Dependency ratio - Cities and FUAs in Gunsan
Gunsan: Dependency ratio - Cities and FUAs was 32.9 Percentage of population aged 15-64 years in 2023. β² Rising
Dependency ratio - Cities and FUAs in Gunsan, 2011β2023
Source: Organisation for Economic Co-operation and Development. Measured in Percentage of population aged 15-64 years.
Analysis
The most recent figure for dependency ratio - cities and fuas in Gunsan is 32.9 Percentage of population aged 15-64 years, measured in 2023. That is the highest value across all 13 years on record.
That represents a change of up 5.4% on the previous year and up 70.5% over ten years.
Over the whole period, dependency ratio - cities and fuas in Gunsan peaked at 32.9 Percentage of population aged 15-64 years in 2023 and was at its lowest, 17.8 Percentage of population aged 15-64 years, in 2011.
Gunsan ranks 425th of 1258 regions on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 13 years of available data.
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2010s | 21.36 Percentage of population aged 15-64 years | 17.8 Percentage of population aged 15-64 years | 25.8 Percentage of population aged 15-64 years | 9 |
| 2020s | 30.27 Percentage of population aged 15-64 years | 27.7 Percentage of population aged 15-64 years | 32.9 Percentage of population aged 15-64 years | 4 |
More reference data data for Gunsan
- Cooling and heating degree days - Cities and FUAs β Cooling degree 441.86 Degree days (2025)
- Cooling and heating degree days - Cities and FUAs β Change in cooling 194.62 Degree days (2025)
- Cooling and heating degree days - Cities and FUAs 2,040 Degree days (2025)
- Cooling and heating degree days - Cities and FUAs β Change in heating 119.82 Degree days (2025)
- Precipitation - Cities and FUAs β Extreme precipitation days 16.43 Days per year (2024)
- Precipitation - Cities and FUAs β Change in extreme precipitation -2.53 Days per year (2024)
- Wind threats - Cities and FUAs β Exposure to wind threats 0 Percentage of area (2023)
- Coastal flooding - Cities and FUAs β Built-up area exposure to 10.06 Percentage of built-up area (2022)
- Internet speed - Cities and FUAs β Downloading speed 4.1 Percentage of national value (2025)
- Internet speed - Cities and FUAs β Uploading speed 7.8 Percentage of national value (2025)
Frequently asked questions
- What is dependency ratio - cities and fuas in Gunsan?
- Dependency ratio - cities and fuas in Gunsan was 32.9 Percentage of population aged 15-64 years in 2023, according to Organisation for Economic Co-operation and Development.
- What is the highest dependency ratio - cities and fuas recorded in Gunsan?
- The highest recorded value was 32.9 Percentage of population aged 15-64 years in 2023.
- What is the lowest dependency ratio - cities and fuas recorded in Gunsan?
- The lowest recorded value was 17.8 Percentage of population aged 15-64 years in 2011.
- How does Gunsan rank for dependency ratio - cities and fuas?
- Gunsan ranks 425th out of 1258 regions with data for 2023.
- Is dependency ratio - cities and fuas rising or falling in Gunsan?
- Over the last ten years it is up 70.5%. The long-run trend across the full record is rising.
- Where does this Gunsan data come from?
- The figures come from Organisation for Economic Co-operation and Development, published as part of Dependency ratio - Cities and FUAs. Statizoid updates them automatically from the source API.
Download this data
CSV Β· JSON β 13 observations, free to reuse under OECD Terms and Conditions (attribution required).
About this data
<p align="justify">This dataset provides an indicator of dependency ratios for OECD Functional Urban Areas (FUAs) and cities.</p> <h3>Data sources and methodology</h3> <p align="justify"> Dependency ratios are derived from population by age and sex data collected at the level of small administrative units (e.g. municipalities) and aggregated at the FUA and city level. The correspondence table between SAUs and FUAs/cities is available in <a href=https://webfs-cfe.oecd.org/files/.Stat/cities_local_areas/fua_cities_sau_mapping.parquet>parquet </a> and <a href=https://webfs-cfe.oecd.org/files/.Stat/cities_local_areas/fua_cities_sau_mapping.csv>csv</a> format.<br /><br /> </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> β 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> β 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> <p>The definition identifies 1 272 FUAs and 1 269 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/1ds>Dependency ratio - Cities and FUAs</a>),Β <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>