FAO Model — Share of non-agricultural AFS employment in total AFS in Southern Africa

Southern Africa: FAO Model — Share of non-agricultural AFS employment in total AFS was 65.31 % in 2023. ▬ Flat

Latest (2023)
65.31 %
Change on year
down 0.5%
Rank
12th
of 31 groups
All-time high
72.32 %
in 2006
All-time low
64.71 %
in 2021
Years of data
24
2000–2023

FAO Model — Share of non-agricultural AFS employment in total AFS in Southern Africa, 2000–2023

0204060802000201120232000: 65.2 %2001: 70.5 %2002: 65.6 %2003: 67.2 %2004: 67.3 %2005: 71.1 %2006: 72.3 %2007: 70.9 %2008: 68.1 %2009: 68.7 %2010: 69.1 %2011: 69.7 %2012: 68.2 %2013: 67.3 %2014: 68.1 %2015: 66.5 %2016: 68.3 %2017: 69 %2018: 68.3 %2019: 67.6 %2020: 64.8 %2021: 64.7 %2022: 65.6 %2023: 65.3 %

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

Analysis

The most recent figure for fao model — share of non-agricultural afs employment in total afs in Southern Africa is 65.31 %, measured in 2023.

That represents a change of down 0.5% on the previous year and down 2.9% over ten years.

Over the whole period, fao model — share of non-agricultural afs employment in total afs in Southern Africa peaked at 72.32 % in 2006 and was at its lowest, 64.71 %, in 2021.

That places Southern Africa 12th out of 31 groups with data for 2023, putting it in the middle of the range.

FAO Model — Share of non-agricultural AFS employment in total AFS in Southern Africa, year by year

Annual values for FAO Model — Share of non-agricultural AFS employment in total AFS employment — Female — Value in Southern Africa, 2000 to 2023.
Year % Change
2000 65.16 %
2001 70.45 % +8.1%
2002 65.59 % -6.9%
2003 67.22 % +2.5%
2004 67.33 % +0.2%
2005 71.13 % +5.6%
2006 72.32 % +1.7%
2007 70.88 % -2.0%
2008 68.06 % -4.0%
2009 68.74 % +1.0%
2010 69.13 % +0.6%
2011 69.66 % +0.8%
2012 68.2 % -2.1%
2013 67.26 % -1.4%
2014 68.12 % +1.3%
2015 66.55 % -2.3%
2016 68.32 % +2.7%
2017 69.02 % +1.0%
2018 68.33 % -1.0%
2019 67.63 % -1.0%
2020 64.83 % -4.1%
2021 64.71 % -0.2%
2022 65.63 % +1.4%
2023 65.31 % -0.5%

Averages by decade

DecadeAverage LowestHighest Years
2000s 68.69 % 65.16 % 72.32 % 10
2010s 68.22 % 66.55 % 69.66 % 10
2020s 65.12 % 64.71 % 65.63 % 4

Countries ranked near Southern Africa

  1. 9 Belgium 89.65 % compare
  2. 10 Estonia 89.2 % compare
  3. 10 Timor-Leste 28.69 % compare
  4. 11 Seychelles 88.52 % compare
  5. 11 United Republic of Tanzania 20.64 % compare
  6. 12 El Salvador 88.51 % compare
  7. 13 Cabo Verde 65.09 % compare
  8. 13 Lao People's Democratic Republic 18.02 % compare
  9. 13 Spain 87.85 % compare
  10. 14 Germany 87.45 % compare
  11. 15 Democratic Republic of the Congo 7.04 % compare
  12. 15 Ireland 86.82 % compare

See the full ranking of 171 places →

More agriculture & rural data for Southern Africa

All data for Southern Africa →

Frequently asked questions

What is fao model — share of non-agricultural afs employment in total afs in Southern Africa?
Fao model — share of non-agricultural afs employment in total afs in Southern Africa was 65.31 % in 2023, according to Food and Agriculture Organization of the United Nations.
What is the highest fao model — share of non-agricultural afs employment in total afs recorded in Southern Africa?
The highest recorded value was 72.32 % in 2006.
What is the lowest fao model — share of non-agricultural afs employment in total afs recorded in Southern Africa?
The lowest recorded value was 64.71 % in 2021.
How does Southern Africa rank for fao model — share of non-agricultural afs employment in total afs?
Southern Africa ranks 12th out of 31 groups with data for 2023.
Is fao model — share of non-agricultural afs employment in total afs rising or falling in Southern Africa?
Over the last ten years it is down 2.9%. The long-run trend across the full record is flat.
Where does this Southern Africa data come from?
The figures come from Food and Agriculture Organization of the United Nations, published as part of FAO Model — Share of non-agricultural AFS employment in total AFS employment — Female — Value. Statizoid updates them automatically from the source API.

Download this data

CSV · JSON — 24 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).

Share, cite or embed this page

Cite this page

FAO Model — Share of non-agricultural AFS employment in total AFS in Southern Africa. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 17 September 2026, from https://agriculture.statizoid.com/stat/fao-model-share-of-non-agricultural-afs-employment-in-total-afs-employment-female-value/southern-africa/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY-NC-SA 3.0 IGO (FAO); please keep the attribution.

<a href="https://agriculture.statizoid.com/stat/fao-model-share-of-non-agricultural-afs-employment-in-total-afs-employment-female-value/southern-africa/">FAO Model — Share of non-agricultural AFS employment in total AFS in Southern Africa</a> — Statizoid

About this data

Indicator
FAO Model — Share of non-agricultural AFS employment in total AFS employment — Female — Value
Unit
%
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
171 places, 3,932 data points, 2000–2023
Last refreshed

The FAOSTAT Employment indicators domain focuses on indicators related to employment in agrifood systems and rural areas. The update is performed yearly, using data from the International Labour Organization (ILO) database that contains a rich set of indicators from a wide range of topics related to labour statistics. The indicators published in FAOSTAT are derived from the labour force statistics (LFS) and rural and urban labour markets (RURURB) databases of the ILOSTAT database. In addition, the ILO modelled estimates and projections (ILOEST) are used to provide information on employment in agriculture. FAOSTAT also publishes indicators on employment in agrifood systems (AFS) from 2000 at the national, regional, and global levels, using a methodology developed by the FAO to estimate the number of people employed within these systems.