Value Added (Agriculture, Forestry and Fishing) — Value Standard in Malaysia
Malaysia: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 102,865 million SLC in 2024. ▲ Rising
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Malaysia, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
The most recent figure for value added (agriculture, forestry and fishing) — value standard in Malaysia is 102,865 million SLC, measured in 2024. That is the highest value across all 55 years on record.
Compared with earlier readings it is up 3.1% on the previous year and up 7.0% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Malaysia peaked at 102,865 million SLC in 2024 and was at its lowest, 20,978 million SLC, in 1970.
That places Malaysia 71st out of 191 countries with data for 2024, putting it 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 Malaysia, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 20,978 million SLC | — |
| 1971 | 26,486 million SLC | +26.3% |
| 1972 | 28,507 million SLC | +7.6% |
| 1973 | 31,862 million SLC | +11.8% |
| 1974 | 34,063 million SLC | +6.9% |
| 1975 | 33,031 million SLC | -3.0% |
| 1976 | 37,074 million SLC | +12.2% |
| 1977 | 37,947 million SLC | +2.4% |
| 1978 | 38,573 million SLC | +1.6% |
| 1979 | 40,791 million SLC | +5.8% |
| 1980 | 41,314 million SLC | +1.3% |
| 1981 | 43,321 million SLC | +4.9% |
| 1982 | 46,196 million SLC | +6.6% |
| 1983 | 45,827 million SLC | -0.8% |
| 1984 | 47,129 million SLC | +2.8% |
| 1985 | 48,065 million SLC | +2.0% |
| 1986 | 50,068 million SLC | +4.2% |
| 1987 | 53,588 million SLC | +7.0% |
| 1988 | 56,495 million SLC | +5.4% |
| 1989 | 59,881 million SLC | +6.0% |
| 1990 | 59,513 million SLC | -0.6% |
| 1991 | 59,458 million SLC | -0.1% |
| 1992 | 63,536 million SLC | +6.9% |
| 1993 | 61,538 million SLC | -3.1% |
| 1994 | 60,376 million SLC | -1.9% |
| 1995 | 58,850 million SLC | -2.5% |
| 1996 | 61,511 million SLC | +4.5% |
| 1997 | 61,927 million SLC | +0.7% |
| 1998 | 60,214 million SLC | -2.8% |
| 1999 | 60,503 million SLC | +0.5% |
| 2000 | 64,169 million SLC | +6.1% |
| 2001 | 64,058 million SLC | -0.2% |
| 2002 | 65,894 million SLC | +2.9% |
| 2003 | 69,868 million SLC | +6.0% |
| 2004 | 73,134 million SLC | +4.7% |
| 2005 | 75,031 million SLC | +2.6% |
| 2006 | 79,410 million SLC | +5.8% |
| 2007 | 80,504 million SLC | +1.4% |
| 2008 | 83,592 million SLC | +3.8% |
| 2009 | 83,637 million SLC | +0.1% |
| 2010 | 85,642 million SLC | +2.4% |
| 2011 | 91,504 million SLC | +6.8% |
| 2012 | 92,383 million SLC | +1.0% |
| 2013 | 94,217 million SLC | +2.0% |
| 2014 | 96,146 million SLC | +2.0% |
| 2015 | 97,539 million SLC | +1.4% |
| 2016 | 93,977 million SLC | -3.7% |
| 2017 | 99,509 million SLC | +5.9% |
| 2018 | 99,637 million SLC | +0.1% |
| 2019 | 101,573 million SLC | +1.9% |
| 2020 | 99,109 million SLC | -2.4% |
| 2021 | 99,000 million SLC | -0.1% |
| 2022 | 99,073 million SLC | +0.1% |
| 2023 | 99,791 million SLC | +0.7% |
| 2024 | 102,865 million SLC | +3.1% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 32,931 million SLC | 20,978 million SLC | 40,791 million SLC | 10 |
| 1980s | 49,189 million SLC | 41,314 million SLC | 59,881 million SLC | 10 |
| 1990s | 60,743 million SLC | 58,850 million SLC | 63,536 million SLC | 10 |
| 2000s | 73,930 million SLC | 64,058 million SLC | 83,637 million SLC | 10 |
| 2010s | 95,213 million SLC | 85,642 million SLC | 101,573 million SLC | 10 |
| 2020s | 99,968 million SLC | 99,000 million SLC | 102,865 million SLC | 5 |
Countries ranked near Malaysia
More environment data for Malaysia
- Historical exposure to drought — Land soil moisture anomaly -1.65 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -1.9 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.179 °C (2025)
- Temperature change 1.25 °C (2025)
- Sawnwood — Export quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood — Export quantity, per capita 0.0278 m3 per person (2024)
- Sawnwood — Export value, annual growth rate -11.04 % change on previous year (2024)
- Sawnwood — Export value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
- Sawnwood — Export value, per capita 0.0127 1000 USD per person (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value standard in Malaysia?
- Value added (agriculture, forestry and fishing) — value standard in Malaysia was 102,865 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 Malaysia?
- The highest recorded value was 102,865 million SLC in 2024.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Malaysia?
- The lowest recorded value was 20,978 million SLC in 1970.
- How does Malaysia rank for value added (agriculture, forestry and fishing) — value standard?
- Malaysia ranks 71st out of 191 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value standard rising or falling in Malaysia?
- Over the last ten years it is up 7.0%. The long-run trend across the full record is rising.
- Where does this Malaysia 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).