currency or the inability to repatriate funds;
  • Non-honouring of sovereign financial obligations;
  • Breach of contract

The final head of cover above covers situations where the government or parastatal entity breaches its contractual obligations, rather than the Project breaching its obligations. Consequently if it is to be used, care needs to be taken during the structuring phase to ensure that the risks being guarded against are included in the contractual arrangements with the government or parastatal (and not only the project).

Interestingly, MIGA appears in the past to have priced its cover as a function of the heads of cover utilised, rather than risk of the cover actually being called. Consequently including an obligation from the sovereign to compensate the project in the event of the other political risks occurring or to not perpetrate them means that the project can purchase the breach of contract cover alone, with significantly lower premiums than if it had purchased the full PRI suite.

 

Export Credit Agencies

Export Credit Agencies (“ECAs”) are quasi-governmental institutions mandated to support and encourage the export of their domicile countries’ goods and services. This support can take the form of credits (financial support) or credit insurance and guarantees (pure cover) or both, depending on the mandate the ECA has been given by its government. ECAs can also offer credit or cover on their own account, similar to normal banking activities. Some agencies are government-sponsored, others private, and others a bit of both.

ECAs currently finance or underwrite about USD 400 billion of business activity abroad – about USD 55 billion of which goes towards project finance in developing countries – and provide USD 14 billion of insurance for new foreign direct investment, dwarfing all other official sources combined (such as the World Bank and Regional Development Banks, bilateral and multilateral aid, etc.). As a result of the claims against developing countries that have resulted from ECA transactions, ECAs hold over 25% of these developing countries’ USD 2.2 trillion debt. (Numbers courtesy of wikipedia – suffice it to say, ECAs are a significant contributor to infrastructure finance.)

ECAs provide both commercial cover, which covers against all risks, and PRI, provided that a qualifying percentage of the goods and services employed in the project (usually the construction) are sourced from the ECA’s home country (“Local Content”). In the case of loans covered by ECAs, 85% of debt is typically the maximum commercial cover provided, although PRI is usually available for the remainder. ECAs prefer investors to be aligned in terms of commercial risks.

ECAs charge a premium for cover, which may be up front or recurring. However, unlike commercial PRI, their mandate is not to maximise profits, but rather exports. Consequently using ECA cover may decrease the aggregate cost of debt, inclusive of the premium. Correspondingly, margins for ECA-covered debt are usually very low, as a (good) ECA will typically have a similar credit rating or quality to its home country. This reduction in margin is not effected through a reduction in the probability of default, but rather a reduction in loss given default of the loan.

 

Investment treaties

Infrastructure transactions often have geographically-dispersed equity holding structures in order to take advantage of tax- and investment treaties between the host country and the countries in which the holding companies are domiciled in. Mauritius is a good example of this, having a large number of tax treaties with various African countries. Similarly, Kenyan projects are often held out of the United Kingdom, which has the lowest withholding tax on dividends of all its investment treaty partners.

An added benefit for investors is that investment treaties provide foreign investors with potential relief when they have experienced business difficulties in a host country arising from the acts or omissions of an arm of the host state such as the executive, the courts, the legislature, or administrative or regulatory officials. An award under such arbitration can be enforced by attaching the non strategic assets of the host country in the investor country.

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Project finance hedges

Project Finance hedges are typically vanilla interest rate- or fx swaps. Contractual protections are usually very similar to those of senior debt, in particular:

  • Ranking in the cash flow waterfalls; and
  • Sharing in security.

This has the consequence that between hedges and debt, Probability of Default (“PD”) is very similar, as is Loss Given Default (“LGD”).  However, the Exposure At Default (“EAD”) of a hedge has significantly different characteristics to that of debt. These similarities and differences to debt lead to synergies in determining the credit risk and consequent credit margin of a hedge, while still requiring some alternate means of quantifying such risk.

The remainder of this post will use a vanilla interest rate swap (“IRS”) as an example, as it is the most significant hedging instrument typical of project finance power transactions. However, similar principles may be applied to different derivative instruments.

Who pays who?

Under an interest rate hedge, the Project will pay the hedge provider a floating interest rate based upon a notional principal loan schedule. In return, it will receive a floating interest rate from the hedge provider based upon the same notional principal outstanding.

The notional principal schedule is usually a percentage of the debt principal. For example, it may be 80% of debt in every period, or a declining percentage, such as 100% of debt in construction and 75% for the next 10 years.

Calculating the fixed rate

The mid swap rate is calculated by setting the NPV of future interest rate payments of the fixed leg equal to that of the floating leg, where the floating leg assumes that the floating interest rate will unfold as per the forward interest rate curve (eg LIBOR or USD-SWAP). The discount rates are taken directly from the forward interest rate curve. A credit spread is then added to the mid rate so calculated to arrive at the fixed rate offered to the Project.

Consequently the day-1 PnL of the swap is equal to the NPV of the credit spread * notional, using the forward interest rate curve to discount back each payment. This is referred to as the (initial) mark-to-market and incidentally is also the initial credit exposure under the hedge.

Therefore: MtM =

∑t(Principal(t) * Fixed interest rate * (1 + i(t))^-t) – ∑t(Principal(t) * it* (1 + i(t))^-t)

where:

  • t is the number of years in the future at time t
  • Principal(t) is the notional principal outstanding at time t
  • i(t) is the forward interest rate at time t

Legal Framework and CSA

Most hedges are governed by an ISDA Master Agreement, developed by the International Swaps and Derivatives Association. This sets standards, simplifies the specific documentation required for a trade and, importantly, allows netting between different trades.

Any hedge which a non-recourse project enters into will not have a CSA – that is, neither the Project nor the Project’s counterparty will post cash collateral. This is simply because margining requirements may become sufficiently onerous as to sink the Project. For example, if the Project is paying fixed and receiving floating, and the prevailing (floating) interest rate drops significantly, then the mark to market of the swap will decrease significantly, with the result that it will be owing from the Project to the hedge counterparty. If the Project were required to post collateral, the cash flow requirement in this scenario might be more than the cash the Project has at hand, thereby rendering the Project insolvent.

Cash flow waterfall ranking pre enforcement

Pre enforcement, the interest rate swap payments will typically rank alongside the senior debt’s interest, and therefore prior to senior principal repayments and certainly prior to mezzanine debt or equity.

However, if the swap is broken and at the same time the senior lenders choose not to enforce against the Project, there may be a hedging termination amount owing to the hedge provider. The exact ranking position in the waterfall differs between transactions, but will typically rank alongside or post senior principal, but again usually prior to mezzanine debt and equity. Note that it may therefore rank post reserve account funding.

The cash flow waterfall ranking of the hedge payments inform the PD of the hedge. As the same project underlies both debt and hedge, and the payment ranking of both is very similar, the PD of both debt and hedge are very similar to each other.

Cash flow waterfall ranking post enforcement

If the Project is put into enforcement, there may again be a hedging termination amount owing to the hedge provider. This will usually rank pari passu with senior debt in the order of payments.

In addition, hedging termination amounts post enforcement will usually share pari passu in the senior security.

This speaks to the LGD of the hedge: It is consequently very similar to that of the senior debt.

Exposure

Unlike the credit exposure under the debt, which is determinable at inception with considerable certainty, the exposure under the hedge is volatile and impossible to predict with certainty. However, it does follows a probability distribution function.

This is because the mark-to-market of the swap changes from inception as time passes, for the following three reasons:

  1. As time passes, payments occur under the swap, and the NPV of the outstanding payments is reduced by the amount already paid (predictable);
  2. The time which the outstanding payments under the swap are discounted by decreases (predictable); and, most importantly
  3. The forward interest rate curve moves upwards or downwards and changes shape (unpredictable)

Exposure – Market risk

The mark-to-market of the swap can change from owing to the hedge provider to owing to the Project if the rate curve rises in aggregate. (The NPV of the fixed rate leg received by the hedge provider will reduce, because of the NPV effect of an increase in discount rates, while the NPV of the floating leg being paid by the hedge provider will remain roughly static, as the interest payable increases, but is offset by the NPV effect.)

Note, however, that the hedge provider would typically hedge his own position by entering into an equal-and-opposite position in the market to the extent that it is desirable to do so.

Exposure – Credit risk

As the mark-to-market moves increasingly in the hedge provider’s favour (as the interest rate curve decreases) the credit risk increases equally. This can be seen by considering the situation where the hedge provider has hedged out his position in turn. If the mark-to-market of the Project-hedge provider hedge is in the hedge provider’s favour, then the mark-to-market of the equal-and-opposite hedge is owing by the hedge provider in a very similar, but slightly lesser, amount.

If the Project then defaults, the hedge provider will still owe its own counterparties under the equal-and-opposite hedge and will experience a net loss.

Consequently, all other things being equal, the lower the interest rate drops the greater the credit risk on the hedge.

Potential Future Exposure (“PFE”)

The PFE of an interest rate swap is calculated by means of Monte Carlo simulations. In each of (say) 10 000 simulations, the forward interest rate curve is projected into the future at each revaluation point over the life of the hedge by means of a random process (such as Brownian motion).

In each simulation, the mark-to-market of the hedge is calculated at each revaluation point. For each revaluation point, the values are then ranked from largest to smallest and the value at each percentile is extracted from the list, generating a distribution function of the mark-to-market at each revaluation point in time. For example, the  500th point is extracted to determine the 95th percentile highest credit exposure, as would the 1000th for the 90th percentile, and so on.

As we project into the future, the projected interest distribution flattens and widens, as does the mark-to-market, resulting in greater variance. However, this effect is countered by the effect of the decreasing notional principal outstanding as the senior debt is repaid and / or the percentage of the senior debt hedged decreases.

This results in the credit exposure of the hedge being distributed roughly as follows (without mean-reverting interest rates):

Additional risk mitigants and considerations

Right-way-round risk: Interest rate swaps are said to enjoy right-way-round risk in that, as the credit exposure under the swap increases, the project benefits from a decrease in its floating interest rate bill, with the consequence that its PD decreases.

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A typical project finance term sheet

 

Equity injection style Up-front; or

Pari-passu with debt; or

Back-ended, subject to full acceleration rights and bank guarantees in the amount of the equity cheque to be provided.
Availability period Construction period + a few months
Term of the Facility Dependent upon project. Usually ~75% of the offtake contract, leaving an ungeared tail.
Repayment profile Capital & interest grace period during construction.

Capital fully amortises over the repayment period.

Capital & interest payments three- or six-monthly in arrears

Capital may be repaid by

o    Equal principal repayment;

o    Mortgage-style redemption; or

o    Sculpted to fit revenue profile, subject to achieving the minimum base case DSCR.

 
Covenants Debt:Equity, ADSCR, LLCR and PLCR may be used as covenants affecting lock up of distributions to shareholders, or leading to default.

The level of the lockup and default covenants will be determined with respect to the volatility of the cash flows and market standards for similar projects.

“Annual Debt Service Cover Ratio” (“ADSCR”) is the value of Cash Flow Available for Debt Service (“CFADS”) (excluding all cash and bank balances) in the applicable measurement period, divided by any debt principal and interest due in the same period.
  CFADS of the Borrower is defined as cash generated in the period, after operating expenses and tax, but before debt service .

“Loan Life Cover Ratio” (“LLCR”) is the net present value of future CFADS (excluding cash) until the final scheduled maturity of a Facility (discounted at the weighted average of the forecast Facility interest rates projected in each period) to the total aggregate of loans outstanding under the Facility.

“Project Life Cover Ratio” (“PLCR”) is the net present value of future CFADS (excluding cash) until the final scheduled maturity of a Project (discounted at the weighted average of the forecast Facility interest rates projected in each period) to the total aggregate of loans outstanding under the Facility.
Hedging Strategy Borrower usually required to hedge a minimum of 50% of the interest rate exposure under each facility (subject to sensitivity tests). All fx risk during construction usually required to be hedged.
Debt Service Reserve Account A Debt Service Reserve Account is required equivalent to the next 6 months’ scheduled interest and principal payments under the facilities and in place at Commercial Operation Date (“COD”), usually funded from debt and equity draw downs and topped up, if required, during the operations period. The DSRA is kept in reserve to provide liquidity when the Project has poor performance and is unable to fund its debt repayment (although it will already be in default when using the DSRA).

The DSRA may be funded from project cash flows rather than prior to COD.
Major maintenance Reserve Account (“MMRA”) Either an adequate MMRA or acceptable guarantee may be required. The MMRA is a reserve account gradually funded over a course of several years against very large future maintenance requirements, such as  refurbishment of turbines or repaving of a road.
Performance Bonds – EPC Design and Construction: An Engineering, Procurement & Construction Performance Bond (acceptable to the lenders), to be put in place, to provide security for Delay- and Performance Liquidated Damages. If the EPC provider fails to meet its obligations to provide the asset (e.g. power plant) up to specification and on time, it will pay delay and / or performance liquidated damages (“LDs”) to the project. These LDs are secured by an unconditional, on-demand bank bond as well as guarantees from the parent company of the EPC contractor.

 
Performance Bonds – O&M Operations and Maintenance: The performance of the O&M Company to be guaranteed by either corporate or bank guarantees (acceptable to the lenders). As per EPC performance bonds, the Operator will pay pre-agreed liquidated damages to the project if it does not perform to contracted specification. These LDs are secured by an unconditional, on-demand bank bond and / or a guarantee from the Operator’s parent company.

 

Security Structure of the Facility		 Common security for project finance facilities, including:

Notarial bonds over movable assets;

Mortgage bonds over immovable assets;

Security cession of all debtors balances and claims which the Borrower may have against third parties, security cession of Project Accounts (other than the Distributions Account) including Debt Service Reserve Account, cash balances and investments of the Borrower;

Security cession of Project Documents & related direct agreements, including the right, title and interest of the Borrower to the offtake contract – note that lenders will have the option to step into the project upon default, run the project, and then sell it in order to exit;

Security cession of all guarantees (including parent company guarantees) and performance bonds;

Cession over all licenses and permits;

Pledge over all shares in the Borrower; and

Direct agreements between the Lenders and EPC contractor, land owner, operator, offtaker, and concession giver.
Conditions Precedent (“CPs”) to Financial Close A Project Finance facility will include an extremely long list of CPs, including without limitation:

Lender satisfaction to the following:

The provisions of the EPC Contract, which as a minimum is usually a fixed priced turnkey contract;

The provisions of the Operations & Maintenance Contract and all other sub-contracts (where applicable);

That the guarantees and performance bonds provided by the EPC and O&M contractor/s are in place;

The audited base case financial model to achieve the minimum base case covenants levels;

Satisfactory External Legal Opinions, as required.

Review of the final technical, environmental, insurance, model (including taxation) and legal due diligence (including review of external legal opinions) to the Lenders’ satisfaction;
  Inter-creditor agreement (including voting rights) to be finalised (where applicable); and

Excon approval, if required.
Information Undertakings The Borrower may be required to provide the Lender with various items of information, including the following:

Annual reports on the operation of the Project and, prior to the  Scheduled COD, quarterly reports on the construction and equipment supply progress of the Project;

Certificate of fulfilment of the Project completion tests), issued by the Lenders’ Technical Advisor (“LTA”);

Prior to the commencement of each financial year, a copy of the operating Project budget for the next 12 months;

Notice of any material loss or damage;

Notice of any material breach, variation or termination of, or right to terminate or material dispute under any of the Project Agreements

Details of material claims, litigation, arbitration or other similar proceedings commenced or threatened by a third party against the Borrower or any project party

·       any indemnity claim made pursuant to any of the Project Agreements.
Events of Default Standard terms typical to Project Finance transactions include the following:

Any events of default under the other Project Documents (offtake contract, EPC, O&M) but usually at a lower threshold than under the relevant Project Document;

Non payment;

Borrower infringes Assignment or Change in Control obligations;

Acts of Insolvency, also for guarantors;

Any breach of a material clause in the Finance Agreement;

Misrepresentation – linked to lists of [repeating] representations and undertakings which the Borrower must make;

Failure to meet a Ratio test and;

Changes to the EPC Guarantee and the O&M Guarantee.
Consequences of Event of Default Upon an event of default, the Lender will have the right to do any of the following:

Cancel all remaining commitments;

Call all amounts due and payable under the Facility and accelerate their repayment;

Realise Security;

Exercise any “step-in” rights that they might have, assuming control of the project;

Apply the Project revenues as directed by the Lender;
Priority of Payments All revenues will be applied in the following order of priority:

Operating and maintenance expenditure, and project taxes;

Costs and fees under the Finance Documents;

[Sometimes scheduled Capex, but usually not];

Interest of the Loan and hedging counterparties to the Term Loan;

Capital in respect of the Loan and any crystalised hedge break amounts;

Any amount necessary into the DSRA and MMRA to require the maintenance of the required balances;

Payment of subordinated interest and principal; and

The remaining amount may be transferred to shareholders.
Fees and margins Dependent upon the particulars of the transaction, but including:

Upfront (arranging and underwriting) fees

Commitment fees

Interest, split into base rate, liquidity costs, statutory costs and credit margin
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Derivatives

Derivatives are used to hedge against uncertainty in macroeconomic factors influencing project cash flows, in particular interest rates, exchange rates, and to a lesser extent CPI and sometimes fuel prices.

Projects make use of such hedges to immunise their cash flows against adverse changes in the underlying factor, thereby  decreasing the volatility of cash flows available for debt service and allowing the project to leverage higher than they would otherwise be able to.

Corporates and Parastatals engaged in infrastructure projects also make use of hedges if they have significant borrowing programs, and more commonly, to lock in exchange rates when they purchase significant capex in a foreign currency.

Hedges, however, come at a cost, with the result that the banks offering them to the projects earn a considerable return. In particular, with the implementation of Basel III, and the Credit Risk Transfer (“CRT”) requirement, also called Counterparty Valuation Adjustment (“CVA”), spreads have widened considerably.

As an indication of how profitable a hedge may be to the investor, banks recognising PnL from derivatives in their trading books up front may earn as much as 2.0% – 3.5% of the notional debt amount on day 1 of the trade. (This is because profit and loss on the trading book is measured as the change in the mark-to-market, or NPV, of each derivative in the book.

Spreads on commodities (fuel) and on CPI are significantly wider than on interest rate swaps and fx swaps, with CPI swaps in particular being of interest because of the investor demand for CPI-linked debt.

Hedging instruments incur both market risk and credit risk. Market risk can be hedged by the investor in turn by entering into an equal and opposite position with its own trading counterparties. However, credit risk is a function of the unknown, but statistically predictable, future fluctuations in the underlying macroeconomic factor(s). Unlike the derivative trading activities which an institution typically enters into with banks, derivatives with a project will not be governed by a collateral agreement or CSA, with the result that the credit exposure can spike. Helpfully, hedges typically rank similarly to the tranche of debt which they are hedging, and are therefore typically senior in both the pre- and post enforcement payment waterfalls. This results in a probability of default (“PD”) and a loss given default (“LGD”) very (very) similar to that of the senior debt. However, the exposure at default changes in accordance with a probability distribution function, as touched on above.

Hedging derivatives can create a significant return kicker for traditional debt instruments, and may constitute an opportunity for a debt investor in that:

  • The work to determine the project’s credit quality may already have been done to evaluate more traditional investments; and
  • The credit exposure can become negative if the underlying moves in the “right” direction, leading to an implied funding benefit.

The investment banks typically reserve credit lines to cover credit risk associated with a hedging instrument provided to a project in the amount of the potential future exposure which will not be exceeded with a  98% probability, sometimes referred to as the swap’s PFE. This is calculated quantitatively by running, for example, 10 000 monte carlo simulations on the underlying asset, for example the interest rate curve. For each simulation, the hedge is revalued at each duration. The exposures at each duration are then sorted in, say, descending order and the 200th largest exposure at each duration is plotted to form the PFE curve. Similarly, expected exposure can be modelled by using the 5000th (or median) exposure at each duration. This process is relatively straight-forward to carry out for interest rate swaps using every-day tools, provided that the original market data is available and the investor is comfortable to rely upon simulated spot rates and forward curves. The same exercises for fx swaps would be more challenging because of the need to maintain a realistic arbitrage-free forward exchange rate curve in simulations.

Using market data available at the time of writing, the PFE for a 12-year vanilla amortising interest rate swap was approximately 15% of the original notional loan amount and decayed rapidly towards zero at later durations as the number of remaining payments contributing towards the NPV reduced.

More details on project finance hedging to follow in later posts…

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Full-recourse debt

Full recourse or corporate debt differs from non-recourse debt in that it is the sponsor that borrows the funds, rather than an insolvency-remote SPV. While funds borrowed may be for the purposes of conducting a project to build a specific infrastructure item, recourse is to the full balance sheet of the borrower. Consequently if the project fails, the borrower must still repay.

Borrowers are typically large corporates or parastatal entities. Evaluation of the debt opportunity presented by these entities is no different to that traditionally used to evaluate corporate or full recourse debt.

Similarly, corporates and parastatals frequently issue bonds. The spreads available on these bonds are readily available on Reuters, INet Bridge or similar.

Corporates with significant infrastructure assets may also issue bonds. However, the funds from such bonds may not in all instances be used to create infrastructure assets, but rather for general corporate purposes.

Infrastructure funders may issue bonds or seek to obtain loans, the proceeds of which are earmarked for infrastructure investments.