RSE Methodology

1. What Is the Rupture Simulation Engine

The Rupture Simulation Engine (RSE) is a deterministic cascade simulator designed for small, externally exposed economies operating under geopolitical fragmentation. Unlike traditional macroeconomic models that assume gradual change and mean reversion, the RSE models shock convergence events — situations where multiple external pressures hit simultaneously and overwhelm a country's fiscal and financial buffers.

The RSE is a scenario-analysis framework, not a forecasting system. It does not predict what will happen. It traces what would follow from a stated set of assumptions, and makes those assumptions inspectable.

Traditional models ask: "How fragile is the economy?"

The RSE asks: "What happens when the system fractures?"

The engine treats Citizenship by Investment (CBI) programs as regulated capital instruments that function simultaneously as fiscal revenue, capital inflow, FX buffer, and political-economy risk vector. This multi-channel treatment is the RSE's core differentiator.

2. Rupture State Model

The RSE defines four system states, determined by simultaneous threshold crossings rather than single indicators:

Rupture is not recession. It is a multi-channel cascade in which external shocks converge, fiscal and financial buffers erode, policy space contracts, market perception shifts, thresholds are crossed, and the system transitions into a new, unstable state.

3. Variable Taxonomy

Structural Baseline Variables (Slow-Moving)

These define the resting equilibrium condition of each country:

Shock Exposure Variables (Fast-Moving)

These represent user-configurable external shocks:

Transmission Coefficients

These parameters control how shocks propagate through the economy. They are country-specific and visible in the parameter panel for every simulation:

4. Mobility Access Index (MAI)

MAI measures the "ease-of-mobility premium" for a country's CBI passport. It collapses visa-free/ETA/visa-required access, administrative friction, and revocation risk across high-income destination blocs into a single demand-relevant score.

MAI ranges from 0 to 1. Higher values indicate stronger passport mobility premium, which drives CBI demand. When MAI drops below the critical threshold (default: 0.4), the non-linear collapse penalty activates.

5. Regulatory Confidence Index (RCI)

RCI captures compliance credibility and perceived risk to international finance. It starts from a baseline and adjusts based on regulatory events with exponential decay.

When RCI drops below the critical threshold (default: 0.3), CBI demand faces a non-linear collapse penalty. RCI is the primary driver of regional contagion.

6. Banking Friction Multiplier (BFM)

BFM represents how difficult it is for CBI funds to move through the financial system — correspondent banking access, de-risking pressure, and transaction delays.

7. CBI Demand Factor

The Demand Factor (DF) determines CBI inflow levels relative to baseline. It combines all three derived indices:

DF = 1.0 means baseline demand. DF = 0.3 means CBI demand has fallen to 30% of baseline. CBI inflows are then computed as: CBI_inflows = CBI_baseline × DF.

8. The 9-Step Cascade

The simulation engine executes a monthly loop with nine sequential steps. Each month's output feeds into the next, creating path-dependent dynamics:

9. Regional Contagion

CBI states are connected via reputational and regulatory linkages. After the primary country simulation, contagion is triggered if:

• The shock has regional scope (e.g., FATF regional assessment), OR
• The primary country's RCI drops below the contagion trigger threshold (default: 0.35)

Spillover Mechanics

For each connected peer country, the engine applies an RCI reduction proportional to the contagion weight: RCI_target -= severity × contagion_weight. A small MAI revocation risk uptick is also applied. The peer country's simulation is then re-run with the propagated shock.

Substitution Effect

When a shock is country-specific (not regional), lost CBI demand is partially re-routed to peers: Shift_to_j ∝ DF_j / Σ DF_others. The substitution share defaults to 30%. When the event has regional scope, substitution is disabled since all countries are simultaneously affected.

Contagion Weights

Weights are directional and asymmetric. Countries with weaker compliance reputations generate stronger outbound contagion. Countries with stronger reform track records have reduced inbound contagion (reform buffer effect). Current weights range from 0.25 to 0.45.

10. Threshold Logic

State transitions are determined by simultaneous threshold crossings. The default thresholds for the CARICOM pilot are:

0 breaches → Stable. 1 breach → Strained. 2–3 breaches → Crisis. 4 breaches → Rupture. These thresholds are calibrated for small open economies and may differ from thresholds appropriate for larger or more diversified states.

11. Data Sources

All data used in the RSE is sourced from publicly available, defensible sources. Every data point has an associated provenance record documenting source, publication date, retrieval date, and confidence level.

12. Limitations

The RSE v1.2.1 has the following known limitations:

• Deterministic only. The engine does not model probability distributions, confidence bands, or tail-risk scenarios. All outputs represent a single path given the specified inputs. Probabilistic overlays are planned for a future version.
• No feedback loops — the transmission is a chain, not a cascade. Political stress, FX reserves and the debt-service ratio are terminal outputs: they are computed, reported, and read nothing back into demand, confidence or borrowing cost. The borrowing rate is fixed at initialisation. Real economic systems reinforce themselves; this model propagates a shock forward through a directed chain and stops. The simplification is intentional and aids transparency, but "cascade" in the engine's name describes the fan-out of one shock into several channels, not self-amplification.
• Reserve dynamics are a fiscal residual, not a balance of payments. FX reserves respond only to CBI inflow and a fraction of the fiscal balance. There is no import bill, no external amortisation, and no capital-account movement. For an ECCU member whose reserves are pooled at the ECCB, this is the wrong object, and the channel is scheduled for structural rebuild. In the interim the reserve threshold rarely governs a classification.
• The no-shock control is not stationary. Running a simulation with no shock applied does not hold the baseline still: reserves accumulate, because CBI inflow is credited with no offsetting sink, and debt-to-GDP drifts because GDP is held constant. The drift is proportional to CBI dependence, so it is largest for exactly the countries whose results carry the most weight. Shock results should be read as differences from a matched control rather than as levels.
• Static mobility shocks. Mobility regime changes are applied once at the start of the simulation and held constant. In reality, visa access can change incrementally over the simulation period.
• No endogenous policy response. The model does not simulate government counter-measures (fiscal adjustment, emergency borrowing, IMF programs). The outputs represent what happens if current conditions persist without intervention.
• Calibration is approximate. Transmission coefficients (α, β, γ) are set based on country archetypes and limited historical calibration, not econometric estimation. They should be treated as reasonable starting points, not precise measurements.
• Data currency. Baseline metrics reflect the most recent available fiscal year data. There may be a 6–18 month lag between the data date and current conditions.
• Contagion depth is capped. Regional contagion propagates at most 2 levels deep. In practice, cascading contagion can amplify through multiple rounds of market re-pricing.
• Not a forecast. The RSE is a scenario analysis tool. Its outputs depend entirely on the shock parameters selected by the user. Different assumptions produce different outcomes.

13. Model Versioning

Every simulation stores which engine version produced it. This ensures full reproducibility: given the same inputs, engine version, and baseline, the output is identical.

Each engine update includes:

• Version number (semantic versioning)
• Change log describing what changed
• Parameter adjustments and their justification
• Methodological modifications
• Effective date
• Whether outputs would differ materially from the previous version

Simulations include a reproducibility hash — a fingerprint of the input parameters, engine version, and the baseline used. This allows any simulation to be independently verified.

Version History