ILOSTAT - Labour force survey — Mean weekly hours actually worked per in Bhutan
Bhutan: ILOSTAT - Labour force survey — Mean weekly hours actually worked per was 53.16 No in 2022. ▲ Rising
ILOSTAT - Labour force survey — Mean weekly hours actually worked per in Bhutan, 2018–2022
Source: Food and Agriculture Organization of the United Nations. Measured in No.
Analysis
In 2022, ilostat - labour force survey — mean weekly hours actually worked per in Bhutan stood at 53.16 No. That is the highest value across all 5 years on record.
That represents a change of up 7.4% on the previous year and up 7.5% over five years.
That places Bhutan 1st out of 88 countries with data for 2022, putting it in the top 10%.
ILOSTAT - Labour force survey — Mean weekly hours actually worked per in Bhutan, year by year
| Year | No | Change |
|---|---|---|
| 2018 | 49.44 No | — |
| 2019 | 50.51 No | +2.2% |
| 2020 | 47.27 No | -6.4% |
| 2021 | 49.49 No | +4.7% |
| 2022 | 53.16 No | +7.4% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 49.97 No | 49.44 No | 50.51 No | 2 |
| 2020s | 49.97 No | 47.27 No | 53.16 No | 3 |
Countries ranked near Bhutan
- 1 Côte d'Ivoire 36.92 No
- 1 Republic of Moldova 38.27 No compare
- 2 Cayman Islands 50 No
- 2 Venezuela (Bolivarian Republic of) 37.33 No
- 3 Mongolia 47.06 No compare
- 3 Türkiye 33.25 No compare
- 4 China, Hong Kong SAR 45.5 No
- 4 Democratic People's Republic of Korea 31.66 No compare
More agriculture & rural data for Bhutan
- Agriculture, forestry, and fishing, value added (current US$), annual 3.41 % change on previous year (2025)
- Agriculture, forestry, and fishing, value added (current US$), per 0.1368 current US$ per US$ of GDP (2025)
- Agriculture, forestry, and fishing, value added (current US$), per 614.64 current US$ per person (2025)
- Rural population, annual growth rate -0.8653 % change on previous year (2025)
- Rural population, per unit of GDP 0.0001 units per US$ of GDP (2025)
- Rural population, per capita 0.5657 units per person (2025)
- Share of GDP from agriculture 13.7% (2025)
- Agriculture as a share of GDP vs. GDP per capita 13.7% (2025)
- Agricultural raw materials exports 2.0% (2025)
- Agricultural raw materials imports 1.8% (2025)
Frequently asked questions
- What is ilostat - labour force survey — mean weekly hours actually worked per in Bhutan?
- Ilostat - labour force survey — mean weekly hours actually worked per in Bhutan was 53.16 No in 2022, according to Food and Agriculture Organization of the United Nations.
- What is the highest ilostat - labour force survey — mean weekly hours actually worked per recorded in Bhutan?
- The highest recorded value was 53.16 No in 2022.
- What is the lowest ilostat - labour force survey — mean weekly hours actually worked per recorded in Bhutan?
- The lowest recorded value was 47.27 No in 2020.
- How does Bhutan rank for ilostat - labour force survey — mean weekly hours actually worked per?
- Bhutan ranks 1st out of 88 countries with data for 2022.
- Where does this Bhutan data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of ILOSTAT - Labour force survey — Mean weekly hours actually worked per employed person in agriculture — Female — Value. Statizoid updates them automatically from the source API.
Download this data
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About this data
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.