Bangladesh vs Low Income Food Deficit Countries (LIFDCs): Chemical wood pulp — Import value

Bangladesh
252,445 1000 USD
in 2024
Low Income Food Deficit Countries (LIFDCs)
163,714 1000 USD
in 2024
Bangladesh rank
23rd
Low Income Food Deficit Countries (LIFDCs) rank
20th

Chemical wood pulp — Import value over time

  • Bangladesh
  • Low Income Food Deficit Countries (LIFDCs)
0100.0k200.0k300.0k196819962024

How they compare

Bangladesh currently reports 252,445 1000 USD against 163,714 1000 USD in Low Income Food Deficit Countries (LIFDCs), a difference of 88,731 1000 USD.

That makes Bangladesh's figure about 1.5 times Low Income Food Deficit Countries (LIFDCs)'s.

The two have swapped places 6 times across 54 shared years of data; in 1971 it was Bangladesh ahead.

Bangladesh ranks 23rd and Low Income Food Deficit Countries (LIFDCs) ranks 20th of 185 countries.

Across the 6 decades both report, Bangladesh averaged higher in 3 and Low Income Food Deficit Countries (LIFDCs) in 3.

Head to head by decade

Decade Bangladesh Low Income Food Deficit Countries (LIFDCs) Difference Ahead
1970s 3,031 1000 USD 2,489 1000 USD 542.33 1000 USD Bangladesh
1980s 5,972 1000 USD 7,199 1000 USD 1,227 1000 USD Low Income Food Deficit Countries (LIFDCs)
1990s 4,586 1000 USD 18,941 1000 USD 14,355 1000 USD Low Income Food Deficit Countries (LIFDCs)
2000s 14,859 1000 USD 46,568 1000 USD 31,709 1000 USD Low Income Food Deficit Countries (LIFDCs)
2010s 153,274 1000 USD 40,516 1000 USD 112,758 1000 USD Bangladesh
2020s 217,814 1000 USD 126,022 1000 USD 91,792 1000 USD Bangladesh

Averages of every year both report within each decade.

Frequently asked questions

Which has higher chemical wood pulp — import value, Bangladesh or Low Income Food Deficit Countries (LIFDCs)?
Bangladesh, at 252,445 1000 USD against 163,714 1000 USD in Low Income Food Deficit Countries (LIFDCs) as of 2024.
What is the difference in chemical wood pulp — import value between Bangladesh and Low Income Food Deficit Countries (LIFDCs)?
88,731 1000 USD, with Bangladesh ahead.
How many years of comparable data are there for Bangladesh and Low Income Food Deficit Countries (LIFDCs)?
54 years are reported by both, from 1971 to 2024.
How do Bangladesh and Low Income Food Deficit Countries (LIFDCs) rank globally for chemical wood pulp — import value?
Bangladesh ranks 23rd and Low Income Food Deficit Countries (LIFDCs) ranks 20th of 185 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Chemical wood pulp — Import value. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Bangladesh vs Low Income Food Deficit Countries (LIFDCs): Chemical wood pulp — Import value. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 12 September 2026, from https://environment.statizoid.com/compare/chemical-wood-pulp-import-value/bangladesh/low-income-food-deficit-countries-lifdcs/

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About this data

Indicator
Chemical wood pulp — Import value
Unit
1000 USD
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
231 places, 9,009 data points, 1968–2024
Last refreshed

The database contains data on the production and trade in roundwood and in primary wood and paper products for all countries and territories in the world.The main types of primary forest products included in this database are roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. These products are detailed further and defined in the Joint Forest Sector Questionnaire (JFSQ) (https://www.fao.org/statistics/data-collection/forestry/en). The database contains details of the following topics: - roundwood removals (production) by coniferous and non-coniferous wood and assortments, - production and trade in industrial roundwood, sawnwood, wood-based panels, wood charcoal, pulp, paper and paperboard, and other products. More detailed information on wood products, including definitions, can be found at: https://www.fao.org/statistics/data-collection/forestry/en