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Global Risks Index

The Global Risks Index · Methodology 1.0.0-draft

One grammar, seven instruments

Indicators to domains to pillars to composite, with intervals, classes, coupling, forecasts, scenarios, tails and a separate perception layer. Every method on this page runs in your browser on numbers you choose.

Composite Construction Explorers
Page GRX-MTHEdition Baseline Edition 2026Evidence close 2026-09-30Method 1.0.0-draftValues not yet publishedMethod v1.0.0-draft
FIG 1 · The risk chain
HazardExposureVulnerabilityImpactLikelihoodRiskCapacityResponseFinancingOutcome
Very low0.0 to < 2.0
Low2.0 to < 3.5
Medium3.5 to < 5.0
High5.0 to < 6.5
Very high6.5 to 10.0
Every indicator sits on the chain; every value lands in a class with its probability.
451
indicator definitions
106
composites
7
instruments
1,000
draws per value

01Principles

Eight principles

P1

A family of indices, not one monolithic score

NXS-GRX (canonical data, provenance and risk) publishes twenty domain indices, four pillar indices, a composite and six instruments. The composite never appears without every pillar and domain beside it, and no independent dimension is collapsed silently.

P2

Classes with intervals, never league tables

Every value carries a 90% interval from Monte Carlo analysis over normalisation, weights, imputation and aggregation. Countries are placed in risk classes with a stated class probability; pages list countries by name or code, never by value.

P3

No data is not zero

A missing input is shown as missing, an imputed input is flagged, and a value is withheld when coverage falls below the method’s minimum. An empty profile, an unavailable source and an observed zero render differently.

P4

Every value resolves to its source

Each value carries its source release, licence, retrieval time, method version and transformation chain (W3C PROV). A correction anywhere propagates to every dependent value and is logged publicly.

P5

Measured, modelled and perceived are kept apart

Status glyphs separate observed, reported, estimated, inferred, forecast, simulated, scenario and expert input. Perception signals form their own instrument and are never blended into measured risk.

P6

Systemic by construction

Standalone risk and coupling-adjusted risk are reported side by side, from typed dependency networks across trade, finance, energy, food, infrastructure and information.

P7

Licence-gated and reproducible

A source enters a public value only when its licence admits that use; withheld values are counted, not hidden. Methods, code paths, seeds and digests are published per release so any value can be recomputed.

P8

Information, not authority

NXS-GRX is research and risk-analytics information. It is not a rating, an official classification, a warning, a benchmark or advice, and it never decides for an institution.

02Pipeline

Source to profile

Every indicator declares its place on the risk chain and its polarity, so aggregation never mixes directions silently.

computation

The NXS-GRX pipeline, from source to profile

Graph24 nodes
Graph
01સ્ત્રોતો
02Harmonise
03Indicators
04Sub-indices
05Domains
06Pillars
07Composite and instruments
08Outputs

100%
List
  1. Event streams

    SOURCES · SOURCES · near real time
    Admitted alert, Earth-observation, conflict-event, price and market streams for the Pulse instrument.
  2. 205 registered sources

    SOURCES · SOURCES · licence-gated
    Every source is registered with its licence; nothing enters a public value its licence does not admit.
  3. Scenario families

    SOURCES · SOURCES · labelled
    Socio-economic and warming pathways and transition families, used as labelled scenario structures.
  4. Surveys and elicitation

    SOURCES · SOURCES · perception
    Structured expert elicitation and public surveys, kept apart from measured risk.
  5. Dependency network

    NETWORK · NETWORK · six layers
    Trade and input–output, finance and debt, energy, food trade, infrastructure and information links.
  6. Harmonised series

    HAR · HAR · units, areas, time
    Source series mapped to Nexus concepts and code lists; units, areas and frequency aligned; no imputation.
  7. 451 indicators

    IND · IND · Indicator Standard
    Native indicators with definitions, units, polarity, levels and crosswalks; flagged imputation only here.
  8. 86 sub-indices

    SUB · SUB · normalised
    Normalised, weighted and aggregated components inside each domain.
  9. 20 domain indices

    IDX · IDX · 1,000 draws
    Twenty domain indices with Monte Carlo intervals and sensitivity.
  10. Systemic coupling score

    COUPLING · COUPLING · S
    Contagion on the dependency network: DebtRank, clearing and threshold cascades.
  11. Hazard and threat exposure

    PILLAR · PILLAR · HTE
    What can strike, how often, how hard and who and what stands in its way?
  12. Human and systems vulnerability

    PILLAR · PILLAR · VUL
    How susceptible are people, livelihoods, ecosystems and essential systems to harm when a shock arrives?
  13. Macro-financial and structural fragility

    PILLAR · PILLAR · MSF
    How much fiscal, financial, external, digital and technological room does the system have before stress turns into crisis?
  14. Lack of coping and adaptive capacity

    PILLAR · PILLAR · LCC
    Can institutions anticipate, absorb, respond, recover and adapt?
  15. Pulse

    INSTRUMENT · INSTRUMENT · weekly
    Nowcast anomaly against each country’s own history.
  16. Outlook

    INSTRUMENT · INSTRUMENT · 1 to 36 months
    Calibrated event probabilities with verification scorecards.
  17. Tail

    INSTRUMENT · INSTRUMENT · exceedance
    Exceedance curves, return-period losses, catastrophic register.
  18. માર્ગો

    INSTRUMENT · INSTRUMENT · to 2100
    Fan charts under named scenario families.
  19. Perception

    INSTRUMENT · INSTRUMENT · separate
    Perceived severity and the perception gap.
  20. NXS-GRX Composite Risk

    COMPOSITE · COMPOSITE · geometric
    Composite = (HTE × VUL × MSF × LCC)^(1/4), each pillar on 0–10 floored at 0.1; pillar = expert-weighted geometric mean of its domain indices
  21. 195 country profiles

    PROFILES · PROFILES · classes, intervals
    Every domain, pillar and instrument per country, never ranked.
  22. 54 series indices

    SERIES · SERIES · global to technology
    Specialised indices from the same domain indices.
  23. API, tiles and bulk files

    ACCESS · ACCESS · machine
    Public cut, SDMX keys, vector tiles, bulk files.
  24. NXS-GRX Coupled Risk

    COMPOSITE · COMPOSITE · × (1 + κ·S)
    Coupled = Composite × (1 + κ·S), S = systemic coupling score in [0,1] from the dependency network, κ disclosed per release (baseline κ = 0.25); reported beside the standalone composite, never instead of it
Not runIn progressDone
FIG 2. Select a stage to trace it; Simulate run plays the pipeline in order. Every stage keeps provenance, so a correction at a source reaches every value that depends on it. Schematic of the construction; source: Indicator Standard composite definitions.
HazardExposureVulnerabilityImpactLikelihoodRiskCapacityResponseFinancingOutcome
03Pillars

Pillars and domain indices

Pillar values are expert-weighted geometric means of their domain indices (equal weights in the baseline, recorded per release); a pillar needs two thirds of its domains, otherwise it is withheld.

HTE · Hazard and threat exposure

HAZMulti-hazard exposure indexgeometric complement · equal weights · 5 components · 17 indicators CLIClimate physical hazard indexgeometric · equal weights · 3 components · 16 indicators CONConflict risk indexMazziotta–Pareto · expert weights · 4 components · 15 indicators SPCSpace-weather exposure indexproduct · equal weights · 2 components · 6 indicators CLIClimate transition exposure indexarithmetic · equal weights · 2 components · 5 indicators

VUL · Human and systems vulnerability

SOCSocio-economic vulnerability indexgeometric · expert weights · 5 components · 18 indicators DEMDisplacement pressure indexarithmetic · expert weights · 4 components · 10 indicators FOOFood insecurity risk indexMazziotta–Pareto · expert weights · 5 components · 20 indicators WATWater security risk indexgeometric · equal weights · 4 components · 11 indicators HLTHealth security risk indexgeometric · expert weights · 5 components · 25 indicators ENVEnvironmental pressure indexarithmetic · equal weights · 5 components · 16 indicators ENEEnergy security risk indexgeometric · expert weights · 5 components · 20 indicators INFInfrastructure fragility indexgeometric · expert weights · 5 components · 24 indicators

MSF · Macro-financial and structural fragility

FISFiscal and public debt risk indexgeometric · expert weights · 7 components · 27 indicators FINFinancial stability risk indexMazziotta–Pareto · expert weights · 7 components · 28 indicators ECOExternal dependence risk indexarithmetic · expert weights · 5 components · 22 indicators CYBCyber risk indexgeometric · equal weights · 3 components · 12 indicators TECTechnology concentration risk indexarithmetic · expert weights · 4 components · 10 indicators

LCC · Lack of coping and adaptive capacity

CRSLack of coping capacity indexgeometric · expert weights · 6 components · 26 indicators GOVGovernance weakness indexarithmetic · expert weights · 4 components · 16 indicators
04Composite

Composite and coupled composite

The composite never appears alone: profiles show each pillar and domain beside it.

Composite
Composite = (HTE × VUL × MSF × LCC)^(1/4), each pillar on 0–10 floored at 0.1; pillar = expert-weighted geometric mean of its domain indices
Coupled composite
Coupled = Composite × (1 + κ·S), S = systemic coupling score in [0,1] from the dependency network, κ disclosed per release (baseline κ = 0.25); reported beside the standalone composite, never instead of it
અનિશ્ચિતતા
1,000 Monte Carlo runs over normalisation, weights, imputation, aggregation (geometric, arithmetic, Mazziotta–Pareto); 90% intervals; Sobol first-order and total-order indices per release
આવરણ
Each pillar needs two thirds of its domain indices; otherwise the composite is withheld and the pillar shown alone
FIG 3 · Simulator: four pillars to the composite and coupled composite
Pillars (0 to 10)
4.2
5.1
3.6
4.8
Coupling and uncertainty
0.4
0.25
0.4
–
runs in your browser

Simulator: Composite = (HTE × VUL × MSF × LCC)^¼ with each pillar floored at 0.1; Coupled = Composite × (1 + κ·S). Draws vary weights, aggregation and inputs. The positions are starting points, not NXS-GRX values. Simulated on your own inputs; not a measured result.
05Classes

Classes and intervals, never league tables

A class is printed with its probability (share of Monte Carlo draws inside the class). Below 60% the adjacent class is printed too (for example High, 54% · Very high, 41%). Fixed bounds keep classes comparable across editions; intervals show when two countries cannot be told apart. Lists are ordered by name or code.

Very low0.0 to < 2.0
Low2.0 to < 3.5
Medium3.5 to < 5.0
High5.0 to < 6.5
Very high6.5 to 10.0
06Construction

Ten construction steps

The steps follow the OECD/JRC handbook on composite indicators and the statistical audit practice of the JRC Competence Centre on Composite Indicators, referenced for method only.

Theoretical framework Risk chain from hazard to outcome; four pillars; twenty index domains; explicit polarity and risk component for every indicator.
Data selection indicator definitions with SDMX-compatible keys, crosswalks to source code lists, evidence class A–E and the licence register.
Missing data Flagged imputation only at IND layer (dimension mean, indicator median, multiple imputation); modelled share capped per composite; coverage minimum two thirds.
Multivariate analysis Correlation structure, principal components and Cronbach’s alpha per sub-index; incoherent components are re-specified before release.
Normalisation Min–max with fixed goalposts, percentile rank or identity on native 0–10 scales; skew and kurtosis treatment (winsorisation, log) above |skew| 2 and kurtosis 3.5.
Weighting and aggregation Equal or expert weights recorded per composite; geometric, arithmetic, Mazziotta–Pareto, product or geometric-complement aggregation as each definition declares; floor 0.1 before geometric means.
Uncertainty and sensitivity At least 1,000 Monte Carlo runs over the declared alternatives; 90% intervals, class probabilities and Sobol indices published with every release.
Back to the data Driver decomposition to indicator level; every value opens to its inputs, sources and transformation chain.
Links to other indicators Published crosswalks and correlation checks against established indices, used as validity evidence, never as inputs to be re-weighted.
Visualisation and dissemination Classes and intervals, never league tables; machine access through API, SDMX keys, tiles and bulk files; corrections and versions public.
07Release

One edition, run as a workflow

An edition is a run: the evidence cut freezes, sources pass the licence gate, 451 indicators are computed for 195 profiles, 1,000 draws give the intervals, and two approval gates stand before anything is published.

on: evidence cut

Edition release run

In progressTriggered by NXS-GRX run service13 jobs2 approval gates6 matrix jobs

Graph
01Cut
02Ingest
03Ingest
04Indicators
05Indices
06Indices
07Indices
08અનિશ્ચિતતા
09અનિશ્ચિતતા
10સમીક્ષા
11સમીક્ષા
12Publish

100%
Timeline
Job0 d5 d10 d15 d20 dTarget
Evidence cut frozenNXS-GRX run service1 h
Licence gateLicence register1 h
HarmoniseNXS-GRX run service6 h
IndicatorsNXS-GRX run service4 h
Sub-indicesNXS-GRX run service1 h
Domain indicesNXS-GRX run service1 h
Coupling scoreNXS-GRX run service2 h
1,000 Monte Carlo drawsMonte Carlo engine3 h
Intervals, classes, SobolMonte Carlo engine1 h
Statistical auditIndependent reviewer10 d
Steward reviewStewards10 d
Profiles and seriesFoundry2 h
Tiles and bulk filesFoundry2 h

End to end on the longest path: about 20.9 d of proposed target service levels. Gates wait for the people named; bars with a fading end have no fixed length.

Steps
  1. Evidence cut frozen

    Cut · NXS-GRX run service · 1 hour
    Input vintages pinned
    NXS-GRX run servicePostgreSQL ledger (row-level security)
  2. Licence gate

    Ingest · Licence register · 1 hour
    Admitted, isolated or withheld
    Licence register
  3. Harmonise matrix · 150 sources

    Ingest · NXS-GRX run service · 6 hours
    Units, areas, time
    NXS-GRX run serviceindicator standard
  4. Indicators matrix · 451 × 195

    Indicators · NXS-GRX run service · 4 hours
    Derivations, flagged imputation
    NXS-GRX run serviceindicator standard
  5. Sub-indices matrix · 86

    Indices · NXS-GRX run service · 1 hour
    Normalise, weight, aggregate
    NXS-GRX run serviceTested model kernels
  6. Domain indices matrix · 20

    Indices · NXS-GRX run service · 1 hour
    Twenty domain indices
    NXS-GRX run serviceTested model kernels
  7. Coupling score

    Indices · NXS-GRX run service · 2 hours
    DebtRank, clearing, cascades
    Dependency networkTested model kernels
  8. 1,000 Monte Carlo draws matrix · 1,000

    Uncertainty · Monte Carlo engine · 3 hours
    Weights, normalisation, aggregation, imputation
    Monte Carlo engine
  9. Intervals, classes, Sobol

    Uncertainty · Monte Carlo engine · 1 hour
    90% intervals · Class probabilities · Sensitivity
    Monte Carlo engine
  10. Statistical audit approval

    Review · Independent reviewer · 10 days
    Coherence, stability
    Tested model kernels
  11. Steward review approval

    Review · Stewards · 10 days
    Method, evidence, public-safe screen
    PostgreSQL ledger (row-level security)
  12. Profiles and series matrix · 195 + 59

    Publish · Foundry · 2 hours
    Published with intervals
    Public cut APINS-1 UNI catalogue
  13. Tiles and bulk files

    Publish · Foundry · 2 hours
    ISO3, ADM1, ADM2, H3 · Deposit with DOI
    Vector tilesZenodo deposit
Artefacts
Artefact Job Who Stage
Cut record Evidence cut frozen NXS-GRX run service Cut
Withheld counts Licence gate Licence register Ingest
HAR series Harmonise NXS-GRX run service Ingest
IND values Indicators NXS-GRX run service Indicators
SUB values Sub-indices NXS-GRX run service Indices
IDX values Domain indices NXS-GRX run service Indices
S per country Coupling score NXS-GRX run service Indices
Draw set with seed 1,000 Monte Carlo draws Monte Carlo engine અનિશ્ચિતતા
Uncertainty report Intervals, classes, Sobol Monte Carlo engine અનિશ્ચિતતા
Audit note Statistical audit Independent reviewer સમીક્ષા
Release decision Steward review Stewards સમીક્ષા
આવૃત્તિ Profiles and series Foundry Publish
Tiles Tiles and bulk files Foundry Publish
DOI Tiles and bulk files Foundry Publish
DoneIn progressWaiting for approvalQueuedApproval gateMatrix jobYou are here
From the evidence cut to published profiles, tiles and API: every stage keeps provenance and two review gates stand before release. The canvas shows where a request stands at the marked job; it is illustrative, not the status of a real request. Durations are proposed target service levels. Select a job for its steps, the people who act, the technology it runs on and what it produces.
08Aggregation

Five aggregation shapes

Try them on the fiscal and public debt index: switch the aggregation and watch the class and interval move.

Aggregation તે શું કરે છે Domain indices using it
geometric Weighted geometric mean after a floor of 0.1: partial compensation, so weakness in one component cannot be fully offset by strength in another. Fiscal and public debt risk · Climate physical hazard · Water security risk · Health security risk · Socio-economic vulnerability · Energy security risk · Infrastructure fragility · Cyber risk · Lack of coping capacity
Mazziotta–Pareto Mean adjusted by the spread across components (non-compensatory): unbalanced profiles read as riskier than balanced ones with the same mean. Financial stability risk · Food insecurity risk · Conflict risk
arithmetic Weighted arithmetic mean: full compensation, used where components are substitutes. External dependence risk · Climate transition exposure · Environmental pressure · Displacement pressure · Governance weakness · Technology concentration risk
geometric complement Complement of the geometric mean of complements: any single high exposure lifts the index, as for multi-hazard exposure. Multi-hazard exposure
product Product of normalised components: risk exists only where all components are present, as for space-weather exposure. Space-weather exposure
FIG 4 · Simulator: aggregate fiscal and public debt risk on your numbers
Components (0 to 10)
3.0
5.0
7.0
4.0
6.0
3.0
5.0
25
1
–
runs in your browser

Contribution of each component (leave one out)
Simulator: the index’s published aggregation run on numbers you set, with 1,000 draws over weights and aggregation. The slider positions are starting points for the explainer, not NXS-GRX values. Simulated on your own inputs; not a measured result.
09Missing data

No data is not zero

Imputation happens only at the indicator layer and is always flagged: dimension mean, indicator median or multiple imputation, as each definition declares. Each composite caps the share of its weight that may rest on modelled or imputed inputs and withholds its value below its coverage minimum. Coverage is published as a vector per country and indicator, never as a single complete flag; fragile and small-island states are where gaps cluster, so their coverage is shown first.

10સ્થિતિ

Status and value states

Glyph સ્થિતિ Means
● અવલોકિત Measured directly and published by the source
□ નોંધાયેલ Reported or declared by a publisher, not independently measured
◆ અંદાજિત Estimated or modelled by a stated method
▲ INFERRED Inferred from related signals
◇ FORECAST Probabilistic statement about a future period
◈ SIMULATED Output of a simulation or stochastic event set
○ SCENARIO Conditional on a named scenario, not a prediction
◎ EXPERT INPUT Structured expert judgement
Value state Means
PUBLISHED Released in an edition with interval, class and sources
NO_DATA No admitted input; not a zero
INSUFFICIENT_EVIDENCE Coverage below the method minimum; value withheld
WITHHELD An input’s licence or the public-safe screen does not admit public display; counted
DEGRADED Published with a stated quality limitation
11સાધન

Pulse

Question
What has changed since the last structural cut?
Cadence
Weekly nowcast, event-driven between releases
પદ્ધતિ
Mixed-frequency dynamic factor model over admitted event streams (multi-hazard alerts, Earth observation, conflict events, prices, shipping, market stress), expressed as a standardised anomaly against each country’s own history.
Outputs
  • Pulse anomaly by domain
  • Signals for review with their sources
  • Threshold crossings for subscribers
Status of outputs
OBSERVEDINFERRED
Pulse publishes with the first edition. Weekly anomalies by country and domain will appear here as a timeline, each signal with its sources and status.
12સાધન

Outlook

Question
How likely are defined adverse outcomes over a stated horizon?
Cadence
Monthly, horizons of 1, 3, 12 and 36 months
પદ્ધતિ
Calibrated probabilistic ensembles (statistical, machine learning and structured expert elicitation) for defined events: conflict onset and escalation, acute food insecurity phase shifts, debt distress signals, disaster losses, displacement surges. Verified with Brier skill, reliability diagrams, ROC and CRPS against outcomes.
Outputs
  • Event probabilities with credible intervals
  • Forecast verification scorecards
  • Back-test record per model version
Status of outputs
FORECAST
FIG 7 · Explainer: how forecasts are verified
0.15
1.4
1
0
–
runs in your browser

Explainer: 3,000 synthetic forecasts and outcomes from your settings, scored the way every Outlook model version is scored: reliability diagram, Brier score, skill against climatology and ROC area.
13સાધન

માર્ગો

Question
How does risk move under alternative futures to 2030, 2050 and 2100?
Cadence
Each annual edition
પદ્ધતિ
Pillar and domain values projected under SSP × warming-level combinations and central-bank-network transition scenario families (used as labelled scenario structures), with demographic, urbanisation, governance and conflict pathways; fan charts, not point paths.
Outputs
  • Fan charts per domain and pillar
  • Scenario cascades
  • Adaptation and transition levers
Status of outputs
SCENARIOSIMULATED
FIG 8 · Explorer: a pathway fan chart to 2100
4
0.35
0.45
10
1
–
runs in your browser

Explorer: 2,000 paths from your drift, volatility and shock settings, shown as a fan chart (50% and 90% bands, median line) against the class bounds. Pathways editions project each domain under named scenario families; this explainer uses no scenario data.
14સાધન

Tail

Question
What does the rare, severe end of the distribution look like?
Cadence
Each annual edition, event-updated
પદ્ધતિ
Event loss tables and year loss tables, exceedance-probability curves, probable maximum loss at 1-in-100 and 1-in-250, expected shortfall, compound-event copulas and a register of low-probability, high-impact and global catastrophic risks.
Outputs
  • Exceedance curves and return-period losses where loss can be modelled
  • Protection-gap readings
  • Catastrophic and frontier risk register
Status of outputs
SIMULATEDMODELLED
FIG 9 · Explorer: exceedance, return-period loss and the protection gap
Frequency and severity
1.2
20
1.4
One risk-transfer layer
60
240
–
runs in your browser

Explorer: 20,000 simulated years from your frequency and severity settings; the exceedance curve, average annual loss, 1-in-100 and 1-in-250 annual losses, expected shortfall, and how one layer splits loss into retained, transferred and gap. Units are yours; nothing here is a modelled loss for any place.
15સાધન

Coupling

Question
Where does risk travel across systems and borders?
Cadence
Each annual edition, quarterly network refresh
પદ્ધતિ
Typed multi-layer dependency network (trade and input–output, finance and debt, energy, food trade, infrastructure and digital links); contagion estimated with DebtRank, Eisenberg–Noe clearing and threshold cascades; systemic importance and exposure scores per country and system.
Outputs
  • Systemic coupling score S
  • Coupled composite beside standalone
  • Transmission paths with status and references
Status of outputs
ESTIMATEDSIMULATED
FIG 10 · Expected direct couplings between systems (row affects column)
WAT ENE FOO HLT BIO FIN TRD INF DIG SEC
Water
Weak expected couplingModerate expected couplingStrong expected coupling
Schematic: the couplings the Coupling instrument expects to estimate. Strengths here are expectations from the literature the edition will cite, not estimates; each becomes ◆ ESTIMATED with its method and references in an edition.
FIG 11 · Simulator: how a shock cascades across systems
0.8
0.7
0.5
0.2
–
runs in your browser

WaterEnergyખોરાકHealthBiodiversityનાણાંTradeInfrastructureDigitalSecurity

Simulator: a threshold cascade on a schematic network of systems. Edge strengths are expected couplings (weak, moderate, strong), not estimates; the shock, coupling, threshold and buffers are yours. NXS-GRX estimates couplings per edition before any coupled value is published.
16સાધન

Perception

Question
Where does perceived risk differ from measured risk?
Cadence
Annual expert and public survey waves
પદ્ધતિ
Structured expert elicitation and public risk surveys, published as their own dimension with a perception-versus-measured gap per domain; never blended into the composite.
Outputs
  • Perceived severity by domain and horizon
  • Perception gap
  • Respondent coverage statement
Status of outputs
EXPERT INPUTREPORTED
Perception publishes with the first survey wave. Perceived severity by domain and horizon, with the perception gap against measured values.
17Geography

Six geographic levels

G0GlobalThe global series aggregates country values population- and exposure-weighted and reads the global systems directly. G1Country195 country profiles: the 193 UN member states and the 2 UN observer states. G2First administrative level (ADM1)Where boundaries and inputs admit; boundary versions are recorded. G3Second administrative level and below (ADM2+)Selected indicators and hazard layers. G4Cities and functional areasCities, river basins, coasts, corridors and islands. G5Hexagonal grid (H3)Resolution 4 to 7 for national views, finer for local layers; one fabric for hazard, exposure and capacity.
18Validation

Validation in public

Back-testing of Structural and Outlook values against realised outcomes

Back-testing of Structural and Outlook values against realised outcomes: disaster mortality and losses, acute food insecurity phases, conflict onset and fatalities, debt distress episodes, displacement.

Forecast verification with Brier skill score

Forecast verification with Brier skill score, reliability diagrams, ROC area and CRPS, published per model version.

Independent statistical audit of each major methodology version (correlation structure

Independent statistical audit of each major methodology version (correlation structure, coherence, uncertainty and rank stability)

Golden-value tests for every kernel with hand derivations

Golden-value tests for every kernel with hand derivations, so a value can be recomputed by anyone.

Country right of reply and public correction log

Country right of reply and public correction log.

19Revisions

Revisions and corrections

Methodology carries a semantic version; a change that breaks comparability is back-cast where inputs allow, and a correction propagates to every dependent value with a public log entry.

DraftComputedEvidence boundReviewedApproved for releasePublishedCorrectedSuperseded
20Vintages

Point-in-time vintages and validation metrics

Validation follows the composite-indicator audit practice of the JRC and the early-warning literature (Kaminsky and Reinhart 1999; Alessi and Detken 2011).

Vintages

Nothing is overwritten

Every edition and every correction is a vintage with its snapshot, frozen inputs and method version. A past value stays retrievable as it was published, so any study can be rerun on the information available at the time.

Revisions

Revisions are measured

Each indicator publishes its revision record between vintages, as the mean absolute revision and its direction, so a reader can see which inputs move after first release.

Stability

Rank reversal is tested

Adding or removing a country or an indicator must not reorder the others beyond the uncertainty already reported; the test is part of each edition’s uncertainty analysis.

Early warning

Signals are back-tested

Forecast and trigger instruments are scored out of sample, in pseudo real time: AUROC with its interval, noise-to-signal ratio, usefulness against the cost of a missed event, and the Brier score for probabilities.

Comparability

Breaks are declared

A method change that breaks comparability is back-cast where inputs allow; otherwise the series carries a declared break and comparisons across it are refused.

Lab

Try the methods yourself

The Index Lab runs these construction and validation methods on your own numbers in the browser.

21Reproducibility

Recompute any value

Each release publishes definitions, method versions, code paths, random seeds and content digests; every kernel is tested against hand-derived golden values.

Indicator Standard
451 indicators · 106 composites · 501 crosswalks
Hazard Standard
14 domains · 120 families · 905 hazards · 281 HIPs 2025 hazards
model registry
670 methods in 23 fabrics
Release
Each edition is deposited with its definitions, method version and inputs, with a DOI

Form

Comment on the methodology

Open consultation on normalisation, weighting, aggregation, imputation, uncertainty and validation; every comment receives a disposition in the consultation record.

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Every method comment is answered in the review record, and accepted changes are versioned and back-cast.

Comment on the method Try the Index Lab

સ્થિતિ

The methodology, structure and definitions of The Global Risks Index are a preparatory working draft (2026), circulated for review and comment and not for implementation. No value appears until an edition is released from a governed evidence cut; values then carry intervals, classes, sources and their correction pathway. Simulators run the published methods on numbers you choose and never show a NXS-GRX value.

What NXS-GRX is not

NXS-GRX is research and risk-analytics information. It is not a credit or ESG rating and uses no rating scale, not a benchmark for financial instruments, not official statistics, not an emergency warning or official classification, and not advice. It must not be used to evaluate natural persons. Risk classes are bands on a published scale, never rankings of countries or people.

Pulse signals and outlook probabilities are information for review by competent authorities, never public warnings; official warnings come only from mandated authorities.

Institutions and sources

The Nexus Consortium is stewarded by three independent not-for-profit institutions: The Global Centre for Risk and Innovation (GCRI), through GCRI US in Washington, DC and GCRI Canada in Ontario, with GCRI Canada as Lead Institution, Consortium Secretariat and lead contracting organisation; The Global Risks Forum (GRF); and The Global Risks Alliance (GRA). Technology, infrastructure and service providers work with the Consortium at arm’s length under written agreements, like every other external party in the public-private-planet model, and hold no role in its stewardship.

Every value carries the attribution of its sources, which keep their own licences. External names are cited for interoperability only. Nexus-authored text is intended for CC BY 4.0 on release.

Avis en français

La méthodologie et les définitions du NXS-GRX sont un projet de travail préparatoire (2026). Le NXS-GRX est une information de recherche et d’analyse des risques : ni notation, ni indice de référence financier, ni statistique officielle, ni alerte, ni conseil. Les classes de risque sont des bandes sur une échelle publiée, non des classements.