Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bangladesh
Bangladesh: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 5.59 million million SLC in 2024. ◆ Volatile
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bangladesh, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Bangladesh recorded 5.59 million million SLC for value added (agriculture, forestry and fishing) — value standard in 2024. That is the highest value across all 55 years on record.
Compared with earlier readings it is up 13.0% on the previous year and up 142.4% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Bangladesh peaked at 5.59 million million SLC in 2024 and was at its lowest, 16,148 million SLC, in 1971.
Bangladesh ranks 27th of 199 countries on this measure, in the top quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bangladesh, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 17,740 million SLC | — |
| 1971 | 16,148 million SLC | -9.0% |
| 1972 | 16,941 million SLC | +4.9% |
| 1973 | 26,845 million SLC | +58.5% |
| 1974 | 41,993 million SLC | +56.4% |
| 1975 | 80,054 million SLC | +90.6% |
| 1976 | 59,686 million SLC | -25.4% |
| 1977 | 57,869 million SLC | -3.0% |
| 1978 | 74,879 million SLC | +29.4% |
| 1979 | 84,673 million SLC | +13.1% |
| 1980 | 87,790 million SLC | +3.7% |
| 1981 | 102,980 million SLC | +17.3% |
| 1982 | 113,579 million SLC | +10.3% |
| 1983 | 127,720 million SLC | +12.5% |
| 1984 | 161,057 million SLC | +26.1% |
| 1985 | 184,636 million SLC | +14.6% |
| 1986 | 204,637 million SLC | +10.8% |
| 1987 | 238,723 million SLC | +16.7% |
| 1988 | 251,609 million SLC | +5.4% |
| 1989 | 266,566 million SLC | +5.9% |
| 1990 | 295,242 million SLC | +10.8% |
| 1991 | 326,533 million SLC | +10.6% |
| 1992 | 339,397 million SLC | +3.9% |
| 1993 | 316,937 million SLC | -6.6% |
| 1994 | 334,823 million SLC | +5.6% |
| 1995 | 386,367 million SLC | +15.4% |
| 1996 | 409,882 million SLC | +6.1% |
| 1997 | 446,877 million SLC | +9.0% |
| 1998 | 490,101 million SLC | +9.7% |
| 1999 | 554,755 million SLC | +13.2% |
| 2000 | 583,661 million SLC | +5.2% |
| 2001 | 590,372 million SLC | +1.1% |
| 2002 | 599,004 million SLC | +1.5% |
| 2003 | 630,569 million SLC | +5.3% |
| 2004 | 672,025 million SLC | +6.6% |
| 2005 | 716,238 million SLC | +6.6% |
| 2006 | 869,847 million SLC | +21.4% |
| 2007 | 992,642 million SLC | +14.1% |
| 2008 | 1.14 million million SLC | +14.6% |
| 2009 | 1.26 million million SLC | +10.5% |
| 2010 | 1.43 million million SLC | +14.0% |
| 2011 | 1.65 million million SLC | +15.1% |
| 2012 | 1.85 million million SLC | +12.4% |
| 2013 | 2.05 million million SLC | +10.3% |
| 2014 | 2.30 million million SLC | +12.6% |
| 2015 | 2.54 million million SLC | +10.1% |
| 2016 | 2.80 million million SLC | +10.1% |
| 2017 | 3.01 million million SLC | +7.8% |
| 2018 | 3.29 million million SLC | +9.4% |
| 2019 | 3.53 million million SLC | +7.3% |
| 2020 | 3.80 million million SLC | +7.6% |
| 2021 | 4.11 million million SLC | +7.9% |
| 2022 | 4.46 million million SLC | +8.5% |
| 2023 | 4.94 million million SLC | +10.9% |
| 2024 | 5.59 million million SLC | +13.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 47,683 million SLC | 16,148 million SLC | 84,673 million SLC | 10 |
| 1980s | 173,930 million SLC | 87,790 million SLC | 266,566 million SLC | 10 |
| 1990s | 390,091 million SLC | 295,242 million SLC | 554,755 million SLC | 10 |
| 2000s | 804,872 million SLC | 583,661 million SLC | 1.26 million million SLC | 10 |
| 2010s | 2.45 million million SLC | 1.43 million million SLC | 3.53 million million SLC | 10 |
| 2020s | 4.58 million million SLC | 3.80 million million SLC | 5.59 million million SLC | 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)
- Sawnwood — Production, annual growth rate 0 % change on previous year (2024)
- Sawnwood — Production, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood — Production, per capita 0.0029 m3 per person (2024)
- Sawnwood — Import quantity, annual growth rate 34.49 % change on previous year (2024)
- Sawnwood — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value standard in Bangladesh?
- Value added (agriculture, forestry and fishing) — value standard in Bangladesh was 5.59 million million SLC in 2024, according to Food and Agriculture Organization of the United Nations.
- What is the highest value added (agriculture, forestry and fishing) — value standard recorded in Bangladesh?
- The highest recorded value was 5.59 million million SLC in 2024.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Bangladesh?
- The lowest recorded value was 16,148 million SLC in 1971.
- How does Bangladesh rank for value added (agriculture, forestry and fishing) — value standard?
- Bangladesh ranks 27th out of 199 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value standard rising or falling in Bangladesh?
- Over the last ten years it is up 142.4%. 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 Standard Local Currency. Statizoid updates them automatically from the source API.
Download this data
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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).