Armenia vs Tokyo: Labour market - FUAs — Labour force
Labour market - FUAs — Labour force over time
- Armenia
- Tokyo
How they compare
Tokyo currently reports 19.32 million Persons against 192,656 Persons in Armenia, a difference of 19.13 million Persons.
That makes Tokyo's figure about 100.3 times Armenia's.
Across all 14 years both countries report, Tokyo has been ahead every year.
Armenia ranks 3rd and Tokyo ranks 1st of 3 countries.
Tokyo has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Armenia | Tokyo | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 180,760 Persons | 18.55 million Persons | 18.36 million Persons | Tokyo |
| 2010s | 194,181 Persons | 19.16 million Persons | 18.97 million Persons | Tokyo |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher labour market - fuas — labour force, Armenia or Tokyo?
- Tokyo, at 19.32 million Persons against 192,656 Persons in Armenia as of 2014.
- What is the difference in labour market - fuas — labour force between Armenia and Tokyo?
- 19.13 million Persons, with Tokyo ahead.
- How many years of comparable data are there for Armenia and Tokyo?
- 14 years are reported by both, from 2001 to 2014.
- How do Armenia and Tokyo rank globally for labour market - fuas — labour force?
- Armenia ranks 3rd and Tokyo ranks 1st of 3 countries.
- Where does this data come from?
- Organisation for Economic Co-operation and Development, published as Labour market - FUAs — Labour force. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
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>