Steam turbines and thermal power plants: Correlation
Prices it moves with, and why
The index covers heavy turbine and generator sets sold on multi-year orders. Prices reflect engineering labour, large steel forgings and alloy blades, and the order cycle for coal, nuclear, biomass and waste plants, rather than monthly commodity moves.
Price index US PPI: steam, gas and other turbines and generators index · monthly, Jan 2006 to Sep 2026What its price moves with
Selected linkSteam turbines and thermal power plants and Steel
Monthly changes 0.09 little or none correlation 12-month changes -0.08 little or none correlation Last 5 years 0.21 monthly changes Lead or lag none No clear lead or lag Price function, Jan 2006 to Sep 2026 Steam turbines and thermal power plants ≈ 33.8 × (Steel)0.26 R² 0.32 On this fit, a 10% higher steel price goes with a 2.5% higher steam turbines and thermal power plants price over the long run. Units: index and index, BLS base period.Chart: Steam turbines and thermal power plants and Steel 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: Steam turbines and thermal power plants price against Steel 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.Casings, rotors and frames are heavy steel forgings and castings. Even so, the link barely shows in the data, with monthly moves correlating at 0.09, because turbine prices are fixed when ordered and delivered years later, with metal costs often covered by escalation clauses.
little or none co-movement month to month · 234 months Show chartsCoal plants have been the largest buyers of steam turbines, so coal power construction drives orders. Coal prices themselves hardly move the index, with monthly changes correlating at -0.04, because plant building follows policy and long planning cycles, not month-to-month fuel prices.
little or none co-movement month to month · 234 months Show chartsNuclear plants use some of the largest steam turbines made. The proxy here is the uranium price, which correlates at -0.01 with the index monthly: uranium is a small part of nuclear cost and turbine orders follow reactor projects, not fuel markets.
little or none co-movement month to month · 234 months Show chartsGeothermal plants also run steam turbines, and their proxy is a closely related turbine index. Monthly moves correlate at 0.68 and yearly at 0.53, mostly because the two indices cover overlapping products from the same makers, not because of any market link.
moderate co-movement month to month · 169 months Show chartsBoilers raise the steam that turbines expand, and both are ordered together for thermal plants. The boiler proxy correlates with the turbine index at 0.26 monthly, a modest link that reflects shared plant projects and similar heavy fabrication costs.
weak co-movement month to month · 234 months Show chartsSteam cycles need very pure water, so plants buy treatment chemicals to prevent scale and corrosion in boilers and turbines. The link is a small operating cost, and the indices correlate at only 0.13 monthly, as expected for unrelated pricing.
little or none co-movement month to month · 234 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.