Scenario simulator
Oil Price Inflation Simulator
Estimate how a change in crude oil prices could affect inflation through gasoline, energy costs, transportation, producer prices, and broader price pass-through. Results are scenario estimates based on historical research and public data, not forecasts or financial advice.
What this simulator does
Use this simulator to estimate possible CPI pressure from oil-price changes through gasoline, energy, transportation, freight, producer prices, and other pass-through channels. Results are scenario estimates, not forecasts.
Assumptions: gasoline CPI weight 3%, baseline pass-through, 12-month scenario horizon. Results are scenario estimates based on historical pass-through, not predictions.
Oil price shock
20.0%
Scenario price compared with current oil price.
Shock classification
Moderate
Based on the absolute size of the oil-price move.
Estimated gasoline price increase
10.0%
Estimated percent change in retail gasoline prices from oil pass-through.
Direct gasoline contribution to all-items CPI
+0.30%
Gasoline's direct contribution to the all-items CPI inflation rate.
Expanded energy contribution to all-items CPI
+0.30% to +0.41%
Gasoline plus direct household energy channels.
Stress scenario total CPI pressure
+0.37% to +0.54%
Direct energy effects plus possible indirect inflation pressure.
Calibrated duration model estimate
+0.35% to +0.52%
Cumulative possible CPI pressure while oil remains elevated.
Historical local projection estimate
20.52%
Estimated historical CPI response to a 10% monthly WTI oil-price shock.
Why the models differ
Direct gasoline contribution is narrow and immediate. It only measures gasoline's direct contribution to all-items CPI. The stress scenario adds possible indirect pressure from related channels. The calibrated duration model estimates cumulative pressure while oil remains elevated. The local projection model estimates historical CPI responses after oil shocks. The experimental tree-based model adds nonlinear scenario assumptions using CPI momentum, oil volatility, regional sensitivity, and duration. These are different model views, not contradictions.
Oil estimate range comparison
Models answer different questions. Direct and historical models show CPI contribution estimates; duration and GBDT models show cumulative pressure while oil remains elevated.
VAR impulse-response estimate
VAR impulse response of CPI variables after WTI oil price shock.
| Horizon | All-items CPI | Core CPI | Energy CPI |
|---|---|---|---|
| 1 months | 0.00% | 0.00% | 0.03% |
| 3 months | 0.03% | 0.01% | 0.23% |
| 6 months | 0.25% | 0.06% | 1.55% |
| 12 months | 2.09% | 0.55% | 13.30% |
| 24 months | 6.75% | 1.80% | 43.63% |
| 36 months | 3.54% | 0.87% | 24.89% |
Trained GBDT scenario estimate
Trained gradient-boosted scenario model using historical oil, gasoline, CPI, and macro data.
| Oil shock | Horizon | Low | Mid | High |
|---|---|---|---|---|
| +10% | 1 months | 0.02 | 0.05 | 0.08 |
| +10% | 3 months | 0.08 | 0.21 | 0.33 |
| +10% | 6 months | 0.88 | 1.23 | 1.58 |
| +10% | 12 months | 2.63 | 3.48 | 4.34 |
| +25% | 1 months | 0.03 | 0.05 | 0.08 |
| +25% | 3 months | 0.09 | 0.21 | 0.34 |
| +25% | 6 months | 1.02 | 1.37 | 1.72 |
| +25% | 12 months | 2.63 | 3.49 | 4.34 |
| +50% | 1 months | 0.03 | 0.06 | 0.09 |
| +50% | 3 months | 0.11 | 0.24 | 0.36 |
| +50% | 6 months | 1.04 | 1.39 | 1.74 |
| +50% | 12 months | 2.63 | 3.49 | 4.34 |
| +100% | 1 months | 0.03 | 0.06 | 0.09 |
| +100% | 3 months | 0.11 | 0.24 | 0.36 |
| +100% | 6 months | 1.04 | 1.39 | 1.74 |
| +100% | 12 months | 2.63 | 3.49 | 4.34 |
Assumptions and direct-channel explanation
Why can a large oil shock have a smaller direct CPI effect?
A 100% oil-price increase does not mean all consumer prices rise 100%. Oil first passes through to refined products like gasoline. If crude oil is roughly half of the retail gasoline price, a 100% oil increase may imply about a 50% gasoline-price increase under the baseline assumption.
Then gasoline's effect on all-items CPI depends on its CPI basket weight. If gasoline is about 3% of the CPI basket, a 50% gasoline-price increase contributes about 1.5% to all-items CPI.
That is only the direct gasoline channel. Larger oil shocks may also create broader pressure through diesel, freight, airfares, heating fuel, electricity, producer prices, food distribution, import prices, and inflation expectations.
Oil shock x oil-to-gasoline pass-through = gasoline price effect
Gasoline price effect x gasoline CPI weight = direct gasoline contribution to all-items CPI
Example: 100% x 50% = 50% gasoline price increase
50% x 3% = 1.5% added to all-items CPI
Current oil price: $75.00
Scenario oil price: $90.00
Oil price change: 20.0%
Oil-to-gasoline pass-through: 50%
Estimated gasoline price increase: 10.0%
Gasoline CPI weight: 3.0%
Shock classification: moderate
Duration: 12 months
Stress multiplier: 1.00x
Local oil exposure: 1.00x
Local projection status: trained
The nonlinear stress floor is not a claim that CPI must rise by this much. It is a stress-scenario guardrail used to avoid understating possible inflationary pressure during severe or extreme oil shocks.
FAQ
How do oil prices affect inflation?
Oil can affect inflation through gasoline, heating fuel, diesel, transportation, freight, producer prices, and expectations.
Why can a large oil shock have a smaller direct CPI effect?
Gasoline can rise sharply, but gasoline is only one part of the overall CPI basket.
What is oil-to-gasoline pass-through?
It is an assumption about how much of a crude oil price change reaches retail gasoline prices.
Why are oil simulator results scenario estimates?
Oil pass-through depends on timing, duration, local exposure, and broader economic conditions, so results are ranges rather than forecasts.
Why do different oil models show different values?
Each model answers a different question, from direct gasoline contribution to broader stress scenarios and historical pass-through estimates.