The first step in assessing the fiscal implications of a proposed PPP is to identify and evaluate the cost of the fiscal commitments implied by the project structure. The process of "identifying" fiscal commitments stems from the process of structuring the PPP. Identifying and evaluating fiscal commitments involves: allocating risks (and hence, identifying which risks are borne by the government, creating a fiscal commitment); defining payment mechanisms, including payments for services required by government; and defining responsibilities, which may include contractual commitments to provide inputs or carry out associated works. As previously noted, the initial assessment of fiscal implications should be reviewed during the procurement process, at each of its stages, considering changes introduced by bidders' proposals or the procurement agency. The PPP contract should require the private partner to regularly provide adequate information on project evolution and performance, allowing for effective and dynamic fiscal risk monitoring and management.
Table 2 provides a sample of the required fiscal commitment analysis during project preparation. During this due diligence phase, the entity responsible for project development should ensure that the relevant information on the project fiscal commitment and analysis are specified in the terms of reference for the transaction advisors who will be supporting the government (the same considerations hold in the event that the transaction studies and due diligence are undertaken by inhouse specialists).
Efforts towards containing the government's fiscal commitments should not translate into biased risk allocation. Contractual risk allocation is critical for project success. The risks that can be contractually allocated should be clearly assigned to one party or the other-"shared risks" may be a relevant source of contingent liabilities. In general, insufficient transfer of risk to the private partners results in low incentives for project performance, creating rents for private parties. But excessive transfer of risk to private partners (in contract provisions) may act in a counterintuitive way by creating large implicit contingency costs for government. Additionally, excessive risk transfer induces adverse selection of PPP operators, creating a breeding ground for rent-seeking firms rather than efficient operators. For instance, allocating to private partners some degree of demand risk creates sound incentives for service provision, but the excessive transfer of demand risk will simply force renegotiation (without competitive pressure and under threat of service disruption) or termination.
Several possible measures can express the cost of fiscal commitments under PPP projects. In the case of direct fiscal
| Table 2: | Key Analysis on Fiscal Commitments in Due Diligence of PPP Transactions (can be used as input in the Terms of Reference of Transaction Advisors for PPP projects) | |
| Type of Fiscal Commitment | Suggested Analysis | |
| All PPP projects | Estimate/Compute the value of the PPP project debt | |
| Direct fiscal support | • Annual cost over the project life (both upfront and ongoing commitments) • Present value of the payment stream for long-term commitments Both values should be calculated under "base case" assumptions, and under "downside" scenarios for key assumptions. | |
| Guarantees on particular risk variables | At a minimum, a scenario analysis approach should include: • Estimated annual cost under different scenarios for each guaranteed risk variable (base case and downside scenarios) • "Trigger points" for relevant risk variables-that is, the change from the base case at which contingent liabilities become payable (for example, percent drop in demand from base case at which a demand guarantee is payable), and qualitative analysis of the likelihood of reaching these values Over time, and for variables for which the government is building up significant exposure, could move toward probabilistic approach (to determine "expected" value and range). | |
| Payment guarantees | Value of underlying payment requirements ("face value" of guarantee), in terms of: • Annual cost over the project life • Present value of the payment stream Analysis of transfers likely to be required to meet payments under different scenarios for key variables (for example, sector tariffs) and a qualitative estimate of likelihood for each scenario. | |
| Termination payment commitments | • Maximum value of the termination payment, under base case assumptions (Value will vary over the project lifetime; maximum typically at project commissioning, when debt has been drawn down and repayments have yet not started.) • For any termination payments triggered by concessionaire default, trigger points for relevant key assumptions at which default might occur (for example, percent drop in demand that would mean insufficient cash for debt service), and a qualitative analysis of the risk of default. | |
| Cost of related investments and associated works | • Total cost to government of the contractual commitments to provide inputs, or requirements to carry out associated works. | |
commitments, suitable measures typically include both the estimated annual value and the present value of the stream of payment commitments over the project lifetime. Evaluating the cost of contingent liabilities is more complex and can be handled through two approaches:
a. Scenario analysis, which involves making assumptions regarding the outcome of any events or variables that affect the value of the contingent liabilities and calculating the cost given those assumptions. For example, this analysis can include "upside," "downside," and "worst case" scenarios for any given risk variable, or for a combination of risk variables;
b. Probabilistic analysis, which is an alternative approach that uses a formula to define how the variables that affect the value of the contingent liabilities will behave. Probabilistic analysis treats all input parameters as variables that change according to an assigned probability distribution function, and then calculates the resultant distribution of possible costs.
As the simpler, more intuitive approach, scenario analysis is almost always the best option for assessing PPP fiscal commitments. Probabilistic analysis requires a lot of information on the underlying risk variables, and it can be difficult to implement and interpret. In practice, only a few countries use this approach to assess exposure to some specific risks, such as Chile's analysis of exposure to revenue and exchange rate guarantees.