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GRA · Public Finance and Sovereign Debt

Spatial financeWhere capital meets hazard, exposure and transition

Scenario design and stress testing for public finance and sovereign debt

Scenario analysis and stress testing show how public debt and fiscal balances would evolve under adverse conditions. On this platform they explain the stress tests in debt sustainability frameworks, contingent liability shocks and climate scenarios for public finances.

01Qeyd

Scenario design and stress testing for public finance and sovereign debt on the record.

Method recordSTEM method
  1. RêbazSêwirandina senaryoyan û ceribandina bin zextê
  2. Applied inDarayiya giştî û deynê serwerî
  3. Canonical pageSTEM Commons
02Serlêdan

What scenario design and stress testing does here.

Scenario design and stress testing construct plausible, severe future conditions to examine how pergalan and institutions would perform. They complement probabilistic analysis where data are scarce or futures are deeply uncertain. In sovereign and public finance, development finance and disaster and crisis, stress tests reveal vulnerabilities that arise when several risks materialise together. They inform capital, contingency and coordination plans across sectors. The canonical description is on the STEM Commons.

Standard DSA stress tests

Shocks to growth, interest rates, exchange rates and the primary balance are applied to debt projections, as in the IMF and World Bank frameworks.

Contingent liability shocks

Scenarios where guarantees are called or state enterprises need support are added to debt paths to show their potential effect.

Climate and disaster scenarios

Disaster shocks and transition paths are introduced into fiscal projections, with assumptions and uncertainty documented for users.

03Çavdêrî bike

Scenario stress.

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

Scenario stress

Public finance and sovereign debt · Scenario design and stress testing · Run R-2370

Severe case breaches limitGRA · Public Finance and Sovereign Debt

Scenario set

Xeta bingehînCentral22Di nav de
Adverse1-in-2549Girtin
Tund1-in-10076Breach
Reverse stressFind the break100Defines edge

Method card

Rêbaz
Sêwirandina senaryoyan û ceribandina bin zextê
Vegotin
compound shock
Horizon
3 years
Nîşan
MODELKIRÎ

Impact build-up, severe case

Scenario stress: 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 scenario design and stress testing on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DaneRolNîşan
Baseline projectionsStarting pathFORECAST
Historical shock sizesCalibrationÇAVDÊRÎKIRÎ
Contingent liability dataShock inputsREPORTED
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
79% of GDP
Paths above the threshold at the horizon
3%
Primary balance that stabilises debt
0.3% of GDP
Jimar, rêbaz û çavkanî
Sal10%25%Median75%90%
070.070.070.070.070.0
168.869.870.971.972.8
268.770.271.673.474.9
369.270.872.574.776.5
469.371.373.275.477.9
569.871.674.276.679.0
670.372.574.977.880.3
770.573.175.779.082.0
871.073.676.680.083.1
971.674.277.881.084.7
1072.075.078.782.485.9

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.

Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.

Kontrol bikinHow it is done
Severity calibrationShocks are calibrated to historical experience
Combined shocksCombined scenarios are run, not only single shocks
Conditional framingResults are presented as conditional, not forecasts

Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.

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 scenario design and stress testing 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 scenario design and stress testing for the Consortium and reviews how it is applied across platforms.

11Pirs

Pirs û bersiv.

What are the limits of scenario design and stress testing in this field?
Scenario choice can reflect prevailing assumptions and miss novel combinations. Results depend on how participants and models represent responses.
How are results checked?
Scenarios are reviewed for plausibility, internal consistency and severity relative to history. Exercise outcomes are compared with actual events when they occur.
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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