GCRI · Economic Development
Public finance and risk
Public finance determines what governments can spend on services and investment, and how well they can respond to shocks. Debt, contingent liabilities, revenue volatility and the fiscal cost of disasters shape that capacity. This page sets out how fiscal risk arises and is managed, how it is measured and disclosed, and what evidence serves the finance ministries, parliaments and auditors responsible.
Public finance and risk in seven parts.
- 01The questionPublic finance and risk: how the risk develops
- 02Across the domainsPublic budgets absorb shocks from every domain
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsWhat experts ask about public finance and risk
- 07Mechanisms and driversHow shocks reach public budgets
Public finance and risk: how the risk develops.
Fiscal capacity and shock exposure. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Debt limits room to respond
High debt and interest costs leave less room for spending in a crisis and raise the risk that markets or lenders refuse new borrowing.
Contingent liabilities hide risk
Guarantees, public-private partnerships, state enterprises and implicit support for banks can become public costs suddenly.
Disasters hit budgets
Disasters raise spending for relief and reconstruction while reducing revenue. Without planned financing, governments cut other spending or borrow at high cost.
Transparency enables management
Fiscal risk statements, credible forecasts and audited accounts let parliaments and markets see risks before they materialise.
Activity and exposure in Africa.
Population density, night lights and flood water over Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Activity and exposure, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra EVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Activity and exposure, framed on Africa.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Optional layers (6 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
Public budgets absorb shocks from every domain.
Fiscal risk analyses are designed for the Country Systems Risk and Resilience series. Fiscal transparency follows the IMF Code (2019) and PEFA (2016); debt analysis follows the joint frameworks. The Global Centre for Risk and Innovation (GCRI) advises on no borrowing.
- Fiscal risk statements governments publish.
- Contingent liability studies.
Shock propagation model.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Shock propagation model
Public finance and risk · National economy · Scenario: import price shock
Output impact by channel
Most affected sectors
| Food processing | ▼ 8 | 3153 | Backward |
| Transport | ▼ 2 | 2865 | Forward |
| Construction | ▼ 3 | 1464 | Backward |
| Retail | ▼ 1 | 6600 | Demand |
Fiscal room
local units, billions, illustrative
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| General government gross debt | percent of GDP | annual | Government finance statistics | Published statistics |
| Interest payments | percent of revenue | annual | Government finance statistics | Published statistics |
| Contingent liabilities disclosed | percent of GDP | annual | Fiscal risk statements | Published statistics |
| Disaster risk financing instruments in place | count by type | annual | Finance ministry records | DECLARED |
| Tax revenue | percent of GDP | annual | Revenue statistics | Published statistics |
| Budget credibility | difference between budgeted and actual spending | annual | PEFA assessments | Published statistics |
Debt dynamics under uncertainty.
The debt ratio evolves by the interest-growth differential and the primary balance; 500 paths with shocks to growth and rates give the fan, the way debt sustainability analyses show it. Teaching model with stated illustrative values, not a prediction. The map on this page shows Africa; the model itself is not tied to a place.
- Median, 25% to 75% and 10% to 90% bands
- No shocks
Controls
- 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
- Years ahead
- 10 years
- Threshold of concern
- 90% of GDP
Readouts
- Median debt at the horizon
- 79% of GDP
- Paths above the threshold at the horizon
- 2%
- Primary balance that stabilises debt
- 0.3% of GDP
Numbers, methods and sources
| Year | 10% | 25% | Median | 75% | 90% |
|---|---|---|---|---|---|
| 0 | 70.0 | 70.0 | 70.0 | 70.0 | 70.0 |
| 1 | 68.9 | 69.8 | 71.1 | 72.1 | 72.9 |
| 2 | 68.9 | 70.2 | 71.8 | 73.3 | 74.7 |
| 3 | 69.0 | 70.7 | 72.7 | 74.8 | 76.3 |
| 4 | 69.5 | 71.3 | 73.6 | 75.8 | 77.8 |
| 5 | 69.7 | 72.0 | 74.3 | 77.0 | 79.3 |
| 6 | 70.4 | 72.4 | 75.1 | 78.1 | 80.7 |
| 7 | 70.9 | 73.4 | 76.1 | 79.0 | 81.8 |
| 8 | 71.4 | 74.2 | 77.4 | 80.0 | 83.6 |
| 9 | 71.9 | 74.9 | 77.9 | 81.1 | 84.2 |
| 10 | 72.2 | 75.4 | 78.6 | 81.9 | 85.4 |
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
Data
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.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Economic Development in Foundry
- Tested at Economic Development in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Economic Development in Reports
- Taught in Faculty of Finance and Economics in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| IMF World Economic Outlook and Government Finance Statistics | Debt, revenue and spending | Public, IMF terms |
| PEFA assessments | Public financial management performance | Public, PEFA terms |
| OECD and partners Global Revenue Statistics | Tax revenue by country | Public, OECD terms |
| World Bank Debt Sustainability Analyses | Debt risk assessments for low-income countries | Public, World Bank terms |
| Global Facility for Disaster Reduction and Recovery disaster risk finance resources | Instruments and practice for disaster risk financing | Public, World Bank terms |
Model public finance and risk as a system. Run the cascade.
Assembled from the Nexus Standards area profile Financial and economic risk standards: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Sea-level rise
- Dam failure
- Coastal flood (set off downstream)
- Storm surge (set off downstream)
- High-tide flooding (set off downstream)
- Coastal erosion (set off downstream)
- Saltwater intrusion (set off downstream)
- Estuary flood (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Coastal habitat squeeze (set off downstream)
- Wetland loss (set off downstream)
- Mangrove loss (set off downstream)
- Groundwater flood (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
- Climate-driven migration and relocation (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-H59Hazard family: Economic shocks and governance failure (NHS-1 soc.economic)NRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H118Hazard family: Organised crime and illicit economies (NHS-1 soc.crime)NRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-U27Universe platform profile: Sovereign Capital Nexus
Observation
- IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
- BIS Data Portal (credit, debt service, property prices, banking statistics) (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- OECD Data Explorer (SDMX API) (listed for reference)
- Macroeconomic Dashboard
- Debt service as a proportion of exports of goods and services
- Financial Soundness Indicators
Example geography
- Western Europe: 152 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
Who decides, and what the evidence serves.
Economic Development prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Ministries of finance | How to manage debt, contingent liabilities and disaster costs | Fiscal risk profiles; financing gap analyses |
| Parliaments and budget committees | Whether budgets and risks are disclosed adequately | Transparency and credibility evidence |
| Supreme audit institutions | Where fiscal risks need scrutiny | Contingent liability evidence |
Outputs this topic produces
- Fiscal risk profiles including contingent liabilities
- Disaster cost and financing gap analyses
- Debt dynamics scenarios with stated assumptions
- Evidence notes for parliaments and auditors
How public finance and risk is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Sensitivity analysis
Which inputs move the result for public finance and risk most, one at a time across their stated ranges.
What experts ask about public finance and risk.
- How much fiscal space does a government have to respond to a shock?
- Which contingent liabilities, such as public backing for state firms or banks, could fall on the budget?
- How do disasters and pandemics affect revenues and spending?
- How stable is the tax base, and how dependent is it on volatile sources?
- How do debt levels and composition affect resilience to shocks?
How shocks reach public budgets.
Shocks affect budgets directly, through emergency spending, reconstruction and social support, and indirectly, through lower economic activity and tax revenues. Governments may also take on liabilities from state-owned enterprises, subnational governments, banks or public-private partnerships when these come under stress.
Fiscal capacity varies widely. Economies with narrow tax bases, high debt or dependence on commodity revenues have less room to respond. Borrowing costs can rise precisely when borrowing is most needed, and debt in foreign currency becomes more costly when the currency weakens.
Responses that cut public investment to meet obligations can slow long-run development. Planning ahead, through contingency budgets, risk financing and fiscal rules with escape clauses, can reduce the cost of shocks.
Methods and their limits.
- 01
Fiscal risk analysis
Identifying and quantifying risks to the budget. Contingent liabilities are often poorly documented.
- 02
Debt sustainability analysis
Projecting debt paths under scenarios. Results depend heavily on growth and interest assumptions.
- 03
Input-output and fiscal models
Estimating how shocks affect revenues and spending using econometrics.
- 04
Disaster cost estimation
Assessing the public cost of past events. Data on indirect and long-term costs are limited.
Fiscal projections are uncertain and sensitive to assumptions; analyses present ranges and the assumptions used.
How it is studied, and what the methods cannot say.
- 01Economics and development economicsGrowth diagnostics · Structural transformation analysis · Distributional incidenceApplied here
- 02EconometricsShock transmission models · Panel analysis across countries · Nowcasting with alternative dataApplied here
- 03Complex systems and agent-based modellingAgent-based macroeconomic scenarios · Feedback in fiscal and financial stressApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Where this page leads across the Consortium.
Questions and answers.
What is fiscal risk?
What is a contingent liability?
What is disaster risk financing?
Does the platform assess a country’s creditworthiness?
Does the platform recommend insurance or risk financing products?
Why do borrowing costs rise when governments most need to borrow?
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