Coimbra vs Malta: Economy - FUAs — Employment at place of work
Economy - FUAs — Employment at place of work over time
- Coimbra
- Malta
How they compare
Malta currently reports 289,458 Persons against 115,931 Persons in Coimbra, a difference of 173,527 Persons.
That makes Malta's figure about 2.5 times Coimbra's.
Across all 22 years both countries report, Malta has been ahead every year.
Coimbra ranks 4th and Malta ranks 2nd of 4 groups.
Malta has averaged higher in every one of the 3 decades both report.
Head to head by decade
| Decade | Coimbra | Malta | Difference | Ahead |
|---|---|---|---|---|
| 2000s | 135,675 Persons | 154,091 Persons | 18,416 Persons | Malta |
| 2010s | 116,488 Persons | 196,511 Persons | 80,022 Persons | Malta |
| 2020s | 115,488 Persons | 255,578 Persons | 140,090 Persons | Malta |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher economy - fuas — employment at place of work, Coimbra or Malta?
- Malta, at 289,458 Persons against 115,931 Persons in Coimbra as of 2023.
- What is the difference in economy - fuas — employment at place of work between Coimbra and Malta?
- 173,527 Persons, with Malta ahead.
- How many years of comparable data are there for Coimbra and Malta?
- 22 years are reported by both, from 2000 to 2021.
- How do Coimbra and Malta rank globally for economy - fuas — employment at place of work?
- Coimbra ranks 4th and Malta ranks 2nd of 4 groups.
- Where does this data come from?
- Organisation for Economic Co-operation and Development, published as Economy - FUAs — Employment at place of work. Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
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