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

For questions and/or comments, please email CitiesStat@oecd.org

[AT002F.A.GDP.USD_​PPP_​PS.FUA] Graz (AT002F) – Annual – Gross domestic product – US dollars per person, PPP converted – FUA

[AT002F.A.GDP.USD_PPP_PS.FUA] Graz (AT002F) – Annual – Gross domestic product – US dollars per person, PPP converted – FUA