# Shared and district heat reuse: Correlation Prices it moves with, and why Source page: https://www.materialinsights.org/energy/e_shared_heat/correlation/ Shared heat schemes pay for pipes, heat pumps and exchangers that carry spare heat from data centres, factories or sewers to nearby users. Their value is the gas or electric heating they replace, and they depend on local heat networks. No public price Shared and district heat reuse has no public monthly price series: Local deals between sites; heat prices are not public. #### What its price moves with Energy [DHN District heating and cooling networks](https://www.materialinsights.org/energy/e_district_heat_net/)Distribution Heat networks carry recovered heat to homes and offices; without one, most waste heat has nowhere to go. Network building, common in northern Europe and China, is the main enabler. Shared heat has no price series, so no statistics are shown. No public price for district heating and cooling networks, so the link is explained in words only. Energy [DC Data centres](https://www.materialinsights.org/energy/e_data_centres/)Heat source Data centres turn nearly all their electricity into low-grade heat, available all year. Growth in data centres, driven by AI, creates large new heat sources near cities, if networks can take it. Not enough overlapping price history to measure. Energy [HP Heat pumps, air conditioning and refrigeration](https://www.materialinsights.org/energy/e_heat_pumps/)Heat upgrade Heat from sewers, metros or data centres is often too cool to use directly, so heat pumps raise its temperature. Their cost and efficiency largely decide whether shared heat beats a gas boiler. Not enough overlapping price history to measure. Energy [Gas Natural gas](https://www.materialinsights.org/energy/natural_gas/)Fuel displaced Most recovered heat replaces gas-fired heating, so gas prices set its value. High European gas prices have encouraged new waste heat projects. Where gas is cheap, as in the US, payback is harder and fewer schemes are built. Not enough overlapping price history to measure. Commodity [St Steel](https://www.materialinsights.org/commodities/steel/)Pipe material Heat networks use pre-insulated steel pipes, a major part of network cost. Steel prices therefore affect the cost of connecting heat sources to users. Laying pipes under city streets often costs more than the pipe itself. Not enough overlapping price history to measure. Energy [Elz Electrolysers](https://www.materialinsights.org/energy/e_electrolysers/)Heat source Large electrolysers for hydrogen give off a lot of heat as a by-product. Projects in Europe plan to sell this heat to district networks, improving the economics of green hydrogen. No public price for electrolysers, so the link is explained in words only. How 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. ## Other sections - [Summary](https://www.materialinsights.org/energy/e_shared_heat/index.md) - [Overview](https://www.materialinsights.org/energy/e_shared_heat/overview/index.md) - [Science and thermodynamics](https://www.materialinsights.org/energy/e_shared_heat/rc-sci/index.md) - [Engineering and integration](https://www.materialinsights.org/energy/e_shared_heat/rc-eng/index.md) - [Economics and contracts](https://www.materialinsights.org/energy/e_shared_heat/rc-econ/index.md) - [Impact and additionality](https://www.materialinsights.org/energy/e_shared_heat/rc-impact/index.md) - [What to track](https://www.materialinsights.org/energy/e_shared_heat/tracking/index.md) - [Relationships](https://www.materialinsights.org/energy/e_shared_heat/links/index.md)