Value Added (Agriculture, Forestry and Fishing) — Value Standard in Thailand
Thailand: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 1.62 million million SLC in 2024. ◆ Volatile
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Thailand, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
In 2024, value added (agriculture, forestry and fishing) — value standard in Thailand stood at 1.62 million million SLC. That is the highest value across all 55 years on record.
The figure is up 5.3% on the previous year and up 21.2% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Thailand peaked at 1.62 million million SLC in 2024 and was at its lowest, 38,227 million SLC, in 1971.
Thailand ranks 46th 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 Thailand, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 39,787 million SLC | — |
| 1971 | 38,227 million SLC | -3.9% |
| 1972 | 44,966 million SLC | +17.6% |
| 1973 | 64,142 million SLC | +42.6% |
| 1974 | 78,630 million SLC | +22.6% |
| 1975 | 84,991 million SLC | +8.1% |
| 1976 | 96,395 million SLC | +13.4% |
| 1977 | 104,225 million SLC | +8.1% |
| 1978 | 124,730 million SLC | +19.7% |
| 1979 | 139,858 million SLC | +12.1% |
| 1980 | 159,550 million SLC | +14.1% |
| 1981 | 168,286 million SLC | +5.5% |
| 1982 | 161,766 million SLC | -3.9% |
| 1983 | 191,460 million SLC | +18.4% |
| 1984 | 179,947 million SLC | -6.0% |
| 1985 | 173,091 million SLC | -3.8% |
| 1986 | 183,983 million SLC | +6.3% |
| 1987 | 211,947 million SLC | +15.2% |
| 1988 | 261,508 million SLC | +23.4% |
| 1989 | 331,224 million SLC | +26.7% |
| 1990 | 225,988 million SLC | -31.8% |
| 1991 | 266,350 million SLC | +17.9% |
| 1992 | 295,792 million SLC | +11.1% |
| 1993 | 261,917 million SLC | -11.5% |
| 1994 | 318,278 million SLC | +21.5% |
| 1995 | 383,011 million SLC | +20.3% |
| 1996 | 420,416 million SLC | +9.8% |
| 1997 | 426,985 million SLC | +1.6% |
| 1998 | 482,343 million SLC | +13.0% |
| 1999 | 425,959 million SLC | -11.7% |
| 2000 | 430,927 million SLC | +1.2% |
| 2001 | 458,563 million SLC | +6.4% |
| 2002 | 501,502 million SLC | +9.4% |
| 2003 | 596,439 million SLC | +18.9% |
| 2004 | 646,130 million SLC | +8.3% |
| 2005 | 700,096 million SLC | +8.4% |
| 2006 | 789,829 million SLC | +12.8% |
| 2007 | 848,424 million SLC | +7.4% |
| 2008 | 977,725 million SLC | +15.2% |
| 2009 | 945,297 million SLC | -3.3% |
| 2010 | 1.14 million million SLC | +20.3% |
| 2011 | 1.31 million million SLC | +15.2% |
| 2012 | 1.42 million million SLC | +8.5% |
| 2013 | 1.46 million million SLC | +2.9% |
| 2014 | 1.33 million million SLC | -8.7% |
| 2015 | 1.22 million million SLC | -8.6% |
| 2016 | 1.24 million million SLC | +1.4% |
| 2017 | 1.30 million million SLC | +5.3% |
| 2018 | 1.34 million million SLC | +3.1% |
| 2019 | 1.37 million million SLC | +2.2% |
| 2020 | 1.36 million million SLC | -0.7% |
| 2021 | 1.41 million million SLC | +3.2% |
| 2022 | 1.52 million million SLC | +7.8% |
| 2023 | 1.54 million million SLC | +1.3% |
| 2024 | 1.62 million million SLC | +5.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 81,595 million SLC | 38,227 million SLC | 139,858 million SLC | 10 |
| 1980s | 202,276 million SLC | 159,550 million SLC | 331,224 million SLC | 10 |
| 1990s | 350,704 million SLC | 225,988 million SLC | 482,343 million SLC | 10 |
| 2000s | 689,493 million SLC | 430,927 million SLC | 977,725 million SLC | 10 |
| 2010s | 1.31 million million SLC | 1.14 million million SLC | 1.46 million million SLC | 10 |
| 2020s | 1.49 million million SLC | 1.36 million million SLC | 1.62 million million SLC | 5 |
Countries ranked near Thailand
More environment data for Thailand
- Historical exposure to drought — Land soil moisture anomaly 1.44 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 1.54 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.306 °C (2025)
- Temperature change 1.01 °C (2025)
- Paper and paperboard — Import quantity, annual growth rate 17.77 % change on previous year (2024)
- Paper and paperboard — Import quantity, per unit of GDP 0 t per US$ of GDP (2024)
- Paper and paperboard — Import quantity, per capita 0.018 t per person (2024)
- Paper and paperboard — Import value, annual growth rate 9.9 % change on previous year (2024)
- Paper and paperboard — Import value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value standard in Thailand?
- Value added (agriculture, forestry and fishing) — value standard in Thailand was 1.62 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 Thailand?
- The highest recorded value was 1.62 million million SLC in 2024.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Thailand?
- The lowest recorded value was 38,227 million SLC in 1971.
- How does Thailand rank for value added (agriculture, forestry and fishing) — value standard?
- Thailand ranks 46th out of 199 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value standard rising or falling in Thailand?
- Over the last ten years it is up 21.2%. The long-run trend across the full record is volatile.
- Where does this Thailand 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.
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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).