China, Hong Kong SAR vs Tonga: ILO: ILO Modelled Estimates Employment in agriculture ILO … Male

China, Hong Kong SAR
4.67 1000 No
in 2025
Tonga
5.83 1000 No
in 2025
China, Hong Kong SAR rank
178th
Tonga rank
177th

ILO: ILO Modelled Estimates Employment in agriculture ILO … Male over time

  • China, Hong Kong SAR
  • Tonga
5101520199120082025

How they compare

Tonga currently reports 5.83 1000 No against 4.67 1000 No in China, Hong Kong SAR, a difference of 1.16 1000 No.

That makes Tonga's figure about 1.2 times China, Hong Kong SAR's.

The two have swapped places 1 time across 35 shared years of data; in 1991 it was China, Hong Kong SAR ahead.

China, Hong Kong SAR ranks 178th and Tonga ranks 177th of 194 countries.

Across the 4 decades both report, China, Hong Kong SAR averaged higher in 1 and Tonga in 3.

Head to head by decade

Decade China, Hong Kong SAR Tonga Difference Ahead
1990s 13.48 1000 No 9.52 1000 No 3.96 1000 No China, Hong Kong SAR
2000s 6.53 1000 No 9.42 1000 No 2.89 1000 No Tonga
2010s 6.08 1000 No 9.67 1000 No 3.59 1000 No Tonga
2020s 4.95 1000 No 6.73 1000 No 1.78 1000 No Tonga

Averages of every year both report within each decade.

Frequently asked questions

Which has higher ilo - ilo modelled estimates — employment in agriculture - ilo, China, Hong Kong SAR or Tonga?
Tonga, at 5.83 1000 No against 4.67 1000 No in China, Hong Kong SAR as of 2025.
What is the difference in ilo - ilo modelled estimates — employment in agriculture - ilo between China, Hong Kong SAR and Tonga?
1.16 1000 No, with Tonga ahead.
How many years of comparable data are there for China, Hong Kong SAR and Tonga?
35 years are reported by both, from 1991 to 2025.
How do China, Hong Kong SAR and Tonga rank globally for ilo - ilo modelled estimates — employment in agriculture - ilo?
China, Hong Kong SAR ranks 178th and Tonga ranks 177th of 194 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as ILO - ILO Modelled Estimates — Employment in agriculture - ILO modelled estimates — Male — Value. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

China, Hong Kong SAR vs Tonga: ILO - ILO Modelled Estimates — Employment in agriculture - ILO. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 24 October 2026, from https://agriculture.statizoid.com/compare/ilo-ilo-modelled-estimates-employment-in-agriculture-ilo-modelled-estimates-male-value/china-hong-kong-sar/tonga/

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/compare/ilo-ilo-modelled-estimates-employment-in-agriculture-ilo-modelled-estimates-male-value/china-hong-kong-sar/tonga/">China, Hong Kong SAR vs Tonga: ILO - ILO Modelled Estimates — Employment in agriculture - ILO</a> — Statizoid

About this data

Indicator
ILO - ILO Modelled Estimates — Employment in agriculture - ILO modelled estimates — Male — Value
Unit
1000 No
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
227 places, 7,928 data points, 1991–2025
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.