E4 · cycle-002.e4-chn

China, scripted, 30 years from 1996

30 simulations of 30 rounds from the 1996 position. China decides by the scripted method; scripted events: Global funding seizure in year 1, Core disaster in year 2, Market access opening in year 5, Severe pandemic in year 7, Core disaster in year 12, Global funding seizure in year 12, Global funding seizure in year 19, Trade bloc rupture in year 22, Severe pandemic in year 24.

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
5.49 (−3.63)
From 9.13; 5.47 to 5.53
Rank by index
111
From 55; 111 to 111
Domains at Tier 1
0
From 0; 0 to 0
Tier rank
56
From 36; 56 to 56

Capability index by round

Rank by index, by round

Every objective at the position and at the horizon
Objective199610th percentileMedian90th percentileBetter
Capability indexprimary9.135.475.495.53higher
Rank by index55111111111lower
Tier rank36565656lower
Domains at Tier 10000higher
Score sum659.5404.7406.6409.0higher
Goal-weighted score659.5404.7406.6409.0higher
Resilient score659.5406.8 (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 79 per cent, buy took 4 per cent, partner took 16 per cent of the 490 credits a simulation spent on actions.

Against history

Started from a reconstructed 1996 position and played along the pathway and shocks China 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
9.13
reconstructed
Observed 2026
15.64
the Index's rating
Simulated 2026
5.50
5.40 to 5.60
Skill against persistence
−0.50
group error 10.18 against 6.76 if nothing changed
Domain1996ObservedSimulatedBiasDirection
Critical Technology5.9417.763.09 3.0–3.2−14.67wrong
Strategic Infrastructure10.5217.437.52 7.3–7.7−9.91wrong
National Security8.7517.306.24 6.1–6.3−11.06wrong
Human Capital9.4213.636.49 6.4–6.6−7.14wrong
Information & Influence9.1816.475.46 5.4–5.5−11.01wrong
Governance & Integrity8.9210.756.16 6.1–6.2−4.59wrong
Financial Strength9.6514.963.72 3.6–3.8−11.23wrong
Production & Innovation9.6715.455.06 5.0–5.2−10.39wrong
Trade & Investment10.0917.065.74 5.7–5.8−11.32wrong

The history it was played under: shocks and events

  • 1997 · S02 × 0.5 The Asian financial crisis hit regional demand and foreign investment, but China's capital controls and currency peg limited direct financial contagion.
  • 1998 · S07 × 0.8 Catastrophic Yangtze and Songhua flooding killed thousands, displaced millions and shut down economic activity across central China.
  • 2001 · S12 × 1 WTO membership opened markets and locked in export-led growth, attracting manufacturing foreign direct investment.
  • 2003 · S10 × 0.5 The SARS outbreak exposed weaknesses in epidemic response and caused regional economic disruption.
  • 2008 · S07 × 0.7 The Wenchuan earthquake devastated Sichuan, destroying infrastructure and industrial capacity.
  • 2008 · S02 × 0.7 The global financial crisis caused a collapse in export demand and prompted a massive domestic stimulus.
  • 2015 · S02 × 0.5 The Shanghai stock market crash forced state intervention and exposed weaknesses in margin finance and market regulation.
  • 2018 · S01 × 0.9 US tariffs and semiconductor export controls fragmented trade and accelerated China's technology self-reliance drive.
  • 2020 · S10 × 1.2 The COVID-19 outbreak in Wuhan triggered nationwide lockdowns, disrupted supply chains and required massive public health mobilisation.

The pathway: what it prioritised, period by period

  • 1997–2002 · build · 5% each State-led infrastructure expansion and state-owned enterprise reform supported the export-led growth strategy ahead of WTO accession. (Transport Infrastructure, Energy Infrastructure, Trade Policy & Market Access, Industrial & Sectoral Base, Export Capability & Sophistication)
  • 2001–2006 · partner · 2% each WTO membership and foreign direct investment integrated China into global value chains and upgraded export processing. (Export Capability & Sophistication, Investment Attraction & Projection, Trade Policy & Market Access, Resource Infrastructure, Global Value Chain Position)
  • 2006–2010 · build · 5% each The 11th Five-Year Plan and post-crisis stimulus launched high-speed rail, energy expansion and indigenous innovation programmes. (Transport Infrastructure, Energy Infrastructure, Research Talent & Knowledge Creation, Space Technologies, Advanced Materials & Manufacturing)
  • 2010–2015 · buy · 2% each The strategic emerging industries initiative targeted advanced manufacturing, semiconductors, biotech and clean energy through state funding and technology acquisition. (Advanced Manufacturing, Semiconductors & Advanced Computing, Biotechnology & Health Technologies, Energy Technologies, Space Technologies)
  • 2015–2020 · build · 5% each Made in China 2025 and the national AI strategy directed national resources to technological self-reliance across digital and frontier sectors. (Artificial Intelligence, Semiconductors & Advanced Computing, Connectivity, Cyber & Trust Technologies, Robotics & Autonomous Systems, Space Technologies)
  • 2020–2026 · build · 5% each Dual circulation and tech self-reliance intensified state-led investment in semiconductors, AI, quantum, clean energy and biotech amid US export controls. (Semiconductors & Advanced Computing, Artificial Intelligence, Quantum Technologies, Energy Technologies, Biotechnology & Health Technologies)

Reconstruction notes (deepseek-v4-pro): The main uncertainty is condensing China's vast regional heterogeneity into a single national score, particularly for military and technology capabilities where 1996 data are opaque. The relative scale against the 1996 world frontier is also imprecise for sectors such as AI and quantum where China's later rise was not yet visible. Mapping real-world crises and policy packages to the event library necessarily simplifies complex, overlapping developments.

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

China played 30 rounds from 1996 under the scripted method, with scripted events, 30 times. Its capability index moved from 9.13 to a median of 5.49 (−3.63), with 90 per cent of simulations between 5.46 and 5.53 [experiment_objectives].

Starting position

In 1996 the nation ranks 55 on the index against the frozen field, holds 0 of nine domains at Tier 1 and has a tier rank of 36. Its base income is 240 credits a year, calibrated so that its 2026 position is affordable with headroom for investment.

What was decided

A simulation spent a median of 490 credits on moves. The five groups that took most were Transport Infrastructure (build, 107 credits, 21.7 per cent); Energy Infrastructure (build, 94 credits, 19.2 per cent); Trade Policy & Market Access (build, 65 credits, 13.4 per cent); Industrial & Sectoral Base (build, 52 credits, 10.5 per cent); Research Talent & Knowledge Creation (build, 29 credits, 5.9 per cent) [experiment_decisions_by_group]. By mode: build 79 per cent, partner 16 per cent, buy 4 per cent [experiment_decisions_by_group]. Concentration of spending (HHI) had a median of 0.136, and the most repeated action appeared in 37 per cent of rounds.

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

What the world did

A median simulation saw 8 shocks and 1 upside events. The most damaging per firing were S10 (60 firings in 30 simulations, −40.5 points each); S07 (60 firings in 30 simulations, −39.9 points each); S01 (30 firings in 30 simulations, −33.6 points each) [experiment_shocks]. Upside events fired 30 times across all simulations [experiment_shocks].

The groups that lost most to shocks, per simulation: Fiscal Capacity & Public Finance −7.49; Trade Facilitation & Logistics −7.48; Financial System Depth & Access −6.25; Labour & Employment −5.76 [experiment_shock_damage_by_group].

The edges that carried most change through the graph, per simulation: Fiscal Capacity & Public Finance to Force Generation & Mobilisation (−1.48 points); Fiscal Capacity & Public Finance to Social Infrastructure (−1.40 points); Fiscal Capacity & Public Finance to Transport Infrastructure (−1.00 points) [experiment_propagation_by_edge].

Where it ended

At 2026 the median rank is 111 (5th to 95th percentile 110 to 111), the median count of Tier 1 domains 0 (0 to 0) and the median tier rank 56; the resilient score, the mean score sum over simulations, is 407 [experiment_objectives].

Why

Without shocks the index ends +4.647 higher on average, so the shocks cost about 4.647 index points [experiment_probe_attribution].

Holding instead of following this method changes the index by −0.181: 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 +0.003 and +0.007, for example 1997 build Transport Infrastructure (12 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 +1.231 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

tier_jump (warn): largest gain in one domain within five years: 3 tiers (30 simulations above 2).

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

The simulation furthest from the median (seed 17) ends +0.04 from it, with 8 shocks and 1 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 9.13 the model ends at 5.50, where the 2026 ratings put it at 15.64. Group scores miss by 10.18 points on average, against 6.77 for assuming nothing changed (skill −0.50); the change in each domain has the right sign in 0 per cent of domains. Furthest below history: critical technology (−14.67); furthest above: governance and integrity (−4.59) [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−0.181−12.70.00
No shocks+4.647+331.60.00
Replay of the recorded actions (must change nothing)0.0000.00.00
Without the 1st largest decision+0.007+0.30.001997 build Transport Infrastructure (12 credits)
Without the 2nd largest decision+0.006+0.20.001997 build Energy Infrastructure (12 credits)
Without the 3rd largest decision+0.004+0.30.001997 build Trade Policy & Market Access (12 credits)
Without the 4th largest decision+0.003+0.20.001997 build Industrial & Sectoral Base (12 credits)
Without the 5th largest decision+0.007+0.30.001998 build Transport Infrastructure (12 credits)
Without the 1st largest shock+1.083+77.00.002020 S10 (-59.1 points)
Without the 2nd largest shock+1.231+88.30.001998 S07 (-41.0 points)
Without the 3rd largest shock+1.027+73.90.002008 S07 (-38.8 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
Trade bloc rupture S01Shock100 per cent22.0−33.5
Global funding seizure S02Shock100 per cent10.7−13.6
Core disaster S07Shock100 per cent7.0−39.9
Severe pandemic S10Shock100 per cent15.5−40.5
Market access opening S12Upside100 per cent5.0+9.6

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
Trade Policy & Market AccessTrade & Investment10.9411.07 10.96 to 11.18+0.135.4281
Energy InfrastructureStrategic Infrastructure9.819.22 9.07 to 9.32−0.593.6094
Transport InfrastructureStrategic Infrastructure11.0010.37 10.00 to 10.63−0.633.90107
Research Talent & Knowledge CreationHuman Capital9.298.08 8.02 to 8.15−1.211.5129
Nuclear DeterrenceNational Security7.135.27 5.23 to 5.33−1.860.000
Resource InfrastructureStrategic Infrastructure10.017.83 7.75 to 7.97−2.180.8416
Regulatory Governance & Strategic ControlsGovernance & Integrity9.867.67 7.64 to 7.68−2.190.000
Advanced ManufacturingStrategic Infrastructure9.777.57 7.48 to 7.66−2.200.8915
Maritime PowerNational Security6.143.94 3.90 to 3.97−2.200.000
Technical & Vocational SkillsHuman Capital9.277.05 7.03 to 7.10−2.220.000
Political Institutions & Civic ParticipationGovernance & Integrity5.933.65 3.59 to 3.68−2.280.000
Transparency, Oversight & AccountabilityGovernance & Integrity6.554.27 4.25 to 4.32−2.280.000
Space TechnologiesCritical Technology9.357.05 6.95 to 7.18−2.300.6117
Justice System & Fundamental RightsGovernance & Integrity7.024.72 4.67 to 4.79−2.300.000
Air PowerNational Security6.324.01 3.95 to 4.05−2.310.000
Lifelong Learning & ReskillingHuman Capital8.255.86 5.81 to 5.91−2.390.000
Internal Security & OrderGovernance & Integrity11.308.91 8.83 to 9.01−2.390.000
Joint Command, Projection & SustainmentNational Security8.205.78 5.72 to 5.87−2.420.000
Advanced Materials & ManufacturingCritical Technology5.443.01 3.00 to 3.04−2.430.5610
Semiconductors & Advanced ComputingCritical Technology3.621.15 0.93 to 1.32−2.470.697
Cyber & Electromagnetic OperationsNational Security8.125.63 5.53 to 5.72−2.490.000
Space OperationsNational Security8.175.68 5.63 to 5.76−2.490.000
Intelligence & AssessmentNational Security10.618.11 8.02 to 8.19−2.500.000
Public Integrity & Anti-CorruptionGovernance & Integrity8.405.90 5.82 to 6.01−2.500.000
Connectivity, Cyber & Trust TechnologiesCritical Technology5.162.64 2.62 to 2.66−2.520.000
Strategic Strike & Missile DefenceNational Security10.477.91 7.79 to 7.96−2.560.000
Digital & AI CompetenceHuman Capital8.525.95 5.90 to 6.00−2.570.000
Quantum TechnologiesCritical Technology5.242.64 2.59 to 2.68−2.600.000
Sensing, Timing & NavigationCritical Technology5.322.72 2.68 to 2.74−2.600.000
Land PowerNational Security9.867.23 7.12 to 7.29−2.630.000
Advanced EducationHuman Capital9.406.74 6.68 to 6.83−2.660.000
Robotics & Autonomous SystemsCritical Technology5.082.41 2.37 to 2.47−2.670.000
Early Childhood DevelopmentHuman Capital10.167.23 7.06 to 7.38−2.930.000
Industrial & Sectoral BaseProduction & Innovation11.128.17 8.10 to 8.23−2.952.6052
Communications & Digital InfrastructureStrategic Infrastructure10.377.41 7.35 to 7.46−2.960.000
Energy TechnologiesCritical Technology4.781.57 1.54 to 1.59−3.210.000
Diaspora & Global CommunitiesInformation & Influence10.757.54 7.51 to 7.57−3.210.000
Artificial IntelligenceCritical Technology8.615.25 5.15 to 5.40−3.360.000
Culture, Language & Education DiplomacyInformation & Influence8.855.44 5.35 to 5.51−3.410.000
Export Capability & SophisticationTrade & Investment9.936.52 6.42 to 6.66−3.412.5232
Alliances & Security CooperationInformation & Influence8.294.86 4.81 to 4.93−3.430.000
Agriculture & Food InfrastructureStrategic Infrastructure12.739.24 9.06 to 9.45−3.490.000
Space, Aerospace & Defence InfrastructureStrategic Infrastructure10.847.28 7.01 to 7.56−3.560.000
Force Generation & MobilisationNational Security12.468.88 8.41 to 9.22−3.580.000
Population HealthHuman Capital9.185.55 5.37 to 5.63−3.630.000
Development Cooperation & Global AssistanceInformation & Influence6.612.95 2.82 to 3.04−3.660.000
Foundational EducationHuman Capital10.977.25 7.04 to 7.39−3.720.000
Financial InfrastructureStrategic Infrastructure11.287.50 7.21 to 7.66−3.780.000
Government Effectiveness & Public AdministrationGovernance & Integrity11.987.91 7.82 to 8.03−4.070.000
National Resilience & Crisis ManagementGovernance & Integrity10.286.20 6.12 to 6.35−4.080.000
Diplomatic Statecraft & Global NetworksInformation & Influence11.637.53 7.40 to 7.62−4.100.000
Structural Transformation & ComplexityProduction & Innovation9.945.69 5.64 to 5.75−4.250.000
Innovation & CommercialisationProduction & Innovation8.043.78 3.73 to 3.83−4.260.000
Technology Adoption & DiffusionProduction & Innovation8.644.30 4.24 to 4.38−4.340.000
Biotechnology & Health TechnologiesCritical Technology6.792.43 2.38 to 2.46−4.360.000
Global Value Chain PositionTrade & Investment10.726.32 6.25 to 6.47−4.401.5016
Sovereign Capital & External Financial PowerFinancial Strength9.214.81 4.77 to 4.88−4.400.000
Information Environment & Strategic CommunicationInformation & Influence8.974.43 4.38 to 4.50−4.540.000
Investment Attraction & ProjectionTrade & Investment11.066.48 6.42 to 6.57−4.581.4916
Water, Sanitation & Waste InfrastructureStrategic Infrastructure9.354.75 4.50 to 4.97−4.600.000
Business Dynamism & EntrepreneurshipProduction & Innovation9.524.86 4.69 to 5.05−4.660.000
Digital & Services TradeTrade & Investment8.213.38 3.33 to 3.44−4.830.000
Health System CapabilityHuman Capital9.754.71 4.53 to 4.89−5.040.000
Financial Regulation & IntegrityFinancial Strength9.494.36 4.33 to 4.41−5.130.000
Financial Stability & Crisis ManagementFinancial Strength9.424.19 4.04 to 4.33−5.230.000
Economic Output & ProductivityProduction & Innovation10.505.08 4.93 to 5.15−5.420.000
Economic Leverage & DependenceTrade & Investment8.983.16 3.03 to 3.30−5.820.000
Social InfrastructureStrategic Infrastructure10.034.06 3.87 to 4.49−5.970.000
Monetary & Currency CapabilityFinancial Strength10.764.69 4.45 to 4.93−6.070.000
Labour & EmploymentProduction & Innovation9.923.53 3.43 to 3.65−6.390.000
Financial System Depth & AccessFinancial Strength9.453.02 2.97 to 3.04−6.430.000
Trade Facilitation & LogisticsTrade & Investment10.773.23 3.18 to 3.28−7.540.000
Fiscal Capacity & Public FinanceFinancial Strength9.591.27 1.15 to 1.49−8.320.000

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: 2.5e-14
  • passscores_in_boundsscores range 0.787 to 15.237
  • 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 9.8e-07 points
  • passmove_without_shocklargest one-year move in a group with no shock landing: 0.71 points; 0% of simulations have one above 3
  • warntier_jumplargest gain in one domain within five years: 3 tiers (30 simulations above 2)
  • passall_tier1_from_outside_top10starting rank 55; 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)
  • passsaturation_low0% of simulations end with a group at 0 that did not start there (median 0 groups)
  • passspend_concentrationmedian concentration of spending across groups (HHI) 0.136; most funded group hard.strategic_infrastructure.transport_infrastructure
  • passsame_actionthe most repeated move (group and mode) appears in a median 37% of rounds

Settings and versions

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

Nation
China (CHN)
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: Global funding seizure in year 1, Core disaster in year 2, Market access opening in year 5, Severe pandemic in year 7, Core disaster in year 12, Global funding seizure in year 12, Global funding seizure in year 19, Trade bloc rupture in year 22, Severe pandemic in year 24
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 239.6 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
4.3 seconds in all; 1071 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.