Jute: Correlation
Prices it moves with, and why
Jute grows mainly in West Bengal and Bangladesh. Prices depend on the monsoon, the area planted against rice, Indian government rules requiring jute sacks for grain and sugar, and competition from plastic bags.
No public price Jute has no public monthly price series: Sold in local Indian and Bangladeshi markets; no long public price series here.What its price moves with
Woven polypropylene sacks are the main rival to jute bags for grain, sugar and cement, and they are cheaper. Without Indian rules reserving packaging for jute, plastic would take much more of the market.
Not enough overlapping price history to measure.Cotton competes with jute for some textile uses, and both feed India's spinning industry. Dearer cotton can help jute blends, but jute has no price series, so the link cannot be measured here.
Not enough overlapping price history to measure.In Bengal and Bangladesh, farmers choose between jute and rice on the same wet fields in the monsoon season. When rice pays more, the jute area shrinks and prices rise the following season.
Not enough overlapping price history to measure.After stripping the fibre, jute sticks are left and are widely burned as cooking fuel or used in particle board. This adds a little to farm income, but there is no public price for it.
No public price for firewood and charcoal supply, 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.