Geopolitical Risk Index — Methodology
Methodology

Geopolitical Risk Index

A quantitative framework for measuring sovereign security risk
Version 2.1.0 · Last updated 27 July 2026

The Blomstra Geopolitical Risk Index is a composite score (0–100) that quantifies country‑level geopolitical risk. It combines three pillars — Militarization, Conflict Intensity, and Displacement — into a single, transparent measure designed for sovereign risk assessment, portfolio allocation, and supply chain monitoring.

A higher score indicates higher geopolitical risk. The index is refreshed weekly and draws exclusively from authoritative, public data sources.

The Three Pillars

Each pillar captures a distinct dimension of geopolitical stress. They are weighted according to their direct impact on security and stability.

⚔️
Militarization
25% weight
Military expenditure as % of GDP. High spending signals external threat perception or internal repression.
💥
Conflict Intensity
45% weight
Battle‑related deaths per 100,000 population. The most direct measure of active violence.
🚶
Displacement
30% weight
Refugee outflows and inflows per 100,000. Outflow signals state collapse; inflow strains host states.

Data Sources

All data is sourced from internationally recognised institutions with open APIs and transparent methodologies.

Pillar Source Indicator Update Frequency
Militarization World Bank / SIPRI MS.MIL.XPND.GD.ZS Annual (latest year via MRV=1)
Conflict Intensity UCDP (Uppsala Conflict Data Program) GED (Georeferenced Event Dataset) Annual, refreshed weekly
Displacement UNHCR Refugee Data Finder Refugee counts by origin & asylum Annual, refreshed weekly

🔍 Auditability: Every data point is verifiable via the original source APIs. We do not use proprietary or black‑box data.

Why Logarithmic Scaling?

Raw indicators vary by orders of magnitude — a country might spend 0.1% of GDP on defence, while another spends 10%. A linear scale would let extreme values dominate the composite. We use logarithmic scaling to ensure that relative differences are captured fairly, and that no single outlier skews the index.

Score = ( log₁₀(Value) − log₁₀(Floor) ) / ( log₁₀(Ceiling) − log₁₀(Floor) ) × 100

Each pillar has a calibrated floor and ceiling that determine the 0–100 mapping. For conflict and displacement, we add 1 to the rate before taking the log to avoid zero values.

Composite Calculation

The final index is a weighted sum of the three pillar scores:

Risk = (Scoremil × 0.25) + (Scoreconflict × 0.45) + (Scoredisplacement × 0.30)

Weights are fixed and reflect the relative importance of each dimension in driving overall geopolitical risk. If a pillar is unavailable for a given country (e.g., no conflict data), its weight is redistributed proportionally among the remaining pillars.

Risk Tiers

Scores are mapped to four intuitive risk categories:

🟢 Low
0 – 25
Stable, predictable
🟡 Medium
26 – 50
Elevated tensions
🔴 High
51 – 75
Active conflict, significant stress
🟣 Extreme
76 – 100
War, state collapse, mass atrocities

Transparency & Data Vintage

Every refresh of the index reports the exact data vintage for each pillar — so you know whether you are looking at 2024 or 2025 data. This is displayed in the admin panel and exposed via the REST API.

📅 Example: World Bank: latest available (mrnev=1) · UCDP: 2025 · UNHCR: 2024 · ACLED: trailing 365 days

No hidden assumptions. Every number is traceable to its source.

Limitations

  • The index is a snapshot — it does not predict future events.
  • Displacement data is a lagging indicator; by the time refugees are counted, the crisis has already occurred.
  • The index does not capture all dimensions of risk (e.g., cyber threats, trade dependencies, diplomatic isolation).
  • It is a quantitative tool intended to complement, not replace, qualitative analysis.
  • Data availability varies by country; some small states may have missing data for certain pillars, which may result in incomplete scores.
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