Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bhutan
Bhutan: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 20,707 million SLC in 2024. ▲ Rising
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bhutan, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Bhutan recorded 20,707 million SLC for value added (agriculture, forestry and fishing) — value standard in 2024. That is the highest value across all 55 years on record.
That represents a change of up 3.1% on the previous year and up 29.4% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Bhutan peaked at 20,707 million SLC in 2024 and was at its lowest, 4,548 million SLC, in 1970.
Bhutan ranks 95th of 191 countries on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 55 years of available data.
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Bhutan, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 4,548 million SLC | — |
| 1971 | 4,670 million SLC | +2.7% |
| 1972 | 4,724 million SLC | +1.1% |
| 1973 | 4,792 million SLC | +1.4% |
| 1974 | 5,045 million SLC | +5.3% |
| 1975 | 4,872 million SLC | -3.4% |
| 1976 | 5,302 million SLC | +8.8% |
| 1977 | 5,756 million SLC | +8.6% |
| 1978 | 6,112 million SLC | +6.2% |
| 1979 | 6,401 million SLC | +4.7% |
| 1980 | 6,909 million SLC | +7.9% |
| 1981 | 7,296 million SLC | +5.6% |
| 1982 | 7,646 million SLC | +4.8% |
| 1983 | 8,234 million SLC | +7.7% |
| 1984 | 8,660 million SLC | +5.2% |
| 1985 | 9,030 million SLC | +4.3% |
| 1986 | 9,484 million SLC | +5.0% |
| 1987 | 9,920 million SLC | +4.6% |
| 1988 | 10,667 million SLC | +7.5% |
| 1989 | 11,263 million SLC | +5.6% |
| 1990 | 11,844 million SLC | +5.2% |
| 1991 | 11,766 million SLC | -0.7% |
| 1992 | 11,840 million SLC | +0.6% |
| 1993 | 11,809 million SLC | -0.3% |
| 1994 | 11,916 million SLC | +0.9% |
| 1995 | 12,091 million SLC | +1.5% |
| 1996 | 12,337 million SLC | +2.0% |
| 1997 | 12,425 million SLC | +0.7% |
| 1998 | 12,144 million SLC | -2.3% |
| 1999 | 11,796 million SLC | -2.9% |
| 2000 | 11,789 million SLC | -0.1% |
| 2001 | 12,453 million SLC | +5.6% |
| 2002 | 12,798 million SLC | +2.8% |
| 2003 | 13,061 million SLC | +2.1% |
| 2004 | 13,326 million SLC | +2.0% |
| 2005 | 13,493 million SLC | +1.2% |
| 2006 | 13,845 million SLC | +2.6% |
| 2007 | 13,963 million SLC | +0.9% |
| 2008 | 14,053 million SLC | +0.6% |
| 2009 | 14,506 million SLC | +3.2% |
| 2010 | 14,644 million SLC | +1.0% |
| 2011 | 14,992 million SLC | +2.4% |
| 2012 | 15,355 million SLC | +2.4% |
| 2013 | 15,639 million SLC | +1.9% |
| 2014 | 16,006 million SLC | +2.3% |
| 2015 | 16,835 million SLC | +5.2% |
| 2016 | 17,607 million SLC | +4.6% |
| 2017 | 18,159 million SLC | +3.1% |
| 2018 | 18,680 million SLC | +2.9% |
| 2019 | 19,003 million SLC | +1.7% |
| 2020 | 19,763 million SLC | +4.0% |
| 2021 | 20,044 million SLC | +1.4% |
| 2022 | 19,815 million SLC | -1.1% |
| 2023 | 20,087 million SLC | +1.4% |
| 2024 | 20,707 million SLC | +3.1% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 5,222 million SLC | 4,548 million SLC | 6,401 million SLC | 10 |
| 1980s | 8,911 million SLC | 6,909 million SLC | 11,263 million SLC | 10 |
| 1990s | 11,997 million SLC | 11,766 million SLC | 12,425 million SLC | 10 |
| 2000s | 13,329 million SLC | 11,789 million SLC | 14,506 million SLC | 10 |
| 2010s | 16,692 million SLC | 14,644 million SLC | 19,003 million SLC | 10 |
| 2020s | 20,083 million SLC | 19,763 million SLC | 20,707 million SLC | 5 |
Countries ranked near Bhutan
More environment data for Bhutan
- Historical exposure to drought — Land soil moisture anomaly 0.2782 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 0.5977 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.257 °C (2025)
- Temperature change 2.08 °C (2025)
- Sawnwood — Export quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood — Export quantity, per capita 0 m3 per person (2024)
- Sawnwood — Export value, annual growth rate -100 % change on previous year (2023)
- Sawnwood — Export value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
- Sawnwood — Export value, per capita 0 1000 USD per person (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value standard in Bhutan?
- Value added (agriculture, forestry and fishing) — value standard in Bhutan was 20,707 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 Bhutan?
- The highest recorded value was 20,707 million SLC in 2024.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Bhutan?
- The lowest recorded value was 4,548 million SLC in 1970.
- How does Bhutan rank for value added (agriculture, forestry and fishing) — value standard?
- Bhutan ranks 95th out of 191 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value standard rising or falling in Bhutan?
- Over the last ten years it is up 29.4%. The long-run trend across the full record is rising.
- Where does this Bhutan 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, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 55 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).
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).