E4 · cycle-002.e4-rwa

Rwanda, scripted, 30 years from 1996

30 simulations of 30 rounds from the 1996 position. Rwanda decides by the scripted method; scripted events: Regional war spillover in year 2, Breadbasket failure in year 4, Global funding seizure in year 12, Severe pandemic in year 24, Breadbasket failure in year 26.

Model 0.1.0 · graph 0.2.0 · parameters 0.1.0 · seeds 1–30 · elasticity sampled within each bracket

The same configuration in other cycles: cycle 3.

Every simulation · Compare with another experiment · More experiments like this

Not a forecast
Simulations of a structural model with seed parameter values, to compare methods and test the model. Other nations stay at their 2026 ratings throughout.

Outcome across simulations

The median at 2026, with the 10th to the 90th percentile of the 30 simulations under it.

Capability index
3.50 (−1.64)
From 5.13; 3.49 to 3.50
Rank by index
159
From 116; 159 to 159
Domains at Tier 1
0
From 0; 0 to 0
Tier rank
146
From 101; 146 to 146

Capability index by round

Rank by index, by round

Every objective at the position and at the horizon
Objective199610th percentileMedian90th percentileBetter
Capability indexprimary5.133.493.503.50higher
Rank by index116159159159lower
Tier rank101146146146lower
Domains at Tier 10000higher
Score sum366.4252.5253.0253.7higher
Goal-weighted score366.4252.5253.0253.7higher
Resilient score366.4253.1 (mean score sum over the simulations)higher

The capability index is the mean of the three dimensions, each the mean of its domains, each the mean of its groups. Tiers are Pareto layers within each domain; the tier rank orders nations by domains held at Tier 1, then Tier 2, and so on. The goal-weighted score is the score sum unless the experiment sets a goal. The primary objective is the one the experiment is judged on; every other objective is reported beside it.

Credits

What each round’s credits went on in the median simulation. Across all simulations, build took 84 per cent, buy took 0 per cent, partner took 16 per cent of the 254 credits a simulation spent on actions.

Against history

Started from a reconstructed 1996 position and played along the pathway and shocks Rwanda actually had, then scored against the 2026 ratings. The position is an estimate, so part of any error is the reconstruction's. The calibration summary across all fifty nations is on the cycle's page under Loop.

Index 1996
5.13
reconstructed
Observed 2026
5.95
the Index's rating
Simulated 2026
3.50
3.45 to 3.54
Skill against persistence
−0.97
group error 2.31 against 1.18 if nothing changed
Domain1996ObservedSimulatedBiasDirection
Critical Technology2.131.861.10 1.1–1.1−0.76right
Strategic Infrastructure5.765.804.16 4.1–4.3−1.64wrong
National Security3.893.762.68 2.6–2.7−1.08wrong
Human Capital6.406.905.38 5.3–5.4−1.51wrong
Information & Influence5.316.733.40 3.4–3.4−3.34wrong
Governance & Integrity6.148.655.09 5.1–5.1−3.55wrong
Financial Strength6.107.233.41 3.4–3.5−3.82wrong
Production & Innovation5.136.063.37 3.3–3.4−2.69wrong
Trade & Investment5.366.552.87 2.8–2.9−3.68wrong

The history it was played under: shocks and events

  • 1998 · S03 × 0.4 Rwanda's military intervention and subsequent involvement in the Second Congo War destabilised the region, diverted budget resources and disrupted cross-border trade, though it did not close a globally important sea route.
  • 2000 · S06 × 0.3 Drought in parts of Rwanda caused localised crop failure and food insecurity, straining the recovering agricultural system.
  • 2008 · S02 × 0.4 The global financial crisis reduced aid disbursements, remittances and export demand, tightening Rwanda's balance of payments and fiscal space.
  • 2020 · S10 × 0.8 COVID-19 reached Rwanda in March 2020; strict lockdowns and border closures caused the first recession since 1994 and sharply cut services and trade, though case mortality was low.
  • 2022 · S06 × 0.5 Russia's invasion of Ukraine drove up wheat, fertiliser and fuel prices, causing food insecurity and inflation in Rwanda and forcing costly import subsidies.

The pathway: what it prioritised, period by period

  • 1997–2000 · build · 2% each The Government of National Unity prioritised restoring security, reopening clinics and schools, and rebuilding subsistence agriculture after the 1994 genocide. (Internal Security & Order, Justice System & Fundamental Rights, Population Health, Social Infrastructure, Agriculture & Food Infrastructure)
  • 2001–2007 · build · 2% each Vision 2020 and the first PRSP channelled aid into primary schooling, basic ICT, roads and power under a strong decentralised administration. (Foundational Education, Communications & Digital Infrastructure, Government Effectiveness & Public Administration, Energy Infrastructure, Transport Infrastructure)
  • 2008–2012 · partner · 2% each After joining the East African Community in 2007, Rwanda aligned trade policy, improved the investment climate and deepened financial inclusion through Vision 2020 Umurenge. (Trade Policy & Market Access, Investment Attraction & Projection, Transport Infrastructure, Business Dynamism & Entrepreneurship, Financial System Depth & Access)
  • 2013–2017 · build · 5% each The second EDPRS and Smart Rwanda pushed fibre backbone, e-government, digital skills and agricultural intensification, with anti-corruption as a flagship. (Connectivity, Cyber & Trust Technologies, Digital & AI Competence, Technology Adoption & Diffusion, Public Integrity & Anti-Corruption, Agriculture & Food Infrastructure)
  • 2018–2024 · build · 2% each National Strategy for Transformation prioritised electricity access, Kigali logistics and aviation, light manufacturing, and health system expansion including the BioNTech vaccine plant. (Energy Infrastructure, Transport Infrastructure, Advanced Manufacturing, Industrial & Sectoral Base, Health System Capability)
  • 2025–2026 · partner · 2% each Rwanda's National AI Policy and innovation partnerships seek to position Kigali as a regional AI and fintech hub. (Artificial Intelligence, Connectivity, Cyber & Trust Technologies, Digital & AI Competence, Innovation & Commercialisation)

Reconstruction notes (deepseek-v4-pro): The 1996 baseline is extremely uncertain because Rwanda's statistical system had collapsed after the 1994 genocide, so many scores are inferential from later surveys. Military and security capabilities are particularly hard to benchmark, and aid dependence means fiscal and external scores may overstate autonomous capacity. The mapping of real events to library shocks is approximate, especially for the Congo wars which had no direct analogue.

Report

Written from the simulation record by the loop's narrator. Every figure names the query it came from, in square brackets.

Batch cycle-002. Model 0.1.0, graph 0.2.0, parameters 0.1.0. 30 simulations, seeds 1 to 30; probes on 10. Every figure is a distribution over simulations of a structural model with seed parameter values; it shows what the model implies under these settings, not what will happen. Other nations are frozen at their 2026 ratings. No reconstructed historical data is used in this experiment.

Headline

Rwanda played 30 rounds from 1996 under the scripted method, with scripted events, 30 times. Its capability index moved from 5.13 to a median of 3.49 (−1.64), with 90 per cent of simulations between 3.49 and 3.51 [experiment_objectives].

Starting position

In 1996 the nation ranks 116 on the index against the frozen field, holds 0 of nine domains at Tier 1 and has a tier rank of 101. Its base income is 90 credits a year, calibrated so that its 2026 position is affordable with headroom for investment.

What was decided

A simulation spent a median of 255 credits on moves. The five groups that took most were Agriculture & Food Infrastructure (build, 24 credits, 9.3 per cent); Energy Infrastructure (build, 19 credits, 7.5 per cent); Transport Infrastructure (build, 19 credits, 7.5 per cent); Digital & AI Competence (build, 17 credits, 6.6 per cent); Technology Adoption & Diffusion (build, 17 credits, 6.6 per cent) [experiment_decisions_by_group]. By mode: build 84 per cent, partner 16 per cent [experiment_decisions_by_group]. Concentration of spending (HHI) had a median of 0.058, and the most repeated action appeared in 47 per cent of rounds.

The leading domain by period: rounds 1 to 5, Strategic Infrastructure; rounds 6 to 10, Strategic Infrastructure; rounds 11 to 15, Trade & Investment; rounds 16 to 20, Strategic Infrastructure; rounds 21 to 25, Strategic Infrastructure; rounds 26 to 30, Strategic Infrastructure [experiment_spend_by_period].

What the world did

A median simulation saw 5 shocks and 0 upside events. The most damaging per firing were S10 (30 firings in 30 simulations, −29.4 points each); S06 (60 firings in 30 simulations, −25.8 points each); S03 (30 firings in 30 simulations, −25.4 points each) [experiment_shocks].

The groups that lost most to shocks, per simulation: Trade Facilitation & Logistics −4.01; Fiscal Capacity & Public Finance −3.81; Monetary & Currency Capability −3.02; Economic Leverage & Dependence −2.64 [experiment_shock_damage_by_group].

The edges that carried most change through the graph, per simulation: Fiscal Capacity & Public Finance to Social Infrastructure (−0.61 points); Fiscal Capacity & Public Finance to Force Generation & Mobilisation (−0.58 points); Connectivity, Cyber & Trust Technologies to Cyber & Electromagnetic Operations (+0.10 points) [experiment_propagation_by_edge].

Where it ended

At 2026 the median rank is 159 (5th to 95th percentile 159 to 159), the median count of Tier 1 domains 0 (0 to 0) and the median tier rank 146; the resilient score, the mean score sum over simulations, is 253 [experiment_objectives].

Why

Without shocks the index ends +1.989 higher on average, so the shocks cost about 1.989 index points [experiment_probe_attribution].

Holding instead of following this method changes the index by −0.286: that is the method's worth against doing nothing [experiment_probe_attribution].

Removing any single one of the five largest actions changes the index by between −0.005 and −0.002, for example 2017 build Connectivity, Cyber & Trust Technologies (3 credits) [experiment_probe_attribution]. The largest actions by credits come late, when income is highest, and are rarely the most valuable.

Removing the largest shock of a simulation raises the index by +0.494 on average [experiment_probe_attribution].

The replay probe reproduces the simulations exactly (index change 0.000000), so the attributions are clean [experiment_probe_attribution].

Surprises

saturation_low (warn): 100% of simulations end with a group at 0 that did not start there (median 5 groups).

retired_words (warn): e4-rwa/report.md: 'simulations' 1 time(s), first near line 38; use 'simulations'.

The simulation furthest from the median (seed 15) ends −0.02 from it, with 5 shocks and 0 upside events [experiment_outlier_simulations].

Comparison

This is the baseline (hold) experiment, or there is none for this nation in the batch.

Against history: from a reconstructed index of 5.13 the model ends at 3.50, where the 2026 ratings put it at 5.95. Group scores miss by 2.31 points on average, against 1.18 for assuming nothing changed (skill −0.97); the change in each domain has the right sign in 11 per cent of domains. Furthest below history: financial strength (−3.82); furthest above: critical technology (−0.76) [experiment_against_history]. The starting position is reconstructed, so part of the error is the reconstruction's.

What each decision and shock was worth

Counterfactual probes on the first 10 seeds: the same simulations with one thing changed, paired seed by seed. A removed decision or shock is taken out and the other decisions replayed unchanged, so the difference is that item's worth.

ProbeIndexScore sumTier 1For example
Hold instead of the method−0.286−21.50.00
No shocks+1.989+139.70.00
Replay of the recorded actions (must change nothing)0.0000.00.00
Without the 1st largest decision−0.004−0.40.002017 build Connectivity, Cyber & Trust Technologies (3 credits)
Without the 2nd largest decision−0.005−0.40.002017 build Digital & AI Competence (3 credits)
Without the 3rd largest decision−0.005−0.30.002017 build Technology Adoption & Diffusion (3 credits)
Without the 4th largest decision−0.003−0.20.002017 build Public Integrity & Anti-Corruption (3 credits)
Without the 5th largest decision−0.002−0.20.002017 build Agriculture & Food Infrastructure (3 credits)
Without the 1st largest shock+0.494+34.20.002022 S06 (-32.8 points)
Without the 2nd largest shock+0.464+32.30.002020 S10 (-29.4 points)
Without the 3rd largest shock+0.452+32.60.001998 S03 (-25.4 points)

Simulations

Three simulations told round by round, each on its own page: the one nearest the median index at the horizon, and those nearest the 10th and the 90th percentile. Every one of the 30 is listed with its outcome on the simulations page.

All 30 simulations

Events

How often each shock and upside event began across the simulations. Shocks come from the ten downside scenarios and upside events from the ten upside ones, at their yearly likelihood.

Event
Kind
Simulations
Mean round
Points
Global funding seizure S02Shock100 per cent12.0−14.2
Regional war spillover S03Shock100 per cent2.0−25.4
Breadbasket failure S06Shock100 per cent15.0−25.8
Severe pandemic S10Shock100 per cent24.0−29.4

Groups across simulations

Every capability group: its position, and its median and spread at the horizon across the simulations, with what the method spent on it.

73 of 73 groups

Capability group
Domain
1996
2026
Change
Levels invested
Credits
Digital & AI CompetenceHuman Capital6.847.63 7.60 to 7.66+0.791.8318
Connectivity, Cyber & Trust TechnologiesCritical Technology2.022.55 2.49 to 2.56+0.531.6218
Nuclear DeterrenceNational Security0.000.00 0.00 to 0.000.000.000
Public Integrity & Anti-CorruptionGovernance & Integrity6.746.59 6.56 to 6.64−0.150.9817
Technology Adoption & DiffusionProduction & Innovation5.444.99 4.95 to 5.00−0.451.3417
Justice System & Fundamental RightsGovernance & Integrity5.264.59 4.57 to 4.62−0.670.427
Energy TechnologiesCritical Technology0.670.00 0.00 to 0.00−0.670.000
Transport InfrastructureStrategic Infrastructure5.855.13 5.01 to 5.25−0.721.3826
Foundational EducationHuman Capital6.675.95 5.88 to 5.99−0.720.7811
Communications & Digital InfrastructureStrategic Infrastructure7.927.04 7.00 to 7.08−0.880.5811
Cyber & Electromagnetic OperationsNational Security5.284.36 4.33 to 4.39−0.920.000
Semiconductors & Advanced ComputingCritical Technology0.950.00 0.00 to 0.00−0.950.000
Regulatory Governance & Strategic ControlsGovernance & Integrity5.684.65 4.64 to 4.65−1.030.000
Sensing, Timing & NavigationCritical Technology1.040.00 0.00 to 0.00−1.040.000
Technical & Vocational SkillsHuman Capital5.614.54 4.53 to 4.56−1.070.000
Advanced EducationHuman Capital6.105.01 4.98 to 5.04−1.090.000
Lifelong Learning & ReskillingHuman Capital5.984.89 4.87 to 4.91−1.090.000
Internal Security & OrderGovernance & Integrity6.485.39 5.34 to 5.41−1.090.407
Transparency, Oversight & AccountabilityGovernance & Integrity5.144.04 4.03 to 4.06−1.100.000
Political Institutions & Civic ParticipationGovernance & Integrity4.253.15 3.12 to 3.16−1.100.000
Intelligence & AssessmentNational Security4.723.58 3.55 to 3.61−1.140.000
Space TechnologiesCritical Technology1.200.00 0.00 to 0.00−1.200.000
Research Talent & Knowledge CreationHuman Capital5.524.29 4.27 to 4.32−1.230.000
Air PowerNational Security2.681.45 1.43 to 1.48−1.230.000
Agriculture & Food InfrastructureStrategic Infrastructure6.184.94 4.86 to 5.00−1.241.1024
Advanced Materials & ManufacturingCritical Technology1.830.56 0.55 to 0.57−1.270.000
Land PowerNational Security5.594.30 4.24 to 4.33−1.290.000
Maritime PowerNational Security1.290.00 0.00 to 0.00−1.290.000
Quantum TechnologiesCritical Technology2.551.24 1.23 to 1.28−1.310.000
Trade Policy & Market AccessTrade & Investment6.144.82 4.75 to 4.90−1.321.197
Robotics & Autonomous SystemsCritical Technology2.941.61 1.60 to 1.65−1.330.000
Artificial IntelligenceCritical Technology4.933.57 3.51 to 3.63−1.360.132
Health System CapabilityHuman Capital7.185.78 5.70 to 5.88−1.400.419
Business Dynamism & EntrepreneurshipProduction & Innovation4.422.99 2.96 to 3.03−1.430.587
Space OperationsNational Security3.381.95 1.88 to 1.99−1.430.000
Government Effectiveness & Public AdministrationGovernance & Integrity8.246.76 6.71 to 6.80−1.480.5611
Industrial & Sectoral BaseProduction & Innovation5.253.76 3.70 to 3.82−1.490.569
Advanced ManufacturingStrategic Infrastructure6.364.84 4.77 to 4.94−1.520.389
Force Generation & MobilisationNational Security6.975.44 5.25 to 5.58−1.530.000
Diaspora & Global CommunitiesInformation & Influence6.514.97 4.96 to 4.97−1.540.000
Population HealthHuman Capital6.384.78 4.73 to 4.81−1.600.447
Joint Command, Projection & SustainmentNational Security5.123.49 3.43 to 3.54−1.630.000
Culture, Language & Education DiplomacyInformation & Influence5.163.53 3.49 to 3.54−1.630.000
Energy InfrastructureStrategic Infrastructure4.022.38 2.34 to 2.40−1.640.9519
Financial System Depth & AccessFinancial Strength6.014.32 4.30 to 4.33−1.690.597
National Resilience & Crisis ManagementGovernance & Integrity7.305.59 5.53 to 5.64−1.710.000
Space, Aerospace & Defence InfrastructureStrategic Infrastructure3.611.89 1.81 to 1.94−1.720.000
Strategic Strike & Missile DefenceNational Security3.912.18 2.10 to 2.24−1.730.000
Biotechnology & Health TechnologiesCritical Technology3.181.45 1.44 to 1.47−1.730.000
Early Childhood DevelopmentHuman Capital7.365.59 5.53 to 5.63−1.770.000
Investment Attraction & ProjectionTrade & Investment4.392.61 2.60 to 2.63−1.780.937
Alliances & Security CooperationInformation & Influence6.975.12 5.05 to 5.20−1.850.000
Development Cooperation & Global AssistanceInformation & Influence3.831.96 1.89 to 2.00−1.870.000
Innovation & CommercialisationProduction & Innovation4.562.68 2.62 to 2.72−1.880.101
Resource InfrastructureStrategic Infrastructure3.361.45 1.42 to 1.49−1.910.000
Social InfrastructureStrategic Infrastructure6.254.33 4.25 to 4.53−1.920.347
Financial InfrastructureStrategic Infrastructure7.805.84 5.68 to 5.94−1.960.000
Structural Transformation & ComplexityProduction & Innovation5.773.72 3.67 to 3.76−2.050.000
Information Environment & Strategic CommunicationInformation & Influence4.542.46 2.44 to 2.48−2.080.000
Digital & Services TradeTrade & Investment6.764.54 4.51 to 4.56−2.220.000
Financial Regulation & IntegrityFinancial Strength6.904.63 4.62 to 4.65−2.270.000
Economic Output & ProductivityProduction & Innovation5.042.76 2.72 to 2.79−2.280.000
Sovereign Capital & External Financial PowerFinancial Strength4.722.43 2.36 to 2.50−2.290.000
Financial Stability & Crisis ManagementFinancial Strength6.434.11 4.04 to 4.17−2.320.000
Water, Sanitation & Waste InfrastructureStrategic Infrastructure6.243.79 3.68 to 3.90−2.450.000
Export Capability & SophisticationTrade & Investment3.591.11 1.07 to 1.15−2.480.000
Diplomatic Statecraft & Global NetworksInformation & Influence4.832.34 2.30 to 2.38−2.490.000
Global Value Chain PositionTrade & Investment6.103.58 3.55 to 3.69−2.520.000
Labour & EmploymentProduction & Innovation5.442.69 2.65 to 2.74−2.750.000
Economic Leverage & DependenceTrade & Investment4.651.69 1.60 to 1.77−2.960.000
Monetary & Currency CapabilityFinancial Strength5.872.59 2.49 to 2.69−3.280.000
Trade Facilitation & LogisticsTrade & Investment5.881.74 1.72 to 1.77−4.140.000
Fiscal Capacity & Public FinanceFinancial Strength6.662.38 2.28 to 2.49−4.280.000

Checks

The automated checks run on this experiment before anything was written about it. A warning is a candidate finding for the improvement loop.

  • passcredits_conservedlargest gap between credits in and credits accounted for: 2.8e-14
  • passscores_in_boundsscores range 0.000 to 8.244
  • passno_nans0 missing values in the trajectory and objectives
  • passprobe_replay_reproducesthe recorded moves played back reproduce the simulation to within 0.0e+00 points (10 simulations)
  • passledger_balancesthe edge ledger sums to the propagated change to within 1.5e-06 points
  • passmove_without_shocklargest one-year move in a group with no shock landing: 0.36 points; 0% of simulations have one above 3
  • passtier_jumplargest gain in one domain within five years: 2 tiers (0 simulations above 2)
  • passall_tier1_from_outside_top10starting rank 116; 0 simulations reach Tier 1 in all nine domains
  • passsaturation_high0% of simulations end with a group at 20 that did not start there (median 0 groups)
  • warnsaturation_low100% of simulations end with a group at 0 that did not start there (median 5 groups)
  • passspend_concentrationmedian concentration of spending across groups (HHI) 0.058; most funded group hard.strategic_infrastructure.transport_infrastructure
  • passsame_actionthe most repeated move (group and mode) appears in a median 47% of rounds

Settings and versions

Experiment cycle-002.e4-rwa. Every simulation records the model, graph and parameter versions, the scenario, the method and its seed, so it can be reproduced exactly.

Nation
Rwanda (RWA)
Position
A reconstructed 1996 position, aligned to the Index's scale
Method
Scripted. Actions fixed in advance by the experiment: for a backcast, the nation's historical pathway.
Scenario
Scripted events: Regional war spillover in year 2, Breadbasket failure in year 4, Global funding seizure in year 12, Severe pandemic in year 24, Breadbasket failure in year 26
Objective
Capability index, the primary objective the experiment is judged on; every other objective is reported beside it
Horizon
30 rounds, 1996 to 2026
Simulations
30 seeds, 1 to 30. Every method in the batch faces the same draws for the same seed.
Graph elasticities
Drawn for each simulation, uniformly within each edge’s bracket
Income
Base credits 89.6 a round, moving with the economic groups
Versions
Model 0.1.0, Capability Dependency Graph 0.2.0, parameters 0.1.0
Batch
Backcast 1996-2026 (cycle-002), cycle 2 of the improvement loop
Runtime
4.2 seconds in all; 1023 microseconds a round
Not a forecast
Every figure is a distribution over the simulations of a structural model, reported to compare methods and test the model. None is a prediction of what a nation will do or become.
Structural parameters
Costs, decay, vulnerability and credits are structural seed values with low or medium confidence, set by domain with single-group exceptions. Five groups have no defensible value in a single-nation model and are flagged in the parameter tables.
Other nations are frozen
One nation is simulated at a time. Every other nation stays at its 2026 rating, so rank and tiers are measured against a still field; where the simulated nation rises past others their own tiers are not re-sorted.
Starting depth and mode are defaults
The position is the National Capability Index ratings. How institutionalised each capability is, and how much was built, bought or partnered, have no data behind them yet and start from structural defaults.
Credits are calibrated, not measured
Each nation’s income is set so that its position is affordable with headroom that rises with its fiscal capacity. It is not yet fiscal capacity as a share of GDP.