Value Added (Agriculture, Forestry and Fishing) — Value US$ in Bangladesh
Bangladesh: Value Added (Agriculture, Forestry and Fishing) — Value US$ was 48,315 million USD in 2024. ◆ Volatile
Value Added (Agriculture, Forestry and Fishing) — Value US$ in Bangladesh, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
The most recent figure for value added (agriculture, forestry and fishing) — value us$ in Bangladesh is 48,315 million USD, measured in 2024.
The figure is up 3.9% on the previous year and up 62.8% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value us$ in Bangladesh peaked at 48,562 million USD in 2022 and was at its lowest, 2,052 million USD, in 1971.
That places Bangladesh 11th out of 200 countries with data for 2024, putting it in the top 10%.
The series is highly variable year to year, so single readings are best treated with caution.
Value Added (Agriculture, Forestry and Fishing) — Value US$ in Bangladesh, year by year
| Year | million USD | Change |
|---|---|---|
| 1970 | 2,437 million USD | — |
| 1971 | 2,052 million USD | -15.8% |
| 1972 | 2,670 million USD | +30.1% |
| 1973 | 2,764 million USD | +3.6% |
| 1974 | 3,399 million USD | +23.0% |
| 1975 | 4,137 million USD | +21.7% |
| 1976 | 3,876 million USD | -6.3% |
| 1977 | 3,764 million USD | -2.9% |
| 1978 | 4,987 million USD | +32.5% |
| 1979 | 5,445 million USD | +9.2% |
| 1980 | 5,681 million USD | +4.3% |
| 1981 | 5,725 million USD | +0.8% |
| 1982 | 5,135 million USD | -10.3% |
| 1983 | 5,189 million USD | +1.0% |
| 1984 | 6,352 million USD | +22.4% |
| 1985 | 6,595 million USD | +3.8% |
| 1986 | 6,730 million USD | +2.0% |
| 1987 | 7,713 million USD | +14.6% |
| 1988 | 7,929 million USD | +2.8% |
| 1989 | 8,260 million USD | +4.2% |
| 1990 | 8,541 million USD | +3.4% |
| 1991 | 8,923 million USD | +4.5% |
| 1992 | 8,713 million USD | -2.3% |
| 1993 | 8,010 million USD | -8.1% |
| 1994 | 8,326 million USD | +4.0% |
| 1995 | 9,592 million USD | +15.2% |
| 1996 | 9,807 million USD | +2.2% |
| 1997 | 10,181 million USD | +3.8% |
| 1998 | 10,449 million USD | +2.6% |
| 1999 | 11,302 million USD | +8.2% |
| 2000 | 11,194 million USD | -1.0% |
| 2001 | 10,579 million USD | -5.5% |
| 2002 | 10,348 million USD | -2.2% |
| 2003 | 10,844 million USD | +4.8% |
| 2004 | 11,292 million USD | +4.1% |
| 2005 | 11,134 million USD | -1.4% |
| 2006 | 12,619 million USD | +13.3% |
| 2007 | 14,412 million USD | +14.2% |
| 2008 | 16,578 million USD | +15.0% |
| 2009 | 18,209 million USD | +9.8% |
| 2010 | 20,575 million USD | +13.0% |
| 2011 | 22,248 million USD | +8.1% |
| 2012 | 22,658 million USD | +1.8% |
| 2013 | 26,202 million USD | +15.6% |
| 2014 | 29,677 million USD | +13.3% |
| 2015 | 32,560 million USD | +9.7% |
| 2016 | 35,620 million USD | +9.4% |
| 2017 | 37,441 million USD | +5.1% |
| 2018 | 39,463 million USD | +5.4% |
| 2019 | 41,851 million USD | +6.1% |
| 2020 | 44,826 million USD | +7.1% |
| 2021 | 48,266 million USD | +7.7% |
| 2022 | 48,562 million USD | +0.6% |
| 2023 | 46,483 million USD | -4.3% |
| 2024 | 48,315 million USD | +3.9% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 3,553 million USD | 2,052 million USD | 5,445 million USD | 10 |
| 1980s | 6,531 million USD | 5,135 million USD | 8,260 million USD | 10 |
| 1990s | 9,384 million USD | 8,010 million USD | 11,302 million USD | 10 |
| 2000s | 12,721 million USD | 10,348 million USD | 18,209 million USD | 10 |
| 2010s | 30,829 million USD | 20,575 million USD | 41,851 million USD | 10 |
| 2020s | 47,290 million USD | 44,826 million USD | 48,562 million USD | 5 |
Countries ranked near Bangladesh
More environment data for Bangladesh
- Historical exposure to drought — Land soil moisture anomaly -2.59 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -2.3 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.236 °C (2025)
- Temperature change 1.67 °C (2025)
- Other paper and paperboard, not elsewhere specified — Import 42.14 % change on previous year (2024)
- Other paper and paperboard, not elsewhere specified — Import 0.0004 t per person (2024)
- Exposure to drought — Land soil moisture anomaly -3.96 Percentage change (2024)
- Exposure to drought — Cropland soil moisture anomaly -5.96 Percentage change (2024)
- Other paper and paperboard, not elsewhere specified — Import value 45.89 % change on previous year (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value us$ in Bangladesh?
- Value added (agriculture, forestry and fishing) — value us$ in Bangladesh was 48,315 million USD in 2024, according to Food and Agriculture Organization of the United Nations.
- What is the highest value added (agriculture, forestry and fishing) — value us$ recorded in Bangladesh?
- The highest recorded value was 48,562 million USD in 2022.
- What is the lowest value added (agriculture, forestry and fishing) — value us$ recorded in Bangladesh?
- The lowest recorded value was 2,052 million USD in 1971.
- How does Bangladesh rank for value added (agriculture, forestry and fishing) — value us$?
- Bangladesh ranks 11th out of 200 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value us$ rising or falling in Bangladesh?
- Over the last ten years it is up 62.8%. 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 Value Added (Agriculture, Forestry and Fishing) — Value US$. Statizoid updates them automatically from the source API.
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About this data
The FAOSTAT Macro Indicators database provides a selection of country-level macro indicators relating to total economy (Gross Domestic Product, Gross Fixed Capital Formation); agriculture activity; agriculture, forestry and fishing activity; total manufacturing activity; manufacturing of food products and beverages activity; manufacturing activity of tobacco products; and manufacturing activity of food, beverage and tobacco products.It releases time series for a selection of National Accounts variables, including gross domestic product, gross fixed capital formation, industry-level value added and gross output. The database also proposes additional indicators such as gross domestic product per capita, year-on-year growth rates and measures of industry contribution to gross domestic product. All data relating to Gross Domestic Product, Gross Fixed Capital Formation, agriculture, forestry and fishing activity, and to total manufacturing activity originates from the United Nations Statistics Division (UNSD) National Accounts Estimates of Main Aggregates database, which consists of a complete and consistent set of time series of the main National Accounts aggregates of all UN Members States and other territories in the world for which National Accounts information is available. The UNSD database's content is based on the countries' official National Accounts data reported to UNSD through the annual National Accounts Questionnaire, supplemented with data estimates for any years and countries with incomplete or inconsistent information (See http://unstats.un.org/unsd/snaama/Introduction.asp). Data series relating to the sub-industry Agriculture activity are obtained from the UNSD national accounts Official Country Data databases while series on the Manufacturing activity of food and beverages products, manufacturing activity of tobacco products and manufacturing activity of food, beverages and tobacco products originates from the United Nations Industrial Development Organization (UNIDO) INDSTAT2 database. In order to ensure that sub-industry series are consistent in levels with National Accounts based series, which is needed to support comparability across industries (agriculture vs. agro-industry and sub-industries), UNIDO originating series are rescaled on UNSD National Accounts Estimates of Main Aggregates data series (See Section 17.5 for a more detailed description of the data processing steps).