OECD Regions and Cities at a Glance 2022
Annex B. Sources and data description
List of variables
|
Variables used |
Chapter(s) |
|---|---|
|
Agricultural droughts |
2 |
|
Cultural employment |
1 |
|
Cultural services spending by subnational government |
1 |
|
Electricity indicators |
2 |
|
Forest fires |
2 |
|
Greenhouse gas (GHG) emissions |
2 |
|
Green areas |
2 |
|
Gross domestic product (GDP) per capita |
2 |
|
Hospital beds |
1 |
|
Hospital accessibility |
4 |
|
Housing expenditure as a share of household disposable income |
4 |
|
Housing prices |
4 |
|
Income distribution: relative poverty rates and S80/S20 ratios |
4 |
|
Internet: broadband connections in households |
4 |
|
Internet: download speed from fixed devices |
4 |
|
Information and communication technology (ICT) jobs vacancies |
4 |
|
Labour productivity: gross value added (GVA) and employment at place of work |
1 |
|
Life expectancy at birth |
4 |
|
Municipal waste |
3 |
|
Population by degree of urbanisation |
3 |
|
Population: exposure to floods |
2 |
|
Population: migrants |
3 |
|
Population: mobility among regions |
3 |
|
Population projections |
3 |
|
Private motor vehicles |
3 |
|
Quarterly labour force |
1 |
|
Remote work uptake |
4 |
|
Tourism: flight passengers |
1 |
|
Tourism: overnight stays |
1 |
|
Trade openness |
1 |
Agricultural droughts
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Copernicus Climate Data Store ERA5-Land monthly average data product. See methodology in Annex C |
1981-2021 |
2, 3, FUA |
Cultural employment
|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
EU countries |
Eurostat, Cultural employment by NUTS regions, main job, table CULT_EMP_REG |
2020 |
2 |
|
Australia |
Australian Census, 2016 |
2016 |
2 |
|
Canada |
Mexican National Survey of Occupation and Employment, 2019 Quarter 4 |
2019 |
2 |
|
United States |
OECD calculations on Census Bureau, American Community Survey (ACS) |
2019 |
2 |
Cultural services spending by subnational government
|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
OECD countries |
OECD National Accounts, General Governments Accounts – Government expenditure by function (COFOG) |
2019 |
1 |
Electricity indicators
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Byers, L. et al. (2021), A Global Database of Power Plants, https://datasets.wri.org/dataset/globalpowerplantdatabase. Dunnett, S. et al. (2020), ”Harmonised global datasets of wind and solar farm locations and power”, Scientific Data, Vol. 7/130, https://doi.org/10.1038/s41597-020-0469-8. |
2019 |
2, 3 |
Forest fires
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Joint Research Centre’s (JRC) Global wildfire dataset for the analysis of fire regimes and fire behaviours, based on MODIS burned area product Collection 6. See methodology in Annex C |
2001-20 |
2 |
Greenhouse gas (GHG) emissions
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Emissions Database for Global Atmospheric Research (EDGAR), version 6.0 of the European Commission (EC) JRC. See methodology in Annex C |
1998-2018 |
2, 3 |
Green areas
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
ESA Worldcover data, which provides worldwide landcover data for 2020. See methodology in Annex C |
2020 |
FUA |
GDP per capita
|
Country |
Source |
Territorial level (last available year) |
|---|---|---|
|
EU countries1,2 |
Eurostat, Regional economic accounts |
2 (2020), 3 (2020) |
|
Australia |
Australian Bureau of Statistics, 5220.0. Gross state product, figures based on fiscal year (July-June) |
2 (2020) |
|
Canada |
Statistics Canada, Provincial economic accounts |
2 (2020) |
|
Chile |
Banco central de Chile. Cuentas nacionales de Chile |
2 (2021) |
|
Colombia |
DANE, Directorate of Synthesis and National Accounts |
2 (2020) |
|
Costa Rica2 |
n.a. |
- |
|
Iceland2 |
n.a. |
- |
|
Israel2 |
n.a. |
- |
|
Japan |
Economic and Social Research Institute, Cabinet Office, data are based on fiscal year (April-March) |
2 and 3 (2018) |
|
Korea |
Korean National Statistical Office |
2 and 3 (2020) |
|
Mexico |
INEGI, System of national accounts of Mexico |
2 (2020) |
|
New Zealand |
Statistics New Zealand |
2 and 3 (2020) |
|
Norway |
Norwegian Regional Accounts |
2 and 3 (2019) |
|
Switzerland |
Swiss Federal Statistical Office, Statweb |
2 and 3 (2019) |
|
Türkiye |
Turkish Statistical Institute (TurkStat) |
2 and 3 (2020) |
|
United States |
Bureau of Economic Analysis |
2 (2021), 3 (2020) |
1. EU countries: TL3 last available year 2019 for AUT, DEU, ESP, FIN, GRC, IRL, ITA, LTU, LVA and POL.
2. Costa Rica, Iceland and Israel: data not available at the regional level.
Hospital accessibility
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries,1 Norway and Switzerland |
Eurostat, Locations of Healthcare Services in Europe data, https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/healthcare-services |
2020 |
3 |
|
Australia |
Australia Institute of Health and Welfare (AIHW), https://www.aihw.gov.au/reports-data/myhospitals/themes/hospital-access#more-data |
2022 |
3 |
|
Canada |
Statistic Canada - The Open Database of Healthcare Facilities (ODHF), https://www.statcan.gc.ca/en/lode/databases/odhf |
2020 |
3 |
|
Chile |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Colombia |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Costa Rica |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Iceland |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Israel |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Japan |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Korea |
Data was sent to the OECD by the Ministry of Land, Infrastructure and Transport (MOLIT) |
2021 |
3 |
|
Mexico |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
New Zealand |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
Türkiye |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
United Kingdom |
Open Street Map, ‘hospital’ amenities (extracted in March 2022) |
2022 |
3 |
|
United States |
Homeland Infrastructure Foundation-Level Data (HIFLD) |
2022 |
3 |
1. EU countries: Data collected from Eurostat except for EST and GRC (Open Street Map).
Hospital beds
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU27, Norway and Switzerland1 |
Eurostat, table EU-hlth_rs_bdsrg |
2020 |
2 |
|
Australia2 |
Australian Institute of Health and Welfare (AIHW), for Public Hospitals: Australia Hospital Statistics (cat. no. 4390.0) |
2016 |
2 |
|
Canada3 |
Canadian Institute for Health Information, Hospital Beds Staffed and In Operation |
2020 |
2 |
|
Chile |
INE, Chile; Department of health statistics and information (DEIS), Ministry of health (MINSAL) |
2021 |
2 |
|
Colombia |
Special Register of Health Services Providers (REPS), Ministry of Health and Social Protection |
2020 |
2 |
|
Costa Rica |
n.a. |
- |
- |
|
Iceland |
n.a. |
- |
- |
|
Israel |
Central Bureau of Statistics Israel. Ministry of Health of Israel, Health Information Department |
2020 |
2 |
|
Japan |
Statistics Bureau, Survey of Medical Institutions, MHLW Japan |
2020 |
2 |
|
Korea |
Statistics Korea. Data provided by the country delegate of the WPTI |
2020 |
2 and 3 |
|
Mexico |
INEGI; Departamento de Estadísticas de Salud; Estadísticas de Salud en Establecimientos Particulares. Ministry of health |
2020 |
2 |
|
New Zealand |
n.a. |
- |
- |
|
Norway |
Statistics Norway, Geir Hjemas |
2020 |
2 and 3 |
|
Switzerland |
Federal Statistical Office (FSO), Neuchâtel; Swiss Medical Association (FMH), Bern; Medical Statistics of Physicians, yearly census |
2017 |
2 and 3 |
|
Türkiye |
Ministry of Health, General Directorate of Health Research, Health Statistics Yearbook |
2018 |
2 |
|
United Kingdom |
NHS UK; Beds open overnight and day, Welsh Government, Northern Ireland Health department, ISD Scotland |
2020 |
2 |
|
United States |
Area Health Resources Files, AHA Annual Survey |
2018 |
2 |
1. EU27 countries: Latest available year 2021 for BEL and IRL; 2019 for DEU, DNK, LUX and LVA; 2018 for BGR, EST, FIN, GRC, HRV, ROU. 2. Australia: Average available beds count from public hospital and private hospital. Private hospital includes both private acute and/or psychiatric hospitals and free-standing day hospital facilities. Available beds are those immediately available (occupied and unoccupied) for the care of admitted patients as required. In the case of free-standing day hospital facilities, they include chairs, trolleys, recliners and cots and are used mainly for post-surgery recovery purposes only.
2. Canada: Beds and cribs available and staffed to provide services to inpatients at the required type and level of service at the beginning of the fiscal year. When the number of hospital beds staffed and in operation is not available, calculations are made based on other methods, such as rated bed capacity. Bassinets set up outside the nursery and used for infants other than new borns are included.
Housing expenditure as a share of household disposable income
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
Australia |
Australia Bureau Statistics; Table 4130.0 |
2017 |
2 |
|
Austria |
Statistics Austria, EU-SILC |
2019 |
2 |
|
Belgium |
Household Budget Survey (HBS). Calculation based on data from the Institute of National Accounts |
2019 |
2 |
|
Canada |
Statistics Canada; CANSIM, Table 203-0022 |
2016 |
2 |
|
Costa Rica |
INEC |
2018 |
2 |
|
Denmark |
Statistics Denmark; Household Budget Survey, Tables FU51 and FU6 |
2016 |
2 |
|
Finland |
Statistics Finland; Table ktutk_003_201600 |
2016 |
2 |
|
Germany |
Statistical Offices of the Federal States, Spatial Monitoring System of the BBSR |
2018 |
2 |
|
Ireland |
Household Budget Survey, Tables HS067 and HS068 |
2015 |
2 |
|
Israel |
Central Bureau of Statistics Israel, Household Expenditure survey |
2015 |
2 |
|
Latvia |
CSB Official statistics https://data.stat.gov.lv/pxweb/en/OSP_PUB/START__POP__MA__MAI/MAI010/ |
2020 |
2 |
|
Netherlands |
Statistics Netherlands |
2018 |
2 |
|
Portugal |
Statistics Portugal, Household Budget Survey |
2020 |
2 |
|
Slovak Republic |
Statistical Office of the SR, Household Budget Survey |
2020 |
2 |
|
Slovenia |
SURS (EU-SILC) |
2020 |
2 |
|
United Kingdom |
Office for National Statistics; Table A35 |
2016 |
2 |
Housing prices
|
Country |
Source |
Period covered |
Geographical units |
|---|---|---|---|
|
Austria |
Statistik Austria |
2019 Q1-2021 Q2 |
955 municipalities |
|
Belgium |
National Bank of Belgium, https://www.nbb.be/en |
2019 Q1-2021 Q2 |
532 municipalities |
|
Denmark |
Statistics Denmark |
2019 Q1-2021 Q2 |
582 postal codes |
|
Estonia |
Estonian Land Board transactions database |
2019 Q1-2021 Q2 |
45 Towns + 13 District |
|
Finland |
Statistics Finland |
2019 Q1-2021 Q2 |
225 municipalities |
|
France |
Demande de valeurs foncières (data.gouv.fr) |
2019 Q1-2021 Q2 |
1 571 communes + 273 districts |
|
Germany |
Vdp Research |
2019 Q1-2021 Q2 |
4 413 postal codes + 121 districts |
|
Hungary |
Hungarian Central Statistics Office |
2019 Q1-2021 Q2 |
2 889 Settlements + 23 Districts |
|
Ireland |
Property Services Regulatory Authority |
2019 Q1-2021 Q2 |
119 local electoral areas + 331 communes |
|
Korea |
MOLIT |
2019 Q1-2021 Q2 |
250 municipalities |
|
Mexico |
Sociedad Hipotecária Federal (SHF) |
2019 Q1-2021 Q2 |
10705 zip codes |
|
Norway |
Statistics Norway |
2019 Q1-2021 Q2 |
56 large municipalities + 11 counties |
|
Portugal |
Confidencial Imobiliário |
2019 Q1-2021 Q2 |
1 222 parishes |
|
Spain |
Spain municipal data (Source: INE); Spanish District data for Barcelona and Madrid (Source: Centro de information estadistica del notariado) |
2019 Q1-2021 Q2 |
5 400 municipalities (+31 districts) |
|
Sweden |
Svensk Mäklarstatistik |
2019 Q1-2021 Q2 |
275 municipalities |
|
United Kingdom |
UK Government Price Paid data |
2019 Q1-2021 Q2 |
8 382 postcode sectors |
|
United States |
Zillow Research Institute |
2019 Q1-2021 Q2 |
29 827 zip codes |
ICT jobs vacancies
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
OECD calculation based on EMSI Burning Glass |
2021 Q1 |
2 |
Income distribution: relative poverty rates and S80/S20 ratios
|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
Australia |
Luxembourg Income Study Database (LIS), based on Australian Bureau of Statistics (ABS) - Survey of Income and Housing (SIH) |
2018 |
2 |
|
Austria |
Luxembourg Income Study Database (LIS), based on Statistics Austria - Survey on Income and Living Conditions (SILC) |
2019 |
2 |
|
Belgium |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2021 |
2 |
|
Canada |
Statistics Canada - Canadian Income Survey (CIS) |
2017 |
2 |
|
Chile |
Luxembourg Income Study Database (LIS), based on Ministry of Social Development - National Socio-Economic Characterization Survey (CASEN) |
2017 |
2 |
|
Colombia |
Luxembourg Income Study Database (LIS), based on National Administrative Department of Statistics (DANE) - Great Integrated Household Survey (GEIH) |
2020 |
2 |
|
Costa Rica |
n.a. |
- |
- |
|
Czech Republic |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
2 |
|
Denmark |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2021 |
2 |
|
Estonia |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
2 |
|
Finland |
EU-SILC based on Statistics Finland - Income Distribution Survey (IDS); Survey on Income and Living Conditions (SILC) |
2020 |
2 |
|
France |
EU-SILC based on Centre Maurice Halbwachs; National Institute of Statistics and Economic Studies - Household Budget Survey (BdF) |
2019 |
2 |
|
Germany |
Luxembourg Income Study Database (LIS), based on German Institute for Economic Research (DIW) - German Socio-Economic Panel (GSOEP) |
2017 |
2 |
|
Greece |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
2 |
|
Hungary |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2015 |
2 |
|
Iceland |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2018 |
1 |
|
Ireland |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2021 |
2 |
|
Israel |
Luxembourg Income Study Database (LIS), based on National Insurance Institute of Israel; Central Bureau of Statistics - Household Expenditure Survey |
2018 |
2 |
|
Italy |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2016 |
2 |
|
Japan1 |
n.a. |
- |
- |
|
Korea1 |
n.a. |
- |
- |
|
Latvia |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
1 |
|
Lithuania |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2021 |
2 |
|
Luxembourg |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2020 |
1 |
|
Mexico |
Luxembourg Income Study Database (LIS), based on National Statistical Institute (INEGI) - Household Income and Expenditure Survey (ENIGH) |
2018 |
2 |
|
Netherlands |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41 |
2021 |
2 |
|
New Zealand |
n.a. |
- |
- |
|
Norway1 |
n.a. |
- |
- |
|
Poland |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2021 |
NUTS2 |
|
Portugal |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2020 |
2 |
|
Slovak Republic |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2020 |
2 |
|
Slovenia |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41 |
2021 |
2 |
|
Spain |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
2 |
|
Sweden |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and EU-SILC |
2021 |
2 |
|
Switzerland |
Eurostat, at-risk-of-poverty rate by NUTS regions table ilc_li41, and LIS |
2020 |
2 |
|
Türkiye |
TurkStats - Income Distribution and Living Conditions Statistics |
2021 |
2 |
|
United Kingdom |
Luxembourg Income Study Database (LIS), based on Department for Work and Pensions (DWP); Office for National Statistics (ONS) - Family Resources Survey (FRS) |
2018 |
NUTS1 |
|
United States |
Luxembourg Income Study Database (LIS), based on Bureau of Labor Statistics (BLS); U.S Census Bureau - Current Population Survey (CPS) - Annual Social and Economic Supplement (ASEC) |
2019 |
TL2 |
1. JPN, KOR and NOR: No recent subnational data.
Internet: Broadband connections in households
|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
EU20 countries |
Eurostat, Regional information society statistics, table isoc_r_broad_h |
2021 |
2 |
|
Australia |
Australian Bureau of Statistics (ABS), Household Use of Information Technology, Australia, 2012-13 (cat. no. 8146.0), Financial year |
2017 |
2 |
|
Canada |
Statistics Canada. CANSIM (database), Table 11-10-0228-01 - Survey of household spending (SHS) |
2019 |
2 |
|
Chile |
Ministerio de Educación from National Socioeconomic Characterization Survey |
2017 |
2 |
|
Colombia |
DANE - Survey on Technologies and Communications ENTIC |
2020 |
2 |
|
Costa Rica |
INEC |
2021 |
2 |
|
Iceland |
n.a. |
.. |
.. |
|
Israel |
Central Bureau of Statistics Israel, Household expenditure survey, Table 16 |
2018 |
2 |
|
Japan |
Statistics Bureau, Ministry of Internal Affairs and Communications, Japan |
2020 |
2 |
|
Korea |
Korean Ministry of Science, ICT and Future Planning - Survey on the Internet Usage (MSIP, KISA) |
2021 |
2 |
|
Mexico |
INEGI-Módulo, Availability and Use of Information Technologies in Households (MODUTIH) |
2021 |
2 |
|
New Zealand |
n.a |
.. |
.. |
|
Switzerland |
Federal Statistical Office of Switzerland (FSO). enquête sur l’utilisation d’Internet par la population |
2021 |
2 |
|
Türkiye |
Eurostat, Regional information society statistics, table isoc_r_broad_h |
2021 |
2 |
|
United Kingdom |
Eurostat, Regional information society statistics, table isoc_r_broad_h |
2019 |
2 |
|
United States |
Census Bureau, American Community Survey (ACS), 1-year estimates, table S1501 |
2019 |
2 |
Internet: Download speed from fixed devices
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
OECD calculation based on Speedtest by Ookla Global Fixed and Mobile Network Performance Map Tiles, https://registry.opendata.aws/speedtest-global-performance |
2019 Q1 - 2021 Q1 |
3, FUA |
Labour productivity: Gross value added (GVA) and employment at place of work
|
Country |
Source |
Territorial level (last available year) |
|---|---|---|
|
EU countries1,2 |
Eurostat, Regional economic accounts |
2 (2020), 3 (2020) |
|
Australia |
Australian Bureau of Statistics, cat. no. 5220.0 - Australian National Accounts: State Accounts, and Table 6291.0.55.003 Labour Force |
2 (2020) |
|
Canada |
Statistics Canada. CANSIM database, Tables 379-0028 Gross domestic product (GDP) at basic prices and 282-0008 Labour force survey estimates (LFS), by North American Industry Classification System |
2 (2020) |
|
Chile |
Banco central de Chile. Cuentas nacionales de Chile |
2 (2021) |
|
Colombia |
DANE, Directorate of Synthesis and National Accounts |
2 (2020) |
|
Costa Rica2 |
n.a. |
- |
|
Iceland2 |
n.a. |
- |
|
Israel2 |
n.a. |
- |
|
Japan |
Economic and Social Research Institute, Cabinet Office, data are based on fiscal year (April-March) |
2 and 3 (2016) |
|
Korea |
Korean National Statistical Office |
2 and 3 (2020) |
|
Mexico |
INEGI, System of national accounts of Mexico |
2 (2020) |
|
New Zealand |
Statistics New Zealand. GDP by industry, per region |
2 and 3 (2019) |
|
Norway |
Norwegian Regional Accounts |
2 and 3 (2019) |
|
Switzerland |
Federal Statistical Office (FSO). Gross value added (GVA) by canton and industries (je‑e-04.06.02) and Swiss Labour Force Survey - SLFS |
2 and 3 (2019) |
|
Türkiye |
Turkish Statistical Institute (TurkStat). Employment data from the Household Labour Force Survey |
2 and 3 (2020) |
|
United States |
Bureau of Economic Analysis. GVA by State and employment by industry (SA25, SA25N) |
2 (2020), 3 (2019) |
1. EU countries: TL3 last available year 2019 for AUT, DEU, ESP, FIN, GRC, IRL, ITA, LTU, LVA, NLD, POL, PRT and SWE.
2. Costa Rica, Iceland and Israel: Data not available at the regional level.
Life expectancy at birth
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU27, Norway and Switzerland 1 |
Eurostat, Regional Demographic Statistics |
2020 |
2 |
|
Australia |
Australian Bureau of Statistics; Table 3302.0 |
2019 |
2 |
|
Canada |
Statistics Canada; CANSIM, Table 053-0003 |
2019 |
2 |
|
Chile |
INE |
2021 |
2 |
|
Colombia |
DANE |
2021 |
2 |
|
Costa Rica |
n.a |
- |
- |
|
Iceland |
n.a. |
- |
- |
|
Israel |
Central Bureau of Statistics |
2019 |
2 |
|
Japan |
Statistics Bureau of Japan, MIC, Population Census |
2015 |
2 |
|
Korea |
Statistics Korea; Kosis, Life tables by Provinces |
2020 |
2 |
|
Mexico |
National Institute of Statistics and Geography (INEGI) |
2021 |
2 |
|
New Zealand |
Statistics New Zealand |
2018 |
2 |
|
Türkiye |
Eurostat, Regional Demographic Statistics |
2019 |
2 |
|
United States |
Measure of America |
2019 |
2 |
1. EU27 countries: Latest available year 2021 for SWE; 2019 for HRV.
Municipal waste
|
Country |
Source |
Last year |
Territorial level |
|---|---|---|---|
|
Australia |
National Waste report |
2018 |
2 |
|
Austria |
Environment Agency Austria (UBA) - Austrian Federal Waste Management Plan and related Status Reports |
2019 |
2 |
|
Belgium |
Statbel (Bruxelles data collected from Brussels Environment, Flemish Region data collected from OVAM) |
2020 |
2 |
|
Chile |
INE, Chile. Pollutant Release and Transfer Register (PRTR) - Registro de Emisiones y Transferencias de Contaminantes (RETC) |
2017 |
2 |
|
Colombia |
DANE |
2019 |
2 |
|
Costa Rica |
INEC |
2020 |
2 |
|
Czech Republic |
Czech Statistical Office CZSO, Annual statistical survey |
2020 |
2 |
|
Estonia |
Eurostat, Municipal waste (env_rwas_gen) |
2013 |
2 |
|
France |
Odd-numbered years: Ademe survey data; Even-numbered years: SDES estimates |
2019 |
2 |
|
Germany |
Waste Statistics of the Federal Statistical Office and the Statistical Offices of the Federal States, Spatial Monitoring System of the BBSR |
2020 |
2 |
|
Hungary |
HCSO, Hungarian Central Statistical Office |
2019 |
2 |
|
Israel |
Central Bureau of Statistics Israel |
2017 |
2 |
|
Italy |
ISPRA (Italian Institute for Environmental Protection and Research) |
2020 |
2 |
|
Japan |
Ministry of Internal Affairs and Communications |
2020 |
2 |
|
Korea |
Korean Ministry of Environment |
2020 |
2 |
|
Latvia |
Official statistics “2-Waste" by Latvian Environment, Geology and Meteorology Agency |
2020 |
2 |
|
Luxembourg |
Eurostat, Municipal waste (env_rwas_gen) |
2013 |
2 |
|
Mexico |
INEGI. Censo Nacional de Gobiernos Municipales y Delegacionales 2017 |
2020 |
2 |
|
Netherlands |
Statistics Netherlands |
2020 |
2 |
|
Norway |
Statistics Norway |
2020 |
2 |
|
Poland |
Central Statistical Office |
2020 |
2 |
|
Portugal |
Statistics Portugal, Urban waste statistics |
2020 |
2 |
|
Slovak Republic |
Statistical Office of the SR statistical survey |
2020 |
2 |
|
Slovenia |
SURS, Generated amounts |
2020 |
2 |
|
Sweden |
Swedish Environmental Protection Agency |
2020 |
2 |
|
Türkiye |
Municipal Waste Statistics Survey |
2014 |
2 |
|
United Kingdom |
Department for Environment, Food and Rural Affairs, Local Authority Collected Waste Statistics |
2020 |
2 |
|
United States |
n.a. |
- |
- |
Population by degree of urbanisation
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
OECD computation based on Florczyk A.J. et al. (2019), GHSL Data Package 2019, EUR 29788 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-13186-1, doi:10.2760/290498, JRC 117104. |
2000-15 |
Degree of urbanisation |
Population: Exposure to floods
|
Country |
Source |
Territorial level |
|---|---|---|
|
All countries |
River Flood Hazard Maps at European and Global Scale, 100-year return period. See methodology in Annex C |
2 |
Population: Migrants
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
OECD countries |
OECD Migrant Municipal Database. OECD (2022), The Contribution of Migration to Regional Development, OECD Regional Development Studies, OECD Publishing, Paris, https://doi.org/10.1787/57046df4-en. |
2017-20 |
2, 3, degree of urbanisation |
Population: Mobility among regions
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
Australia1 |
Australian Bureau of Statistics (ABS), ABS.Stat |
2016-19 |
3 |
|
Austria |
Statistics Austria, Migration statistics |
2016-19 |
3 |
|
Belgium |
FPS Economie/Statistics Belgium |
2016-19 |
3 |
|
Canada |
Statistics Canada. Cansim table 17-10-0015-01 |
2016-19 |
3 |
|
Chile |
INE, Population and Housing Census |
2015-17 |
3 |
|
Colombia |
n.a. |
- |
- |
|
Costa Rica |
n.a. |
- |
- |
|
Czech Republic |
Czech Statistical Office CZSO - Immigrants table Code: DEMD130062-6-1/8 |
2016-19 |
3 |
|
Denmark |
Statistics Denmark, StatBank, table FLY66 |
2016-19 |
3 |
|
Estonia |
Statistics Estonia, Statistical database, table RVR07 |
2016-19 |
3 |
|
Finland |
Statistics Finland, Population Statistics, Migration |
2016-19 |
3 |
|
France |
INSEE, Recensement de la Population |
2018 |
3 |
|
Germany |
Spatial Monitoring System of the BBSR. Periodic update of population statistics by the Federal Office of Germany and the Statistical Offices of the Federal States |
2016-19 |
3 |
|
Greece2 |
n.a. |
- |
- |
|
Hungary |
HCSO, Hungarian Central Statistical Office, Internal migration statistics based on the registration system of home addresses |
2016-19 |
3 |
|
Iceland |
Statistics Iceland, Internal migration |
2016-19 |
3 |
|
Ireland2 |
n.a. |
- |
- |
|
Israel |
Central Bureau of Statistics Israel |
2018 |
3 |
|
Italy |
Istat, Iscrizioni e cancellazioni anagrafiche (changes of residence from/to Italian municipalities) |
2016-19 |
3 |
|
Japan |
Statistics Bureau, Migrants by prefecture derived from the Basic Resident Registers |
2016-19 |
3 |
|
Korea |
Statistics Korea, KOSIS database - Internal Migration Statistics |
2016-19 |
3 |
|
Latvia |
Central Statistical Bureau of Latvia |
2016-19 |
3 |
|
Lithuania |
Statistics Lithuania, Data sources – the State Enterprise Centre of Registers, the Population Register; the Ministry of the Interior |
2016-19 |
3 |
|
Luxembourg |
n.a. |
- |
- |
|
Mexico |
INEGI. Censo de población y vivienda |
2015 |
3 |
|
Netherlands |
Statistics Netherlands on Statline |
2016-19 |
2 |
|
New Zealand2 |
n.a. |
- |
- |
|
Norway |
Statistics Norway. Statbank, table 01222: Population change (M) |
2016-19 |
3 |
|
Poland |
Central Statistical Office of Poland, PESEL register |
2016-19 |
3 |
|
Portugal2 |
n.a. |
- |
- |
|
Slovak Republic |
Statistical Office of the SR |
2016-19 |
3 |
|
Slovenia |
Statistical Office of the Republic of Slovenia, Ministry of the Interior - Central Population Register, Ministry of the Interior - Administrative Internal Affairs Directorate |
2016-19 |
3 |
|
Spain |
INE - Data provided by the delegate of the OECD Working Party on Territorial Indicators |
2016-19 |
3 |
|
Sweden |
Statistics Sweden, Central Office for Administrative and Electronic Public Services registration system |
2016-19 |
3 |
|
Switzerland |
Swiss Federal Statistical Office, 1990 to 2010: Annual Population Statistics (ESPOP), from 2011 onwards: Population and Households Statistics (STATPOP) |
2016-19 |
3 |
|
Türkiye |
Turkish Statistical Institute (TurkStat), Address-Based Population Registration System |
2016-19 |
3 |
|
United Kingdom3 |
National Statistical Office, Population Estimates |
2016-19 |
3 |
|
United States |
Census Bureau. County-to-County Migration Flows, 5-year ACS datasets |
2017 |
3 |
Note: Data refer to domestic migration: inflows and outflows of population from one region to another region of the same country. They do not include international immigration and outmigration.
1. Australia: Regional internal migration covers the movement of people from one location to another within Australia. Regional internal migration estimates (RIME) are prepared for sub-state regions and capture moves over each financial year on an annual basis.
2. Greece, Ireland, New Zealand and Portugal: Recent data not available at the regional level.
3. United Kingdom: Data do not include Northern Ireland and Scotland.
Population projections in regions
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU countries |
Eurostat, Population on 1st January by age, sex, type of projection and NUTS 3 region (proj_19rp3) |
2020-40 |
3 |
|
Japan |
National Institute of Population and Social Security Research; Regional Population Projections for Japan: 2015-2045 (2018) |
2020-40 |
3 |
|
Korea |
Statistics Korea, KOSIS database |
2020-40 |
3 |
Population projections in functional urban areas
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
All countries |
Schiavina M., S. Freire and K. MacManus (2022), GHS-POP R2022A - GHS Population Grid Multitemporal (1975-2030), Joint Research Centre (JRC), European Commission |
2020-30 |
FUA |
Private motor vehicles
|
Country |
Source |
Year |
Territorial Level |
|---|---|---|---|
|
Australia |
Australian Bureau of Statistics (ABS), Motor Vehicle Census (cat. no. 9309.0) |
2021 |
2 |
|
Austria |
Statistics Austria, Transport statistics |
2021 |
2 |
|
Belgium |
Statbel and IWEPS computation. https://statbel.fgov.be/fr/themes/mobilite/circulation/parc-de-vehicules |
2021 |
2 |
|
Canada |
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 |
2 |
|
Chile |
INE |
2020 |
2 |
|
Colombia |
DANE -RUNT 2021 |
2021 |
2 |
|
Costa Rica |
n.a. |
- |
- |
|
Czech Republic |
Czech Statistical Office CZSO, Ministry of Transport of the Czech Republic. www.mdcr.cz |
2020 |
2 |
|
Denmark |
Statistics Denmark, StatBank Table BIL707: Stock of vehicles per 1 January by region, passenger cars (for private use, taxis and rental) |
2021 |
2 |
|
Estonia |
Statistics Estonia |
2011 |
2 |
|
Finland |
Statistics Finland, Transport and tourism statistics |
2020 |
2 |
|
France |
MEDDTL (CGDD/SOeS) Fichier central des automobiles. https://www.statistiques.developpement-durable.gouv.fr/ |
2021 |
2 |
|
Germany |
Motorist’s Federal Office (Kraftfahrt-Bundesamt), Spatial Monitoring System of the BBSR. Private cars |
2019 |
2 |
|
Greece |
Hellenic Statistical Authority |
2020 |
2 |
|
Hungary |
Hungarian Central Statistical Office. Until 2017: Central Office for Administrative and Electronic Public Services, from 2017 Ministry of Interior - stock of road vehicles |
2021 |
2 |
|
Iceland |
Iceland road traffic directorate (www.us.is/umferdarstofa). Private vehicles, http://bifreidatolur.samgongustofa.is/?nid=1233 |
2014 |
2 |
|
Ireland |
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 |
2020 |
2 |
|
Israel |
Central Bureau of Statistics Israel |
2019 |
2 |
|
Italy |
Automobile club d’Italia |
2020 |
2 |
|
Japan |
Ministry of Internal Affairs and Communications |
2013 |
2 |
|
Korea |
Ministry of Land, Infrastructure and Transport |
2021 |
2 |
|
Latvia |
CSB Directorate of Road Traffic Safety |
2021 |
2 |
|
Lithuania |
State Enterprise Regitra, Register of Road Motor Vehicles of the Republic of Lithuania |
2020 |
2 |
|
Luxembourg |
.. |
2012 |
2 |
|
Mexico |
INEGI. Statistics of Motor Vehicles Registered in Circulation; Administrative record of the light vehicle automotive industry |
2020 |
2 |
|
Netherlands |
CBS, datasets 70072ned and 71405ned |
2020 |
2 |
|
New Zealand |
n.a. |
- |
- |
|
Norway |
Statistics Norway: Tables 07849 and 11823 |
2020 |
2 |
|
Poland |
Ministry of Interior of Poland, Central Register of Vehicles |
2020 |
2 |
|
Portugal |
Institute of Registries and Notaries |
2020 |
2 |
|
Slovak Republic |
Ministry of Interior of the SR |
2021 |
2 |
|
Slovenia |
Statistical Office of the Republic of Slovenia (SURS), the Central Register of Vehicles and Traffic Documents (MRVL) by the Ministry of Infrastructure (MZI) |
2020 |
2 |
|
Spain |
Govierno de España, Ministerio del Interior, Direción General de Tráfico. Parque de vehículos por provincias y tipos. http://www.dgt.es/portal/ca/seguridad_vial/estadistica/parque_vehiculos/por_provincia_y_tipo_parque/ |
2005 |
2 |
|
Sweden |
Statistics Sweden, Registered vehicles, table START__TK__TK1001__TK1001A |
2021 |
2 |
|
Switzerland |
Federal Statistical Office (FSO), Federal Roads Office (FEDRO): Stock of road vehicles (MFZ) |
2021 |
2 |
|
Türkiye |
Data sent by the Türkiye delegate of the OECD Working Party on Territorial Indicators |
2014 |
2 |
|
United Kingdom |
Office for National Statistics, United Kingdom Ministerial Department for Transport statistics |
2020 |
2 |
|
United States |
Federal Highway Administration. State Motor-Vehicle Registrations. Private and commercial automobiles (including taxicabs), http://www.fhwa.dot.gov/policyinformation/statistics.cfm |
2020 |
2 |
Quarterly labour force
|
Country |
Source |
Last available quarter |
Territorial Level |
|---|---|---|---|
|
Australia |
ABS 6291.0.55.001 Labour Force, Australia, Detailed. Table 02 and Table 03 (youth data); ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Austria |
Austrian Micro census - Labour Force Survey Quarterly Data N, Q, Smetadata; ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Belgium |
StatBel. Active (working and unemployed) population since 2017 based on the reformed Labour Force Survey, by quarter, region, age class and level of education; ages 15-64 and 15-24 |
2022 Q1 |
2 |
|
Canada |
Statistics Canada. Table 14-10-0017-01 Labour force characteristics by sex and detailed age group, monthly, unadjusted for seasonality (x 1 000); ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Chile |
Chilean National Statistical Institute. National Labour Force Survey (ENE). Unemployment rate; ages 15+. |
2022 Q2 |
2 |
|
Colombia |
DANE Gran encuesta integrada de hogares - Ciudades (23) data; ages 15+ |
2022 Q2 |
2 |
|
Costa Rica |
INEC-Costa Rica. Encuesta Continua de Empleo (ECE). Temas especiales de empleo. Sinopsis de la condición de actividad de las regiones de planificación; ages 15+ |
2022 Q2 |
2 |
|
Czech Republic |
Source: LFS - labour force survey. Table Code: ZAM01-A/13; ages 15+ |
2022 Q1 |
2 |
|
Denmark |
Statistics Denmark. AKU120K and AKU121K: Labour force status by employment status and region; ages 15-64 |
2022 Q2 |
2 |
|
Estonia |
Statistika andmebaas – tables: TT467 - Labour status of population aged 15-74 by region (quarters); TT497 - Youth employment rate; TT468 - Youth participation rate |
2022 Q2 |
2 |
|
Finland |
137i -- Population aged 15-74 by labour force status, sex and major region, quarterly data, 2012Q1-2022Q2 - 11c9 -- Population aged 15-74 by labour force status, sex and major region, quarterly data |
2022 Q2 |
2 |
|
France |
Localised unemployment rates ; ages 15+ |
2022 Q1 |
2 |
|
Germany |
n.a. |
- |
|
|
Greece |
Hellenic Statistical Authority. Labour force (Quarterly data) - Table 02B. Population 15+ (employment status, region) |
2022 Q2 |
2 |
|
Hungary |
Economic Activity Measures of Population Aged 15-74 by Sex Non-institutional population. Table LD4F04 |
2022 Q2 |
2 |
|
Iceland |
Statistics Iceland; ages 16-74 |
2022 Q2 |
2 |
|
Ireland |
CSO - QLF08 - Persons aged 15 years and over; QLF07 - Persons aged 15-89 years in Employment |
2022 Q2 |
2 |
|
Israel |
CBS; ages 15+ |
2022 Q2 |
2 |
|
Italy |
ISTAT Unemployment rate: Regional data - age; ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Japan |
Labour Force Survey/Basic Tabulation Historical data; ages 15+ |
2022 Q2 |
2 |
|
Korea |
Statistics Korea, Economically Active Population Survey - Summary of economically active pop. by city & province/gender (table DT_1ES3B01S); ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Latvia |
DotStat Short Term Labour statistics; ages 15+ and 15-24 |
2022 Q2 |
1 |
|
Lithuania |
DotStat Short Term Labour statistics; ages 15+ and 15-24 |
2022 Q2 |
1 |
|
Luxembourg |
DotStat Short Term Labour statistics; ages 15+ and 15-24 |
2022 Q2 |
1 |
|
Mexico |
INEGI. Encuesta Nacional de Ocupación y Empleo.; ages 15+ |
2022 Q2 |
2 |
|
Netherlands |
CBS - Labour participation; province; ages 15-75 |
2022 Q1 |
2 |
|
New Zealand |
Household Labour Force Survey - HLF - Table: Labour Force Status; ages 15+ and 15-24 |
2022 Q2 |
2 |
|
Norway |
Statistics Norway, table 13497: Population, by labour force status, age and region; ages 15-74 |
2022 Q2 |
2 |
|
Poland |
Statistics Poland//Category K4 Labour Market//Group G623 Economic activity of the 15-89 and 15-24 population (quarterly data)// Subgroup P3969 Economic activity of the population by place of residence |
2022 Q2 |
2 |
|
Portugal |
Statistics Portugal - Unemployment rate (Series 2011 - %) by Place of residence (NUTS - 2013) and Sex; Quarterly - Statistics Portugal, LFS; ages 16-84 and 16‑24 |
2022 Q2 |
2 |
|
Slovak Republic |
Statistical Office of the Slovak Republic, Balance of economic activity of population aged 15+ (since 2021) [pr3102qr] |
2022 Q2 |
2 |
|
Slovenia |
Working age population by activity and activity rates, age groups, sex and cohesion regions, Slovenia, quarterly; ages 15+ |
2022 Q2 |
2 |
|
Spain |
INE - Economic activity, unemployment and employment rates, by province; ages 15+ |
2022 Q2 |
2 |
|
Sweden |
Statistics Sweden - table AM0401UZ. Population aged 15-74 (LFS) by region, labour status and sex. Quarter 2005K2 - 2020K4; ages 15+ |
2022 Q2 |
3 |
|
Switzerland |
OFS - Swiss Labour Force Survey in 2nd quarter 2022 - table je-f-03.02.00.02.02.01 |
2022 Q2 |
2 |
|
Türkiye |
n.a. |
- |
|
|
United Kingdom |
ONS - annual population aged 16+ survey - regional - labour market status by age |
2022 Q2 |
2 |
|
United States |
Based on US BLS - Local Area Unemployment Statistics ages 16+. Monthly unemployment rates averaged by quarter |
2022 Q2 |
2 |
Remote work uptake
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU20 countries, Norway, and Switzerland1 |
European Labour Force survey, based on the work presented at the Annual Congress of the European Regional Science Association, Pécs, Hungary, August 2022: “From potential to reality: Regional enablers and inhibitors of telework across European regions” by Zhiwu Wei, Davide Luca, Cem Özüzel |
2019-20 |
Degree of urbanisation |
1. The number of individuals, as a share of all workers, who reported having “usually worked from home” (i.e. more than 50% of the time in the survey reference month).
Tourism: Flight passengers
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU20 countries, Norway, and Switzerland |
Eurostat, table tran_r_avpa_nm |
2020 |
2 |
|
Mexico |
Dirección General De Aeronáutica Civil |
2020 |
2 |
|
United Kingdom |
UK Civil Aviation Authority |
2020 |
2 |
|
United States |
Federal Aviation Administration |
2020 |
2 |
Tourism: Overnight stays in tourist accommodations
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
EU20 countries, Norway, and Switzerland |
Eurostat, table tour_occ_nin2 |
2020 |
2 |
|
Australia |
Australian Trade and Investment Commission – Tourism Research Australia |
2020 |
2 |
|
Chile |
INE, https://www.ine.cl/estadisticas/economia/comercio-servicios-y-turismo/actividad-del-turismo |
2020 |
2 |
|
Israel |
Central Bureau of Statistics Israel |
2020 |
2 |
|
Japan |
Statistics bureau |
2020 |
2 |
Trade openness
|
Country |
Source |
Year |
Territorial level |
|---|---|---|---|
|
Australia |
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 |
2019 |
2 |
|
Austria1 |
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 |
2019 |
2 |
|
Belgium |
National Bank of Belgium – Foreign trade, national concept |
2019 |
2 |
|
Canada |
Statistics Canada. CANSIM database. Table 228-0060 Merchandise imports and domestic exports |
2019 |
2 |
|
Colombia |
National Administrative Department of Statistics - DANE, Directorate of Methodology and Statistical Production |
2019 |
2 |
|
France |
Douanes. Statistiques départementales et régionales du commerce extérieur pour l’exportation de marchandises |
2019 |
2 |
|
Germany |
Spatial Monitoring System of the BBSR |
2019 |
2 |
|
Greece |
Hellenic Statistical Authority. External Trade Survey |
2019 |
2 |
|
Italy |
ISTAT, Instrastat System |
2019 |
2 |
|
Korea |
Statistics Korea |
2019 |
2 |
|
Latvia2 |
The External trade database and the Business register information of the Central Statistical Bureau |
2019 |
2 |
|
Lithuania3 |
Statistics Lithuania, Lithuanian Customs: extra-EU trade Customs declarations, intra-EU trade (since 2004) Intrastat survey; Statistics Lithuania: Statistical Business Register |
2019 |
2 |
|
Portugal4 |
Statistics Portugal, Statistics on external trade of goods |
2019 |
2 |
|
Slovenia |
SURS |
2019 |
2 |
|
Spain |
Ministerio de hacienda y funcion publica - Agencia Tributaria |
2019 |
2 |
|
Sweden |
Statistics Sweden |
2019 |
2 |
|
Switzerland5 |
Swiss Federal Customs Administration FCA |
2019 |
2 |
|
United Kingdom |
HM Revenue and Customs: Trade Statistics, UK Regional Trade in Goods Statistics |
2019 |
2 |
|
United States |
U.S. Census Bureau: Economic Indicators Division USA Trade Online. U.S. Import and Export Merchandise trade statistics |
2019 |
2 |
|
China |
National Bureau of Statistics China. Customs statistics |
2019 |
2 |
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 national official statistical institution, individual records are matched and reassigned by resorting to already existing data sources.
2. Latvia: Unspecified data have been adjusted for non-response as well as trade below the threshold related to the trade between the member states. Other unspecified information includes trade figures about the enterprises that are not registered in the business register (foreign enterprises) but which carried out the trade in goods activities in Latvia.
3. Lithuania: Trade data are compiled according to the Special Trade System. Data by region were compiled by linking International Trade in Goods Statistics (ITGS) 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 on the information of only successfully linked enterprises.
4. Portugal: The value for Portugal may not match the sum of the regions, since the head offices of some economic operators are not identified or are located abroad.
5. Switzerland: Data include gold, silver in bars and coins, electricity, returned goods and outward processing. Data omits two regions considered by FCA (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, www.swiss-impex.admin.ch.