Economy - FUAs — Employment at place of work in Gyeongsan

Gyeongsan: Economy - FUAs — Employment at place of work was 162,672 Persons in 2023. ▲ Rising

Latest (2023)
162,672 Persons
Change on year
down 0.0%
Rank
375th
of 487 regions
All-time high
162,704 Persons
in 2022
All-time low
150,202 Persons
in 2009
Years of data
16
2008–2023

Economy - FUAs — Employment at place of work in Gyeongsan, 2008–2023

050.0k100.0k150.0k2008201520232008: 153.0k Persons2009: 150.2k Persons2010: 151.7k Persons2011: 150.7k Persons2012: 154.0k Persons2013: 155.1k Persons2014: 158.4k Persons2015: 157.9k Persons2016: 157.8k Persons2017: 160.0k Persons2018: 159.4k Persons2019: 155.1k Persons2020: 156.7k Persons2021: 158.0k Persons2022: 162.7k Persons2023: 162.7k Persons

Source: Organisation for Economic Co-operation and Development. Measured in Persons.

Analysis

In 2023, economy - fuas — employment at place of work in Gyeongsan stood at 162,672 Persons.

Compared with earlier readings it is up 4.9% over ten years.

Over the whole period, economy - fuas — employment at place of work in Gyeongsan peaked at 162,704 Persons in 2022 and was at its lowest, 150,202 Persons, in 2009.

Gyeongsan ranks 375th of 487 regions on this measure, in the bottom quarter.

The long-run direction has been consistently rising across the 16 years of available data.

Economy - FUAs — Employment at place of work in Gyeongsan, year by year

Annual values for Economy - FUAs — Employment at place of work in Gyeongsan, 2008 to 2023.
Year Persons Change
2008 153,036 Persons
2009 150,202 Persons -1.9%
2010 151,728 Persons +1.0%
2011 150,747 Persons -0.6%
2012 154,017 Persons +2.2%
2013 155,129 Persons +0.7%
2014 158,388 Persons +2.1%
2015 157,908 Persons -0.3%
2016 157,832 Persons -0.0%
2017 160,034 Persons +1.4%
2018 159,402 Persons -0.4%
2019 155,063 Persons -2.7%
2020 156,698 Persons +1.1%
2021 158,006 Persons +0.8%
2022 162,704 Persons +3.0%
2023 162,672 Persons -0.0%

Averages by decade

DecadeAverage LowestHighest Years
2000s 151,619 Persons 150,202 Persons 153,036 Persons 2
2010s 156,025 Persons 150,747 Persons 160,034 Persons 10
2020s 160,020 Persons 156,698 Persons 162,704 Persons 4

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Frequently asked questions

What is economy - fuas — employment at place of work in Gyeongsan?
Economy - fuas — employment at place of work in Gyeongsan was 162,672 Persons in 2023, according to Organisation for Economic Co-operation and Development.
What is the highest economy - fuas — employment at place of work recorded in Gyeongsan?
The highest recorded value was 162,704 Persons in 2022.
What is the lowest economy - fuas — employment at place of work recorded in Gyeongsan?
The lowest recorded value was 150,202 Persons in 2009.
How does Gyeongsan rank for economy - fuas — employment at place of work?
Gyeongsan ranks 375th out of 487 regions with data for 2023.
Is economy - fuas — employment at place of work rising or falling in Gyeongsan?
Over the last ten years it is up 4.9%. The long-run trend across the full record is rising.
Where does this Gyeongsan data come from?
The figures come from Organisation for Economic Co-operation and Development, published as part of Economy - FUAs — Employment at place of work. Statizoid updates them automatically from the source API.

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Economy - FUAs — Employment at place of work in Gyeongsan. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 06 September 2026, from https://labour.statizoid.com/stat/economy-fuas-employment-at-place-of-work/gyeongsan/

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About this data

Indicator
Economy - FUAs — Employment at place of work
Unit
Persons
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
493 places, 10,805 data points, 2000–2023
Last refreshed

This dataset provides economic indicators for FUAs of more than 250 000 inhabitants, including GDP, GDP per capita, jobs and labour productivity. Data sources and methodology When economic statistics are unavailable at a more granular level than the FUA (e.g. municipal level), indicators are estimated by adjusting regional (OECD TL2 and TL3 regions) values to FUA boundaries, based on the population distribution in each region. Regional values (GDP and jobs) in TL3 regions are used as data inputs and combined with gridded population data (European Commission, GHSL Data Package 2023). 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. GDP) 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. When a more granular level is available, data is aggregated for each FUA. For example in the United States, GDP estimates are available at the county-level (US Bureau of Economic Analysis), and then aggregated by FUA. Defining FUAs and cities The OECD, in cooperation with the EU, has developed a harmonised definition of functional urban areas (FUAs) to capture the economic and functional reach of cities based on daily commuting patterns (OECD, 2012). FUAs consist of: A city – defined by urban centres in the degree of urbanisation, adapted to the closest local administrative units to define a city. A commuting zone – including all local areas where at least 15% of employed residents work in the city. The delineation process includes: Assigning municipalities surrounded by a single FUA to that FUA. Excluding non-contiguous municipalities. The definition identifies 1 285 FUAs and 1 402 cities in all OECD member countries except Costa Rica and three accession countries. Cite this dataset OECD Regions, cities and local areas database (Economy - FUAs), http://oe.cd/geostats Further information OECD Local Data Portal OECD Regions and Cities at a Glance For questions and/or comments, please email CitiesStat@oecd.org