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Arya Roy Bardhan, The Strait That Shakes Prices: Impact of the Hormuz Disruption on Inflation in India, Observer Research Foundation, May 2026.
On 28 February 2026, coordinated United States (US) and Israeli airstrikes on Iran triggered the closure of the Strait of Hormuz, through which one-fifth of the world’s seaborne crude oil and liquefied natural gas (LNG) had flowed before the crisis. The International Energy Agency has called it the largest supply disruption in the history of the global oil market. Traffic through the strait collapsed from over 130 daily ship transits to fewer than 10. The Indian crude oil basket nearly doubled in a single month, from US$69 per barrel in February to US$126 in March, peaking at US$157. Qatar declared force majeure on LNG exports after missile strikes damaged its Ras Laffan facility. Global urea prices jumped 50 percent, threatening the spring planting season in the Northern Hemisphere.
India is among the most exposed large economies across the globe. It imports 88 percent of its crude oil, with roughly half of this volume typically arriving via the strait. Over 60 percent of household LPG is imported, and 90 percent of those imports transit Hormuz. More than half of India’s LNG arrives from Qatar and the UAE through the same route. The Government of India responded with excise duty cuts on motor fuels, a Natural Gas Control Order rationing supply, customs duty exemptions on petrochemical products, and bilateral negotiations with Iran for safe passage of Indian-flagged vessels. Despite these measures, however, inflationary pressures are building, and the imperative for policymakers is to know which sectors are most vulnerable and through which channels the shocks are transmitting.
Current forecasts from investment banks and rating agencies project Indian CPI inflation of 5–6 percent in Q2–Q3 2026. However, these forecasts share three limitations: they are aggregate (i.e., they cannot tell which sectors are driving the increase), opaque (they are based on proprietary models that cannot be independently verified), and they miss the amplification structure (how a primary energy shock cascades through petrochemicals, fertilisers, agriculture, and food processing, accumulating at each stage). This report addresses these gaps.
This study applies a Leontief input-output price model[1] to India’s official Supply and Use Tables for 2021–22, published by the Central Statistics Office. Think of the Indian economy as a web of 140 products, each of which uses others as inputs. Steel needs coal and electricity. Fertiliser needs natural gas and chemicals. Food processing needs agriculture, packaging, and transport. When the price of an imported input like crude oil rises, the cost increase ripples outward through this web, raising the price of every product that uses oil, then of every product that uses those products, and so on.
The model captures this entire cascade mathematically. It separates each product’s inputs into a domestic component (whose price is determined within the Indian economy) and an imported component (whose price is set by world markets). When the Hormuz closure raises world prices for crude oil, LNG, and other commodities, the model traces how that cost shock enters through the import channel and propagates through all rounds of domestic inter-industry linkages until it reaches every corner of the economy.
The report calibrates the model with observed commodity price movements from February to March 2026 and runs four scenarios of increasing breadth. It then maps the resulting 140-product price-change vector onto the 12 divisions of India’s revised Consumer Price Index (base 2024) using official consumption weights, and adjusts for the empirically observed gap between producer prices and consumer prices—a gap created by pipeline lags, government intervention, and firms absorbing costs in their margins.
Structural cost-push ceiling on CPI: 4.48pp shock (Scenario 4, full pass-through)
Realised CPI impact (12–18 months): 1.6–2.2pp above baseline
Implied peak headline CPI: 5.0–5.6% in 2026
RBI tolerance band status: Within 2–6% band at plausible pass-through ratios
Products affected (>1% price increase): 122 out of 140 (87% of the economy)
Dominant channel: Crude oil alone accounts for 71% of the total price impact
3.1 The Shock Is Systemic, Not Sectoral
Under the most comprehensive scenario (Scenario 4), 122 of 140 products in the Indian economy experience a price increase exceeding 1 percent, and 55 products exceed 5 percent. This is not a fuel crisis confined to petrol pumps—it is an economy-wide cost shock that reaches textiles through synthetic fibres, pharmaceuticals through petrochemical feedstocks, food through fertilisers, and construction through cement and steel. The mean producer-price increase across all products is 5.78 percent.
3.2 Crude Oil Dominates All Commodities
The primary energy shock (crude oil, LNG, and coal) alone accounts for 71 percent of the total price impact. Downstream commodity shocks (fertilisers, chemicals) add 27 percent, and secondary effects (freight, insurance) add just 2 percent. This has a clear policy implication. Securing alternative crude supply at competitive prices is the single highest-return intervention available.
A caveat is important, however. The 71 percent figure captures the price channel. It does not capture the quantity-constraint channel—the physical unavailability of LPG and natural gas that no price adjustment can resolve. The government’s rationing of gas to fertiliser plants at 70 percent of previous supply is a response to a shortage, not merely to a price increase. A complementary analysis of physical supply constraints would be needed to assess this dimension.
3.3 The Chemical–Agricultural Nexus Is the Most Consequential Indirect Pathway
The model reveals a critical amplification chain: crude oil → petroleum products → organic chemicals → fertilisers → agriculture → food. The direct cost shock on fertilisers from the crude oil channel is only 0.19 percent. However, after tracing through all indirect rounds of inter-industry linkage, the total effect on fertiliser prices reaches 17.8 percent—an amplification ratio exceeding 90. Air transport is the most directly exposed service sector, with petroleum products constituting 42.7 percent of its input costs, producing a 23.7 percent price increase.
Figure 1. Sectors Worst- and Least-Affected by Hormuz Disruption
Source: Created with AI tool, Claude, using author’s estimations of shocks.
3.4 The CPI Impact: Structural Ceiling and Realised Estimate
Translating producer-price impacts into consumer-price effects requires two adjustments: mapping the 140 SUT products onto the CPI’s consumption-weighted structure, and applying a pass-through ratio that accounts for the gap between wholesale cost increases and what consumers actually pay. Table 1 shows the division-level decomposition.
Table 1: CPI Division-Level Decomposition (Scenario 4, Structural Ceiling)
Note: Green = below 5% | Yellow = 5–10% | Red = above 10%. Contribution = Weight × Price Change, in percentage points of CPI.
Source: Author’s own calculations.
Transport (23.5 percent of headline impact) and Food (28.2 percent) are the two largest contributors, together accounting for over half the total. Transport experiences a disproportionate impact because of its extreme energy intensity, while Food’s contribution is driven by its sheer weight in the CPI basket (36.75 percent). Housing (12.4 percent) is affected through electricity and gas prices, and Clothing (9.4 percent) through the synthetic textile chain.
Caveat: The structural ceiling of 4.48 percent assumes full pass-through with no government intervention, no input substitution, and no demand response. It is not a forecast. The March 2026 CPI reading of 3.40 percent—barely above the pre-Middle East February war reading of 3.21 percent despite crude nearly doubling—confirms that pass-through frictions are substantial. Transport inflation was 0.00 percent year-on-year, reflecting excise duty cuts and margin absorption by oil marketing companies.
3.5 The Realistic Central Estimate
To arrive at a realistic number, this report applies a pass-through ratio—the fraction of the producer-price shock that actually reaches consumers. Based on empirical studies of Indian CPI transmission, a 35–50 percent ratio over 12–18 months is plausible.
Table 2: Possible Impacts on Consumers
Baseline: March 2026 CPI = 3.40% YoY. RBI target: 4%, tolerance band: 2–6%. Highlighted rows indicate the plausible range.
Source: Author’s own calculations.
Central estimate: At 35–50 percent pass-through, peak CPI inflation reaches 5.0–5.6 percent in 2026—above the Reserve Bank of India’s (RBI) 4 percent target but within the 2–6 percent tolerance band. This aligns closely with independent forecasts, providing external validation.
Figure 2. Where Inflation in India Could Land
Source: Author’s own, created with AI tool, Claude.
Note: Pass-through ratios of 75 percent or higher, which become more likely if the conflict persists and fiscal policy space is exhausted, would push CPI above the RBI’s 6-percent upper tolerance, triggering a formal deviation requiring the Monetary Policy Committee to explain to the government.
The model identifies three groups of products by severity of impact, each requiring a different policy response:
Group 1: Moderate Impact (<5-percent price increase)
Education, recreation, restaurants, communication, and real estate
Food and agriculture, clothing and textiles, housing and utilities, health, iron and steel, cement
Petroleum products, chemicals, fertilisers, air transport, plastics, rubber, synthetic textiles
The estimates are structured upper bounds, not forecasts. The model assumes fixed input recipes (no substitution between inputs), full cost pass-through at every stage (no margin absorption), and no government intervention. These assumptions are violated in practice, which is why the structural ceiling of 4.48 percent is substantially above the realised March 2026 CPI of 3.40 percent. The pass-through adjustment partially corrects this, but a full general equilibrium model (CGE) would be needed to endogenise substitution, fiscal response, and exchange rate effects.
Quantity constraints are not modelled. The model assumes every product remains available at the right price. For LPG, natural gas, and fertiliser intermediates, the Hormuz Strait closure has created physical shortages that cannot be resolved by price adjustment alone. The government’s gas rationing order is a response to quantity constraints, not merely price increases. A complementary supply-side analysis would be needed to assess output losses from physical unavailability.
The production structure is from 2021–22. India’s economy has evolved since then: more renewable energy, lower energy intensity, and a shift in import sources toward Russian crude. These changes are not reflected and therefore the analysis may modestly overstate coal-related transmission while understating the resilience from source diversification.
Petroleum products are treated as a single aggregate. The SUT classifies all refined products (diesel, petrol, LPG, ATF, naphtha) as one category, but their import dependencies are vastly different: LPG at 60.3 percent import share versus diesel at 0.1 percent. This understates the household impact (which is LPG-driven) and overstates the transport impact (which is diesel-driven).
Exchange rate and monetary policy feedbacks are absent. The rupee has weakened during the crisis (MUFG projects USD/INR at 95–97.50 at $100–120/bbl oil), which would amplify the domestic cost of all imports. This effect is not captured and would raise the realised CPI impact above this report’s central estimate.
Read the report here.
Arya Roy Bardhan is Junior Fellow, Centre for New Economic Diplomacy, Observer Research Foundation.
All views expressed in this publication are solely those of the author, and do not represent the Observer Research Foundation., either in its entirety or its officials and personnel.
[1] Wassily W. Leontief developed this method in the late 1940s to portray the entire economy by plotting the consumption-production structure at the sectoral level. When further decomposed, this model allows the mapping of commodity-to-commodity shocks, enabling a granular analysis of exogenous shocks. See: https://cooperative-individualism.org/leontief-wassily_input-output-economics-1951-oct.pdf.
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Arya Roy Bardhan is a Junior Fellow at the Centre for New Economic Diplomacy, Observer Research Foundation. His research interests lie in the fields of ...
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