Labour market - FUAs — Labour force in Jinju
Jinju: Labour market - FUAs — Labour force was 203,253 Persons in 2024. ▲ Rising
Labour market - FUAs — Labour force in Jinju, 2000–2024
Source: Organisation for Economic Co-operation and Development. Measured in Persons.
Analysis
In 2024, labour market - fuas — labour force in Jinju stood at 203,253 Persons.
That represents a change of down 0.3% on the previous year and up 5.7% over ten years.
Over the whole period, labour market - fuas — labour force in Jinju peaked at 205,321 Persons in 2019 and was at its lowest, 159,443 Persons, in 2000.
Jinju ranks 371st of 579 regions on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 25 years of available data.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2000s | 170,980 Persons | 159,443 Persons | 180,687 Persons | 10 |
| 2010s | 194,100 Persons | 181,817 Persons | 205,321 Persons | 10 |
| 2020s | 203,642 Persons | 203,253 Persons | 203,965 Persons | 5 |
More work & labour data for Jinju
- Labour market - FUAs — Employment 198,631 Persons (2024)
- Economy - FUAs — Employment at place of work 201,208 Persons (2023)
Frequently asked questions
- What is labour market - fuas — labour force in Jinju?
- Labour market - fuas — labour force in Jinju was 203,253 Persons in 2024, according to Organisation for Economic Co-operation and Development.
- What is the highest labour market - fuas — labour force recorded in Jinju?
- The highest recorded value was 205,321 Persons in 2019.
- What is the lowest labour market - fuas — labour force recorded in Jinju?
- The lowest recorded value was 159,443 Persons in 2000.
- How does Jinju rank for labour market - fuas — labour force?
- Jinju ranks 371st out of 579 regions with data for 2024.
- Is labour market - fuas — labour force rising or falling in Jinju?
- Over the last ten years it is up 5.7%. The long-run trend across the full record is rising.
- Where does this Jinju data come from?
- The figures come from Organisation for Economic Co-operation and Development, published as part of Labour market - FUAs — Labour force. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 25 observations, free to reuse under OECD Terms and Conditions (attribution required).
About this data
<p align="justify">This dataset provides labour market indicators for FUAs of more than 250 000 inhabitants, including labour force, participation rate, employment, employment to population ratio, unemployment and unemployment rate.</p> <h3>Data sources and methodology</h3> <p align="justify"> When labour statistics are unavailable at a more granular level than FUAs (e.g. municipal level), the indicators are estimated by adjusting the regional (OECD TL2 and TL3 regions) values to the FUA boundaries, based on the population distribution in each region. Regional values (labour force, employment and unemployment) in TL3 regions are used as data inputs and combined with gridded population data <a href=https://doi.org/10.2760/098587>(European Commission, GHSL Data Package 2023)</a>. FUA boundaries are intersected with TL3 borders to compute the share of the regional population that lives within FUAs in each region. This share is then applied to the variable of interest (e.g. employment) and allocated to the FUA. In case several regions intersect the FUA, the adjusted values of intersecting regions are summed. For countries where TL3-level data is not available, data for TL2 regions is used. This approach assumes that the variable of interest has the same spatial distribution as population. Therefore, the modelled indicators should be interpreted with caution.<br /><br /> When a more granular level is available, data is aggregated for each FUA. For example in the United States, labour market data is available at the county-level (<a href=https://www.bls.gov/lau/#cntyaa>US Bureau of Labor Statistics</a>), and then aggregated by FUA. </p> <h3>Defining FUAs and cities</h3> <p align="justify">The OECD, in cooperation with the EU, has developed a harmonised <a href="https://www.oecd.org/en/data/datasets/oecd-definition-of-cities-and-functional-urban-areas.html">definition of functional urban areas</a> (FUAs) to capture the economic and functional reach of cities based on daily commuting patterns <a href=https://doi.org/10.1787/9789264174108-en>(OECD, 2012)</a>. FUAs consist of: <ol> <li><b>A city</b> – defined by urban centres in the degree of urbanisation, adapted to the closest local administrative units to define a city.</li> <li><b>A commuting zone</b> – including all local areas where at least 15% of employed residents work in the city.</li> </ol> The delineation process includes: <ul> <li>Assigning municipalities surrounded by a single FUA to that FUA.</li> <li>Excluding non-contiguous municipalities.</li> </ul> The definition identifies 1 285 FUAs and 1 402 cities in all OECD member countries except Costa Rica and three accession countries.</p> <h3>Cite this dataset</h3> <p>OECD Regions, cities and local areas database (<a href="http://data-explorer.oecd.org/s/1dx">Labour market - FUAs</a>), <a href="http://oe.cd/geostats">http://oe.cd/geostats</a></p> <h3>Further information</h3> <ul> <li> <a href=https://localdataportal.oecd.org/>OECD Local Data Portal </a> </li> <li> <a href=https://www.oecd.org/en/publications/oecd-regions-and-cities-at-a-glance-2024_f42db3bf-en.html/>OECD Regions and Cities at a Glance </a> </li> </ul> <p align="justify">For questions and/or comments, please email <a href="mailto:CitiesStat@oecd.org">CitiesStat@oecd.org</a>