# Bagasse and black-liquor cogeneration: Correlation Prices it moves with, and why Source page: https://www.materialinsights.org/energy/e_bio_cogen/correlation/ Sugar and paper mills burn bagasse and black liquor they already produce, so fuel is nearly free. Output depends on how much cane is crushed and pulp made, and surplus power earns tariffs set by grid buyers and regulators. No public price Bagasse and black-liquor cogeneration has no public monthly price series: Built inside sugar and paper mills; no separate public price. #### What its price moves with Commodity [Su Sugar](https://www.materialinsights.org/commodities/sugar/)Host industry Bagasse, the fibre left after crushing cane, fuels the mill's boilers, so cogeneration output rises and falls with the cane crush. Good sugar prices keep mills running longer, as in India and Brazil. Cogeneration has no price series, so no statistics are shown. Not enough overlapping price history to measure. Chemical [EtOH Bioethanol](https://www.materialinsights.org/energy/bioethanol/)Sister product Cane mills also make ethanol from molasses or juice, using steam and power from their own bagasse boilers. Ethanol blending programmes, such as India's, raise mill earnings and support investment in more efficient cogeneration. Not enough overlapping price history to measure. Chemical [NaOH Caustic soda](https://www.materialinsights.org/chemicals/caustic_soda/)Pulping chemicals Kraft pulp mills cook wood with caustic soda and sodium sulphide, then burn the spent black liquor in recovery boilers to reclaim those chemicals while making steam and power. This recovery cuts both chemical purchases and energy bills. Not enough overlapping price history to measure. Commodity [Tm Timber](https://www.materialinsights.org/commodities/lumber/)Wood market Paper mills draw on the same forests and sawmill residues as the timber trade, so wood supply links black liquor cogeneration to forest products. The sawnwood price is only a loose guide to pulpwood costs. Not enough overlapping price history to measure. Energy [ST Steam turbines and thermal power plants](https://www.materialinsights.org/energy/e_steam_turbines/)Main equipment Mills use back-pressure steam turbines that produce power while passing exhaust steam to the process. Higher-pressure boilers and better turbines let mills export more electricity from the same bagasse. Upgrades are often funded by power purchase agreements with state utilities. Not enough overlapping price history to measure. Energy [Tc Thermal coal](https://www.materialinsights.org/energy/thermal_coal/)Fuel displaced Mills that run short of bagasse or liquor often fire coal, and grid power they replace is largely coal-fired in India. Bagasse power therefore competes with coal, and dear coal makes surplus mill power more valuable. Not enough overlapping price history to measure. 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_bio_cogen/index.md) - [Overview](https://www.materialinsights.org/energy/e_bio_cogen/overview/index.md) - [Science and thermodynamics](https://www.materialinsights.org/energy/e_bio_cogen/rc-sci/index.md) - [Engineering and integration](https://www.materialinsights.org/energy/e_bio_cogen/rc-eng/index.md) - [Economics and contracts](https://www.materialinsights.org/energy/e_bio_cogen/rc-econ/index.md) - [Impact and additionality](https://www.materialinsights.org/energy/e_bio_cogen/rc-impact/index.md) - [What to track](https://www.materialinsights.org/energy/e_bio_cogen/tracking/index.md) - [Relationships](https://www.materialinsights.org/energy/e_bio_cogen/links/index.md)