Global Data Investigation · 2025
How armed conflicts raise the cost of living for countries that never voted for them — transmitted through energy, food, and shipping markets.
CBOT settlement data · conservative range 65–72%
Freightos Baltic Index · range 200–250%
IMF · World Bank · FAO · direct transmission only
Executive Summary
This investigation examines how armed conflict functions as an involuntary economic tax on countries with no involvement in hostilities. Drawing on data from four conflicts across two decades, it identifies a repeating transmission pattern: conflict disrupts energy supplies, food commodity markets, and maritime shipping simultaneously. Price shocks travel through global trade networks and are absorbed disproportionately by import-dependent, low-income countries.
The investigation introduces the War Externality Index (WEI) — a comparative classification framework scoring countries on five structural dimensions of exposure. The same countries appear in the highest vulnerability tier across all four conflicts. All data is drawn from public institutional sources. Estimates are conservative and reflect direct price transmission only.
Key Findings
How It Works
Armed conflict activates up to three simultaneous price transmission channels. Each operates through global markets, respects no political borders, and lands with compounded force on countries whose structural characteristics leave them with the least capacity to absorb the cost. These channels are explained here once. All later sections assume reader familiarity and present evidence only.
Channel 01
Energy
Conflict disrupts oil and gas supply or transit routes. Benchmark prices rise globally. Every net energy-importing country pays more — with the cost compounded by currency depreciation in vulnerable economies.
"A single broken pipe raises pressure throughout the entire network."
Channel 02
Food
Conflict zones are often major agricultural exporters. When supply is removed from the market, global commodity prices spike. Countries with concentrated import pipelines face both the price increase and accelerated supply competition.
"Remove one major water source and every downstream user pays the scarcity premium."
Channel 03
Shipping
Conflict near shipping lanes triggers route diversion and war-risk insurance premiums. Every traded good on affected routes costs more to import — and small, high-dependency importers have least leverage to negotiate alternatives.
"When one road closes, every vehicle on the detour pays for the extra distance."
Case Study One · All Three Channels
The largest concurrent activation of all three channels since the 2008 commodity crisis.
The full-scale Russian invasion of Ukraine on February 24, 2022 produced the most significant concurrent commodity price shock in this investigation's scope. All three transmission channels activated simultaneously — wheat supply disruption, oil price escalation, and compounding container freight stress — arriving in household budgets of high-WEI countries before institutional responses were possible.
Ukraine's Black Sea ports, through which the majority of its grain exports move, were effectively closed from the first weeks of conflict. The period from February through July 2022 represented a near-complete interruption of Ukrainian wheat export capacity. Russia — the world's largest wheat exporter — faced simultaneous sanctions-driven trade uncertainty. The combined effect pushed wheat futures to levels not seen since the 2008 food crisis. [CBOT]
CBOT Wheat Futures — Jan 2021 to Dec 2022 (USD per metric ton, indicative range)
The inequality of impact is measurable at the household level. IMF spillover analysis found food price inflation in low-income countries averaged 12–15 percentage points higher than in advanced economies during 2022. World Bank household survey data from twelve developing countries found bottom-quintile households lost an estimated 3–5% of real income to food price inflation — versus 0.8–1.2% for top-quintile households in the same countries. [IMF][WB]
Currency depreciation compounded food channel effects. Bangladesh's taka depreciated approximately 20–25% against the USD in 2022. Sri Lanka's rupee fell approximately 40–45% — driven by pre-existing fiscal fragility that the commodity shock accelerated. The war did not cause all inflation in these countries. It contributed a measurable, war-aligned component through identified channels.
| Country | Wheat import share from RU/UA | Food CPI change 2022 | Reserve buffer (pre-invasion) | Est. bottom-quintile real income loss |
|---|---|---|---|---|
| Egypt | ~70–80% | +21% approx. | ~4–5 months | 5–7% (conservative range) |
| Bangladesh | ~40–55% | +8–9% (food) | ~4–5 months | 3.5–5% (conservative range) |
| Ethiopia | ~35–45% | +30–35% approx. | ~1–2 months | 6–9% (conservative range) |
| Sri Lanka | ~60–70% | +45% approx. | <1 month (crisis) | 8–11% (conservative range) |
| Pakistan | ~30–40% | +22–24% approx. | ~2–3 months | 4.5–6.5% (conservative range) |
| Tunisia | ~45–55% | +10–12% approx. | ~3 months | 3.8–5.5% (conservative range) |
Case Study Two · Shipping Channel
A sustained shipping shock layered onto commodity markets still recovering from 2022.
Beginning October 2023, Houthi forces conducted attacks on commercial vessels in the Red Sea and Bab-el-Mandeb strait. By December 2023, major container carriers had suspended Red Sea transits. The crisis activated the shipping channel in near-isolation — operating as an additional cost layer on a market environment that had not fully normalised from 2022.
Route diversion from the Suez Canal to the Cape of Good Hope added approximately 3,000–3,500 nautical miles per voyage — 10 to 14 additional sailing days at standard commercial speeds. Each additional day represents direct fuel cost, crew cost, and reduced fleet capacity as vessels complete fewer annual round trips. [UNCTAD]
Container Freight Rates — Before vs. Peak Crisis (USD per FEU, approximate ranges)
| Route | Nov 2023 (approx.) | Jan–Feb 2024 peak | Approx. change | Primary exposed importers |
|---|---|---|---|---|
| Shanghai – Rotterdam | ~USD 1,500/FEU | ~USD 5,000–5,500 | +230–270% | South Asia, East Africa, MENA |
| Shanghai – East Africa | ~USD 1,200/FEU | ~USD 3,800–4,200 | +215–250% | Kenya, Ethiopia, Tanzania |
| Asia – South Asia | ~USD 900–1,100/FEU | ~USD 2,800–3,400 | +190–240% | Bangladesh, Pakistan, India |
| War risk insurance | Near zero | ~0.5–1% vessel value/voyage | New cost layer | All Red Sea–dependent routes |
Countries most exposed to the shipping channel are precisely those the WEI identifies as most structurally vulnerable: high-import-dependency nations with limited capacity to negotiate preferential freight terms or substitute through alternative routes. Bangladesh imports approximately 85% of its raw cotton, significant wheat volumes, and refined petroleum through routes influenced by Red Sea freight pricing — meaning the cost increase embedded across multiple import categories simultaneously.
The Core Finding
The central finding of this investigation is not specific to any single war. It is the structural consistency of the transmission pattern across four geographically, politically, and militarily distinct conflicts over two decades.
The conflict's geography changes. Its political context changes. Its military dynamics change. The transmission pathway does not.
2003–2004
Iraq War
Energy Food ShippingBrent Crude: ~+100% over 18 months. Primary exposed: Sub-Saharan Africa, South Asia, Central Asia.
2011
Arab Spring / Libya
Energy Food ShippingOil ~+50%; FAO Food Price Index peak. Exposed: Egypt, Tunisia, Yemen, Jordan, Bangladesh.
2022
Russia-Ukraine War
Energy Food ShippingAll three channels simultaneously. Largest concurrent shock in study period. Exposed: Bangladesh, Egypt, Ethiopia, Sri Lanka, Pakistan.
2023–24
Red Sea Crisis
Energy Food ShippingShipping channel dominant; layered on unresolved 2022 commodity stress. Ongoing as of mid-2024. Exposed: Bangladesh, Kenya, Ethiopia, Pakistan, India.
| Conflict | Dominant channel | Est. welfare cost, bottom quintile | Recurring high-WEI countries |
|---|---|---|---|
| Iraq War 2003 | Energy | ~1.5–2.5% real income | Ethiopia, Bangladesh, Nepal, Central Africa |
| Arab Spring 2011 | Energy + Food | ~2.5–4.5% real income | Egypt, Tunisia, Yemen, Bangladesh, Jordan |
| Ukraine 2022 | Food + Energy + Shipping | ~3.5–8% real income | Bangladesh, Egypt, Ethiopia, Sri Lanka, Pakistan |
| Red Sea 2023–24 | Shipping | ~0.8–2.5% real income (ongoing) | Bangladesh, Kenya, Ethiopia, Pakistan, India |
Original Framework
The WEI is a comparative classification framework — not a welfare loss calculator or a moral ranking. It identifies which countries are structurally positioned to absorb conflict-driven commodity shocks, and why the same countries appear across multiple conflicts. Scores reflect position in global trade architecture, not governance quality.
High-WEI countries are not unlucky. They are structurally exposed — by import concentration, shallow fiscal buffers, and limited monetary resilience. These characteristics predate every conflict in this study. That is why the same countries absorb the cost each time.
Measured as the percentage of food calories consumed that are sourced through imports. High-exposure threshold: >40% of food calories. Source: FAO food balance sheets. Countries exceeding this threshold face direct exposure to global commodity price movements with limited domestic substitution. The threshold is drawn from FAO food security literature on structural import dependency.
Percentage of primary energy consumed that is imported. High-exposure threshold: >70% of petroleum products. Source: IEA / World Bank energy data. Above this level, transport, agriculture, and manufacturing costs rise simultaneously during energy price shocks, creating a broad-based cost increase that cannot be isolated to a single sector.
Central bank reserves expressed as months of import cover. High-exposure threshold: <3 months, per IMF minimum adequacy benchmark. Source: IMF International Financial Statistics. Countries below this threshold have limited capacity to defend their currency or finance temporary import cost increases through reserve drawdown, meaning commodity shocks pass directly into domestic prices.
Local currency depreciation against the USD over a preceding two-year window. High-exposure threshold: >20% depreciation. Source: BIS exchange rate data. Most commodity trade is denominated in USD; a depreciating currency creates a multiplicative (not additive) cost effect when combined with commodity price increases.
Government capacity to deploy subsidies, cash transfers, or duty adjustments. Measured through debt-to-GDP ratio, fiscal deficit position, and domestic revenue capacity. High-exposure threshold: debt >80% GDP + deficit >5%. Source: IMF Fiscal Monitor. Constrained fiscal space means commodity price shocks pass through to household budgets more completely, as governments cannot sustain cushioning measures.
The WEI does not produce a single composite score in this publication, as weighting choices would introduce analytical assumptions beyond what the data supports. The five dimensions are used qualitatively to classify countries into exposure tiers. A quantitative scoring version with explicit weighting rationale is under development and will be published in the companion technical note. All dimension data is publicly available and independently verifiable from the cited sources.
Evidence from Peer Cases
This section presents structural interventions that the cross-conflict data supports as having reduced transmission costs in specific peer cases. These are observations from evidence, not policy prescriptions.
Countries maintaining above 90 days of domestic cereal stock coverage experienced food price inflation 3–7 percentage points below countries with fewer than 30 days of coverage during commodity shock periods, based on World Bank cross-country analysis. India's stock release during the 2022 price spike contributed to food CPI running below regional peer averages for the first half of the year. Reserve maintenance has direct fiscal costs. Evidence consistently suggests those costs are smaller than the welfare costs of absorbing uncushioned shocks. [WB]
Countries that maintained supply relationships across multiple exporting regions before 2022 were better positioned to source alternative wheat supply when Black Sea exports were disrupted — accepting moderately higher prices rather than facing acute supply compression. Diversification in normal periods typically involves a cost premium. The cross-conflict evidence suggests that premium functions as insurance with positive expected value. [FAO]
Countries with functioning cash transfer or food voucher infrastructure deployed targeted support to affected households within weeks of the 2022 price surge. Countries without such infrastructure faced the choice between expensive untargeted subsidies or no response. Building social protection delivery capacity during non-crisis periods is the preparatory investment the evidence most consistently supports.
Conclusion
Across four conflicts and approximately two decades, the same structural outcome recurs: armed conflict produces commodity price increases absorbed, disproportionately, by low-income import-dependent countries with no involvement in the hostilities. The mechanism is not unpredictable. The countries most exposed are not unknown. The transmission channels are not novel.
Conservative estimates suggest low-income net food importers paid USD 8–12 billion in additional food import costs in 2022 alone — before energy or shipping costs. The full figure, across all three channels and all four conflicts, is not calculable with the precision this investigation's data discipline permits. It is substantially larger.
The wars examined here have ended or continue. The structural conditions that make certain countries absorb their economic costs remain. The next conflict will activate the same channels. The same countries will appear in the same exposure tier. This investigation cannot prevent that. It can document that the invoice exists, specify its approximate value, and identify the structural conditions that will generate it again.
NO REPARATION HAS BEEN PAID. NO MECHANISM EXISTS TO PAY IT.
The cross-conflict analysis above uses aggregated national-level data and household survey ranges. Aggregate data obscures the distributional and sectoral detail necessary for a precise accounting of how commodity shocks move through domestic supply chains to specific household categories. Bangladesh — which appears in the high-exposure tier of the WEI across all four conflicts, holds comprehensive household survey data through the BBS HIES series, and illustrates multi-channel exposure with unusual clarity — is the subject of a companion country-level audit published separately.
Read: Bangladesh's Bill → MethodologyTechnical Note
This investigation draws exclusively on publicly available data: FAO Food Price Index and GIEWS food security series; UN Comtrade bilateral trade data; Freightos Baltic Index and Baltic Exchange container and dry bulk freight data; IMF World Economic Outlook, International Financial Statistics, and Fiscal Monitor; World Bank Open Data, PovcalNet household survey database; UNCTAD Maritime Review reports; EIA Brent Crude and natural gas price series; BIS exchange rate data; UNICEF nutrition databases.
The attribution of price increases to war-driven commodity shocks is based on alignment of timing, magnitude, and transmission channel — not on formal econometric causal identification. Multiple factors contributed to inflation in all countries examined. This report attributes only the war-aligned component, identified through price decomposition and pass-through ratio methodology from IMF and World Bank literature. This distinction is explicit throughout the text and must be maintained in any citation of specific figures.
All welfare loss estimates reflect direct price transmission effects only. Excluded from estimates: second-order effects (reduced investment, fiscal deterioration acceleration, currency crisis cascades, nutrition-linked productivity losses). Including these effects would substantially increase total estimated welfare costs. This exclusion is conservative by design.
Where institutional sources reported conflicting figures for the same country and period, this investigation uses the more conservative estimate. Discrepancies are noted in the accompanying technical dataset.
The War Externality Index is an original analytical framework. It is a comparative classification tool, not a precise welfare loss calculator or governance ranking. High WEI scores reflect structural trade and financial integration characteristics that are largely independent of recent policy decisions. The framework is open to methodological critique and will be updated as new data and peer review feedback is received.