Value Added (Agriculture, Forestry and Fishing) — Value US$ in Southern Africa

Southern Africa: Value Added (Agriculture, Forestry and Fishing) — Value US$ was 13,054 million USD in 2024. ▲ Rising

Latest (2024)
13,054 million USD
Change on year
up 15.3%
Rank
28th
of 29 groups
All-time high
13,444 million USD
in 2022
All-time low
1,362 million USD
in 1970
Years of data
55
1970–2024

Value Added (Agriculture, Forestry and Fishing) — Value US$ in Southern Africa, 1970–2024

2.5k5.0k7.5k10.0k12.5k197019972024

Source: Food and Agriculture Organization of the United Nations. Measured in million USD.

Analysis

In 2024, value added (agriculture, forestry and fishing) — value us$ in Southern Africa stood at 13,054 million USD.

Compared with earlier readings it is up 15.3% on the previous year and up 31.9% over ten years.

Over the whole period, value added (agriculture, forestry and fishing) — value us$ in Southern Africa peaked at 13,444 million USD in 2022 and was at its lowest, 1,362 million USD, in 1970.

That places Southern Africa 28th out of 29 groups with data for 2024, putting it in the bottom quarter.

The long-run direction has been consistently rising across the 55 years of available data.

Value Added (Agriculture, Forestry and Fishing) — Value US$ in Southern Africa, year by year

Annual values for Value Added (Agriculture, Forestry and Fishing) — Value US$ in Southern Africa, 1970 to 2024.
Year million USD Change
1970 1,362 million USD
1971 1,622 million USD +19.1%
1972 1,692 million USD +4.3%
1973 2,223 million USD +31.4%
1974 3,272 million USD +47.2%
1975 3,024 million USD -7.6%
1976 2,579 million USD -14.7%
1977 2,980 million USD +15.6%
1978 3,270 million USD +9.7%
1979 3,610 million USD +10.4%
1980 5,322 million USD +47.4%
1981 5,679 million USD +6.7%
1982 4,569 million USD -19.5%
1983 4,056 million USD -11.2%
1984 3,782 million USD -6.8%
1985 3,078 million USD -18.6%
1986 3,391 million USD +10.2%
1987 4,945 million USD +45.8%
1988 5,520 million USD +11.6%
1989 5,334 million USD -3.4%
1990 5,386 million USD +1.0%
1991 5,864 million USD +8.9%
1992 5,361 million USD -8.6%
1993 5,603 million USD +4.5%
1994 6,492 million USD +15.9%
1995 6,180 million USD -4.8%
1996 6,356 million USD +2.8%
1997 6,279 million USD -1.2%
1998 5,346 million USD -14.9%
1999 5,042 million USD -5.7%
2000 4,828 million USD -4.3%
2001 4,544 million USD -5.9%
2002 4,505 million USD -0.9%
2003 6,260 million USD +39.0%
2004 7,291 million USD +16.5%
2005 7,365 million USD +1.0%
2006 7,621 million USD +3.5%
2007 9,252 million USD +21.4%
2008 9,426 million USD +1.9%
2009 9,308 million USD -1.3%
2010 10,587 million USD +13.7%
2011 11,287 million USD +6.6%
2012 10,579 million USD -6.3%
2013 9,532 million USD -9.9%
2014 9,896 million USD +3.8%
2015 9,227 million USD -6.8%
2016 9,276 million USD +0.5%
2017 11,276 million USD +21.6%
2018 11,092 million USD -1.6%
2019 9,321 million USD -16.0%
2020 10,468 million USD +12.3%
2021 12,802 million USD +22.3%
2022 13,444 million USD +5.0%
2023 11,325 million USD -15.8%
2024 13,054 million USD +15.3%

Averages by decade

DecadeAverage LowestHighest Years
1970s 2,564 million USD 1,362 million USD 3,610 million USD 10
1980s 4,568 million USD 3,078 million USD 5,679 million USD 10
1990s 5,791 million USD 5,042 million USD 6,492 million USD 10
2000s 7,040 million USD 4,505 million USD 9,426 million USD 10
2010s 10,207 million USD 9,227 million USD 11,287 million USD 10
2020s 12,218 million USD 10,468 million USD 13,444 million USD 5

Countries ranked near Southern Africa

  1. 25 Australia 35,101 million USD compare
  2. 26 Malaysia 34,257 million USD compare
  3. 27 Saudi Arabia 30,424 million USD compare
  4. 28 Kenya 26,578 million USD compare
  5. 29 Republic of Korea 25,802 million USD compare
  6. 30 Poland 23,559 million USD compare
  7. 31 Uzbekistan 21,268 million USD compare

See the full ranking of 249 places →

More environment data for Southern Africa

All data for Southern Africa →

Frequently asked questions

What is value added (agriculture, forestry and fishing) — value us$ in Southern Africa?
Value added (agriculture, forestry and fishing) — value us$ in Southern Africa was 13,054 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 Southern Africa?
The highest recorded value was 13,444 million USD in 2022.
What is the lowest value added (agriculture, forestry and fishing) — value us$ recorded in Southern Africa?
The lowest recorded value was 1,362 million USD in 1970.
How does Southern Africa rank for value added (agriculture, forestry and fishing) — value us$?
Southern Africa ranks 28th out of 29 groups with data for 2024.
Is value added (agriculture, forestry and fishing) — value us$ rising or falling in Southern Africa?
Over the last ten years it is up 31.9%. The long-run trend across the full record is rising.
Where does this Southern Africa 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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Value Added (Agriculture, Forestry and Fishing) — Value US$ in Southern Africa. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 29 August 2026, from https://environment.statizoid.com/stat/value-added-agriculture-forestry-and-fishing-value-us/southern-africa/

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About this data

Indicator
Value Added (Agriculture, Forestry and Fishing) — Value US$
Unit
million USD
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
249 places, 12,769 data points, 1970–2024
Last refreshed

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).