E4 · cycle-002.e4-bgd

Bangladesh, scripted, 30 years from 1996

30 simulations of 30 rounds from the 1996 position. Bangladesh decides by the scripted method; scripted events: Core disaster in year 2, Legitimacy rupture in year 11, Breadbasket failure in year 12, Severe pandemic in year 24, Breadbasket failure in year 26, Legitimacy rupture in year 28.

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
4.17 (−2.30)
From 6.47; 4.16 to 4.18
Rank by index
136
From 90; 136 to 136
Domains at Tier 1
0
From 0; 0 to 0
Tier rank
136
From 101; 135 to 136

Capability index by round

Rank by index, by round

Every objective at the position and at the horizon
Objective199610th percentileMedian90th percentileBetter
Capability indexprimary6.474.164.174.18higher
Rank by index90136136136lower
Tier rank101135136136lower
Domains at Tier 10000higher
Score sum458.4299.0299.7300.4higher
Goal-weighted score458.4299.0299.7300.4higher
Resilient score458.3299.6 (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 90 per cent, buy took 0 per cent, partner took 10 per cent of the 416 credits a simulation spent on actions.

Against history

Started from a reconstructed 1996 position and played along the pathway and shocks Bangladesh 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
6.47
reconstructed
Observed 2026
6.73
the Index's rating
Simulated 2026
4.17
4.11 to 4.23
Skill against persistence
−1.94
group error 2.54 against 0.86 if nothing changed
Domain1996ObservedSimulatedBiasDirection
Critical Technology2.672.501.12 1.1–1.1−1.38wrong
Strategic Infrastructure6.838.505.31 5.2–5.4−3.19wrong
National Security4.845.712.41 2.3–2.5−3.30wrong
Human Capital7.257.366.02 6.0–6.1−1.34wrong
Information & Influence6.657.123.47 3.4–3.5−3.66wrong
Governance & Integrity7.787.385.75 5.7–5.8−1.63right
Financial Strength7.847.193.83 3.8–3.9−3.36right
Production & Innovation6.907.364.83 4.8–4.9−2.52wrong
Trade & Investment7.457.424.79 4.7–4.9−2.62wrong

The history it was played under: shocks and events

  • 1998 · S07 × 0.8 Catastrophic monsoon floods submerged nearly two-thirds of Bangladesh, destroying crops, homes and transport links and forcing massive relief operations.
  • 2007 · S05 × 0.6 A disputed electoral process led to a military-backed caretaker government, emergency rule and suspension of normal politics.
  • 2008 · S06 × 0.5 The global food price spike doubled rice prices in Bangladesh, worsening food insecurity for millions and testing the public distribution system.
  • 2020 · S10 × 0.8 COVID-19 arrived in March 2020, collapsing ready-made garment orders, disrupting remittances and straining a weak health system.
  • 2022 · S06 × 0.4 Russia's invasion of Ukraine sharply raised imported fuel, fertiliser and food prices, worsening Bangladesh's terms of trade and inflation.
  • 2024 · S05 × 0.8 Mass student-led protests over job quotas escalated into a national uprising that toppled Sheikh Hasina and installed an interim government amid violence.

The pathway: what it prioritised, period by period

  • 1997–2001 · build · 5% each The first Awami League government prioritised food security, garment export growth and basic services after the return to elected rule. (Agriculture & Food Infrastructure, Export Capability & Sophistication, Foundational Education, Population Health, Water, Sanitation & Waste Infrastructure)
  • 2002–2006 · partner · 2% each The BNP-led coalition channelled public and donor finance into roads, power and garment-sector expansion, with private investment taking the lead. (Transport Infrastructure, Energy Infrastructure, Industrial & Sectoral Base, Export Capability & Sophistication)
  • 2007–2010 · build · 5% each The caretaker emergency pushed anti-corruption and administrative reforms, followed by the Awami League's Digital Bangladesh and power-generation drives. (Communications & Digital Infrastructure, Government Effectiveness & Public Administration, Public Integrity & Anti-Corruption, Energy Infrastructure, Foundational Education)
  • 2011–2018 · build · 5% each Mega-infrastructure such as the Padma Bridge, rapid power-plant construction, industrial zones and social safety nets dominated the Awami League's second term. (Transport Infrastructure, Energy Infrastructure, Industrial & Sectoral Base, Export Capability & Sophistication, Social Infrastructure)
  • 2019–2026 · build · 5% each The later Awami League years pursued a digital services push, energy transition, pandemic health response and preparation for LDC graduation. (Communications & Digital Infrastructure, Energy Infrastructure, Health System Capability, Water, Sanitation & Waste Infrastructure, Trade Policy & Market Access)

Reconstruction notes (deepseek-v4-pro): The main uncertainty is the relative scoring of Bangladesh's large but low-productivity agricultural and garment sectors against the global scale; international data for 1996 are patchy. National capability estimates are also blurred by the informal economy and the dominant role of NGOs in health, education and microfinance, which public statistics understate. Mapping Bangladesh's repeated floods and political crises to the event library requires judgement about severity relative to the scenario's severe case.

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

Bangladesh played 30 rounds from 1996 under the scripted method, with scripted events, 30 times. Its capability index moved from 6.47 to a median of 4.17 (−2.30), with 90 per cent of simulations between 4.15 and 4.18 [experiment_objectives].

Starting position

In 1996 the nation ranks 90 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 123 credits a year, calibrated so that its 2026 position is affordable with headroom for investment.

What was decided

A simulation spent a median of 415 credits on moves. The five groups that took most were Energy Infrastructure (build, 77 credits, 18.4 per cent); Foundational Education (build, 49 credits, 11.9 per cent); Communications & Digital Infrastructure (build, 44 credits, 10.7 per cent); Transport Infrastructure (build, 35 credits, 8.5 per cent); Export Capability & Sophistication (build, 33 credits, 7.8 per cent) [experiment_decisions_by_group]. By mode: build 90 per cent, partner 10 per cent [experiment_decisions_by_group]. Concentration of spending (HHI) had a median of 0.116, and the most repeated action appeared in 60 per cent of rounds.

The leading domain by period: rounds 1 to 5, Human Capital; rounds 6 to 10, Strategic Infrastructure; rounds 11 to 15, Strategic Infrastructure; 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 6 shocks and 0 upside events. The most damaging per firing were S05 (60 firings in 30 simulations, −36.2 points each); S10 (30 firings in 30 simulations, −33.3 points each); S07 (30 firings in 30 simulations, −30.5 points each) [experiment_shocks].

The groups that lost most to shocks, per simulation: Fiscal Capacity & Public Finance −5.83; Monetary & Currency Capability −4.74; Information Environment & Strategic Communication −4.49; Trade Facilitation & Logistics −4.33 [experiment_shock_damage_by_group].

The edges that carried most change through the graph, per simulation: Fiscal Capacity & Public Finance to Social Infrastructure (−0.79 points); Fiscal Capacity & Public Finance to Force Generation & Mobilisation (−0.74 points); Fiscal Capacity & Public Finance to Transport Infrastructure (−0.47 points) [experiment_propagation_by_edge].

Where it ended

At 2026 the median rank is 136 (5th to 95th percentile 136 to 136), the median count of Tier 1 domains 0 (0 to 0) and the median tier rank 136; the resilient score, the mean score sum over simulations, is 300 [experiment_objectives].

Why

Without shocks the index ends +2.800 higher on average, so the shocks cost about 2.800 index points [experiment_probe_attribution].

Holding instead of following this method changes the index by −0.416: 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 −0.002 and +0.002, for example 1997 build Agriculture & Food Infrastructure (6 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 +0.631 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 4 groups).

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

The simulation furthest from the median (seed 28) ends −0.02 from it, with 6 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 6.47 the model ends at 4.17, where the 2026 ratings put it at 6.73. Group scores miss by 2.53 points on average, against 0.86 for assuming nothing changed (skill −1.94); the change in each domain has the right sign in 22 per cent of domains. Furthest below history: information and influence (−3.66); furthest above: human capital (−1.34) [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−0.416−31.70.00
No shocks+2.800+197.20.00
Replay of the recorded actions (must change nothing)0.0000.00.00
Without the 1st largest decision+0.002+0.20.001997 build Agriculture & Food Infrastructure (6 credits)
Without the 2nd largest decision−0.000+0.10.001997 build Export Capability & Sophistication (6 credits)
Without the 3rd largest decision−0.002−0.10.001997 build Foundational Education (6 credits)
Without the 4th largest decision−0.002−0.10.001997 build Population Health (6 credits)
Without the 5th largest decision+0.002+0.20.001998 build Agriculture & Food Infrastructure (6 credits)
Without the 1st largest shock+0.600+41.50.002024 S05 (-42.3 points)
Without the 2nd largest shock+0.537+37.50.002020 S10 (-33.3 points)
Without the 3rd largest shock+0.631+44.70.001998 S07 (-30.5 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
Legitimacy rupture S05Shock100 per cent19.5−36.2
Breadbasket failure S06Shock100 per cent19.0−17.2
Core disaster S07Shock100 per cent2.0−30.5
Severe pandemic S10Shock100 per cent24.0−33.3

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
Foundational EducationHuman Capital7.749.17 9.07 to 9.23+1.433.3449
Energy InfrastructureStrategic Infrastructure4.996.32 6.26 to 6.38+1.334.3387
Export Capability & SophisticationTrade & Investment7.197.92 7.82 to 8.04+0.733.3743
Communications & Digital InfrastructureStrategic Infrastructure8.629.10 9.07 to 9.15+0.482.3645
Industrial & Sectoral BaseProduction & Innovation7.998.07 7.95 to 8.18+0.082.5943
Nuclear DeterrenceNational Security0.000.00 0.00 to 0.000.000.000
Transport InfrastructureStrategic Infrastructure7.046.65 6.50 to 6.79−0.392.3346
Public Integrity & Anti-CorruptionGovernance & Integrity7.406.88 6.83 to 6.93−0.521.1720
Population HealthHuman Capital7.086.08 6.01 to 6.12−1.001.3322
Semiconductors & Advanced ComputingCritical Technology1.060.00 0.00 to 0.00−1.060.000
Advanced EducationHuman Capital7.646.38 6.30 to 6.46−1.260.000
Sensing, Timing & NavigationCritical Technology1.300.00 0.00 to 0.00−1.300.000
Space TechnologiesCritical Technology1.320.00 0.00 to 0.00−1.320.000
Technical & Vocational SkillsHuman Capital6.455.12 5.07 to 5.15−1.330.000
Agriculture & Food InfrastructureStrategic Infrastructure8.106.76 6.67 to 6.85−1.341.2329
Digital & AI CompetenceHuman Capital7.195.83 5.79 to 5.85−1.360.000
Connectivity, Cyber & Trust TechnologiesCritical Technology3.481.97 1.96 to 1.98−1.510.000
Regulatory Governance & Strategic ControlsGovernance & Integrity7.205.65 5.64 to 5.65−1.550.000
Lifelong Learning & ReskillingHuman Capital6.404.84 4.82 to 4.86−1.560.000
Advanced Materials & ManufacturingCritical Technology2.250.68 0.66 to 0.69−1.570.000
Energy TechnologiesCritical Technology1.620.00 0.00 to 0.00−1.620.000
Quantum TechnologiesCritical Technology2.550.92 0.90 to 0.96−1.630.000
Robotics & Autonomous SystemsCritical Technology3.051.41 1.39 to 1.45−1.640.000
Research Talent & Knowledge CreationHuman Capital6.544.82 4.81 to 4.87−1.720.000
Artificial IntelligenceCritical Technology4.933.14 3.07 to 3.21−1.790.000
Advanced ManufacturingStrategic Infrastructure7.395.44 5.37 to 5.54−1.950.000
Government Effectiveness & Public AdministrationGovernance & Integrity9.407.43 7.37 to 7.47−1.971.0420
Early Childhood DevelopmentHuman Capital8.416.39 6.32 to 6.43−2.020.000
Resource InfrastructureStrategic Infrastructure4.542.50 2.46 to 2.57−2.040.000
Structural Transformation & ComplexityProduction & Innovation7.345.23 5.21 to 5.26−2.110.000
Biotechnology & Health TechnologiesCritical Technology5.203.08 3.04 to 3.11−2.120.000
Space, Aerospace & Defence InfrastructureStrategic Infrastructure3.801.62 1.53 to 1.68−2.180.000
Financial InfrastructureStrategic Infrastructure9.277.01 6.84 to 7.12−2.260.000
Health System CapabilityHuman Capital7.825.55 5.49 to 5.66−2.270.347
Technology Adoption & DiffusionProduction & Innovation6.914.64 4.62 to 4.69−2.270.000
Political Institutions & Civic ParticipationGovernance & Integrity6.784.46 4.41 to 4.50−2.320.000
Transparency, Oversight & AccountabilityGovernance & Integrity7.334.99 4.97 to 5.02−2.340.000
Intelligence & AssessmentNational Security5.703.34 3.30 to 3.38−2.360.000
Economic Output & ProductivityProduction & Innovation6.714.35 4.28 to 4.40−2.360.000
Justice System & Fundamental RightsGovernance & Integrity7.024.65 4.62 to 4.69−2.370.000
Cyber & Electromagnetic OperationsNational Security5.753.32 3.27 to 3.38−2.430.000
Joint Command, Projection & SustainmentNational Security6.143.70 3.63 to 3.77−2.440.000
Innovation & CommercialisationProduction & Innovation5.753.31 3.27 to 3.36−2.440.000
National Resilience & Crisis ManagementGovernance & Integrity9.226.78 6.70 to 6.85−2.440.000
Business Dynamism & EntrepreneurshipProduction & Innovation7.244.77 4.69 to 4.86−2.470.000
Maritime PowerNational Security3.721.24 1.21 to 1.27−2.480.000
Diaspora & Global CommunitiesInformation & Influence8.435.86 5.86 to 5.87−2.570.000
Air PowerNational Security4.672.09 2.05 to 2.14−2.580.000
Strategic Strike & Missile DefenceNational Security4.271.68 1.59 to 1.74−2.590.000
Land PowerNational Security6.123.52 3.41 to 3.56−2.600.000
Digital & Services TradeTrade & Investment7.404.80 4.78 to 4.83−2.600.000
Internal Security & OrderGovernance & Integrity7.865.18 5.14 to 5.22−2.680.000
Space OperationsNational Security3.500.79 0.72 to 0.85−2.710.000
Culture, Language & Education DiplomacyInformation & Influence6.393.67 3.62 to 3.69−2.720.000
Trade Policy & Market AccessTrade & Investment8.545.67 5.59 to 5.76−2.870.000
Alliances & Security CooperationInformation & Influence7.564.68 4.62 to 4.74−2.880.000
Labour & EmploymentProduction & Innovation6.343.46 3.42 to 3.52−2.880.000
Water, Sanitation & Waste InfrastructureStrategic Infrastructure6.823.87 3.74 to 4.00−2.950.194
Economic Leverage & DependenceTrade & Investment6.273.30 3.20 to 3.40−2.970.000
Global Value Chain PositionTrade & Investment8.665.68 5.63 to 5.80−2.980.000
Financial Regulation & IntegrityFinancial Strength8.015.02 5.00 to 5.03−2.990.000
Development Cooperation & Global AssistanceInformation & Influence4.621.61 1.51 to 1.66−3.010.000
Sovereign Capital & External Financial PowerFinancial Strength6.063.05 3.01 to 3.08−3.010.000
Financial Stability & Crisis ManagementFinancial Strength8.575.50 5.40 to 5.59−3.070.000
Diplomatic Statecraft & Global NetworksInformation & Influence7.384.08 4.01 to 4.11−3.300.000
Financial System Depth & AccessFinancial Strength8.304.80 4.77 to 4.82−3.500.000
Investment Attraction & ProjectionTrade & Investment6.723.16 3.12 to 3.20−3.560.000
Social InfrastructureStrategic Infrastructure7.763.79 3.69 to 4.04−3.970.000
Force Generation & MobilisationNational Security8.544.37 4.12 to 4.55−4.170.000
Trade Facilitation & LogisticsTrade & Investment7.393.02 3.00 to 3.04−4.370.000
Information Environment & Strategic CommunicationInformation & Influence5.520.92 0.89 to 0.95−4.600.000
Monetary & Currency CapabilityFinancial Strength8.313.12 2.96 to 3.29−5.190.000
Fiscal Capacity & Public FinanceFinancial Strength7.761.52 1.43 to 1.62−6.240.000

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: 1.4e-14
  • passscores_in_boundsscores range 0.000 to 10.279
  • 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 9.9e-07 points
  • passmove_without_shocklargest one-year move in a group with no shock landing: 0.43 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 90; 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 4 groups)
  • passspend_concentrationmedian concentration of spending across groups (HHI) 0.116; most funded group hard.strategic_infrastructure.energy_infrastructure
  • passsame_actionthe most repeated move (group and mode) appears in a median 60% of rounds

Settings and versions

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

Nation
Bangladesh (BGD)
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: Core disaster in year 2, Legitimacy rupture in year 11, Breadbasket failure in year 12, Severe pandemic in year 24, Breadbasket failure in year 26, Legitimacy rupture in year 28
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 122.9 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; 1043 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.