Kenaf, and other textile bast fibres, raw or retted — Gross in Bangladesh
Bangladesh: Kenaf, and other textile bast fibres, raw or retted — Gross was 134 1000 Int$ in 2024. ◆ Volatile
Kenaf, and other textile bast fibres, raw or retted — Gross in Bangladesh, 1961–2024
Source: Food and Agriculture Organization of the United Nations. Measured in 1000 Int$.
Analysis
In 2024, kenaf, and other textile bast fibres, raw or retted — gross in Bangladesh stood at 134 1000 Int$.
Compared with earlier readings it is up 211.6% on the previous year and down 70.5% over ten years.
Over the whole period, kenaf, and other textile bast fibres, raw or retted — gross in Bangladesh peaked at 35,568 1000 Int$ in 1967 and was at its lowest, 32 1000 Int$, in 2017.
That places Bangladesh 24th out of 26 countries with data for 2024, putting it in the bottom quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Kenaf, and other textile bast fibres, raw or retted — Gross in Bangladesh, year by year
| Year | 1000 Int$ | Change |
|---|---|---|
| 1961 | 21,080 1000 Int$ | — |
| 1962 | 21,417 1000 Int$ | +1.6% |
| 1963 | 20,969 1000 Int$ | -2.1% |
| 1964 | 27,554 1000 Int$ | +31.4% |
| 1965 | 33,469 1000 Int$ | +21.5% |
| 1966 | 16,041 1000 Int$ | -52.1% |
| 1967 | 35,568 1000 Int$ | +121.7% |
| 1968 | 16,524 1000 Int$ | -53.5% |
| 1969 | 27,175 1000 Int$ | +64.5% |
| 1970 | 17,416 1000 Int$ | -35.9% |
| 1971 | 13,213 1000 Int$ | -24.1% |
| 1972 | 14,735 1000 Int$ | +11.5% |
| 1973 | 13,843 1000 Int$ | -6.1% |
| 1974 | 8,173 1000 Int$ | -41.0% |
| 1975 | 8,435 1000 Int$ | +3.2% |
| 1976 | 9,180 1000 Int$ | +8.8% |
| 1977 | 10,030 1000 Int$ | +9.3% |
| 1978 | 11,450 1000 Int$ | +14.2% |
| 1979 | 9,495 1000 Int$ | -17.1% |
| 1980 | 6,042 1000 Int$ | -36.4% |
| 1981 | 5,971 1000 Int$ | -1.2% |
| 1982 | 5,594 1000 Int$ | -6.3% |
| 1983 | 5,277 1000 Int$ | -5.7% |
| 1984 | 5,190 1000 Int$ | -1.6% |
| 1985 | 5,972 1000 Int$ | +15.1% |
| 1986 | 5,938 1000 Int$ | -0.6% |
| 1987 | 4,729 1000 Int$ | -20.4% |
| 1988 | 3,495 1000 Int$ | -26.1% |
| 1989 | 4,347 1000 Int$ | +24.4% |
| 1990 | 8,824 1000 Int$ | +103.0% |
| 1991 | 3,068 1000 Int$ | -65.2% |
| 1992 | 614 1000 Int$ | -80.0% |
| 1993 | 614 1000 Int$ | +0.0% |
| 1994 | 4,296 1000 Int$ | +599.7% |
| 1995 | 614 1000 Int$ | -85.7% |
| 1996 | 1,428 1000 Int$ | +132.6% |
| 1997 | 614 1000 Int$ | -57.0% |
| 1998 | 1,841 1000 Int$ | +199.8% |
| 1999 | 1,152 1000 Int$ | -37.4% |
| 2000 | 1,083 1000 Int$ | -6.0% |
| 2001 | 1,017 1000 Int$ | -6.1% |
| 2002 | 961 1000 Int$ | -5.5% |
| 2003 | 880 1000 Int$ | -8.4% |
| 2004 | 819 1000 Int$ | -6.9% |
| 2005 | 760 1000 Int$ | -7.2% |
| 2006 | 703 1000 Int$ | -7.5% |
| 2007 | 648 1000 Int$ | -7.8% |
| 2008 | 110 1000 Int$ | -83.0% |
| 2009 | 150 1000 Int$ | +36.4% |
| 2010 | 283 1000 Int$ | +88.7% |
| 2011 | 288 1000 Int$ | +1.8% |
| 2012 | 334 1000 Int$ | +16.0% |
| 2013 | 583 1000 Int$ | +74.6% |
| 2014 | 455 1000 Int$ | -22.0% |
| 2015 | 1,505 1000 Int$ | +230.8% |
| 2016 | 83 1000 Int$ | -94.5% |
| 2017 | 32 1000 Int$ | -61.4% |
| 2018 | 221 1000 Int$ | +590.6% |
| 2019 | 36 1000 Int$ | -83.7% |
| 2020 | 48 1000 Int$ | +33.3% |
| 2021 | 42 1000 Int$ | -12.5% |
| 2022 | 43 1000 Int$ | +2.4% |
| 2023 | 43 1000 Int$ | +0.0% |
| 2024 | 134 1000 Int$ | +211.6% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1960s | 24,422 1000 Int$ | 16,041 1000 Int$ | 35,568 1000 Int$ | 9 |
| 1970s | 11,597 1000 Int$ | 8,173 1000 Int$ | 17,416 1000 Int$ | 10 |
| 1980s | 5,256 1000 Int$ | 3,495 1000 Int$ | 6,042 1000 Int$ | 10 |
| 1990s | 2,306 1000 Int$ | 614 1000 Int$ | 8,824 1000 Int$ | 10 |
| 2000s | 713.1 1000 Int$ | 110 1000 Int$ | 1,083 1000 Int$ | 10 |
| 2010s | 382 1000 Int$ | 32 1000 Int$ | 1,505 1000 Int$ | 10 |
| 2020s | 62 1000 Int$ | 42 1000 Int$ | 134 1000 Int$ | 5 |
Countries ranked near Bangladesh
- 21 Guatemala 169 1000 Int$ compare
- 22 Pakistan 163 1000 Int$ compare
- 23 Spain 143 1000 Int$ compare
- 25 Madagascar 98 1000 Int$ compare
- 26 Central African Republic 71 1000 Int$ compare
More agriculture & rural data for Bangladesh
- Agriculture, forestry, and fishing, value added (current US$), annual 3.73 % change on previous year (2025)
- Agriculture, forestry, and fishing, value added (current US$), per 0.1142 current US$ per US$ of GDP (2025)
- Agriculture, forestry, and fishing, value added (current US$), per 296.72 current US$ per person (2025)
- Rural population, annual growth rate 0.38 % change on previous year (2025)
- Rural population, per unit of GDP 0.0003 units per US$ of GDP (2025)
- Rural population, per capita 0.6676 units per person (2025)
- Share of GDP from agriculture 11.4% (2025)
- Agriculture as a share of GDP vs. GDP per capita 11.4% (2025)
- Agricultural raw materials exports 0.8% (2018)
- Agricultural raw materials imports 6.0% (2018)
Frequently asked questions
- What is kenaf, and other textile bast fibres, raw or retted — gross in Bangladesh?
- Kenaf, and other textile bast fibres, raw or retted — gross in Bangladesh was 134 1000 Int$ in 2024, according to Food and Agriculture Organization of the United Nations.
- What is the highest kenaf, and other textile bast fibres, raw or retted — gross recorded in Bangladesh?
- The highest recorded value was 35,568 1000 Int$ in 1967.
- What is the lowest kenaf, and other textile bast fibres, raw or retted — gross recorded in Bangladesh?
- The lowest recorded value was 32 1000 Int$ in 2017.
- How does Bangladesh rank for kenaf, and other textile bast fibres, raw or retted — gross?
- Bangladesh ranks 24th out of 26 countries with data for 2024.
- Is kenaf, and other textile bast fibres, raw or retted — gross rising or falling in Bangladesh?
- Over the last ten years it is down 70.5%. The long-run trend across the full record is volatile.
- Where does this Bangladesh data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of Kenaf, and other textile bast fibres, raw or retted — Gross Production Value (constant 2014-2016 thousand I$). Statizoid updates them automatically from the source API.
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About this data
The domain provides detailed data on the value of agricultural production that is calculated by the agricultural production data and the price data at farm gate. Thus, the value of production measures the agricultural production in monetary terms at the farm gate level.