E4 · cycle-003.e4-sgp

Singapore, scripted, 30 years from 1996

30 simulations of 30 rounds from the 1996 position. Singapore decides by the scripted method; scripted events: Global funding seizure in year 1, Severe pandemic in year 7, Global funding seizure in year 12, Trade bloc rupture in year 22, Severe pandemic in year 24.

Model 0.2.0 · graph 0.2.0 · parameters 0.1.1 · seeds 1–30 · elasticity sampled within each bracket

The same configuration in other cycles: cycle 2.

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: 15.24 (−0.01); From 15.25; 15.23 to 15.25
Rank by index: 10; From 10; 10 to 10
Domains at Tier 1: 6; From 6; 6 to 6
Tier rank: 2; From 2; 2 to 2

Capability index by round

Rank by index, by round

Every objective at the position and at the horizon
Objective	1996	10th percentile	Median	90th percentile	Better
Capability indexprimary	15.25	15.23	15.24	15.25	higher
Rank by index	10	10	10	10	lower
Tier rank	2	2	2	2	lower
Domains at Tier 1	6	6	6	6	higher
Score sum	1093.1	1103.7	1104.4	1104.9	higher
Goal-weighted score	1093.1	1103.7	1104.4	1104.9	higher
Resilient score	1093.1	1104.4 (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 78 per cent, buy took 22 per cent, partner took 0 per cent of the 5,902 credits a simulation spent on actions.

Against history

Started from a reconstructed 1996 position and played along the pathway and shocks Singapore 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: 15.25; reconstructed
Observed 2026: 15.20; the Index's rating
Simulated 2026: 15.24; 15.20 to 15.28
Skill against persistence: −0.26; group error 1.99 against 1.57 if nothing changed

Domain	1996	Observed	Simulated	Bias	Direction
Critical Technology	11.84	12.56	14.88 14.8–14.9	+2.32	right
Strategic Infrastructure	15.72	14.49	15.24 15.2–15.3	+0.75	right
National Security	10.47	12.10	10.29 10.2–10.3	−1.81	wrong
Human Capital	16.42	17.20	18.09 18.1–18.1	+0.89	right
Information & Influence	12.78	13.14	11.80 11.7–11.8	−1.34	wrong
Governance & Integrity	16.76	15.21	16.08 16.1–16.1	+0.87	right
Financial Strength	18.40	17.82	17.39 17.4–17.4	−0.43	right
Production & Innovation	17.16	16.19	17.31 17.3–17.4	+1.12	wrong
Trade & Investment	17.67	18.08	16.09 16.1–16.1	−2.00	wrong

The history it was played under: shocks and events

1997 · S02 × 0.5 Asian Financial Crisis hit Singapore through regional contagion, capital flight and a sharp recession despite strong domestic fundamentals.
2003 · S10 × 0.45 SARS outbreak infected 238 people in Singapore, killed 33, and severely disrupted tourism, retail and regional travel.
2008 · S02 × 0.6 Global financial crisis caused Singapore's trade-dependent economy to contract sharply, though its banks and reserves remained stable.
2018 · S01 × 0.4 US-China trade war and technology restrictions disrupted Singapore's entrepot trade, electronics exports and supply-chain role.
2020 · S10 × 0.7 COVID-19 pandemic closed borders, collapsed tourism and aviation, and caused Singapore's deepest recession since independence despite strong public health response.

The pathway: what it prioritised, period by period

1997–2003 · build · 5% each Asian Financial Crisis recovery and Industry 21 pushed upgrading of manufacturing, finance and productivity. (Financial Regulation & Integrity, Financial Stability & Crisis Management, Economic Output & Productivity, Semiconductors & Advanced Computing, Advanced Manufacturing)
2000–2006 · buy · 5% each Biomedical Sciences Initiative attracted global pharmaceutical manufacturing and built Biopolis research capacity. (Biotechnology & Health Technologies, Research Talent & Knowledge Creation, Advanced Education, Innovation & Commercialisation, Advanced Manufacturing)
2006–2011 · build · 5% each Research, Innovation and Enterprise 2010 broadened R&D beyond biomedicine and digitised services. (Research Talent & Knowledge Creation, Innovation & Commercialisation, Connectivity, Cyber & Trust Technologies, Digital & AI Competence, Technology Adoption & Diffusion)
2010–2015 · build · 5% each Productivity and Innovation Credit and SkillsFuture framework pushed workforce upgrading and SME productivity. (Technical & Vocational Skills, Lifelong Learning & Reskilling, Economic Output & Productivity, Business Dynamism & Entrepreneurship, Technology Adoption & Diffusion)
2014–2020 · build · 5% each Smart Nation initiative integrated digital identity, payments, sensors and cybersecurity across government and economy. (Connectivity, Cyber & Trust Technologies, Artificial Intelligence, Digital & AI Competence, Communications & Digital Infrastructure, Government Effectiveness & Public Administration)
2016–2025 · build · 5% each RIE2020 and RIE2025 expanded national research into AI, quantum, autonomy, semiconductors and biomedicine. (Artificial Intelligence, Robotics & Autonomous Systems, Semiconductors & Advanced Computing, Quantum Technologies, Biotechnology & Health Technologies)
2018–2026 · buy · 5% each Defence modernisation procured F-35s, submarines and digital/cyber capabilities while maintaining conscription and reserves. (Air Power, Maritime Power, Cyber & Electromagnetic Operations, Intelligence & Assessment, Force Generation & Mobilisation)

Reconstruction notes (deepseek-v4-pro): Scores for a city-state require care: high per-capita quality in infrastructure, finance, education and governance earns advanced or frontier scores, but small absolute scale on defence, agriculture and natural-resource groups lowers them. Intelligence, cyber and some critical-technology capabilities are only partly observable, so those scores carry wider uncertainty. The event magnitudes reflect Singapore's exposure through trade and openness rather than domestic institutional failure.

Report

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

Batch cycle-003. Model 0.2.0, graph 0.2.0, parameters 0.1.1. 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

Singapore played 30 rounds from 1996 under the scripted method, with scripted events, 30 times. Its capability index moved from 15.25 to a median of 15.24 (−0.01), with 90 per cent of simulations between 15.23 and 15.25 [experiment_objectives].

Starting position

In 1996 the nation ranks 10 on the index against the frozen field, holds 6 of nine domains at Tier 1 and has a tier rank of 2. Its base income is 1,154 credits a year, calibrated so that its 2026 position is affordable with headroom for investment.

What was decided

A simulation spent a median of 5,900 credits on moves. The five groups that took most were Semiconductors & Advanced Computing (build, 594 credits, 10.1 per cent); Economic Output & Productivity (build, 504 credits, 8.5 per cent); Artificial Intelligence (build, 461 credits, 7.8 per cent); Financial Stability & Crisis Management (build, 412 credits, 7.0 per cent); Financial Regulation & Integrity (build, 412 credits, 7.0 per cent) [experiment_decisions_by_group]. By mode: build 78 per cent, buy 22 per cent [experiment_decisions_by_group]. Concentration of spending (HHI) had a median of 0.072, and the most repeated action appeared in 37 per cent of rounds.

The leading domain by period: rounds 1 to 5, Financial Strength; rounds 6 to 10, Human Capital; rounds 11 to 15, Human Capital; rounds 16 to 20, Human Capital; rounds 21 to 25, Critical Technology; rounds 26 to 30, Critical Technology [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 (60 firings in 30 simulations, −17.1 points each); S01 (30 firings in 30 simulations, −10.8 points each); S02 (60 firings in 30 simulations, −8.6 points each) [experiment_shocks].

The groups that lost most to shocks, per simulation: Labour & Employment −1.90; Fiscal Capacity & Public Finance −1.87; Biotechnology & Health Technologies −1.81; Trade Facilitation & Logistics −1.80 [experiment_shock_damage_by_group].

The edges that carried most change through the graph, per simulation: Research Talent & Knowledge Creation to Innovation & Commercialisation (+1.04 points); Research Talent & Knowledge Creation to Biotechnology & Health Technologies (+0.84 points); Economic Output & Productivity to Fiscal Capacity & Public Finance (+0.55 points) [experiment_propagation_by_edge].

Where it ended

At 2026 the median rank is 10 (5th to 95th percentile 10 to 10), the median count of Tier 1 domains 6 (6 to 6) and the median tier rank 2; the resilient score, the mean score sum over simulations, is 1,104 [experiment_objectives].

Tier 1 probability changed most in: critical technology (0 to 100 per cent of simulations); trade and investment (100 to 0 per cent of simulations) [experiment_tiers_by_round].

Why

Without shocks the index ends +0.694 higher on average, so the shocks cost about 0.694 index points [experiment_probe_attribution].

Holding instead of following this method changes the index by −1.112: 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 −0.001 and +0.003, for example 2003 build Financial Regulation & Integrity (60 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 +0.241 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_high (warn): 100% of simulations end with a group at 20 that did not start there (median 4 groups).

retired_words (warn): e4-sgp/report.md: 'simulations' 1 time(s), first near line 39; use 'simulations'.

The simulation furthest from the median (seed 4) ends −0.01 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 15.25 the model ends at 15.24, where the 2026 ratings put it at 15.20. Group scores miss by 1.99 points on average, against 1.57 for assuming nothing changed (skill −0.26); the change in each domain has the right sign in 56 per cent of domains. Furthest below history: trade and investment (−2.00); furthest above: critical technology (+2.32) [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.

Probe	Index	Score sum	Tier 1	For example
Hold instead of the method	−1.112	−88.3	−4.00
No shocks	+0.694	+42.7	+1.00
Replay of the recorded actions (must change nothing)	0.000	0.0	0.00
Without the 1st largest decision	0.000	+0.0	0.00	2003 build Financial Regulation & Integrity (60 credits)
Without the 2nd largest decision	0.000	+0.0	0.00	2003 build Financial Stability & Crisis Management (60 credits)
Without the 3rd largest decision	−0.000	0.0	0.00	2003 build Economic Output & Productivity (60 credits)
Without the 4th largest decision	+0.003	+0.2	0.00	2004 buy Biotechnology & Health Technologies (60 credits)
Without the 5th largest decision	−0.001	−0.0	0.00	2004 buy Research Talent & Knowledge Creation (60 credits)
Without the 1st largest shock	+0.241	+15.1	0.00	2020 S10 (-20.9 points)
Without the 2nd largest shock	+0.190	+13.5	+1.00	2003 S10 (-13.2 points)
Without the 3rd largest shock	+0.145	+9.2	+1.00	2018 S01 (-10.8 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 S01	Shock	100 per cent	22.0	−10.8
Global funding seizure S02	Shock	100 per cent	6.5	−8.6
Severe pandemic S10	Shock	100 per cent	15.5	−17.1

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.

Find a group

Domain

73 of 73 groups

Capability group	Domain	1996	2026	Change	Levels invested	Credits
Robotics & Autonomous Systems	Critical Technology	12.06	20.00 20.00 to 20.00	+7.94	9.68	280
Artificial Intelligence	Critical Technology	12.43	20.00 20.00 to 20.00	+7.57	9.94	461
Research Talent & Knowledge Creation	Human Capital	13.61	19.65 19.63 to 19.65	+6.04	9.60	597
Quantum Technologies	Critical Technology	7.03	12.08 11.88 to 12.40	+5.05	5.23	100
Biotechnology & Health Technologies	Critical Technology	14.23	19.03 19.00 to 19.05	+4.80	7.42	318
Lifelong Learning & Reskilling	Human Capital	15.15	19.80 19.79 to 19.80	+4.65	13.73	236
Innovation & Commercialisation	Production & Innovation	15.83	19.66 19.57 to 19.72	+3.83	6.69	507
Connectivity, Cyber & Trust Technologies	Critical Technology	16.11	19.89 19.89 to 19.90	+3.78	8.49	402
Technical & Vocational Skills	Human Capital	16.32	19.79 19.78 to 19.79	+3.47	11.47	236
Economic Output & Productivity	Production & Innovation	16.18	19.53 19.52 to 19.53	+3.35	8.66	504
Semiconductors & Advanced Computing	Critical Technology	16.79	20.00 20.00 to 20.00	+3.21	5.45	594
Advanced Education	Human Capital	16.41	19.54 19.53 to 19.56	+3.13	3.93	291
Digital & AI Competence	Human Capital	17.37	18.66 18.59 to 18.78	+1.29	1.68	33
Advanced Manufacturing	Strategic Infrastructure	18.72	20.00 19.90 to 20.00	+1.28	3.63	441
Air Power	National Security	13.73	14.37 14.36 to 14.38	+0.64	1.15	58
Financial Regulation & Integrity	Financial Strength	19.11	19.20 19.19 to 19.21	+0.09	4.12	412
Maritime Power	National Security	12.82	12.83 12.75 to 12.87	+0.01	0.47	21
Nuclear Deterrence	National Security	0.00	0.00 0.00 to 0.00	0.00	0.00	0
Cyber & Electromagnetic Operations	National Security	12.86	12.77 12.68 to 12.85	−0.09	0.00	0
Intelligence & Assessment	National Security	12.57	12.42 12.28 to 12.53	−0.15	0.00	0
Space Technologies	Critical Technology	3.53	3.20 3.18 to 3.21	−0.33	0.00	0
Advanced Materials & Manufacturing	Critical Technology	15.74	15.39 15.11 to 15.57	−0.35	0.00	0
Space Operations	National Security	5.78	5.43 5.41 to 5.44	−0.35	0.00	0
Land Power	National Security	11.47	11.03 11.01 to 11.06	−0.44	0.00	0
Joint Command, Projection & Sustainment	National Security	12.00	11.54 11.51 to 11.55	−0.46	0.00	0
Financial Stability & Crisis Management	Financial Strength	19.67	19.20 19.18 to 19.22	−0.47	3.94	412
Strategic Strike & Missile Defence	National Security	9.87	9.37 9.33 to 9.39	−0.50	0.00	0
Agriculture & Food Infrastructure	Strategic Infrastructure	10.03	9.51 9.48 to 9.53	−0.52	0.00	0
Force Generation & Mobilisation	National Security	13.64	13.12 13.07 to 13.15	−0.52	0.00	0
Energy Technologies	Critical Technology	9.52	8.99 8.86 to 9.07	−0.53	0.00	0
Communications & Digital Infrastructure	Strategic Infrastructure	18.41	17.83 17.81 to 17.85	−0.58	0.00	0
Space, Aerospace & Defence Infrastructure	Strategic Infrastructure	11.33	10.74 10.70 to 10.76	−0.59	0.00	0
Justice System & Fundamental Rights	Governance & Integrity	15.50	14.90 14.89 to 14.92	−0.60	0.00	0
Transparency, Oversight & Accountability	Governance & Integrity	14.36	13.76 13.75 to 13.77	−0.60	0.00	0
Internal Security & Order	Governance & Integrity	17.84	17.24 17.22 to 17.25	−0.60	0.00	0
Regulatory Governance & Strategic Controls	Governance & Integrity	18.24	17.63 17.63 to 17.64	−0.61	0.00	0
Resource Infrastructure	Strategic Infrastructure	14.11	13.48 13.45 to 13.52	−0.63	0.00	0
Energy Infrastructure	Strategic Infrastructure	14.79	14.16 14.13 to 14.18	−0.63	0.00	0
Political Institutions & Civic Participation	Governance & Integrity	14.37	13.74 13.73 to 13.76	−0.63	0.00	0
Public Integrity & Anti-Corruption	Governance & Integrity	18.05	17.42 17.40 to 17.45	−0.63	0.00	0
Water, Sanitation & Waste Infrastructure	Strategic Infrastructure	15.50	14.86 14.82 to 14.89	−0.64	0.00	0
Transport Infrastructure	Strategic Infrastructure	18.92	18.26 18.21 to 18.30	−0.66	0.00	0
Early Childhood Development	Human Capital	17.50	16.83 16.79 to 16.86	−0.67	0.00	0
Culture, Language & Education Diplomacy	Information & Influence	10.90	10.11 10.02 to 10.17	−0.79	0.00	0
Financial Infrastructure	Strategic Infrastructure	18.53	17.74 17.68 to 17.78	−0.79	0.00	0
Sensing, Timing & Navigation	Critical Technology	10.98	10.18 10.10 to 10.25	−0.80	0.00	0
Development Cooperation & Global Assistance	Information & Influence	11.60	10.79 10.72 to 10.86	−0.81	0.00	0
Government Effectiveness & Public Administration	Governance & Integrity	19.07	18.19 18.14 to 18.24	−0.88	0.00	0
Technology Adoption & Diffusion	Production & Innovation	18.85	17.96 17.91 to 18.00	−0.89	0.00	0
Population Health	Human Capital	16.53	15.62 15.58 to 15.67	−0.91	0.00	0
National Resilience & Crisis Management	Governance & Integrity	16.69	15.77 15.74 to 15.79	−0.92	0.00	0
Diaspora & Global Communities	Information & Influence	10.36	9.43 9.42 to 9.45	−0.93	0.00	0
Foundational Education	Human Capital	18.13	17.16 17.12 to 17.19	−0.97	0.00	0
Diplomatic Statecraft & Global Networks	Information & Influence	15.46	14.49 14.41 to 14.57	−0.97	0.00	0
Social Infrastructure	Strategic Infrastructure	16.83	15.84 15.78 to 15.90	−0.99	0.00	0
Health System Capability	Human Capital	16.80	15.81 15.77 to 15.86	−0.99	0.00	0
Alliances & Security Cooperation	Information & Influence	15.46	14.44 14.42 to 14.47	−1.02	0.00	0
Industrial & Sectoral Base	Production & Innovation	15.96	14.78 14.75 to 14.80	−1.18	0.00	0
Structural Transformation & Complexity	Production & Innovation	17.39	16.20 16.18 to 16.23	−1.19	0.00	0
Sovereign Capital & External Financial Power	Financial Strength	17.10	15.90 15.87 to 15.93	−1.20	0.00	0
Business Dynamism & Entrepreneurship	Production & Innovation	18.82	17.61 17.57 to 17.66	−1.21	0.00	0
Digital & Services Trade	Trade & Investment	17.10	15.81 15.79 to 15.84	−1.29	0.00	0
Information Environment & Strategic Communication	Information & Influence	12.91	11.54 11.46 to 11.59	−1.37	0.00	0
Fiscal Capacity & Public Finance	Financial Strength	18.76	17.38 17.25 to 17.51	−1.38	0.00	0
Financial System Depth & Access	Financial Strength	17.25	15.81 15.80 to 15.82	−1.44	0.00	0
Global Value Chain Position	Trade & Investment	19.97	18.42 18.37 to 18.44	−1.55	0.00	0
Export Capability & Sophistication	Trade & Investment	17.64	16.07 16.01 to 16.12	−1.57	0.00	0
Economic Leverage & Dependence	Trade & Investment	12.15	10.58 10.55 to 10.61	−1.57	0.00	0
Investment Attraction & Projection	Trade & Investment	19.29	17.71 17.67 to 17.76	−1.58	0.00	0
Trade Policy & Market Access	Trade & Investment	17.73	16.14 16.12 to 16.18	−1.59	0.00	0
Labour & Employment	Production & Innovation	17.08	15.48 15.40 to 15.54	−1.60	0.00	0
Monetary & Currency Capability	Financial Strength	18.49	16.85 16.81 to 16.88	−1.64	0.00	0
Trade Facilitation & Logistics	Trade & Investment	19.81	17.88 17.85 to 17.90	−1.93	0.00	0

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-13
passscores_in_boundsscores range 0.000 to 20.000
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 1.0e-06 points
passmove_without_shocklargest one-year move in a group with no shock landing: 2.91 points; 0% of simulations have one above 3
passtier_jumplargest gain in one domain within five years: 2 tiers (0 simulations above 2); tiers are reported, not an objective
passall_tier1_from_outside_top10starting rank 10; 0 simulations reach Tier 1 in all nine domains
warnsaturation_high100% of simulations end with a group at 20 that did not start there (median 4 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) 0.072; most funded group soft.human_capital.research_talent_and_knowledge_creation
passsame_actionthe most repeated move (group and mode) appears in a median 37% of rounds
passregression_index_p50index_p50 moved 0.7% since cycle-002 (15.34 to 15.24); versions changed (0.1.0 to 0.1.1, graph 0.2.0 to 0.2.0)
passregression_score_sum_p50score_sum_p50 moved 0.6% since cycle-002 (1111.46 to 1104.42); versions changed (0.1.0 to 0.1.1, graph 0.2.0 to 0.2.0)

Settings and versions

Experiment cycle-003.e4-sgp. Every simulation records the model, graph and parameter versions, the scenario, the method and its seed, so it can be reproduced exactly.

Nation: Singapore (SGP)
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, Severe pandemic in year 7, Global funding seizure in year 12, 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 1,154.4 a round, moving with the economic groups
Versions: Model 0.2.0, Capability Dependency Graph 0.2.0, parameters 0.1.1
Batch: Backcast 1996-2026 (cycle-003), cycle 3 of the improvement loop
Runtime: 7.4 seconds in all; 1910 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.