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GRA · Public Finance and Sovereign Debt

Spatial financeWhere capital meets hazard, exposure and transition

Decision analysis under uncertainty for public finance and sovereign debt

Decision analysis structures choices under uncertainty. On this platform it helps frame debt management strategy, fiscal rule design, guarantee approval and investment selection, making trade-offs and value judgements explicit for the public servants who decide.

02Serlêdan

What decision analysis under uncertainty does here.

Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In sovereign and public finance, development finance and disaster and crisis, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on the STEM Commons.

Debt management strategy

Alternative borrowing strategies are compared on cost and risk across scenarios, following the medium-term debt management strategy approach.

Fiscal rule design

Rule options are compared for flexibility, simplicity and enforceability, with escape clauses and their triggers made explicit.

Guarantee approval

Criteria for approving guarantees weigh policy benefits against expected cost and tail risk, with each choice recorded.

03Çavdêrî bike

Uncertainty analysis.

The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.

Uncertainty analysis

Public finance and sovereign debt · Decision analysis · Run R-4487

Sensitivity rankedGRA · Public Finance and Sovereign Debt

Total-order sensitivity

Output distribution

Têketin

Public debtBeta of GDP, statedexpert elicitation
Gross financing needsUniform of GDP, statedexpert elicitation
Interest to revenueNormal of revenue, statedexpert elicitation
Share of FX debtNormal of debt, statedexpert elicitation
Uncertainty analysis: the screen’s structure, terms and states for Public finance and sovereign debt.Nav û nirxên nimûneyî; sêwiran e, ne qeyd an pergaleke zindî ye.
04Dane

What the method consumes.

Datasets and records used by decision analysis under uncertainty on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DaneRolNîşan
Debt portfolio dataCost and riskStatîstîkên weşandî
Scenario projectionsOutcome rangesMODELKIRÎ
Rule and legal textsConstraintsStatîstîkên weşandî
05Scenario model

Sovereign debt paths and the odds of breaching a threshold.

The distribution of debt paths, and the share above a threshold of concern at the horizon, that sovereign investors and rating analysts read from a fan chart. Teaching model with stated illustrative values, not a prediction.

  • Median, 25% to 75% and 10% to 90% bands
  • No shocks

Kontrol

Debt today
70% of GDP
Effective nominal interest rate
5.0%
Nominal GDP growth
4.5%
Primary balance
−0.5% of GDP
Volatility of growth
2.0 points
Volatility of the interest rate
1.0 points
Salên pêş
10 years
Threshold of concern
90% of GDP

Xwendin

Median debt at the horizon
78% of GDP
Paths above the threshold at the horizon
2%
Primary balance that stabilises debt
0.3% of GDP
Jimar, rêbaz û çavkanî
Sal10%25%Median75%90%
070.070.070.070.070.0
168.969.870.771.872.6
268.970.271.673.174.2
369.370.672.474.276.1
469.471.273.375.577.2
569.671.774.176.778.4
670.072.475.077.879.7
770.773.175.778.681.0
871.273.576.879.883.3
971.774.377.680.984.1
1072.075.078.382.085.6

Rêbaz

  1. Debt dynamics and the interest-growth differential Blanchard (2019), Public debt and low interest rates, American Economic Review 109
  2. Stochastic fan charts Celasun, Debrun and Ostry (2006), IMF Staff Papers 53
  3. Sovereign risk and debt sustainability framework IMF (2022), Staff Guidance Note on the SRDSF

Dane

No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.

Sovereign debt paths and the odds of breaching a threshold. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Debt dynamics and the interest-growth differential (Blanchard (2019), Public debt and low interest rates, American Economic Review 109); Stochastic fan charts (Celasun, Debrun and Ostry (2006), IMF Staff Papers 53); Sovereign risk and debt sustainability framework (IMF (2022), Staff Guidance Note on the SRDSF).

Li seranserê şeş stûnan, bi pêşengiya Nexus Consortium

06Erêkirin

How results are checked.

Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.

Kontrol bikinHow it is done
Options statedAll options, including the status quo, are listed
Trade-offs explicitCost-risk trade-offs are shown, not hidden in a single score
RobustnessChoices are tested across scenarios

Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.

07Exposure, loss and capital

What it means for exposure, loss and capital.

The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.

Capital, solvency and fiscal indicators

The indicators a risk officer, supervisor or ministry of finance reads first on decision analysis under uncertainty for public finance and sovereign debt.

IndicatorUnitWho reads itFramework
Public debt% of GDPMinistries of finance, IMFDebt Sustainability Framework
Gross financing needs% of GDP per yearMinistries of finance, investorsDebt Sustainability Framework
Contingent liabilities% of GDP, by sourceMinistries of financeFiscal risk statements
Interest to revenue% of revenueMinistries of finance, rating usersPublic finance statistics
Sovereign spreadbasis points over a benchmarkInvestors, debt managersMarket data
CET1 ratio% of risk-weighted assetsBanks, supervisorsBasel framework
Liquidity coverage ratio% of stressed outflowsBanks, central banksBasel framework
Source: the frameworks named in each row. Indicator names, units and frameworks only; values belong to each institution’s own reporting and are never shown here.
NGFS climate scenarios · Network for Greening the Financial SystemIFRS S2 Climate-related Disclosures · ISSBTCFD recommendations · Financial Stability Board TCFDPrinciples for the effective management of climate-related financial risks · Basel Committee on Banking Supervision
09Stewardship

Who maintains the method.

Rêveberiya xetera pergalî stewards decision analysis under uncertainty for the Consortium and reviews how it is applied across platforms.

11Pirs

Pirs û bersiv.

What are the limits of decision analysis under uncertainty in this field?
Results depend on elicited probabilities and preferences that may be biased. Deep uncertainty can make expected value comparisons misleading.
How are results checked?
Analyses are checked through sensitivity analysis, peer review and stakeholder scrutiny. Retrospective review compares decisions with outcomes.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
Çavdêrxaneya canonical method page lists every platform that applies it.
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rêzeya Pergalên Stratejîk is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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