preview
The Primacy Premium
Conditional forecasts of defense and commercial markets under Chinese military primacy, 2026 to 2035
§1 the question, and the argument
If China attains nuclear parity and Indo-Pacific conventional primacy by 2035, how do global defense expenditure, arms transfer flows, and commercial risk pricing reallocate, and does the pathway to primacy condition those outcomes more strongly than the fact of primacy itself?
The argument in one line: markets do not price whether China overtakes the United States; they price how. The project therefore refuses a single scenario. It builds three, runs each through parameters measured from history, and reports full distributions. It is deliberately not called prediction. There is no training data for an event that has never occurred, so the model estimates responses from the historical record and imposes the scenario exogenously. That framing, conditional forecasting with Monte Carlo uncertainty propagation, is the stronger epistemic position and the project states it plainly.
§2 three pathways to one endpoint
Accretion
China grows, the United States grows more slowly. The balance closes without an event. Hedging is gradual and markets reprice at the margin.
Anchored on measured 2015 to 2025 real growth: China +5.5% and the USA +1.0% per year.
Retrenchment
Primacy arrives because Washington withdraws. Allied budgets and supplier choices move first, before any Chinese gain.
Anchored on the peace dividend, the only measured decade of sustained US real contraction: -3.8% per year, 1988 to 1998.
Demonstration
A contingency resolves in Beijing's favor. Repricing is discontinuous: the shock quarter matters as much as the decade.
Anchored on the one modern observation of this class: the 2022 freezing of Russian reserves, replayed at a random quarter, 2028 to 2031.
If the model produced similar outputs across those three roads, the model would be wrong. Pathway divergence is the test, not the assumption.
§3 the hypothesis ledger
| no. | claim | status in this build |
|---|---|---|
| H1 | Identical 2035 endpoints, reached by different pathways, produce statistically distinguishable outcomes in defense expenditure and arms transfer flows. | awaiting layers 2 and 4 |
| H2 | American retrenchment moves allied budgets and supplier market shares faster than Chinese growth alone: the hegemon's exit is the stronger signal. | awaiting layers 2 and 4 |
| H3 | Reserve currency composition is the slowest and least pathway-sensitive of the four commercial channels; the dollar's share erodes toward diversification, not toward the renminbi. | supported in current build |
§4 method, in five stages
- Data engineering. Three parsers turn published sources into tidy, validated tables: IMF COFER quarterly reserve composition, 1999 to 2026 (parse_cofer.py, with an independent share reconciliation that must pass to 0.05 pp); the SIPRI Military Expenditure Database, 1949 to 2025, in constant 2024 dollars (parse_milex.py); and the SIPRI Arms Transfers Database, both the global delivery series from 1950 and a thirty-thousand-row deal register aggregated into supplier concentration (parse_arms_transfers.py).
- Historical calibration. Every parameter the simulation consumes is estimated, none assumed (calibrate.py). The reserve channel response is a Newey-West regression of quarterly dollar-share changes on the year-over-year change in the log China to US expenditure ratio; named calibration cases (the peace dividend, the 2022 sanctions shock, the accretion decade) are computed from the panel and written to a single JSON artifact with confidence intervals attached.
- Conditional simulation. A Monte Carlo engine (simulate.py) propagates three uncertainties jointly, parameter, innovation, and scenario timing, through 10,000 draws per pathway per currency to 2035-Q4. Innovations are bootstrapped from measured residuals, so simulated quarters keep the true fat tails. Everything is seeded and reproducible.
- Visualization. Four plates (make_figures.py) and this page (build_preview.py), which injects the computed numbers so that no figure in the text can drift from the model that produced it.
- Analytic handoff. Tidy exports (simulation_fan.csv and the processed tables) load directly into Power BI or Tableau for interactive exploration; the repository is the model of record.
§5 the plates
| the ledger at 2026-Q1 | usd | eur | jpy | gbp | cny | other |
|---|---|---|---|---|---|---|
| share of allocated reserves, % | 57.1 | 20.0 | 5.4 | 4.4 | 2.0 | 6.2 |
§6 what the current build finds
- The defense coefficient is a precisely estimated near-null: a one-log-point year-over-year change in the China to US expenditure ratio moves the quarterly dollar share by +1.04 pp, 95% CI [-0.80, +2.88], n = 105 quarters. The interval spans zero; the model cannot even resolve the sign of the pathway effect on reserves.
- Median 2035-Q4 dollar share: 50.7% under accretion, 52.8% under retrenchment, 51.3% under demonstration, against an 80% band of roughly 44 to 58%. Pathway separation is 0.36 standard deviations of endpoint spread: small, as H3 predicts.
- The probability the dollar falls below half of allocated reserves by 2035 ranges from 0.33 to 0.45 across pathways: material under every road, decisive under none.
- The renminbi diverges where the dollar does not: a median 2035 share of 3.2% under accretion against 0.0% under a 2022-style demonstration. The reserve channel punishes the challenger for coercion.
Read honestly: the demonstration replay rests on a single modern precedent (n = 1, the 2022 sanctions episode) sustained for the remaining horizon, which makes the renminbi collapse an upper bound on reversal, not a point forecast. Valuation effects in COFER are unadjusted in this preview and are flagged for the exchange-rate-adjusted robustness series in the monograph.
§7 falsification tripwires
A model someone can use is a model that names, in advance, the observables that would break it:
- Allied defense expenditure as a share of GDP, against the pathway II elasticities.
- Arms import supplier diversification (the Herfindahl of Plate III) among US treaty allies.
- Renminbi share in trade settlement versus its COFER reserve share: the settlement-reserve gap should widen under accretion and snap shut only with convertibility, not coercion.
- The nontraditional-currency share of reserves, which should keep absorbing the dollar's decline under every pathway.
- Defense equity and war-risk premia behavior around Taiwan Strait exercise events, once the layer 4 event studies are estimated.
§8 status of the work
Complete in this preview
- Full data pipeline over three primary sources, with validation gates
- Calibration of the reserve channel and three named historical cases
- Monte Carlo engine: 10,000 seeded draws, three uncertainty sources
- H3 tested end to end; four plates; BI-ready exports
In progress for the monograph
- Layer 2 system dynamics: arms-race and alliance feedback
- Layer 4 event studies: war risk premia, semiconductors, shipping
- Chinese budget opacity carried as a distribution, not a choice
- Exchange-rate-adjusted COFER robustness series; H1 and H2 tests
§9 data and reproduction
Sources: IMF, Currency Composition of Official Foreign Exchange Reserves (COFER), quarterly through 2026-Q1, retrieved 24 July 2026; SIPRI Military Expenditure Database, 1949 to 2025 (v1.2, April 2026); SIPRI Arms Transfers Database, trend indicator values and trade register, retrieved 24 July 2026. Raw files are not redistributed here; the README explains where to obtain them and where to place them. The pipeline then reproduces every number on this page in order: parse_cofer.py, parse_milex.py, parse_arms_transfers.py, calibrate.py, simulate.py, make_figures.py, build_preview.py. The simulation fan and processed tables import directly into Power BI or Tableau.