[1] OECD (2024), “Health care resources”, OECD Health Statistics (database), https://doi.org/10.1787/data-00541-en (accessed on 25 March 2024).
OECD Regions and Cities at a Glance 2024
Report
OECD Regions and Cities at a Glance
Table of contents
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Annex B. Sources and data description
Copy link to Annex B. Sources and data descriptionTable B.1. List of variables
Copy link to Table B.1. List of variables|
Indicators |
Chapter(s) |
|---|---|
|
Air temperature, hot days and icing days (historical series) |
3 |
|
Air temperature, hot days and icing days by emission scenario (projected series) |
3 |
|
Broadband download speed |
4 |
|
Built-up surface |
3 |
|
Dwellings by main energy source |
3 |
|
Electricity generation by source |
3 |
|
Female employment rate |
2 |
|
Final energy consumption by sector and by source |
3 |
|
Foreign-born |
2 |
|
Forest cover |
3 |
|
Greenhouse gas emissions by sector and by gas |
3 |
|
Green tasks jobs |
2 |
|
Greenfield foreign direct investment (GFDI) |
1 |
|
Gross domestic product (GDP), GDP per capita, gross value added per worker |
1 |
|
Higher education institutions (location, enrolment, enrolment by gender, science, technology, engineering and mathematics enrolment) |
2 |
|
Homeownership |
1 |
|
Housing prices |
1 |
|
Housing costs |
1 |
|
Labour market tightness |
2 |
|
Location of childcare facilities |
4 |
|
Location of general hospitals |
4 |
|
Location of pharmacies |
4 |
|
Location of primary schools |
4 |
|
Location of public transport using General Transit Feed Specification (GTFS) data |
4 |
|
Main mode of transport for commuting |
3 |
|
Mean disposable income in functional urban areas |
4 |
|
Municipal waste and waste recovery |
3 |
|
Passenger vehicles, electric and hybrid vehicles |
3 |
|
Patent applications and climate-related patents |
1, 3 |
|
Population |
1 |
|
Remote work uptake |
2 |
|
Regional output price index (ROPI) |
1 |
|
Regional consumer price index (RCPI) |
1 |
|
S80/S20 ratios for disposable income |
4 |
|
Share of workers at high risk of automation |
2 |
|
Subnational government climate-significant expenditure and investment |
3 |
|
Trade openness |
1 |
|
Women in relative poverty compared to men in relative poverty |
4 |
Air temperature, hot days and icing days (historical series)
Copy link to Air temperature, hot days and icing days (historical series)|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Muñoz Sabater, J. (2019), ERA5-Land Hourly Data from 1950 to Present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.e2161bac. See methodology in Annex C. |
1981-2023 |
TL2, TL3, FUA |
Air temperature, hot days and icing days by emission scenario (projected series)
Copy link to Air temperature, hot days and icing days by emission scenario (projected series)|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Thrasher, B. et al. (2022), NASA Global Daily Downscaled Projections, CMIP6, Sci Data 9, 262, https://doi.org/10.1038/s41597-022-01393-4. See methodology in Annex C. |
2030-60 |
TL2, TL3, FUA |
Broadband download speed
Copy link to Broadband download speed|
Country |
Source |
Period |
Territorial level |
|---|---|---|---|
|
All countries |
Speedtest® by Ookla® Global Fixed and Mobile Network Performance Maps. Based on analysis by Ookla of Speedtest Intelligence® data. Provided by Ookla and accessed on 25 September 2024. |
2019Q1-2024Q2 |
TL3 |
Built-up surface
Copy link to Built-up surface|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Schiavina M. et al. (2023), GHS-POP R2023A - GHS Population Grid Multitemporal (1975-2030), Joint Research Centre, European Commission, http://data.europa.eu/89h/2ff68a52-5b5b-4a22-8f40-c41da8332cfe |
1975-2030 (5‑year intervals) |
TL2, TL3, FUA, municipalities and local areas |
Dwellings by main energy source
Copy link to Dwellings by main energy source|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
CHE |
2021-22 |
Municipalities and local areas |
|
|
CHL |
Encuesta de caracterización socioeconómica nacional, Ministerio de Desarollo Social y Familia |
2022 |
Municipalities and local areas |
|
CZE |
2021 |
Municipalities and local areas |
|
|
DEU |
Zensus 2022, Gebaüde und Wohnungen, DESTATIS |
2022 |
Municipalities and local areas |
|
DNK |
2010-23 |
Municipalities and local areas |
|
|
FIN |
116h -- Number of buildings by intended use and heating fuel, 2022, Statistics Finland |
2022 |
Municipalities and local areas |
|
FRA |
2019 |
Municipalities and local areas |
|
|
GBR |
Energy efficiency of Housing, England and Wales, local authority districts, ONS; Census 2021 main statistics housing and accommodation tables, Northern Ireland Statistics; Scotland Housing Census 2022 |
2022 |
Municipalities and local areas |
|
GRC |
2011 |
Municipalities and local areas |
|
|
HUN |
Summary data of dwellings by settlement, Census database, KSH |
2001, 2011, 2021 |
Municipalities and local areas |
|
IRL |
Permanent private households - local electoral areas (SAU3), Irish CSO |
2011, 2016, 2022 |
Municipalities and local areas |
|
LUX |
Luxembourg 2021 Census, STATEC |
2021 |
Municipalities and local areas |
|
NLD |
2010-21 |
Municipalities and local areas |
|
|
NZL |
2018 |
Municipalities and local areas |
|
|
PRT |
2011 |
Municipalities and local areas |
|
|
SVK |
2021 |
Municipalities and local areas |
|
|
USA |
2015-21 |
Municipalities and local areas |
Electricity generation by source
Copy link to Electricity generation by source|
Country |
Source |
Product types |
Year |
Territorial level |
|
|---|---|---|---|---|---|
|
AUS |
Coal, natural gas, oil products, biofuel and waste, wind, solar |
2015-22 |
TL2 |
||
|
CAN |
Canada's energy future 2023: Energy demand and demand projections to 2050 |
Oil, natural gas, coal and coke, uranium, wind, solar, biomass/geothermal, hydro/wave/tidal |
2005-23 |
TL2 |
|
|
DEU |
Bruttostromerzeugung nach Energieträgern, Bruttostromerzeugung nach Erneuerbaren Energieträgern, Länderarbeitskreis Energiebilanzen |
Total, coal, oil, natural gas, renewables, nuclear, other |
1990-2021 |
TL2 |
|
|
FIN |
Electricity production by region 2007-2022, Energiateollisuus |
Total, hydro, wind, nuclear, fossil |
2007-22 |
TL3, TL2 |
|
|
FRA |
Données régionales de production et de consommation finale de l'énergie |
Total, natural gas, coal, oil, nuclear, solar, wind, biofuels and waste, geothermal, other |
2014-21 |
TL2 |
|
|
GBR |
Regional Renewable Statistics/Regional Statistics 2003-2022: Generation |
Renewables, wind, solar, hydro, biomass and waste |
2003-22 |
TL2 |
|
|
JPN |
Gas, coal, oil, wind, solar, hydro, nuclear, biomass/waste |
2016-23 |
TL2 |
||
|
NOR |
08308: Production of electricity, by type of power (GWh) (C) 2006 - 2022, Statistics Norway |
Total, hydro, thermal, wind, pump storage |
2006-22 |
TL2 |
|
|
POL |
Total, fossil, hydro, renewables |
2000-20 |
TL2 |
||
|
PRT |
Total, wind, solar, hydro, thermal, geothermal |
2011-21 |
TL2 |
||
|
SWE |
Total, hydro, wind, nuclear, fossil |
2009-21 |
TL3, TL2 |
||
|
USA |
Total, coal, oil, natural gas, biomass, wind, solar, hydro |
2001-22 |
TL2 |
||
Female employment rate
Copy link to Female employment rate|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries |
Eurostat, Regional employment rates by sex (lfst_r_lfe2emprt) |
2023 |
TL2 |
|
AUS |
ABS 6291.0.55.001 Labour Force, Australia, Detailed |
2023 |
TL2 |
|
CAN |
Statistics Canada. Table 14-10-0327-01 Labour force characteristics by sex |
2023 |
TL2 |
|
CHE |
OFS - Swiss Labour Force Survey in 2nd quarter 2022 - Table je-f-03.02.00.02.02.01 |
2023 |
TL2 |
|
COL |
DANE, Gran encuesta integrada de hogares |
2023 |
TL2 |
|
CRI |
INEC-Costa Rica, Encuesta Continua de Empleo |
2023 |
TL2 |
|
ISL |
Statistics Iceland |
2023 |
TL2 |
|
ISR |
CBS |
2023 |
TL2 |
|
JPN |
Labour Force Survey/Basic Tabulation Historical data |
2023 |
TL2 |
|
KOR |
Statistics Korea, Economically Active Population Survey |
2023 |
TL2 |
|
MEX |
INEGI, Encuesta Nacional de Ocupación y Empleo |
2023 |
TL2 |
|
NZL |
Household Labour Force Survey - HLF - Table: Labour Force Status |
2023 |
TL2 |
|
NOR |
Statistics Norway, Table 13497: Population, by labour force status, age and region |
2023 |
TL2 |
|
TUR |
Turkish Statistical Institute (TurkStat) Household Labour Force Survey |
2023 |
TL2 |
Final energy consumption by sector and by source
Copy link to Final energy consumption by sector and by source|
Country |
Source |
Sectors |
Fuel types |
Year |
Territorial level |
|---|---|---|---|---|---|
|
AUS |
Total; agriculture, forestry and fishing; mining; manufacturing; electricity, gas, water and waste services; construction; transport, postal and warehousing; residential; solvents, lubricants, greases and bitumen |
Total, coal, oil, natural gas, renewables |
1973-2021 |
TL2 |
|
|
AUT |
STATcube: Energy balances for the federal provinces as of 1988 |
Total, industry, transport, residential, agriculture, commercial and public services |
Total, coal, oil, gas, renewables, wastes |
1988-2022 |
TL2, TL3 |
|
BEL |
Industry, residential, services, transport, agriculture |
Electricity, gas, oil, wastes, coal, heat, other |
1990-2021 |
TL2 |
|
|
CAN |
Total, industry, residential, commercial, transport |
Total, electricity, gas, oil, biofuels and emerging energy, other |
2005-23 |
TL2 |
|
|
DEU |
Endenergieverbrauch nach Energieträgern, Endenergieverbrauch nach Verbrauchergruppen, Länderarbeitskreis Energiebilanzen, (43531-01-02-4: Energieverbrauch - Jahressumme - regionale Tiefe: Kreise und krfr. Städte, 43531-01-02-4-B: Energieverbrauch - Jahressumme - regionale Ebenen, Regional Datenbank) |
Total |
Total, coal, oil, natural gas, renewables, electricity, heat, others |
2003-21 |
TL2, TL3 |
|
FIN |
Housing and agriculture, industry, services and construction, total |
Electricity |
2007-21 |
TL2, TL3 |
|
|
FRA |
Agriculture, residential, services, industry, other |
Electricity, gas, heat, petroleum products |
2018-22 |
TL2, TL3 |
|
|
KOR |
Total |
Total |
1996, 2000, 2010-21 |
TL2, TL3 |
|
|
NLD |
Built environment, traffic and transport, industry, energy, waste, water, agriculture, forestry and fishing |
Total, electricity, natural gas, district heating, solar |
2010-21 |
TL2, TL3 |
|
|
POL |
Consumption of fuels and energy carriers 2022, 2021, 2020, 2019, Statistics Poland |
Total, industry, energy, residential, transport, agriculture, other |
Hard coal, natural gas, LPG, light fuel oil, heavy fuel oil, heat, electricity |
2001-22 |
TL2 |
|
PRT |
Consumption of electric energy (kWh) by Geographic localization (NUTS - 2013) and Type of consumption; Annual, Consumption of natural gas (Nm³) by Geographic localization (NUTS - 2013); Annual, Consumption of motor fuel by inhabitant (toe/ inhab.) by Place of residence (NUTS - 2013); Annual |
For electricity only: residential, non-residential, industry, agriculture, lightning of public roads, inner lightning of state/public buildings, others |
Electricity, natural gas, motor fuel |
2011-21 |
TL2, TL3 |
|
SVK |
Consumption of fuels, electricity, heat, Slovakia Statistics |
Total |
Electricity, heat, natural gas, fuel oil, coal, diesel oil |
2000-22 |
TL2, TL3 |
|
SWE |
Agriculture, industry, public sector, services, transport, residential, other |
Electricity, district heating, natural gas (non-renewable and renewable), fixed (non-renewable and renewable), liquid (non-renewable and renewable) |
2009-21 |
TL2, TL3 |
|
|
USA |
Consumption, all consumption estimates in Btu, State Energy Data System (SEDS): 1960-2021 (complete), EIA US States, EIA, US Department of Energy |
Total, coal, oil, natural gas |
2021 |
TL2 |
Foreign-born
Copy link to Foreign-born|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
OECD Migrant Municipal Database. Astruc-Le Souder, M., et al. (2024), « The OECD Municipal Migration Database : Going granular », OECD Regional Development Papers, n° 96, Éditions OCDE, Paris, https://doi.org/10.1787/a79b007d-en. OECD (2022), The Contribution of Migration to Regional Development, OECD Regional Development Studies, OECD Publishing, Paris, https://doi.org/10.1787/57046df4-en. |
2012-22 |
TL2 and TL3 |
Forest cover
Copy link to Forest cover|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Hansen, M.C. et al. (2013), “High-resolution global maps of 21st-century forest cover change”, Science, Vol. 342, p.p. 850-53, https://doi.org/10.1126/science.1244693. Data available at: https://glad.earthengine.app/view/global-forest-change. |
2000-22 |
TL2, TL3, FUA, municipalities and local areas |
Greenhouse gas emissions by sector and by gas
Copy link to Greenhouse gas emissions by sector and by gas|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Emissions Database for Global Atmospheric Research (EDGAR) Community GHG Database, a collaboration between the European Commission Joint Research Centre (JRC), the International Energy Agency (IEA) and comprising IEA-EDGAR CO2, EDGAR CH4, EDGAR N2O, EDGAR F-GASES version 8.0, (2023) European Commission, JRC (Datasets). See methodology in Annex C. |
1970-2022 |
TL2, TL3, FUA |
Green-task jobs
Copy link to Green-task jobs|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries,1 CHE, ISL, NOR |
Eurostat |
2022 |
TL2, DEGURBA |
|
AUS |
Australian Bureau of Statistics (ABS) |
2022 |
TL2 |
|
CAN |
Labour Force Survey |
2022 |
TL2 |
|
GBR |
UK Labour Force Survey |
2022 |
TL2, DEGURBA |
|
NZL |
Household Labour Force Survey (HLFS) |
2022 |
TL2 |
|
USA |
Bureau of Labour Statistics |
2022 |
TL2 |
1. EU countries 21022, except POL and SVN (2021).
Greenfield foreign direct investment
Copy link to Greenfield foreign direct investment|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
OECD countries |
fDi Markets (2022), Homepage, Financial Times Limited, www.fdimarkets.com. Accessed in July 2024. |
2023 |
TL2 |
Note: The fDi Markets database primarily gathers information from publicly available media and business sources.
Gross domestic product (GDP), GDP per capita, gross value added per worker
Copy link to Gross domestic product (GDP), GDP per capita, gross value added per worker|
Country |
Source |
Territorial level (GDP last available year) |
|---|---|---|
|
EU countries1 |
Eurostat, Regional economic accounts |
TL2 (2022), TL3 2(021) |
|
AUS |
Australian Bureau of Statistics, 5220.0. Gross state product, figures based on fiscal year (July-June) |
TL2 (2022) |
|
CAN |
Statistics Canada, Provincial economic accounts |
TL2 (2022) |
|
CHE |
Swiss Federal Statistical Office, Statweb |
TL2 and TL3 (2021) |
|
CHL |
Banco Central de Chile, Cuentas nacionales de Chile |
TL2 (2022) |
|
COL |
DANE, Directorate of Synthesis and National Accounts |
TL2 (2022) |
|
CRI2 |
Not available |
- |
|
ISL2 |
Not available |
- |
|
ISR2 |
Not available |
- |
|
JPN |
Economic and Social Research Institute, Cabinet Office, data are based on fiscal year (April-March) |
TL2 and TL3 (2020) |
|
KOR |
Korean National Statistical Office |
TL2 and TL3 (2022) |
|
MEX |
INEGI, System of national accounts of Mexico |
TL2 (2022) |
|
NZL |
Statistics New Zealand |
TL2 and TL3 (2022) |
|
NOR |
Norwegian Regional Accounts |
TL2 and TL3 (2021) |
|
TUR |
Turkish Statistical Institute (TurkStat) |
TL2 and TL3 (2022) |
|
USA |
Bureau of Economic Analysis |
TL2 and TL3 (2022) |
1. EU countries: TL3 last available year 2022 for CZE, DNK, EST, NLD, PRT, SWE and SVK.
2. CRI, ISL and ISR: data not available at the regional level.
Higher education institutions (location, enrolment, enrolment by gender, science, technology, engineering and mathematics enrolment)
Copy link to Higher education institutions (location, enrolment, enrolment by gender, science, technology, engineering and mathematics enrolment)|
Country |
Source |
Year |
|---|---|---|
|
EU countries |
2011-21 |
|
|
AUS |
Department of Education, Skills and Employment (DESE) |
2019 |
|
CAN |
https://www.cicic.ca/869/results.canada?search=&t=1,2,3,4&ud=20,9,4,8,3,2 |
2019 |
|
CHL |
https://www.mifuturo.cl/bases-de-datos-de-matriculados/, https://www.mifuturo.cl/instituciones-de-educacion-superior-en-chile/ |
2021 |
|
COL |
https://snies.mineducacion.gov.co/portal/ESTADISTICAS/Bases-consolidadas/ |
2020 |
|
KOR |
https://kess.kedi.re.kr/eng/post/6681132?itemCode=03&menuId=m_03_03_03 |
2020 |
|
MEX |
2020 |
|
|
NZL |
https://www.educationcounts.govt.nz/directories/list-of-tertiary-providers |
2021 |
|
USA |
2020 |
Homeownership
Copy link to Homeownership|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
AUS |
Luxembourg Income Study (LIS) |
2018 |
TL2 |
|
AUT |
2020 |
TL2 |
|
|
CAN |
2019 |
TL2 |
|
|
CHE |
2019 |
TL2 |
|
|
COL |
2020 |
TL2 |
|
|
DEU |
2019 |
TL2 |
|
|
ESP |
2018 |
TL2 |
|
|
EST |
2016 |
TL3 |
|
|
GBR |
2021 |
TL2 |
|
|
IRL |
2019 |
TL2 |
|
|
ISR |
2021 |
TL2 |
|
|
ITA |
2020 |
TL2 |
|
|
LTU |
2020 |
TL3 |
|
|
MEX |
2022 |
TL2 |
|
|
POL |
2020 |
TL2 |
|
|
SVK |
2018 |
TL2 |
|
|
SWE |
2021 |
TL2 |
Housing prices
Copy link to Housing prices|
Country |
Source |
First year |
Last year |
Territorial level |
House price definition |
|---|---|---|---|---|---|
|
AUS |
Australian Bureau of Statistics (ABS) |
2018 |
2023 |
Municipalities and local areas |
Median price |
|
AUT |
Statistik Austria |
2015 |
2021 |
Median price per square metre (m2) |
|
|
BEL |
Statistics Belgium (Statbel) |
2013 |
2022 |
Mean price per m2 |
|
|
DEU |
vdpResearch |
2018 |
2021 |
Mean price per m2 |
|
|
DNK |
Statistics Denmark |
2018 |
2023 |
Mean price per m2 |
|
|
ESP |
INE |
2013 |
2022 |
Mean price per m2 |
|
|
FIN |
Statistics Finland |
2013 |
2023 |
Mean price per m2 |
|
|
FRA |
Demande de valeurs foncières (DVF) |
2014 |
2023 |
Median price per m2 |
|
|
GBR |
UK Government Price Paid Data |
2018 |
2023 |
Mean price adjusted by dwelling characteristics |
|
|
HUN |
Hungarian Central Statistics Office |
2013 |
2023 |
Mean price per m2 |
|
|
IRL |
Irish Central Statistics Office (CSO) |
2019 |
2021 |
Median price |
|
|
KOR |
Ministry of Land, Infrastructure and Transport (MOLIT) |
2018 |
2023 |
Mean price per m2 |
|
|
MEX |
Sociedad Hipotecária Federal (SHF) |
2016 |
2021 |
Mean price per m2 |
|
|
NLD |
Statistics Netherlands (CBS) |
2013 |
2023 |
Mean price |
|
|
POL |
Statistics Poland |
2013 |
2022 |
Mean price per m2 |
|
|
PRT |
Statistics Portugal (INE) |
2019 |
2022 |
Median price per m2 |
|
|
SWE |
Svensk Mäklarstatistik |
2015 |
2023 |
Mean price per m2 |
|
|
USA |
Zillow Research Institute |
2013 |
2023 |
Mean price |
Housing costs
Copy link to Housing costs|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
AUS |
Luxembourg Income Study (LIS) |
2018 |
TL2 |
|
AUT |
2020 |
TL2 |
|
|
CAN |
2019 |
TL2 |
|
|
CHE |
2019 |
TL2 |
|
|
COL |
2020 |
TL2 |
|
|
ESP |
2018 |
TL2 |
|
|
EST |
2016 |
TL3 |
|
|
GBR |
2021 |
TL2 |
|
|
IRL |
2019 |
TL2 |
|
|
ISR |
2021 |
TL2 |
|
|
ITA |
2016 |
TL2 |
|
|
LTU |
2020 |
TL3 |
|
|
MEX |
2022 |
TL2 |
|
|
SVK |
2018 |
TL2 |
|
|
SWE |
2021 |
TL2 |
|
|
USA |
American Community Survey (ACS) |
2021 |
TL2 |
Labour market tightness
Copy link to Labour market tightness|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Job vacancy data come from online job postings collected by Lightcast. Employment data are taken from labour force surveys and national statistics. |
2022 |
TL2 |
Location of childcare facilities
Copy link to Location of childcare facilities|
Country |
Source |
Link |
Year |
|---|---|---|---|
|
AUS |
For Flanders: Opgroeien (Grandir) for nurseries and Onderwijs for kindergartens; For Wallonia and Brussels: ONE (Office de la naissance et de l'enfance) for nurseries and Enseignement.be, Annuaire des écoles d’enseignement fondamental ordinaire, for kindergartens |
For Flanders: https://data-onderwijs.vlaanderen.be/onderwijsaanbod/bao/lijst?hs=111+121 For Wallonia and Brussels: http://www.enseignement.be/index.php?page=25932 |
Flanders: 2024 Wallonia: 2023 |
|
AUT |
Ministerio de Educacion y Formacion Profesional |
2023 |
|
|
ESP |
Ministerio de Educacion y Formacion Profesional |
2023 |
|
|
EST |
Haridus - ja teadusministeerium |
2023 |
|
|
FIN |
Oeptus – Ja Kulttuuriministeriö (OKM) |
Data sent via email |
2023 |
|
FRA |
Annuaire de l’éducation |
https://data.education.gouv.fr/explore/dataset/fr-en-annuaire-education/table |
2024 |
|
GRC |
Υπουργείο Πολιτισμού, Παιδείας και Θρησκευμάτων |
2015 |
|
|
IRL |
The Department of Children, Equality, Disability, Integration and Youth (DCEDIY) |
Data sent via email |
2023 |
|
ITA |
Ministerio dell'Istruzione e del Merito |
2022 |
|
|
NLD |
Ministrie van Onderwijs, Cultuur en Wetenschap |
https://data.overheid.nl/dataset/gegevens-kinderopvanglocaties-lrk#panel-description |
2022 |
|
NOR |
Utdanningsdirektoratet |
https://barnehagefakta.no/sok ; https://www.udir.no/om-udir/data/barnehagefakta-baf/ |
2023 |
|
NZL |
Ministry of Education |
https://www.educationcounts.govt.nz/directories/early-childhood-services |
2022 |
|
USA |
Homeland Infrastructure Foundation-Level Data (HIFLD) database |
https://hifld-geoplatform.hub.arcgis.com/datasets/geoplatform::child-care-centers/about |
2023 |
Location of general hospitals
Copy link to Location of general hospitals|
Country |
Source |
Link |
Year |
|---|---|---|---|
|
EU countries |
Eurostat GISCO, Healthcare services in Europe |
2023 (reference year is different for each country) |
|
|
AUS |
Australian Institute of Health and Welfare |
https://www.aihw.gov.au/reports-data/myhospitals/themes/hospital-access |
2024 |
|
AUT |
Statistics Canada, The Open Database of Healthcare Facilities |
2020 |
|
|
JPN |
National Land Numerical Information, Ministry of Land, Infrastructure, Transport and Tourism |
https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-P04-v3_0.html |
2020 |
|
NZL |
New Zealand Ministry of Health |
Public: https://www.health.govt.nz/your-health/certified-providers/public-hospital Private: https://www.health.govt.nz/your-health/certified-providers/ngo-hospital |
2024 |
|
USA |
HIFLD Open Data |
https://hifld-geoplatform.hub.arcgis.com/search?collection=Dataset&q=hospital |
2023 |
Note: Additional filtering was done for each of the source dataset, to select general hospitals as defined in the OECD healthcare resources dataset (OECD, 2024[1]) and ensure international comparability.
Location of pharmacies
Copy link to Location of pharmacies|
Country |
Source |
Link |
Year |
|---|---|---|---|
|
EU countries |
HIFLD Open Data |
https://hifld-geoplatform.hub.arcgis.com/datasets/geoplatform::pharmacies-/about |
2021 |
|
USA |
ESPON Database |
2023 |
Location of primary schools
Copy link to Location of primary schools|
Country |
Source |
Link |
Year |
|---|---|---|---|
|
AUS |
Australian Curriculum, Assessment and Reporting Authority |
2023 |
|
|
AUT |
OPEN DATA Wallonia-Brussels, Vlaams ministerie van onderwijs en vorming |
https://www.odwb.be/explore/dataset/243300/ ; https://data-onderwijs.vlaanderen.be/onderwijsaanbod/bao/lijst?hs=211 and https://data-onderwijs.vlaanderen.be/onderwijsaanbod/so/structuur/1stegraad |
2023 |
|
CZE |
Ministerstvo školství, mládeže a tělovýchovy |
2023 |
|
|
ESP |
Ministerio de Educacion y Formacion Profesional |
2023 |
|
|
EST |
Haridus - ja teadusministeerium |
2023 |
|
|
FIN |
Tilastokeskuksen |
https://www.paikkatietohakemisto.fi/geonetwork/srv/eng/catalog.search#/metadata/6a8b4061-7a48-4667-bbdb-13952726c79f https://tilastokeskus.fi/tup/oppilaitosrekisteri/index_en.html |
2023 |
|
FRA |
Ministère de l'Éducation nationale et de la Jeunesse |
https://data.education.gouv.fr/explore/dataset/fr-en-annuaire-education |
2024 |
|
GRC |
Υπουργείο Πολιτισμού, Παιδείας και Θρησκευμάτων |
||
|
IRL |
SchoolDays.ie |
http://www.schooldays.ie/articles/primary-Schools-in-Ireland-by-County |
2023 |
|
ITA |
Ministerio dell'Istruzione e del Merito |
||
|
JPN |
National Land Information Division, Ministry of Land, Infrastructure, Transport and Tourism of Japan |
https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-P29-v2_0.html |
2021 |
|
KOR |
National Geographic Information Institute (NGII) |
Data sent via email |
2023 |
|
LTU |
Geoportal Lithuania |
https://www.geoportal.lt/geoportal/en/web/en/search#queryText=educational%20establishments |
2022 |
|
LVA |
Latvia Ministry of Education and Science |
Data sent via email |
2023 |
|
MEX |
Sistema de Información y Gestión Educativa (SIGED) |
2024 |
|
|
NLD |
Statistics Netherlands (CBS) |
Data sent via email |
2022 |
|
NOR |
Utdanningsdirektoratet |
||
|
NZL |
New Zealand Ministry of Education |
https://www.educationcounts.govt.nz/directories/list-of-nz-schools# |
2024 |
|
PRT |
Instituto Nacional de Estatística |
Data sent via email |
|
|
SWE |
National Agency for Education |
https://www.skolverket.se/om-oss/oppna-data/api-for-skolenhetsregistret |
2022 |
|
USA |
National Center for Education Statistics (NCES) |
Public schools: https://data-nces.opendata.arcgis.com/datasets/nces::public-school-characteristics-current/about Private schools: https://nces.ed.gov/surveys/pss/pssdata.asp |
2023 |
Location of public transport using General Transit Feed Specification (GTFS) data
Copy link to Location of public transport using General Transit Feed Specification (GTFS) dataMain mode of transport for commuting
Copy link to Main mode of transport for commuting|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
Eurostat |
Eurostat |
Transport - functional urban areas, Eurostat |
|
|
AUS |
Data by region 2011-2022, by ASGS main structure (ASGS Ed. 3, 2021) |
2011-22 |
Municipalities and local areas, FUAs |
|
CAN |
2021 |
Municipalities and local areas, FUAs |
|
|
CHL |
Encuesta de caracterización socioeconómica nacional, Ministerio de Desarollo Social y Familia |
2022 |
Municipalities and local areas, FUAs |
|
FRA |
2020 |
Municipalities and local areas, FUAs |
|
|
GBR |
2021 |
Municipalities and local areas, FUAs |
|
|
JPN |
System of Social and Demographic Statistics H Dwelling, Statistics of Japan |
2020 |
Municipalities and local areas, FUAs |
|
KOR |
2020 |
Municipalities and local areas, FUAs |
|
|
MEX |
Encuesta Intercensal 2015, INEGI |
2015 |
Municipalities and local areas, FUAs |
|
NZL |
2018 |
Municipalities and local areas, FUAs |
|
|
USA |
2010-22 |
Municipalities and local areas, FUAs |
Mean disposable income in functional urban areas
Copy link to Mean disposable income in functional urban areas|
Country |
Source |
Year |
Territorial level |
Income definition |
|---|---|---|---|---|
|
AUT |
Statistics Austria |
2018 |
Municipalities and local areas |
Individual gross income plus transfers |
|
BEL |
Statbel |
2019 |
Household gross income |
|
|
CAN |
Statistics Canada |
2021 |
Disposable income |
|
|
CHE |
Federal Tax Administration |
2018 |
Household gross income |
|
|
DEU |
ifo Schnelldienst |
2018 |
Total income |
|
|
DNK |
Statistics Denmark |
2020 |
Household disposable income |
|
|
ESP |
Spanish Statistical Office |
2019 |
Household disposable income |
|
|
FIN |
Statistics Finland |
2020 |
Household disposable income |
|
|
FRA |
Institut national de la statistique et des études économiques |
2020 |
Disposable income |
|
|
GBR |
Office for National Statistics |
2018 |
Disposable income |
|
|
LUX |
Ministry for Social Security |
2020 |
Household disposable income |
|
|
NOR |
Statistics Norway |
2019 |
Household disposable income |
|
|
PRT |
Statistics Portugal |
2019 |
Household disposable income |
|
|
SWE |
Statistics Sweden |
2019 |
Household disposable income |
|
|
USA |
American Community Survey |
2021 |
Total income |
Note: The mean disposable income in the city and commuting zone are computed as the average of the median disposable income in the small area units (SAU3) within those areas (mean incomes for DEU and GBR).
Municipal waste and waste recovery
Copy link to Municipal waste and waste recovery|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
AUS |
National Waste report |
2018 |
TL2 |
|
AUT |
Environment Agency Austria (UBA) - Austrian Federal Waste Management Plan and related Status Reports |
2019 |
TL2 |
|
CHL |
INE, Chile. Pollutant Release and Transfer Register (PRTR) - Registro de Emisiones y Transferencias de Contaminantes (RETC) |
2017 |
TL2 |
|
CZE |
Czech Statistical Office CZSO, Annual statistical survey |
2013 |
TL2 |
|
DEU |
Waste Statistics of the Federal Statistical Office and the Statistical Offices of the Federal States, Spatial Monitoring System of the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR |
2021 |
TL2 |
|
ESP |
National Institute of Statistics/Instituto Nacional de Estadística (INE) |
2021 |
TL2 |
|
EST |
Eurostat, Municipal waste (env_rwas_gen) |
2021 |
TL2 |
|
FRA |
Odd-numbered years: enquêtes collecte de l’Ademe ; Even-numbered years: estimations SDES |
2019 |
TL2 |
|
GBR |
Department for Environment, Food and Rural Affairs, Local Authority Collected Waste Statistics |
2021 |
TL2 |
|
HUN |
HCSO, Hungarian Central Statistical Office |
2021 |
TL2 |
|
ISR |
Central Bureau of Statistics Israel |
2021 |
TL2 |
|
ITA |
Italian Institute for Environmental Protection and Research (ISPRA) |
2020 |
TL2 |
|
JPN |
Ministry of Internal Affairs and Communications |
2021 |
TL2 |
|
KOR |
Korean Ministry of Environment |
2021 |
TL2 |
|
LVA |
Official statistics 2-Waste by Latvian Environment, Geology and Meteorology Agency |
2020 |
TL2 |
|
LUX |
Eurostat, Municipal waste (env_rwas_gen) |
2013 |
TL2 |
|
MEX |
INEGI. Censo Nacional de Gobiernos Municipales y Delegacionales 2017 |
2020 |
TL2 |
|
NLD |
Statistics Netherlands |
2021 |
TL2 |
|
NOR |
Statistics Norway |
2020 |
TL2 |
|
POL |
Central Statistical Office |
2021 |
TL2 |
|
PRT |
Statistics Portugal, Urban waste statistics |
2020 |
TL2 |
|
SVK |
Statistical Office of the Slovak Republic, statistical survey |
2021 |
TL2 |
|
SVN |
Statistical Office of the Republic of Slovenia (SURS), Generated amounts |
2021 |
TL2 |
|
TUR |
Municipal Waste Statistics Survey |
2020 (2016 recovery) |
TL2 |
Passenger vehicles, electric and hybrid vehicles
Copy link to Passenger vehicles, electric and hybrid vehicles|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
AUS |
Australian Bureau of Statistics (ABS), Motor Vehicle Census (cat. no. 9309.0) |
2021 |
TL2 |
|
AUT |
Statistics Austria, Transport statistics |
2021 |
TL2 |
|
BEL |
Statbel and IWEPS computation: https://statbel.fgov.be/fr/themes/mobilite/circulation/parc-de-vehicules |
2021 |
TL2 |
|
CAN |
Statistics Canada. CANSIM database: Table 23-10-0067-01 Vehicle registrations, by type of vehicle; Electric vehicles OECD estimates based on Table 20-10-0025-01 Zero-emission vehicle registrations, quarterly |
2019 |
TL2 |
|
CHE |
Federal Statistical Office, Federal Roads Office: Stock of road vehicles (MFZ) |
2022 |
TL2 |
|
CHL |
INE |
2021 |
TL2 |
|
CZE |
Czech Statistical Office CZSO, Ministry of Transport of the Czechia. www.mdcr.cz |
2021 |
TL2 |
|
DEU |
Motorist’s Federal Office (Kraftfahrt-Bundesamt), Spatial Monitoring System of the BBSR, Private cars |
2021 |
TL2 |
|
DNK |
Statistics Denmark, StatBank Table BIL707: Stock of vehicles per 1 January by region, passenger cars (for private use, taxis and rental) |
2022 |
TL2 |
|
ESP |
Govierno de España, Ministerio del Interior, Direción General de Tráfico. Parque de vehículos por provincias y tipos, https://www.dgt.es/menusecundario/dgt-en-cifras/dgt-en-cifras-resultados/?categorias=/Tema/Vehiculos/ |
2022 |
TL2 |
|
EST |
Statistics Estonia |
2022 |
TL2 |
|
FIN |
Statistics Finland, Transport and tourism statistics |
2022 |
TL2 |
|
FRA |
MEDDTL (CGDD/SOeS) Fichier central des automobiles, https://www.statistiques.developpement-durable.gouv.fr/ |
2022 |
TL2 |
|
GBR |
Office for National Statistics, United Kingdom Ministerial Department for Transport statistics |
2021 |
TL2 |
|
GRC |
Hellenic Statistical Authority |
2020 |
TL2 |
|
HUN |
Hungarian Central Statistical Office. Until 2017: Central Office for Administrative and Electronic Public Services, from 2017 Ministry of Interior - stock of road vehicles |
2022 |
TL2 |
|
IRL |
CSO Department of Transport, Tourism and Sport. Irish Bulletin of vehicle and driver statistics, Table 5a. Number of Private Cars by CO2 Emission Band in each Licensing Authority Area, http://www.dttas.ie |
2021 |
TL2 |
|
ISR |
Central Bureau of Statistics Israel |
2022 |
TL2 |
|
ITA |
Automobile club d’Italia |
2020 |
TL2 |
|
KOR |
Ministry of Land, Infrastructure and Transport |
2021 |
TL2 |
|
LVA |
CSB Directorate of Road Traffic Safety |
2021 |
TL2 |
|
LTU |
State Enterprise Registrar, Register of Road Motor Vehicles of the Republic of Lithuania |
2021 |
TL2 |
|
MEX |
INEGI. Statistics of Motor Vehicles Registered in Circulation; Administrative record of the light vehicle automotive industry |
2021 |
TL2 |
|
NLD |
CBS, datasets 70072ned and 71405ned |
2022 |
TL2 |
|
NOR |
Statistics Norway: Tables 07849 and 11823 |
2020 |
TL2 |
|
POL |
Ministry of Interior of Poland, Central Register of Vehicles |
2021 |
TL2 |
|
SVK |
Ministry of Interior of the Slovac Republic |
2022 |
TL2 |
|
SVN |
Statistical Office of the Republic of Slovenia (SURS), the Central Register of Vehicles and Traffic Documents (MRVL) by the Ministry of Infrastructure (MZI) |
2021 |
TL2 |
|
SWE |
Statistics Sweden, Registered vehicles, table START__TK__TK1001__TK1001A |
2022 |
TL2 |
|
TUR |
Türkiye Statistical Institute (TurkStat) |
2022 |
TL2 |
|
USA |
Federal Highway Administration, State Motor Vehicle Registrations, Private and commercial automobiles (including taxis cabs), http://www.fhwa.dot.gov/policyinformation/statistics.cfm |
2021 |
TL2 |
Patent applications and climate-related patents
Copy link to Patent applications and climate-related patentsPatent data refer to patent applications at the internationalisation phase filled under the Patent Cooperation Treaty (PCT) at the World Intellectual Property Organization. Patent counts are based on the inventor’s region of residence. Patent rates at the subnational level may be influenced by “headquarters effects” when patents are registered under a company’s headquarters address rather than the site of the actual inventive activity. This bias may inflate patent rates in areas with a high concentration of headquarters, which are often large cities or capital-city regions.
Climate-related patents include climate adaptation and mitigation technologies, based on OECD (2023), Patents - Technology Development, OECD, Paris, (link to metadata, pdf).
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
OECD countries |
Authors elaboration based on OECD, STI Micro-data Lab: Intellectual Property Database, http://oe.cd/ipstats |
2023 |
FUA, TL3 typology |
Population
Copy link to Population|
Country |
Source |
Territorial level (last available year) |
|---|---|---|
|
EU countries, CHE, NOR and TUR |
Eurostat, Regional demographic statistics (reg_dem), population at 1st of January |
2 and 3 (2023) |
|
AUS |
Australian Bureau of Statistics (ABS), Australian Demographic Statistics (cat. no. 3101.0) |
2 and 3 (2023) |
|
AUT |
Statistics Canada. Cansim TL2: Table 051-0001 - Estimates of population, by age group and sex for July 1, Canada, provinces and territories |
2 and 3 (2023) |
|
CHL |
INE, Chile. Population projection and estimates by sex and age. Break in series before 2002 (as from 2002, 2002-2035 projection data) |
2 and 3 (2023) |
|
COL |
DANE - Departamento Administrativo Nacional de Estadistica. Estimation of population 1985-2005 and projection of population 2005-2023 by department. June 30. 2018: Census data. |
2 and 3 (2023) |
|
CRI |
Costa Rica Población total estimada al 30 de junio por grupos de edades, según provincia y sexo. Population projections from 2000-2025. National Institute of Statistics and Census. |
2 and 3 (2023) |
|
ISL |
Statistics Iceland. Population at 1st of January by municipality |
2 and 3 (2023) |
|
ISR |
Central Bureau of Statistics Israel. |
2 and 3 (2023) |
|
JPN |
Statistics Bureau, Current Population Estimates as of October 1st. |
2 and 3 (2023) |
|
KOR |
Statistics Korea, KOSIS database. Yearly average projected population by age |
2 and 3 (2023) |
|
MEX |
INEGI, mid-year estimates, Population and Housing Census 2020 ; OECD estimates for intercensus years. |
2 and 3 (2023) |
|
NZL |
Statistics New Zealand, Population Statistics, Estimated resident population at 30 June.. NZ.DOTSTAT (Tablecode 7501) |
2 and 3 (2023) |
|
USA |
United States Census Bureau - State and County Population Estimates |
2 and 3 (2023) |
Regional output price index (ROPI)
Copy link to Regional output price index (ROPI)|
Country |
Note |
TL2 |
TL3 |
Data source |
|---|---|---|---|---|
|
AUS |
1 |
2000-22 |
ABS - 5220.0 Australian National Accounts: State Accounts. Table 1. Gross State Product |
|
|
AUT |
3 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
BEL |
2,3 |
2003-22 |
Eurostat - table nama_10r_2gvagr |
|
|
CAN |
1 |
2000-22 |
Statistic Canada - Statistics Canada. Table 36-10-0222-01 - Gross domestic product |
|
|
CHE |
4 |
Not available |
||
|
CHL |
3 |
2013-22 |
Banco Central de Chile - Gasto del PIB volumen a precios del año anterior encadenado y a precios corrientes, Link to method (bcentral.cl) |
|
|
COL |
1,3 |
2005-22 |
DANE - PIB por departamento. Link to method (dane.gov.co - pdf) |
|
|
CZE |
2000-22 |
2000-22 |
Czech Statistical Office CZSO - GDP, volume indices. Table REG_HDP_SC_V, |
|
|
DEU |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
DNK |
2,3 |
2000-22 |
2000-22 |
Statistics Denmark - NRHP: 1-2.1.1 Production, GDP and generation of income by region, |
|
ESP |
3 |
2000-22 |
Spanish Regional Accounts (SRA) 2000-22 Series. National Statistics Institute |
|
|
EST |
1 |
2000-22 |
2000-22 |
Statistics Estonia. Table RAA0053 chain-linking and Table RAA0052 current prices |
|
FIN |
1 |
2000-22 |
2000-21 |
Statistics Finland - 12bc Gross domestic product Link to data source (stat.fi) |
|
FRA |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
GBR |
3 |
2000-22 |
2000-22 |
Office for National Statistics, ONS, Link to GDP data source (ons.gov.uk); Link to GVA data source (ons.gov.uk) |
|
GRC |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
HUN |
2,3 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
IRL |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
ITA |
1,3 |
2000-22 |
ISTAT Gross domestic product supply side |
|
|
JPN |
1 |
2006-20 |
Statistics Bureau - Gross prefectural domestic product |
|
|
KOR |
1,3 |
2000-22 |
2000-22 |
Statistics Korea, KOSIS database - Korean Regional Accounts Link to data source |
|
LVA |
2000-22 |
OECD Annual National Accounts, GDP deflator |
||
|
LTU |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
LUX |
2000-22 |
OECD Annual National Accounts, GDP deflator |
||
|
MEX |
3 |
2003-22 |
INEGI. System of National Accounts of Mexico |
|
|
NLD |
1 |
2000-22 |
2000-22 |
Statistics Netherlands, StatLine database |
|
NZL |
4 |
Not available |
||
|
NOR |
4 |
Not available |
||
|
POL |
2,3 |
2003-22 |
Eurostat - table nama_10r_2gvagr |
|
|
PRT |
3 |
2000-22 |
2000-22 |
Statistics Portugal (INE), Regional accounts |
|
SVK |
1 |
2000-22 |
2000-22 |
Statistical Office of the Slovak Republic, database DATAcube tables nu3001rr and nu3803rr |
|
SVN |
2,3 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
SWE |
3 |
2000-22 |
2000-22 |
Statistics Sweden, National Accounts |
|
TUR |
3 |
2004-22 |
2004-22 |
Türkiye Statistical Institute (TurkStat). Regional accounts |
|
USA |
1 |
2000-23 |
2001-22 |
Bureau of Economic Analysis table SAGDP1 and CAGDP1 State and county annual GDP |
|
BGR |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
BRA |
1 |
2010-20 |
Instituto Brasileiro de Geografia e Estatística, IBGE, regional accounts |
|
|
HRV |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
|
|
PER |
1 |
2007-23 |
Instituto Nacional de Estadística e Informática - Cuentas Nacionales |
|
|
ROU |
2 |
2000-22 |
Eurostat - table nama_10r_2gvagr |
1. ROPIs are estimated by dividing the current regional GDP by the GDP chain-linked volumes and rebased on the reference year 2015.
2. Eurostat table “Gross domestic product (GDP) and Gross value added (GVA) in volume by NUTS 2 regions” (nama_10r_2gvagr), from which ROPIs are derived.
3. ROPIs transmitted through the regional questionnaire by the delegates of the OECD Working Party on Territorial Indicators: AUT, CHL, DNK, ITA, KOR, MEX, POL, PRT, ESP, TUR and GBR (GDP and GVA deflators); SWE (GDP deflator); BEL, HUN and SVN (GVA deflator).
4. Regional GDP series in volume not available.
Regional consumer price index (RCPI)
Copy link to Regional consumer price index (RCPI)|
Country |
Data sources and methods |
TL (periodicity: Monthly/Quarterly/Yearly) |
|---|---|---|
|
AUS1 |
ABS, Consumer Price Index, 8 cities, 130 categories |
8 capital cities (M) |
|
CAN |
Statistics Canada, Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife – Shelter. Link to data source, Link to methods |
TL2 (M) |
|
CZE |
CZSO, Consumer price indices according to ECOICOP, 2015=100. Link to data source, Link to methods |
Prague (M) |
|
DNK2 |
Statistics Denmark, Household budget survey, table FU07 - Consumption by group of consumption, region and price unit, current and real prices. Link to data source. |
TL2 (Y) |
|
DEU |
Destatis, Table 61111-0011 - Consumer price index, and price index for rents: Länder, months. Link to data source, Link to method |
TL2 (M) |
|
ESP |
INE - Table 50913. Consumer Price Index. Base 2016 Indices by Autonomous Community: overall and by ECOICOP group. Link to data source, Link to methods |
TL3 (M) |
|
ITA |
ISTAT CPI ECOICOP classification (3 digit) - prov., indexes (100 categories) and weights (12 categories) ECOICOP classification (3 digit) - prov. (istat.it). Link to method |
TL3 (M) |
|
JPN |
e-stat.go.jp Retail price survey (trend). Link to data source, Link to methods |
TL3 (M) |
|
KOR |
KOSIS - CPI by Item(Expenditure Category:2020=100) Source: https://Kosis.kr/eng > Statistical Database > Prices > Consumer Price Survey. Link to method |
TL2 (M) |
|
NZL |
StatsNZ - Table CPI Regional Groups (Broad Regions) (Qrtly-Mar/Jun/Sep/Dec) Source: statnz > Economic indicators > Consumers Prices index – CPI. Link to methods |
Broad regions (Q) |
|
POL3 |
Statistics Poland, Table P2955 - Price indices of consumer goods and services Source: https://bdl.stat.gov.pl/bdl/dane/podgrup/temat > Prices > Prices indices. Link to methods |
TL2 (Y) |
|
PRT |
Statistics Portugal - Price indices of consumer goods and services Consumer price index (Month-on-month growth rate - Base 2012 - %) Link to data source |
TL2 (M) |
|
TUR |
Türkiye Statistical Institute (TurkStat) |
TL2(M) |
|
USA |
BEA, table SAIRPD - Implicit regional price deflators by state. Link to data source, Link to methods |
TL2 (Y) |
1. Australia: An alternative to measure inflation for consumers is the implicit deflator of Final Demand, which excludes exports (ABS Australian National Accounts: State Accounts, 5220.0).
2. Denmark: The implicit regional CPI computed from Table FU07 downloaded in September 2024 differs from the national CPI Table PRIS8, by around -2% for the reference year 2022 due to differences in methodologies and the lag between updates.
3. Poland: The index available for Mazowieckie voivodship (PL9) has been duplicated for both embedded TL2 regions: Warszawski stołeczny (PL91) and Mazowiecki regionalny (PL92).
Remote work uptake
Copy link to Remote work uptakeThe Labour Force Survey (LFS) includes a specific question on working-from-home (WFH) practices. It classifies respondents according to the frequency with which they work from home in their primary employment: (1) those who “mainly work at home”; (2) those who “sometimes work at home”; and (3) those who “never work at home.” In the survey question, within a reference period of four to twelve working weeks prior to the reference week, “mainly” denotes working from home at least half of the time, “sometimes” denotes working from home less than half of the time, and “never” indicates no instances of working from home.
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries |
OECD calculation based on the European Labour Force Survey |
2019-22 |
TL2, DEGURBA |
|
TUR |
Turkish Labour Force Survey |
2019-22 |
TL2, DEGURBA |
S80/S20 ratios for disposable income
Copy link to S80/S20 ratios for disposable income|
Country |
Source |
First year |
Last year |
Territorial level |
|---|---|---|---|---|
|
AUS |
Luxembourg Income Study (LIS) |
2010 |
2018 |
TL2 |
|
AUT |
LIS |
2010 |
2020 |
TL2 |
|
BEL |
EU statistics on income and living conditions (EU-SILC) |
2010 |
2022 |
TL2 |
|
CAN |
LIS |
2010 |
2019 |
TL2 |
|
CHE |
LIS |
2010 |
2019 |
TL2 |
|
CHL |
LIS |
2011 |
2017 |
TL2 |
|
COL |
LIS |
2010 |
2020 |
TL2 |
|
CZE |
EU-SILC |
2010 |
2022 |
TL2 |
|
DEU |
LIS |
2010 |
2019 |
TL2 |
|
ESP |
EU-SILC |
2010 |
2022 |
TL2 |
|
FIN |
EU-SILC |
2010 |
2022 |
TL2 |
|
FRA |
LIS |
2010 |
2018 |
TL2 |
|
GBR |
LIS |
2010 |
2021 |
TL2 |
|
GRC |
EU-SILC |
2010 |
2022 |
NUTS1 |
|
HUN |
EU-SILC |
2010 |
2022 |
NUTS1 |
|
IRL |
LIS |
2011 |
2019 |
TL2 |
|
ISR |
LIS |
2010 |
2021 |
TL2 |
|
LTU |
LIS |
2010 |
2020 |
TL3 |
|
MEX |
LIS |
2010 |
2022 |
TL2 |
|
POL |
EU-SILC |
2010 |
2022 |
NUTS1 |
|
SVK |
LIS |
2010 |
2018 |
TL2 |
|
SWE |
LIS |
2010 |
2021 |
TL2 |
|
USA |
LIS |
2010 |
2021 |
TL2 |
Share of workers at high risk of automation
Copy link to Share of workers at high risk of automationThe OECD methodology (https://doi.org/10.1787/646aad77-en) focuses on task-based analysis to identify workers at high risk of automation. It evaluates the automatability of tasks within occupations, linking them to the required skills. Jobs with a higher proportion of routine, manual tasks are considered more vulnerable to automation.
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries, CHE, ISL, NOR |
Eurostat |
2022 |
TL2, DEGURBA |
|
AUS |
Australian Bureau of Statistics (ABS) |
2023 |
TL2 |
|
CAN |
Labour Force Survey |
2024 |
TL2 |
|
COL |
Gran Encuesta Integrada de Hogares (GEIH) |
2023 |
TL2 |
|
CRI |
Encuesta Continua de Empleo |
2023 |
TL2 |
|
GBR |
UK Labour Force Survey |
2023 |
TL2, DEGURBA |
|
MEX |
Mexican National Survey of Occupation and Employment (ENOE) |
2023 |
TL2 |
|
USA |
Bureau of Labour Statistics |
2023 |
TL2 |
Subnational government climate-significant expenditure and investment
Copy link to Subnational government climate-significant expenditure and investment|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
OECD Subnational Government Climate Finance Database |
2019 |
Country |
Trade openness
Copy link to Trade opennessSome care is needed in interpreting measures of trade openness. The first concerns what can be referred to as “smaller country biases”, which reflect the fact that smaller countries will typically need to source more of their inputs from abroad compared to larger countries. The second reflects that the measures respect gross trade. In countries with large processing activities, the contribution of trade (in value-added terms) to growth may be much smaller than implied by gross trade data. Third, for regional measures of trade openness, there may be “port biases”, which reflect the fact that exports (imports) may be recorded as originating from those destinations even if the actual origin of the producer (or destination of the imports) is elsewhere. However, trade data typically reflect the final destination for imports and the producer for origin, rather than the location of the company’s head office or logistical hubs (such as airports, ports and warehouses); exceptions are detailed in the table below.
|
Country |
Note |
Source |
Territorial level |
|---|---|---|---|
|
AUS |
Australian Bureau of Statistics, 5368.0 - International Trade in Goods and Services. Table 15a. Merchandise exports, State and Australia, FOB Value and Table 15b. Merchandise imports, State and Australia, Customs Value, States of final destination (imports) and origin (exports), ABS data, ABS method |
TL2 |
|
|
AUS |
1 |
Statistics Austria compiles on behalf of the Austrian Chamber of Commerce (WKO) and the nine Austrian federal states regionalised foreign trade data by federal states |
TL2 |
|
AUT |
National Bank of Belgium, Dataset=EXTTRADEBENAT, region of final destination (imports) and initial origin (exports), NBB data, NBB method |
TL2 |
|
|
CAN |
Statistics Canada. CANSIM database. Table 228-0060 Merchandise imports and domestic exports (customs basis), Statcan data, Statcan method |
TL2 |
|
|
CHE |
7 |
Swiss Federal Customs Administration, FCA data |
TL2 |
|
COL |
National Administrative Department of Statistics - DANE, Directorate of Methodology and Statistical Production, DANE data |
TL2 |
|
|
FIN |
2 |
Tulli, Tilastointi - Tullen, Statistik - Finnish Customs, Statistics Tulli data, Tulli method |
TL2, TL3 |
|
FRA |
3 |
Douanes. Statistiques départementales et régionales du commerce extérieur pour l’exportation de marchandisesDouane data |
TL2, TL3 |
|
DEU |
Spatial Monitoring System of the BBSR |
TL2 |
|
|
ESP |
Agencia Tributaria, Ministerio de Hacienda y Función Pública |
TL2, TL3 |
|
|
GBR |
HM Revenue and Customs: Trade Statistics, UK Regional Trade in Goods Statistics |
TL2 |
|
|
GRC |
Hellenic Statistical Authority. External Trade Survey |
TL2 |
|
|
ITA |
ISTAT, Instrastat System |
TL2, TL3 |
|
|
KOR |
Statistics Korea |
TL2 |
|
|
LVA |
4 |
The External trade database and the Business register information of the Central Statistical Bureau |
TL2, TL3 |
|
LTU |
5 |
Statistics Lithuania, Lithuanian Customs: extra-EU trade Customs declarations, intra-EU trade (since 2004) Intrastat survey; Statistics Lithuania: Statistical Business Register |
TL2 |
|
PRT |
6 |
Statistics Portugal, Statistics on external trade of goods |
TL2, TL3 |
|
SVN |
SURS |
TL2 |
|
|
SWE |
Statistics Sweden |
TL2, TL3 |
|
|
USA |
U.S. Census Bureau: Economic Indicators Division USA Trade Online. U.S. Import and Export Merchandise trade statistics |
TL2 |
|
|
CHN |
National Bureau of Statistics China. Customs statistics |
TL2 |
1. Austria: Austrian federal states regionalised foreign trade data by federal states. In order to calculate statistically reliable regional foreign trade data in compliance with the principles of the official national statistical institution, individual records are matched and reassigned by resorting to already existing data sources.
2. Finland: Some large companies file declarations centrally, so no office-specific data are available in Intrastat or customs declarations. Customs estimates these data based on previous years and adjusts for actual production locations when necessary.
3. France: On exports, the department is the initial place from which the goods are exported (not the department of the exporting company’s head office). On import, it is the department of the final destination of the imported goods (and not the department of the importer’s head office). However, i) this general rule does not apply to trade in natural gas and electricity (by pipeline or high-voltage line): flows assigned by agreement to the Ile-de-France region and the department of Paris (75); ii) there are some structural effects: in some cases, the department indicated on customs documents is that of storage and not necessarily that of dispatch (for export), consumption or use (for import). In this way, flows are attributed to regions with major logistical hubs for trade (airports, ports, warehouses), even though they may not have originated in or been destined for these regions; this is notably the case for petroleum products.
4. Latvia: Unspecified data have been adjusted for non-response as well as trade below threshold related to the trade between the member states. Other unspecified information includes trade figures about the enterprises not registered in the business register (foreign enterprises) but which were carried out in trade in goods activities in Latvia.
5. Lithuania: Trade data are compiled according to the Special Trade System. Data by regions were compiled by linking International Trade in Goods Statistics and Statistical Register of Economic Entities (Statistical Business Register) data. Intrastat adjustments for non-response and trade below exemption thresholds are not included. Data are based only on the information of successfully linked enterprises.
6. Portugal: The country’s value may not match the sum of the regions since the head offices of some economic operators are not identified or are located abroad.
7. Switzerland: Data include gold, silver in bars and coins, electricity, returned goods and outward processing. Data omit two regions considered by the Federal Customs Administration (the Principality of Liechtenstein and canton not specified); therefore, the sum of CH01-CH07 does not correspond to the official Swiss foreign trade at the total level.
Women in relative poverty compared to men in relative poverty
Copy link to Women in relative poverty compared to men in relative poverty|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
AUS |
Luxembourg Income Study (LIS) |
2018 |
TL2 |
|
AUT |
LIS |
2020 |
TL2 |
|
BEL |
EU statistics on income and living conditions (EU-SILC) |
2022 |
TL2 |
|
CAN |
LIS |
2019 |
TL2 |
|
CHE |
LIS |
2019 |
TL2 |
|
CHL |
LIS |
2017 |
TL2 |
|
COL |
LIS |
2020 |
TL2 |
|
CZE |
EU-SILC |
2022 |
TL2 |
|
DEU |
EU-SILC |
2022 |
TL2 |
|
ESP |
EU-SILC |
2022 |
TL2 |
|
FIN |
EU-SILC |
2022 |
TL2 |
|
FRA |
LIS |
2018 |
TL2 |
|
GBR |
LIS |
2021 |
TL2 |
|
GRC |
EU-SILC |
2022 |
NUTS1 |
|
HUN |
EU-SILC |
2022 |
NUTS1 |
|
IRL |
LIS |
2019 |
TL2 |
|
ISR |
LIS |
2021 |
TL2 |
|
LTU |
LIS |
2020 |
TL2 |
|
MEX |
LIS |
2022 |
TL2 |
|
POL |
EU-SILC |
2022 |
NUTS1 |
|
PRT |
EU-SILC |
2022 |
TL2 |
|
SVK |
LIS |
2018 |
TL2 |
|
SWE |
LIS |
2021 |
TL2 |
|
USA |
LIS |
2021 |
TL2 |