Energy-intensive industry: Correlation
Prices it moves with, and why
The proxy is the US industrial electricity tariff, which follows fuel costs at power plants, mainly natural gas, plus network charges, with regulators smoothing changes. For steel, aluminium, cement and ammonia, power and gas are a big part of cost.
Proxy US PPI: industrial electric power index · monthly, Jan 2006 to Sep 2026There is no free public price for energy-intensive industry itself, so this tab uses the closest public series as a stand-in. Read the numbers as an indication, not as the price of this exact item.
What its price moves with
Selected linkEnergy-intensive industry and Natural gas
Monthly changes -0.08 little or none correlation 12-month changes 0.35 weak correlation Last 5 years -0.14 monthly changes Lead or lag −2 mo Energy-intensive industry tends to lead by 2 months (r 0.14) Price function, Jan 2006 to Sep 2026 Energy-intensive industry ≈ 158.4 × (Natural gas)0.09 R² 0.07 On this fit, a 10% higher natural gas price goes with a 0.8% higher energy-intensive industry price over the long run. Units: index and $/mmbtu. The fit is loose, so treat the function as a rough guide.Chart: Energy-intensive industry and Natural gas prices rebased to 100 at Jan 2006, log scale
Both prices rebased to 100 at Jan 2006, on a log scale so equal percentage moves look the same size.Chart: Energy-intensive industry price against Natural gas price, monthly, log scales, with fitted line
Each dot is one month; paler dots are older (2006), darker dots recent (2026); the ringed dot is the latest month. The dashed line is the fitted price function. Both axes are logarithmic.Gas sets the marginal cost of power in many grids and is burned directly in heavy industry. Monthly moves correlate at -0.08 with European gas but yearly at 0.35, because US tariffs follow American gas with a delay set by regulators.
little or none co-movement month to month · 249 months Show chartsCommercial and industrial tariffs are set by the same utilities from the same generation costs. Monthly moves correlate at 0.83, the strongest link here, showing a shared fuel and network cost base rather than any trade between the two users.
strong co-movement month to month · 249 months Show chartsHousehold tariffs also come from the same utilities and fuel costs, but include more network and retail charges. Monthly moves correlate at 0.63 with the industrial tariff, as residential prices are smoothed further by regulation.
moderate co-movement month to month · 248 months Show chartsAluminium smelting uses so much electricity that power is its largest cost, so high tariffs close smelters. Monthly moves correlate at -0.11 with US industrial power, since aluminium is priced globally and most smelters run on long-term power deals.
little or none co-movement month to month · 249 months Show chartsAmmonia uses natural gas as both fuel and feedstock, so it moves with energy costs. Yearly moves correlate at 0.35 with industrial power but monthly moves over the last five years at -0.46, as fertiliser markets swung on their own supply shocks.
little or none co-movement month to month · 249 months Show chartsCoal still fuels part of US power and much of power in India and China, where heavy industry is concentrated. Yearly moves correlate at 0.37 with the US industrial tariff, a weak link given coal's falling share of US generation.
little or none co-movement month to month · 249 months Show chartsHow to read these numbers
Correlation of monthly changes (the number in the coloured pill) compares how much each price moved, month by month, since 2006 or the first month both series exist. It runs from −1 to +1: near +1 the two usually rise and fall in the same months, near 0 there is no link, and a negative number means they tend to move in opposite directions. Above 0.7 is strong, 0.4 to 0.7 moderate, 0.2 to 0.4 weak.
12-month changes compare year-on-year moves, which shows whether two prices share the same cycles even when the month-to-month noise differs.
Price function is a straight-line fit of the two prices on logarithmic scales: price ≈ k × (partner price)β. β is how much this price moves, in per cent, for a 1% move in the partner over the whole period, and R² is the share of the variation the fit explains. Two prices that both drift up with inflation can fit well without any real link, so read it together with the monthly correlation.
Lead or lag checks whether the monthly correlation is clearly higher when one price is shifted by 1 to 6 months.
Correlation is not cause. The reasons on each card explain the economic link; the numbers show how strongly it has shown up in prices. Proxy series are US producer price indexes or related prices and can blur the real link.
Data: World Bank Commodity Price Data (Pink Sheet), October 2026; US Bureau of Labor Statistics producer price indexes, IMF primary commodity prices and US EIA prices via FRED, Federal Reserve Bank of St. Louis, retrieved November 2026. Calculations by this site.