Iran War Oil Cost Tracker
Current and future U.S. costs from oil supply disruption
Last Updated: May 12th, 2026
Economic Costs to Date
The Iran war is constraining global oil supply, leading to sharply increased oil prices. Using current oil prices and consumption data from the U.S. Energy Information Administration, we track the ongoing costs of the conflict to the U.S. economy via increased oil spending by the barrel.
We use our US-AFFORD model to translate the running tab into higher gasoline and diesel prices, more expensive energy, and inflation across the economy. While some of these costs have already been experienced, some are yet to hit consumers. See more detail in the methodology below.
Projected Losses through 2026
The U.S. Energy Information Administration forecasts that the U.S. will pay an extra $282 billion for oil consumption in 2026, relative to pre-war expectations. Using the US-AFFORD model, we analyze the household impacts of this scenario, finding that it leads to:
$1,535 in increased costs per household
A $213 billion decrease in GDP
1.6 million jobs lost due to decreased household spending
An increase in oil prices leads to a decrease in household spending on other goods and services, which in turn fuels GDP and job losses across the broader economy. This map shows how much households can expect to pay in each state, both directly (via higher fuel prices) and indirectly (via broader inflation). See below for our methodology.
Methodology
Economic Costs to Date
The running tab is calculated based on observed oil prices relative to pre-disruption expectations. Weekly Europe Brent spot prices, as reported by the U.S. Energy Information Administration, are compared to the projected 2026 average price of $58 per barrel from the February 2026 Short-Term Energy Outlook (STEO). The difference between observed and projected prices is expressed as a percentage deviation from this baseline.
This percentage difference is applied to the projected $435.5 billion in U.S. petroleum expenditures for 2026, also from the February STEO. This produces an estimated incremental increase in petroleum spending for each week of higher SPOT prices.
Weekly incremental costs are calculated beginning February 27, 2026, and summed to produce the running total shown. The displayed rate of increase is derived from the most recent weekly spot price, converted into a linear incremental cost per unit of time relative to the STEO February baseline.
Per household effects of the running tab are derived from the US-AFFORD model, which is explained further below.
This tracker estimates the increase in total petroleum spending across U.S. households, businesses, and institutions. Petroleum consumption is assumed to remain consistent with February projections, implying limited short-term demand response to price changes, which is consistent with STEO assumptions in more recent publications. Weekly spot prices are used as a proxy for contemporaneous cost impacts, though real-world price pass-through to end users does not happen in real time. These estimates do not account for changes in consumer behavior, substitution effects, inventory adjustments, or policy interventions.
It does not measure realized retail price changes for specific fuels (e.g gasoline or diesel). It also does not include broader macroeconomic impacts or net economic welfare losses, which are calculated below as part of the US-AFFORD model. As a result, these estimates should be interpreted as a first-order approximation of increased spending, rather than a full general equilibrium estimate of economic impact.
Projected Losses through 2026
Using changes in federal energy outlooks, combined with Greenline Insights’ US-AFFORD model, this analysis estimates the projected macroeconomic losses and household net losses through 2026 due to energy supply disruption.
The February 2026 STEO is used as a baseline representing pre-disruption expectations. While it acknowledges rising geopolitical tensions, it does not yet incorporate the subsequent price shock into its quantitative projections.
The May 2026 STEO reflects updated market conditions, including significantly higher projected oil prices due to supply disruption. This leads to a revised average oil price of $94.85 per barrel in 2026, compared to $58 in the February outlook. This revision implies an estimated $282 billion increase in U.S. petroleum consumption expenditures, when applying price differentials to projected U.S. consumption volume in the STEO. This incremental increase in spending serves as the primary input to the US-AFFORD model.
US-AFFORD translates economy-wide economic events into macroeconomic impacts and household-level financial impacts across states and income groups. The model allocates impacts in several stages:
Initial allocation: The increase in petroleum spending is distributed across households, industries, and institutions based on observed consumption patterns from IMPLAN.
Sectoral disaggregation: IMPLAN data is used to further map impacts across 500 industries, nine household income groups, and government sectors.
Government pass-through: Costs borne by government are re-allocated to households and businesses through assumed higher taxation and spending flows.
Business pass-through: Increased costs to firms are passed forward to consumers using IMPLAN’s forward linkage framework.
Household aggregation: All direct and indirect impacts are combined to estimate total household cost burdens by state and income level.
Underling data powering the AFFORD model is primarily derived from IMPLAN, reflecting 2024 economic structure and consumption patterns. Consumption behavior is assumed to remain consistent with baseline projections. The model does not account for demand responses, substitution, or efficiency improvements. All price impacts on governments and industries are assumed to fully pass through to end consumers, with the AFFORD model distinguishing between domestic and foreign consumers.
All impacts are assumed to occur within 2026 and are not distributed over time. State-level results are driven by modeled allocations and should be interpreted as estimates of relative burden, rather than precise forecasts.