Canadá

Number of grants of citizenship of the reporting country to persons usually resident in the reporting country who have previously been citizens of another country or who have been stateless.

The annual Eurostat's collection on statistics on acquisitions of citizenship is structured as follows:   Data Collection Info & Legislation UNIDEMO Unified Demographic The most extended annual collection on demography and migration, collecting data at national and regional level for population, births, deaths, immigrants, emigrants, acquisition and loss of citizenship, marriages and divorces by a large number of breakdowns. (Art. 3 of the Regulation (EU) No 1260/2013 and Art. 3 of the Regulation (EC) No 862/2007)   The annual demography data collections aim at collecting from the National Statistical Institutes both mandatory data and voluntary data. The mandatory data are those defined by the legislation listed on "6.1. Institutional Mandate - legal acts and other agreements". The demographic data collected on voluntary basis depend on the availability and on the quality of information available in the National Statistical Institutes. For more specific information on mandatory/voluntary data collection see 6.1. Institutional Mandate - legal acts and other agreements.   The following data on acquisition and loss of citizenship are collected:Acquisitions of  citizenship by age, sex and former citizenshipLoss of citizenship by sex and new citizenship   Naturalisation rates: based on the different breakdowns of data on acquisition of citizenship and migrant population received, Eurostat produces the following:Statistics available in migr_acqs:                  a.   share of foreign citizens who have acquired citizenship                  b.   share of EU citizens who have acquired citizenship                  c.   share of  non-EU citizens who have acquired citizenship

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Canada: Actual hours worked at main job by industry, monthly, seasonally adjusted, last 5 months

The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture. The Economic accounts for agriculture (EAA) are a satellite account of the European System of Accounts (ESA2010), providing complementary information and concepts adapted to the particular nature of the agricultural industry. Although their structure very closely matches that of the national accounts, their compilation requires the formulation of appropriate rules and methods. National Statistical Institutes or Ministries of Agriculture are responsible for data collection and calculation of national EAA, in accordance with EC Regulations. Eurostat is responsible for the EU aggregations. Regional data EAA accounts are compiled at regional level (NUTS2), but only in values in current prices. The labour input data and Unit values are not broken down to regional level. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data. Frequency of data collection for data under Regulation (EC) 138/2004 and gentlemen's agreement, deadline for transmission for years 2015-2016.

The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2014The data describe the average use of chemical and mineral fertilizers per area of cropland (arable land and permanent crops) at national, regional, and global level in a time series from 2002 to 2015

The Livestock Patterns domain of the FAOSTAT Agri-Environmental Indicators contains data on livestock numbers, shares of major livestock species and livestock densities in the agricultural area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961–2014. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.

The data describe the average use of pesticides per area of cropland (arable land and permanent crops) at national level in a time series from 1990 to 2014. 

The gross nutrient balances (N and P) are calculated as the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers, livestock manure), and the quantity of nutrient outputs leaving the system (mainly uptake of nutrients by crops and grassland). Gross nutrient balances are expressed in tonnes of nutrient surplus (when positive) or deficit (when negative). This calculation can be used as a proxy to reveal the status of environmental pressures, such as declining soil fertility in the case of a nutrient deficit, or for a nutrient surplus the risk of polluting soil, water and air. The nutrient balance indicator is also expressed in terms of kilogrammes of nutrient surplus per hectare of agricultural land to facilitate the comparison of the relative intensity of nutrients in agricultural systems between countries.

The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).

The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).

The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).

The air accident data are provided to Eurostat by the European Aviation Safety Agency (EASA). EASA as an Agency is responsible for providing common standards of safety and environmental protection in civil aviation in Europe and worldwide. It is the centrepiece of regulations creating a single European market in the aviation industry. The Agency’s responsibilities include aviation safety analysis and research for which it also collects statistics on European and worldwide aviation safety. The statistics are grouped according to type of operation, such as commercial air transport or general aviation, and aircraft category, such as aeroplanes, helicopters or gliders. The EASA manages and is responsible for the entire data collection. The selection of data made available to Eurostat does not differ from those available through the EASA (http://easa.europa.eu). In Eurobase, the following data are available: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca); Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw); Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah); Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal).

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS) (1),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders. (1) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS) (1),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Generally, only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders. (1) This designation shall not be construed as recognition of a State of Palestine and is without prejudice to the individual positions of the Member States on this issue.

The indicator shows the volume of goods transported in Europe (in tonnes), broken down by country and by year. The data covers the total volume of freight and mail loaded/unloaded.

Monthly aircraft movements (civil itinerant, civil local, military itinerant, military local) for airports with NAV CANADA towers.

Annual aircraft movements by class of operation (itinerant and local) by rank and number of movements, for airports with NAV CANADA flight service stations.

Monthly aircraft movements (civil itinerant, civil local, military itinerant, military local) for airports with NAV CANADA flight service stations.

Monthly aircraft movements (itinerant and local) by rank, number, peak hour and peak day, for airports with NAV CANADA flight service stations. Aircraft movements, by class of operation and peak hour and peak day of movements, airports with NAV CANADA flight service stations, monthly

Monthly aircraft movements (itinerant and local) by rank, number, peak hour and peak day, for airports with NAV CANADA towers.   Aircraft movements, by class of operation and peak hour and peak day of movements, for airports with NAV CANADA towers, monthly

Residence permits statistics refers to third-country nationals (persons who are not EU citizens) receiving a residence permits or an authorisation to reside in one of the EU or EFTA Member States. The definitions used for residence permits and other concepts (e.g. first permit) are presented in the section 3.4. Statistical concepts and definitions. The detailed data collection methodology is presented in Annex 8 of this metadta file. LEGAL FRAMEWORK - Residence data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007.  This legal framework refers to the initial residence permits data colection with 2008 first reference period (e.g. first residence permits; change of immigration status or reason to stay; all valid residence permits in the end of the year and long-term residence permits valid in the end of the year) and it provides also a general framework for newer data collections based on speciffic European legal acts (e.g. statistics on EU Blue Cards and statistics on single permits) or provided on voluntary basis (e.g. new long-term residence permits issued during the year and residence permits issued for family reunification with beneficiaries of  protection status). DATA SOURCE - Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following the reference year. AVAILABLE DATASETS I. Residence permits statistics by reason to stay, citizenship and permit's lenght of validity based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007. These statistics are avilable from 2008 reference year.     First Permits - see the definition in the section 3.4. Statistical concepts and definitions. First permits by reason, length of validity and citizenship (migr_resfirst)2. The totals presented in this tables are depended on data availability in the following four tables migr_resfam + migr_resedu+ migr_resocc+ migr_resoth.First permits issued for family reasons by reason, length of validity and citizenship (migr_resfam)First permits issued for education reasons by reason, length of validity and citizenship (migr_resedu)First permits issued for remunerated activities by reason, length of validity and citizenship (migr_resocc)First permits issued for other reasons by reason, length of validity and citizenship (migr_resoth)     Residence Permits issued with the occasion of changing the immigration status or reason to stay Change of immigration status permits by reason and citizenship (migr_reschange)               Residence permits valid in the end of the year All valid permits by reason, length of validity and citizenship on 31 December of each year (migr_resvalid)Long-term residents by citizenship on 31 December of each year (migr_reslong)     Share of long term residence permitsLong-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%) (migr_resshare) II. Residence permits statistics by age (5-year age groups) and sex collected on voluntary basis. These statistics are avilable from 2010 reference year. First permits by reason, age, sex and citizenship (migr_resfas)  All valid permits by age, sex and citizenship on 31 December of each year (migr_resvas)               Long-term residents by age, sex and citizenship on 31 December of each year (migr_reslas) III. EU Blue Cards data collection based on Article 20 of the Directive 2009/50/EC. These statistics are avilable from 2012 reference year2. EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1)       Admitted family members of EU Blue Cards holders by type of decision and citizenship (migr_resbc2)EU Blue Cards holders and family members by Member State of previous residence (migr_resbc3) IV. Single Permit data collection based on Art 15 Directive 2011/98/EU. These statistics are avilable from 2013 reference year. Single Permits issued by type of decision, length of validity (migr_ressing)  V. Pilot data collections collected on voluntary basis. These statistics are avilable from 2016 reference year and the data quality assesment is ongoing. Long-term residence permits issued during the year (migr_resltr)First permits issued for family reunification with a beneficiary of protection status (migr_resfrps1)Permits valid at the end of the year for family reunification with a beneficiary of protection status (migr_resfrps2) VI. New statistics on Intra-Corporate Transfers and Seasonal Workers New data collections with 2017 first reference period are in the preparetion phase to be released in 2018: Intra-Corporate Transfers data collection under Art 24 of Directive 2014/66/EU and Seasonal Workers data collection under Art 26 Directive 2014/36/EU.   Share of long-tem residence permits The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories.   Data consistency between tables The data providers should use the same methodological specifications provided by Eurostat and some tables from Resper statistics should be consistent between them according to this methodology.  However, consistency issues between tables exist due to some technical limitations (e.g. different data sources) or different methodology applied to each table (see the quality information from below or the national metadata files) or different point in time of producing each tables.   1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions. 2 The EU Blue cards issued during the year are collected in two datasets: 1. in the table migr_resocc countig the EU Blue Cards issued as "first permits" and 2. in the EU Blue Cards counting all EU Blue Cards issued. The diference between these two categories is represented by the EU Blue cards that are not first permits. However these two tables might be updated/revised at a different point in time and the consistency between tables might be affected.

Residence permit means any authorisation valid for at least 3 months issued by the authorities of a Member State allowing a third country national to stay legally on its territory. All valid permits on 31st December (end of the year). This data include statistics on all valid permits at the end of reference period, therefore including first permits, change of status or reasons to stay and renewed permits.

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

AITRAW = All in average income tax rates at average wage OECD Taxing Wages. Taxing Wages provides unique information on income tax paid by workers and social security contributions levied on employees and their employers in OECD countries. In addition, this annual publication specifies family benefits paid as cash transfers. Amounts of taxes and benefits are detailed program by program, for eight household types which differ by income level and household composition. Results reported include the marginal and effective tax burden for one- and two-earner families, and total labour costs of employers.

The OECD's ANalytical Business Enterprise Research and Development (ANBERD) database presents annual data on Research and Development (R&D) expenditures by industry and was developed to provide analysts with comprehensive data on business R&D expenditures. The ANBERD database incorporates a number of estimations that build upon and extend national submissions of business enterprise R&D data by industry (main activity/industry orientation). The current version of the ANBERD database presents OECD countries' and selected non-member economies' business expenditure on R&D since 1987, broken down across 100 manufacturing and service industry groups. The reported data follow the International Standard Industrial Classification, Revision 4 (ISIC Rev. 4) and are expressed in national currencies as well as in US dollars at Purchasing Power Parity (PPP), both at current and constant prices.   Main activity and industry orientation: The 2015 Frascati Manual practice is to report BERD on an enterprise basis. The main economic activity of an enterprise is usually defined as that which accounts for most of its economic outputs; this may be identified directly from sales or indirectly proxied (such as by numbers of personnel devoted to different activities). This determines the industry in which the enterprise, and any BERD it carries out, is classified. As such, all BERD of a diversified enterprise (i.e. one with multiple lines of business) is allocated to the same industry, that of its main activity. This enables, as far as possible, the alignment and compatability of BERD data with other economic statistics (e.g. value added broken down by industry). In addition, the Frascati Manual also recommends reporting BERD by industry orientation, whereby the statistical unit’s R&D is distributed across the various lines of business to which it relates. In a few countries, hybrid approaches are followed and reported as main activity data. As an example, some countries primarily follow the main activity approach but redistribute the R&D of large diversified firms across the economic activities to which it relates. This can affect interpretation of the data and resulting statistics. There are also important differences between countries in the treatment of R&D undertaken by firms in the service sector but closely associated (though not necessarily contractually) with manufacturing firms. Industrial research institutes, largely funded by the manufacturing industries they serve, are the most frequent examples. With the implementation of the 2015 Frascati Manual, such hybrid data will be phased out in favour of a strict main activity approach. Countries still reporting hybrid data are flagged in the ANBERD country notes.

Animal output is valued at basic prices. The basic price is defined as the price received by the producer, after deduction of all taxes on products but including all subsidies on products. The concept of output comprises sales, changes in stocks, and products used for processing and own final use by the producers.

Livestock numbers are derived from surveys of farms or from administrative sources in November or December for each Member State.

Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below.   Table 3.1: Data tables disseminated regarding animal production statistics

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category:Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below:Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

The data correspond to quarterly financial accounts for the general government sector and follows the ESA2010 methodology. The data covers financial transactions and balance sheet items for general government (consolidated and non-consolidated) and its subsectors. This includes a number of financial instruments (F.1, F.2, F.3, F.4, ...) as well as some balancing items such as net financial transactions, net financial worth and net financial assets and liabilties. Data are available in million of euro, million of national currency (average exchange rates are used for transactions and end of period exchange rates are used for stocks) and as a percentage of GDP (for transactions quarterly GDP is used; for stocks a rolling sum of the last four quarters is used). In the table gov_10a_ggfa, annualised quarterly financial accounts for general government are presented. For financial transactions, data is summed over the four quarters of each year. For the conversion from national currency into euro, the yearly average exchange rate is used. For balance sheet items (stocks), the annualised data corresponds to the data of the fourth quarter. The percentage of GDP data of annualised data uses annual GDP transmitted by the Member States. In the course of the annualisation, small rounding differences may be amplified. Geographic coverage: EU and euro area. Main data sources are the tables provided according to the European Parliament and Council Regulation (EU) N° 549/2013 of 21 May 2013 (OJ No L174/1).

The “ALFS Summary tables” dataset is a subset of the Annual Labour Force Statistics database which presents annual labour force statistics and broad population series for 34 OECD member countries plus Brazil, Columbia and Russian Federation and 4 geographical areas (Major Seven, Euro area, European Union and OECD-Total). Data are presented in thousands of persons, in percentage or as indices with base year 2010=100. This dataset contains estimates from the OECD Secretariat for the latest years when countries did not provide data. These estimates are necessary to compile aggregated statistics for the geographical areas for a complete span of time. Since 2003, employment data by sector for the United States are compiled following the North American Industrial Classification System (NAICS); therefore they are not strictly comparable with other countries’ data. Euro area and European Union data were extracted from Eurostat (LFS Series, Detailed annual survey results in New Cronos). Euro area refer to Euro area with 17 countries (geo = ea17). European Union refers to European Union with 27 countries (geo = eu27).

Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast of Council Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).

Eurostat collects road transport statistics by two means: 1. Data on infrastructure, transport equipment, enterprises, economic performance, employment, traffic, aggregated data on transport of passengers and goods as well as data on accidents are collected using the Common Questionnaire of the United Nations Economic Commission for Europe (UNECE), Eurostat and the International Transport Forum (ITF, in the framework of OECD). The method of the Common Questionnaire data collection is presented in a separate document. 2. Data on carriage of goods by road, using heavy goods vehicles, are based on a continuum of legal acts: 2.1 Data collection on carriage of goods by road until 1998 (included) was based on Directives 78/546/EEC and 89/462/EEC and covered tonnes and tonne-kilometres only. 2.2 Data since the reference period 1999 are derived from micro-data collected in the framework of Regulation (EU) No 70/2012 of the European parliament and of the council on statistical returns in respect of the carriage of goods by road, a recast of Council Regulation (EC) 1172/98 which has replaced the previous Directives. The figures are aggregated on the basis of sample surveys carried out by the reporting countries. The data cover tonnes, tonne-kilometres, vehicle-kilometres and numbers of journeys. These metadata pages only refer to road freight statistics based on the European Union's legal acts (point 2 above) and, in particular, to the data for reference years 1999 and after (2.2).

Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.

Aquaculture economic statistics, value added account, Canada and provinces (dollars x 1,000). Data are available on an annual basis.

Data source used: The aquaculture production data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies. Data on marine landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.

Total production of fish, crustaceans, molluscs and other aquatic organisms from aquaculture ("fish-farming") from 2008 onwards, excluding hatcheries and nurseries. The data are expressed in Tonnes Live Weight (TLW, incl. shells, skeletons, etc.), Euro and Euro/Tonne. Production data from hatcheries and nurseries can be found in the fish_aq2b, fish_aq4a and fish_aq4b tables. Older data (1950-2007), excluding production from hatcheries and nurseries, are contained in the "Aquaculture production until 2007 (fish_aq08)" database.

Aquaculture, production and value, Canada and provinces (in dollars and tonnes). Data are available on an annual basis.

Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

Average yield, area harvested and planted, total and marketed production of vegetables.

Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to:Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.

Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to:Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.

Asylum applicant means a person having submitted an application for international protection or having been included in such application as a family member during the reference period. New asylum applicant means a person having submitted an application for international protection for the first time

Asylum applicant means a person having submitted an application for international protection or having been included in such application as a family member during the reference period. New asylum applicant means a person having submitted an application for international protection for the first time.

Asylum applicants considered to be unaccompanied minors.

Data series on asylum applications contain statistical information based on Article 4 of the Council Regulation (EC) No 862/2007 with reference to:Asylum and first time asylum applicants by age, sex and citizenshipPersons subject to applications pending at the end of reference period by age, sex and citizenshipApplications for asylum withdrawn by age, sex and citizenshipAsylum applicants considered to be unaccompanied minors by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented by country and for groups of countries: the European Union (EU28, EU27) and the European Free Trade Association (EFTA). Data has been rounded to the nearest 5.

The indicator shows the number of first-time asylum applicants per million inhabitants and the number of positive first instance decisions per million inhabitants. Please note that caution is required when comparing these two values, since applications received in a given year might not be processed until a later year. Source data are supplied to Eurostat by the national Ministries of Interior and related official agencies. A first-time applicant for international protection is a person who lodged an application for asylum for the first time in a given Member State. First instance decisions are decisions granted by the respective authority acting as a first instance of the administrative/judicial asylum procedure in the receiving country.

Data cited at:  CBS StatLine databank https://opendata.cbs.nl/statline/portal.html?_la=en&_catalog=CBS Publication: Asylum requests; international https://opendata.cbs.nl/portal.html?_la=en&_catalog=CBS&tableId=80498ENG&_theme=1088 License: http://creativecommons.org/licenses/by/4.0/   Requests for asylum in member states of the European Union and some countries outside the European Union. In addition to the total number of asylum requests, the number of first asylum requests is also included. The data with respect to EU member states in this table is based on data from Eurostat and is partly different from data published in the table Asylum requests; international 1990-2009. See link section 3. The figures for the countries outside the European Union are submitted by the UNHCR. Data available from: 2008. Status of the figures: The data are final, but it occasionally happens that countries provide revised data. Therefore, the data in the table may be subject to change. Changes as of 22 December 2017: The figures for EU-28, Austria, France, Ireland and the United Kingdom have been adjusted for the year 2016 and the figure for Canada has been adjusted for the year 2015. The figures for Canada and Australia have been added for the year 2016. For the United States there is no current figure available for the year 2016. When will new figures be published? Figures for 2017 will be published in April 2018.

This table contains 42560 series, with data for years 2009 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...); Price (2 items: Original prices; Current prices); Age (2 items: Average age; Remaining useful service life ratio); Industry (20 items: Total all industries; Agriculture, forestry, fishing and hunting; Mining, quarrying and oil and gas extraction; Utilities; ...); Assets (38 items: Total non-residential; Building; Industrial buildings; Office buildings; ...).

The concept used is the total number of hours worked over the year divided by the average number of people in employment. The data are intended for comparisons of trends over time; they are unsuitable for comparisons of the level of average annual hours of work for a given year, because of differences in their sources. Part-time workers are covered as well as full-time workers. The series on annual hours actually worked per person in total employment presented in this table for all 34 OECD countries are consistent with the series retained for the calculation of productivity measures in the OECD Productivity database (www.oecd.org/statistics/productivity/compendium). However, there may be some differences for some countries given that the main purpose of the latter database is to report data series on labour input (i.e. total hours worked) and also because the updating of databases occur at different moments of the year. Hours Hours actually worked per person in employment are according to National Accounts concepts for 18 countries: Austria, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Italy, Korea, the Netherlands, Norway, the Slovak Republic, Spain, Sweden, Switzerland and Turkey. OECD estimates for Belgium, Ireland, Luxembourg and Portugal for annual hours worked are based on the European Labour Force Survey, as are estimates for dependent employment only for Austria, Estonia, Greece, the Slovak Republic and Slovenia. The table includes labour-force-survey-based estimates for the Russian Federation.countries: For further details and country specfic notes see: www.oecd.org/employment/outlook and www.oecd.org/employment/emp/ANNUAL-HOURS-WORKED.pdf

This dataset contains data on average annual wages per full-time and full-year equivalent employee in the total economy.  Average annual wages per full-time equivalent dependent employee are obtained by dividing the national-accounts-based total wage bill by the average number of employees in the total economy, which is then multiplied by the ratio of average usual weekly hours per full-time employee to average usually weekly hours for all employees.   Average wages are converted in USD PPPs using 2017 USD PPPs for private consumption and are deflated by a price deflator for private final consumption expenditures in 2017 prices.   Real compensation per employee (instead of real wages) are considered for Chile, Iceland, Mexico and New Zealand.

The average effective age of retirement is calculated as a weighted average of (net) withdrawals from the labour market at different ages over a 5-year period for workers initially aged 40 and over. In order to abstract from compositional effects in the age structure of the population, labour force withdrawals are estimated based on changes in labour force participation rates rather than labour force levels. These changes are calculated for each (synthetic) cohort divided into 5-year age groups. The estimates shown in red are less reliable as they have been derived from interpolations of census data rather than from annual labour force surveys. The estimates for women in Turkey are based on 3-yearly moving averages of participation rates for each 5-year age group. OECD estimates based on the results of national labour force surveys, the European Union Labour Force Survey and, for earlier years in some countries, national censuses.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.

Average usual hours and wages of employees (full- and part-time) by age group, sex, union coverage, job permanency, and National Occupational Classification (NOC), last 5 months.

Average weekly earnings (including overtime) for all employees by enterprise size and North American Industry Classification System (NAICS), last 5 quarters.

Average weekly hours (including overtime) for employees paid by the hour, by enterprise size and North American Industry Classification System (NAICS), last 5 quarters.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

Sugar Data of United States

STAN Bilateral Trade Database by Industry and End-use category (BTDIxE) provides values of imports and exports (as well as re-imports and re-exports) of goods broken down by industrial sectors and by end-use categories. BTDIxE was designed to extend the old BTD database which provided bilateral trade in goods by industry only.  BTDIxE allows, for example, insights into the patterns of trade in intermediate goods between countries to track global production networks and supply chains, and it helps to address policy issues such as trade in value added and trade in tasks.  The database presents estimates of bilateral flows of goods from 1990 to the latest available year, i.e. 2018; the latest year shown is subject to the availability of underlying product-based annual trade statistics.  Reporters are the OECD member countries and a large number of non-OECD economies, including the BRIICS: Brazil, the Russian Federation, India, Indonesia, People's Republic of China and South Africa; other selected G20 and Asian economies; and major African and Latin American nations.  It should be noted that starting from mid-2012, the OECD and the United Nations agreed to centralise the data collection and processing procedures within UNSD Comtrade.  The list of partners covers the OECD countries, more than a hundred of non-member economies as well as the partners "World", "Rest of the World" and "Unspecified". The partner "Total foreign trade" corresponds to the flows with partner "World" excluding intra-country flows. Trade flows are divided into economic activities based on the Revision 4 of ISIC and nine end-use categories including capital goods, intermediate goods and household consumption.

The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document (see Business demography indicators).  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).

Data on cultural enterprises come from 2 data collections and are summarised in 4 Tables : a) SBS (Structural Business Statistics) Table 1. Number and average size of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_num) Table 2. Value added and turnover of enterprises in the cultural sectors by NACE Rev. 2 activity (cult_ent_val), in millions of EUR and as a percentage of services except trade and financial and insurance activities (i.e. NACE Rev. 2 sections H to N, without K) Table 3. Services by employment size class (NACE Rev. 2, H-N, S95) (sbs_sc_1b_se_r2)   b) Business Demography (BD) Table 4. Business demography by size class (from 2004 onwards, NACE Rev. 2) (bd_9bd_sz_cl_r2)   The data focus on culture-related sectors of activity, as identified by international experts in the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012).   The cultural sphere in business statistics is therefore captured through the following NACE Rev. 2 codes, when they are covered (see 3.3. Sector coverage for details): J58.11 Book publishing J58.13 Publishing of newspapers J58.14 Publishing of journals and periodicals J58.21 Publishing of computer games J59 Motion picture, video and television programme production, sound recording and music publishing activities J60 Programming and broadcasting activities J63.91 News agency activities M71.11 Architectural activities M74.1 Specialised design activities R90 Creative, arts and entertainment activities R91 Libraries, archives, museums and other cultural activities

Business demography produces information such as birth rates, death rates, survival rates, and their employment shares. These main derived indicators are expressed as ratios of total active enterprises or enterprises born in the reference period. Presented data refer to the business economy, covering sections B to N (excluding activities of holding companies – K64.2) according to NACE Rev. 2.

Business demography contains information for characteristics and demography of the business population. The category presents main variables, such as enterprise births (often referred to as business entries), enterprise deaths (often referred to as business exits), and enterprise survivals. Enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not included in this data. Information refers to the business economy, covering sections B to N (excluding activities of holding companies – K64.2) according to NACE Rev. 2.

This table contains 20475 series, with data for years 2014 - 2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Newfoundland and Labrador; Prince Edward Island; Nova Scotia; New Brunswick; ...) North American Industry Classification System (NAICS) (75 items: Total all industries; Agriculture, forestry, fishing and hunting; Agriculture (except aquaculture) and support activities for crop production and animal production; Forestry, logging and support activities for forestry; ...) Country of control (3 items: Total country of control; Canada; Foreign) Research and development characteristics (7 items: Total in-house research and development expenditures; Total current in-house research and development expenditures in Canada; Total capital in-house research and development expenditures in Canada; Total in-house research and development personnel; ...).

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB), Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE)  at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors under Annexes section. Within the sectoral approach, a second classification was created , named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions under Annexes section. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. . For more details, see definition of high-tech products under Annexes section. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents under Annexes section. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

The business tendency survey indicators cover a standard set of indicators for four economic sectors: manufacturing, construction, retail trade and other services. This includes an indicator of overall business conditions or business confidence in each sector. The consumer opinion survey indicators cover a restricted set of indicators on consumer confidence, expected economic situation and price expectations.   Business and consumer opinion (tendency) surveys provide qualitative information that has proved useful for monitoring the current economic situation. Typically they are based on a sample of enterprises or households and respondents are asked about their assessments of the current situation and expectations for the immediate future. For enterprise surveys this concerns topics such as production, orders, stocks etc. and in the case of consumer surveys their intentions concerning major purposes, economic situation now compared with the recent past and expectations for the immediate future. Many survey series provide advance warning of turning points in aggregate economic activity as measured by GDP or industrial production. Such series are known as leading indicators in cyclical analysis. These types of survey series are widely used as component series in composite leading indicators.   The main characteristic of these types of surveys is that instead of asking for exact figures, they usually ask for the direction of change e.g. a question on tendency by reference to a “normal” state, e.g. of production level. Possible answers are generally of the three point scale type e.g. up/same/down or above normal/normal/below normal for enterprise surveys and of the five point scale type e.g. increase sharply/increase slightly/remain the same/fall slightly/fall sharply for consumer surveys. In presenting the results as a time series, only the balance is shown. That is “same” or “normal” answers are ignored and the balance is obtained by taking the difference between percentages of respondents giving favourable and unfavourable answers.   Virtually all business tendency and consumer opinion survey data are presented as time series of balances in this dataset, either in raw or seasonally adjusted form. Very few series are presented as indices, and where these exist they have generally been converted from underlying balances by countries before submitting the data to the OECD.

This table contains 29 series, with data for years 2009 - 2019 (not all combinations necessarily have data for all years).This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Central government debt (29 items: A. Federal debt (accumulated deficit), (B - E); B. Net debt, (C - D); C. Liabilities, gross debt; Accounts payable and accrued liabilities; ...).

Farm product price index (FPPI), monthly weights, Canada (index, 2007=100). Data are available on a monthly basis.

Owner occupied and landlord and tenant occupied expenditures for Canada, the provinces and territories, annual.

Canadian government finance statistics (CGFS), statement of operations and balance sheet for the Canada and Quebec pension plans, annual (dollars x 1,000,000), 5 most recent time periods.

Canadian government finance statistics (CGFS), statement of operations and balance sheet for education institutions, annual (dollars x 1,000,000), 5 most recent time periods.

Eurostat Dataset Id:cpc_ecgov  The focus of this domain is on the following country groups:Acceeding country: Croatia (HR)Candidate countries: the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Iceland (IS), Serbia (RS) and Turkey (TR)Potential candidate countries: Albania (AL), Bosnia and Herzegovina (BA), as well as Kosovo under UNSCR 1244/99 (XK)

The focus of this domain is on enlargement countries, in other words the following country groups: candidate countries — Albania (AL), the former Yugoslav Republic of Macedonia (MK), Montenegro (ME), Serbia (RS) and Turkey (TR)potential candidates — Bosnia and Herzegovina (BA), and Kosovo (XK) (*) An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. (*) This designation is without prejudice to positions on status and is in line with UNSCR 1244/1999 and the ICJ Opinion on the Kosovo declaration of independence.

The data in this dataset comes from the Common Questionnaire for Transport Statistics, developed and surveyed in co-operation between the United Nations Economic Commission for Europe (UNECE), the International Transport Forum (ITF) and Eurostat. The Common Questionnaire is not supported by a legal act, but is based on a gentlemen's agreement with the participating countries; the completeness varies from country to country. Eurostat’s datasets based on the Common Questionnaire cover annual data for the EU Member States, EFTA states and Candidate countries to the EU. Data for other participating countries are available through the ITF and the UNECE. In total, comparable transport data collected through the Common Questionnaire is available for close to 60 countries worldwide. The Common Questionnaire collects aggregated annual data on: Railway transportRoad transportInland waterways transportOil pipelines transportGas pipelines transport For each mode of transport, the Common Questionnaire cover some or all of the following sub-modules (the number of questions/variables within each sub-module varies between the different modes of transport): Infrastructure (All modes)Transport equipment (RAIL, ROAD and INLAND WATERWAYS)Enterprises, economic performance and employment (All modes)Traffic (RAIL, ROAD and INLAND WATERWAYS)Transport measurement (All modes) Accidents (ROAD only) The Common Questionnaire is completed by the competent national authorities. The responsibility for completing specific modules (e.g. Transport by Rail) or part of modules (e.g. Road Infrastructure) may be delegated to other national authorities in charge of specific fields.

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

Catches of fish, crustaceans, molluscs and other aquatic organisms by species and fishing area for EU and associated countries (in live weight equivalent of the landings). European data on fish catches, in tonnes live weight (TLW) have been recorded since 1950. Historical data up to 1999 are displayed under [fish_ca_h] while data from 2000 onwards are released in the [fish_ca] tables. These exclude catches in inland waters and focus on marine fishing areas that are legally covered, namely: 21 - Atlantic, Northwest 27 - Atlantic, Northeast 34 - Atlantic, Eastern Central 37 - Mediterranean and Black Sea 41 - Atlantic, Southwest 47 - Atlantic, Southeast 51 - Indian Ocean, Western

The total annual catch of fishery products by EU Member States, Iceland and Norway and other major fishing nations from all oceans and internal waters of the world. The data are expressed in the live weight equivalent of the landings. This is the weight as the product is taken from the water (that is, before processing) but excludes any products which, for a variety of reasons, are not landed.

The total annual catches by EU Member States, Iceland, Norway and other major fishing nations in the Eastern Central Atlantic. This region of the Atlantic Ocean, is roughly the area to the east of 40°W longitude between latitudes 36°N and 6°S. The data are expressed in the live weight equivalent of the landings. This is the weight as the product is taken from the water (that is, before processing) but excludes any products which, for a variety of reasons, are not landed.

The total annual catches by EU Member States, Iceland, Norway and other major fishing nations in the Mediterranean. This region, known as FAO Major Fishing Area 37, comprises the Mediterranean and the adjacent Black Sea. The data are expressed in the live weight equivalent of the landings. This is the weight as the product is taken from the water (that is, before processing) but excludes any products which, for a variety of reasons, are not landed.

The total annual catches by EU Member States, Iceland, Norway and other major fishing nations in the North-east Atlantic. This region of the Atlantic Ocean, is roughly the area to the east of 42°W longitude and north of 36°N latitude. It includes the waters of the Baltic Sea. The data are expressed in the live weight equivalent of the landings. This is the weight as the product is taken from the water (that is, before processing) but excludes any products which, for a variety of reasons, are not landed.

The total annual catches by EU Member States, Iceland, Norway and other major fishing nations in the North-west Atlantic. This region of the Atlantic Ocean, is roughly the area to the west of 42°W longitude and north of 35°N latitude. The data are expressed in the live weight equivalent of the landings. This is the weight as the product is taken from the water (that is, before processing) but excludes any products which, for a variety of reasons, are not landed.

Cattle and calves statistics, number of farms reporting and average number of cattle and calves per farm, Canada and provinces (number). Data are available on a semi-annual basis.

Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics <

Cattle statistics, supply and disposition of cattle, Canada and provinces (head x 1,000). Data are available on an annual basis.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

This table contains 26 series, with data for years 2009 - 2019 (not all combinations necessarily have data for all years), and was last released on 2019-07-29. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Central government operations (26 items: A. Budgetary balance, deficit (-) / surplus (+), (B - C); B. Revenues; C. Expenses; Program expenses; ...).   Canada: Central government operations: budgetary balance, non-budgetary transactions, and financial source/requirement

CGPITRT: Central government personal income tax rates and threshold   This table reports statutory central government personal income tax rates for wage income plus the taxable income thresholds at which these statutory rates apply. The table also reports basic/standard tax allowances, tax credits and surtax rates. The information is applicable to a single person without dependents. The threshold, tax allowance and tax credit amounts are expressed in national currencies Tapered means that the tax relief basic amount is reduced with increasing income Further explanatory notes may be found in the Explanatory Annex This data represents part of the data presented within the Excel file “Personal income tax rates and thresholds for central governments - Table I.1”. The Data for 1981 to 1999 is not included here within as not all the data for these years is either available, or can be verified. The OECD tax database provides comparative information on a range of tax statistics - tax revenues, personal income taxes, non-tax compulsory payments, corporate and capital income taxes and taxes on consumption - that are levied in the 34 OECD member countries.” Tax policy Analysis homepage OECD Tax Database Taxing Wages Dissemination format(s) This data is also presented through the OECD Tax database webpage. OECD Tax Database

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

Total sales of flowers, plants, fruit and vegetables to retail florists, wholesalers, market chain stores, public agencies, etc.

Starting from 1750 Population statistics have been digitised into PDF format in the National Library's Doria service: Publications on Population structure and Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) --- Description of statistic Quality descriptions Concepts and definitionsRegionThese statistics apply the regional division of 1 January 2019 to the whole time series.NationalityCountries (ISO 3166). The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. In the classification of continents, Europe does not include the figures for Finland. Non-autonomous states are combined with the mother country. Czech Republic = Czech Republic + Former Czechoslovakia Sudan = Sudan + Former Sudan If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. --- HDI = Human Development Index Ranking according to the 2016 HDI index by country: The former Soviet Union is included in the Russia HDI category The former Czechoslovakia is included in the Czech Republic HDI category The former Yugoslavia and Serbia and Montenegro are included in the Serbia HDI categoryAgeAge refers to a person's age in whole years as at 31 December.InformationPopulation 31 DecPopulation at the end of the statistical reference period.

... confidentialFor reasons of privacy protection, cells with less than 10 cases of citizenship by municipality have been marked with three dots. Starting from 1750 Population statistics have been digitized into PDF format in the National Library's Doria service: Publications on Population structure and Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) --- Description of statistic Quality descriptions Concepts and definitionsAreaThese statistics apply the regional division of 1 January 2019 to the whole time series. Data for merged municipalities have been combined. Partial municipal mergers have not been taken into account in the years preceding the merger.NationalityCountries (ISO 3166). The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. In the classification of continents, Europe does not include the figures for Finland. Non-autonomous states are combined with the mother country. Czech Republic = Czech Republic + Former Czechoslovakia Sudan = Sudan + Former Sudan If a person has two nationalities and one of them is Finnish, he/she will be included in statistics as a Finnish national. --- HDI = Human Development Index Ranking according to the 2016 HDI index by country: The former Soviet Union is included in the Russia HDI category The former Czechoslovakia is included in the Czech Republic HDI category The former Yugoslavia and Serbia and Montenegro are included in the Serbia HDI categoryInformationPopulation 31 DecPopulation at the end of the statistical reference period.

The Questionnaire on Air Transport Statistics is aimed to collect aggregated annual data on the air transport sector for the following domains: I. Infrastructure (covering commercial airports only) (status at 31/12) II. Transport equipment (covering commercial aircrafts only) (status at 31/12) III. Enterprises, economic performance and employment (status at 31/12) IV. Accidents (annual data) - as from 2015 data on accidents are no longer collected by the questionnaire but are obtained from European Aviation Safety Agency (EASA) and disseminated under Air Transport Safety (tran_sf_avia) part of Eurobase Data are collected and disseminated at country level or at airport level for major European airports. The questionnaire is not supported by any legal acts and it is based on a gentlemen's agreement with the participating countries (Member States, Iceland, Norway, Switzerland, Turkey, FYROM and Montenegro). It is usually prefilled by Eurostat using its own sources as well as other ones (e.g. Airclaims or EASA) and sent to the countries for completion and validation. The completeness varies from country to country. Please note that information concerning data collected in the frame of the Air Transport Statistics Regulation can be found in the metadata documentation provided for this domain (Air Transport Measurement). The section on "Infrastructure" contains three tables: Number of main airports (with more than 150 000 passenger units per year) and other airports (between 15 000 and 150 000 passenger units per year) at country levelAirport infrastructures by type at airport levelAirport connections to other modes of transport at airport level. The section on "Transport Equipment" contains two tables: Commercial aircraft fleet by type of aircraft at country levelCommercial aircraft fleet by age of aircraft at country level The section on "Enterprises economic performance and employment" contains three tables: Number of aviation and airport enterprises at country levelEmployment in aviation and airport enterprises by gender at country levelEmployment in main airports by gender at airport level The section on "Accidents" (which contained two tables Number of injury accidents at country level and Number of fatalities in injury accidents at country level) has been removed from dissemination (in September 2015) and replaced by Air Transport Safety (tran_sf_avia) tables: Air accident victims in commercial air transport, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaca);Air accident victims in aerial works, by country of occurrence and country of registry of aircraft (EASA data) (tran_sf_aviaaw);Air accident victims in general aviation, by country of occurrence and country of registry of aircraft – maximum take-off mass above 2250 kg (EASA data) (tran_sf_aviagah);Air accident victims in general aviation by country of occurrence and country of registry of aircraft – maximum take-off mass under 2250 kg (EASA data) (tran_sf_aviagal). More information on air accident victims under the following link.

Commercial sales of milk and cream, Canada and provinces (in kilolitres). Data are available on a monthly basis.

Compensation of employees is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter. In particular, it also includes social contributions paid by the employer.

Compensation of employees (at current prices) is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during the accounting period. Compensation of employees consists of wages and salaries, and of employers' social contributions. The input data are obtained through official transmissions of national accounts' country data in the ESA 2010 transmission programme. The data are expressed in million national currency.

Compensation of employees (at current prices) (ESA 2010, 4.02) is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during the accounting period. Compensation of employees consists of wages and salaries, and of employers' social contributions. Seasonally and calendar adjusted data (SCA).

Compensation of employees (at current prices) is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during the accounting period. Compensation of employees consists of wages and salaries, and of employers' social contributions. The input data are obtained through official transmissions of national accounts' country data in the ESA 2010 transmission programme. The data are expressed in million national currency.

Business surveys provide a rapid means of compiling simple statistics with the results available before those of traditional statistical methods, and provide also information on areas not covered by quantitative statistics. Details provided by respondents are generally of very high quality since the questions related to subjects with which they are familiar, thus the past and future performance of their business is highly reliable. Similarly, consumers provide a very high quality information on their purchasing information and price trend. Source: DG ECFIN

Industry, Trade and Services statistics are part of Short-term statistics (STS), they give information on a wide range of economic activities according to NACE Rev.2 classification (Statistical Classification of Economic Activities in the European Community). The industrial import price indices offer information according to the CPA classification(Statistical Classification of Products by Activity in the European Economic Community). Construction indices are broken down by Classification of Types of Construction (CC). All data under this heading are index data. Percentage changes are also available for each indicator. The index data are presented in the following forms:UnadjustedCalendar adjustedSeasonally-adjusted Depending on the STS regulation, data are accessible monthly and quarterly. This heading covers the indicators listed below in four different sectors. Based on the national data, Eurostat compiles EU and euro area infra-annual economic statistics. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of prime importance for the conduct of monetary and economic policy of the euro area. These indicators are mainly released through Eurostat's website under the heading Euro-indicators. There are eight PEEIs contributed by STS and they are marked with * in the text below. INDUSTRYProduction Index*Turnover IndexProducer Prices (Domestic Output Prices index)*Import Prices Index*: Total, Euro area market, Non euro area market (euro area countries only)Labour Input Indicators: Number of Persons Employed, Hours Worked, Gross Wages and Salaries CONSTRUCTIONProduction Index*: Total of the construction sector, Building construction, Civil EngineeringLabour input indicators: Number of Persons Employed, Hours Worked, Gross Wages and SalariesConstruction costs IndexBuilding permits indicators*: Number of dwellings WHOLESALE AND RETAIL TRADEVolume of sales (deflated turnover)*Turnover (in value)Labour input indicators: Number of Persons Employed SERVICES Turnover Index*Producer prices (Ouput prices)*

Eurostat Dataset Id:ei_bsbu_q_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Eurostat Dataset Id:ei_bsco_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published:as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Eurostat Dataset Id:ei_bsco_q Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Fertilisers contain important nutrients, such as nitrogen (N) and phosphorus (P), which plants absorb from the soil for their growth. With the harvest of crops for human and livestock consumption and industrial uses, N and P is removed from the soil. Continuing agricultural production without fertilisation could lead to soil degradation and erosion. Fertilisers are therefore essential to sustain agricultural production. Fertilisers are also used to improve crop yields and soils. The use of manufactured fertilizers as a regular farming practice began in most European countries in the mid to late nineteenth century but the greatest increase in consumption in these countries occurred in the three decades following World War II. The manufacturing of fertilisers greatly enhanced crop yields and agricultural production, and aided the large increase in the world population in the 20th Century. However when the amount of fertiliser applied exceeds the plants' nutritional requirements, there is a greater risk of nutrient losses from agricultural soils into ground and surface water. The resulting higher concentration of nutrients (eutrophication) can cause serious degradation of ecosystems. With the storage and application to the land of manufactured fertilisers, Nitrogen can volatilise into the air as ammonia contributing to acidification, eutrophication and atmospheric particulate pollution, and nitrous oxides, a potent greenhouse gas contributing to climate change.  In addition fertilisers may also have adverse environmental effects resulting from their production processes. More specifically, nitrogenous fertilisers require large amounts of energy to be produced leading potentially to higher levels of greenhouse gas emissions. In a different way, phosphorus fertilisers also have an environmental impact, since the raw materials used to produce them are mined, therefore potentially leading to landscape destruction, water contamination, excessive water consumption or air pollution. This table contains data on the total use of manufactured fertilisers expressed in tonnes of N and tonnes of P received from the countries. Manufactured fertilisers are also often referred to as inorganic fertilisers or mineral fertilisers. For a definition see 3.4.

El costo de la mano de obra es el costo que corre a cargo del empleador que ocupa a la mano de obra durante un período de referencia especificado. El concepto estadístico del costo de la mano de obra abarca la remuneración por el trabajo cumplido, la remuneración por tiempo no trabajado, las primas y gratificaciones, los gastos en concepto de comidas, bebidas y otros pagos en especie, los costos de vivienda de los trabajadores a cargo de los empleadores, los gastos de seguridad social de los empleadores, los gastos de formación profesional a cargo de los empleadores, el costo de los servicios de bienestar y los costos no clasificados en otros grupos, como los gastos de transporte de los trabajadores, el suministro de ropa de trabajo y los gastos de contratación, así como los impuestos considerados como costos de mano de obra. Se trata de una serie armonizada: (1) los datos referentes a costos semanales, mensuales o anuales fueron convertidos a costos horarios en moneda local utilizando datos sobre las horas de trabajo (donde estaban disponibles); y luego (2) los datos se convierten a una moneda común, el dólar constante en paridad de poder adquisitivo 2017, utilizando la tasa de cambio con el dólar US y la tasa de paridad de poder adquisitivo del 2017. Esta serie basada en una moneda común permite de realizar comparaciones internacionales teniendo en cuenta las diferencias de precio relativas entre países. Los datos están desagregados por actividad económica, utilizando la versión más reciente disponible cada año de la Clasificación Industrial Internacional Uniforme de todas las actividades económicas (CIIU). Para obtener más información, consulte la página de conceptos y definiciones.

Crop output is valued at basic prices. The basic price is defined as the price received by the producer, after deduction of all taxes on products but including all subsidies on products. The concept of output comprises sales, changes in stocks, and crop products used as animal feedingstuffs, for processing and own final use by the producers.

Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.

Crop statistics refer to the following types of annual data: area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop.The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in: 17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.

Crop statistics refer to the following types of annual data:area under cultivation, harvested production, yield,  humidity and main area for cereals and for other main field crops (mainly dried pulses, root crops, fodder and industrial crops);harvested area, harvested production and main area for vegetables ;production area, harvested production and main area for permanent crop. The data are provided at national level. For some products regional figures (NUTS 1 or 2) are available too. The areas  are expressed in 1 000 hectares,  the harvested quantities in 1 000 tonnes and the yields in t/ha. The production and yield data are available in EU standard humidity (apro_cpsh) and in national humidity (apro_cpnh). The information concerns more than 100 crop products. The earliest data are available from 1955 for cereals and from the early 1960's for fruits and vegetables. However, most Member States have started to send in data in the 1970's and 1980's. The statistical system has progressively improved and enlarged. The current Regulation (EC) No 543/2009 entered into force in January 2010. The annex was updated in 2015 through a Commission Delegated Regulation (EU) No 2015/1557. At present Eurostat receives and publishes harmonised statistical data from 28 Member States, form the EFTA countries and from the candidate and potential candidate countries broken down in:17 categories and subcategories for cereals;29 categories and  subcategories for other main crops (mainly dry pulses and protein crops, root crops industrial crops and plants harvested green from arable land);40 categories and subcategories for vegetables;41 categories and subcategories for permanent crops;18 categories and subcategories for the Utilised Agricultural Area (UAA). For the full list of crops, please consult Annex. Some additional crops and transmission deadlines are covered by an ESS agreement on annual crop statistics. The main data sources are administrative records, surveys and expert estimates. National Statistical Institutes or Ministries of Agriculture are responsible for the national data collection in accordance with the Regulations and agreements in force. Eurostat is responsible for drawing the EU aggregations. Regional metadata Please note that for paragraphs where no metadata for regional data has been specified the regional metadata is identical to the metadata for the national data.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

Data on the production of the crushing of seed, oil and meal.

Statistics on culture cover many aspects of economic and social life. According to the Europe 2020 strategy, the role of culture is crucial for achieving the goal of a "smart, sustainable and inclusive" growth. Employment in cultural sector statistics aim at investigating on the dimension of the contribution of cultural employment to the overall employment. Cultural employment statistics are derived from data on employment based on the results of the European Labour Force Survey (see EU-LFS metadata) that is the main source of information about the situation and trends on the labour market in the European Union. The final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012, in particular pp. 129-226) deals with the methodology applied to cultural statistics, including the scope of the 'cultural economic activities' and 'cultural occupations' based on two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the employer’s main activity, andthe ISCO classification(‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow to characterize cultural employment by different variables such as gender, age, employment status, working time, educational attainment, permanency of jobs by cross-tabulating ISCO and NACE cultural codes as defined in the ESS-Net Culture Report 2012 (Annex 3 – Table 26 and Annex 4 – Table 27).

Current taxes on income, wealth, etc. (ESA 2010 code D.5) cover all compulsory, unrequited payments, in cash or in kind, levied periodically by general government and by the rest of the world on the income and wealth of institutional units, and some periodic taxes which are assessed neither on that income nor that wealth. In ESA 2010, current taxes on income, wealth, etc. are divided into taxes on income and other current taxes.

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. Data cited at: https://www.ncei.noaa.gov/data/global-summary-of-the-day/archive/

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.

This dataset contains three earnings-dispersion measures - ratio of 9th-to-1st, 9th-to-5th and 5th-to-1st - where ninth, fifth (or median) and first deciles are upper-earnings decile limits, unless otherwise indicated, of gross earnings of full-time dependent employees. The dataset also includes series on: the incidence of low-paid workers defined as the share of full-time workers earning less than two-thirds of gross median earnings of all full-time workers; the incidence of high of high-paid workers defined as the share of full-time workers earning more than one-and-half time gross median earnings of all full-time workers; gender wage gap unadjusted and defined as the difference between median wages of men and women relative to the median wages of men.

Notes: Figures 019 are estimates. The NATO Europe and NATO Total aggregates from 2017 include Montenegro, which became an Ally on 5 June 2017

This dataset traces net changes in terms of volume in the growing stock of standing wood on forest land. Forest depletion and growth describe balances or imbalances in different types of forests. The intensity of use of forest resources reflects various forest management methods and their sustainability. These data should be read in connection with other indicators, in particular land use changes and forest quality (species diversity, forest degradation), and be complemented with data on forest management practices and protection measures. Please bear in mind that definitions and estimation methods vary for some countries.

Con el objetivo de promover la comparabilidad internacional, las estadísticas presentadas en ILOSTAT se basan en definiciones internacionales estándar siempre que sea posible y pueden diferir de las cifras nacionales oficiales. Esta serie se basa en las definiciones de la 13.ª CIET. Para la comparabilidad de series temporales, incluye países que han implementado las normas de la 19.ª CIET, cuyos datos también están disponibles en la base de datos Work Statistics -- 19.ª CIET (WORK). Las personas en desocupación son todas aquellas que se hallan: a) sin empleo durante el período de referencia, es decir, que no tienen un puesto de trabajo salariado ni independiente; b) corrientemente disponibles para trabajar, es decir, disponibles para trabajar en un puesto de trabajo salariado o independiente durante el período de referencia; y c) en busca de un puesto de trabajo, es decir, que tomaron medidas concretas para buscar un puesto de trabajo salariado o independiente en un período reciente especificado. Para obtener más información, consulte la descripción de la base de datos Estadísticas del mercado laboral (LFS y STLFS).

Con el objetivo de promover la comparabilidad internacional, las estadísticas presentadas en ILOSTAT se basan en definiciones internacionales estándar siempre que sea posible y pueden diferir de las cifras nacionales oficiales. Esta serie se basa en las definiciones de la 13.ª CIET. Para la comparabilidad de series temporales, incluye países que han implementado las normas de la 19.ª CIET, cuyos datos también están disponibles en la base de datos Work Statistics -- 19.ª CIET (WORK). Las personas en desocupación son todas aquellas que se hallan: a) sin empleo durante el período de referencia, es decir, que no tienen un puesto de trabajo salariado ni independiente; b) corrientemente disponibles para trabajar, es decir, disponibles para trabajar en un puesto de trabajo salariado o independiente durante el período de referencia; y c) en busca de un puesto de trabajo, es decir, que tomaron medidas concretas para buscar un puesto de trabajo salariado o independiente en un período reciente especificado. Para obtener más información, consulte la descripción de la base de datos Estadísticas del mercado laboral (LFS y STLFS).

Annual final consumption expenditure for the household sector excluding sales tax; provincial sales taxes, and; Goods and Services tax, by province and territory.

Annual final consumption expenditure for the household sector, in current and constant 2007 prices, by province and territory.

The disposable income of private households is the balance of primary income (operating surplus/mixed income plus compensation of employees plus property income received minus property income paid) and the redistribution of income in cash. These transactions comprise social contributions paid, social benefits in cash received, current taxes on income and wealth paid, as well as other current transfers. Disposable income does not include social transfers in kind coming from public administrations or non-profit institutions serving households.

Monthly itinerant movements (domestic, transborder and international) by type of operation (level I-III and foreign air carriers, level IV-VI, other commercial, private, government civil and government military), for airports with NAV CANADA flight service stations. Domestic and international itinerant movements, by type of operation, airports with NAV CANADA flight service stations, monthly

Monthly itinerant movements (domestic, transborder and international) by type of operation (level I-III and foreign air carriers, level IV-VI, other commercial, private, government civil and government military) for airports with NAV CANADA towers.   Domestic and international Itinerant movements, by type of operation, airports with NAV CANADA towers, monthly

This table includes the areas, productions and humidity of field peas, broad and field beans, sweet lupins, dry beans, other dry peas, lentils, chickling vetch, chick peas, vetches and other protein crops sown in pure crops or as mixtures with cereals harvested dry for grain. This indicator uses the concepts of "area under cultivation", "harvested production" and "humidity". 1) The "area under cultivation" corresponds: • before the harvest, to the sown area; • after the harvest, to the sown area excluding the non-harvested area (e.g. area ruined by natural disasters, area not harvested for economic reasons, etc.) 2) The "harvested production" corresponds to the production for which harvesting started in year N, even thought harvesting may finish in year N+1. So N is the reference year for data published by Eurostat. 3) In order to facilitate the comparisons of production between the Members States, the publication of "humidity" for each country is needed. Only the EU-aggregate for the production is published with a standard EU humidity.

The economic accounts for forestry and logging are based on national accounts, but are collected with greater detail. Current prices means prices of that particular year. Annual inflation must yet be taken into account if one wishes to compare the values of different years. Basic prices means the price received by the producer after deduction of all taxes on products, but including all subsidies on products. Gross value added is the value of the output less the value of intermediate consumption. Fixed capital relates to longer-lived assets (e.g. equipment or buildings) that are either acquired (this is gross fixed capital formation) or consumed (this is fixed capital consumption, the annual reduction in the value of fixed assets). The definition of the activity of forestry and logging is based on Division 02 of NACE Rev. 2.

Eurostat's database covers 1) Production and trade in roundwood and wood products, including primary and secondary products 2) Economic data on forestry and logging, including employment data 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging.  The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU).  Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'.  Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

The OECD Economic Outlook analyzes the major economic trends over the coming 2 years. It provides in-depth coverage of the main economic issues and the policy measures required to foster growth in each member country. Forthcoming developments in major non-OECD economies are also evaluated in detail. Each edition of the Outlook provides a unique resource to keep abreast of world economic developments. The OECD Economic Outlook database is a comprehensive and consistent macroeconomic database of the OECD economies, covering expenditures, foreign trade, output, labor markets, interest and exchange rates, balance of payments and government debt. For the non-OECD regions, foreign trade and current account series are available. Variables are defined in such a way that they are as homogenous as possible for the countries covered. Breaks in underlying series are corrected as far as possible. Sources for the historical data are publications of national statistical agencies and OECD data bases such as Quarterly National Accounts, Annual National Accounts, Labor Force Statistics and Main Economic Indicators. The cut-off date for information used in the compilation of the projections was June 1, 2023. The aggregation of world trade takes into account the projections made for the main non-OECD economies. Thus, besides OECD and the OECD euro area, the following regions are available: Dynamic Asian Economies (Chinese Taipei, Hong Kong, Malaysia, the Philippines, Singapore, Thailand, Vietnam); Oil Producers (Algeria, Angola, Azerbaijan Bahrain, Brunei, Chad, Rep. of Congo, Ecuador, Equatorial Guinea, Gabon, Iran, Iraq, Kazakhstan, Kuwait, Libya, Nigeria, Oman, Qatar, Saudi Arabia, Sudan, Timor-Leste , Trinidad and Tobago, Turkmenistan, United Arab Emirates, Yemen, Venezuela); with the remaining countries in a residual 'Rest of the World' group.

This indicator presents internationally comparable data regarding the labour force status and the educational attainment level by the National Educational Attainment Categories (NEAC) as reported by the labour force survey (LFS) and published in OECD Education at a Glance 2017. For trend data, the Education at a Glance Database includes data from 1981 to 2016 (or years with available data).

 This indicator measures the proportion of earnings that are lost to either higher taxes or lower benefit entitlements when a jobless person takes up employment. It is commonly referred to as "Participation Tax Rate (PTR)" as it measures financial disincentives to participate in the labour market.

Related data is available here: https://knoema.com/PTRCCSA/ptrs-for-parents-claiming-guaranteed-minimum-income-gmi-benefits-and-using-childcare-services This indicator measures the proportion of earnings that are lost to either higher taxes, lower benefits or childcare costs when a parent with young children takes up full-time employment and requires use of centre-based childcare services.

Total number of long-term emigrantsleaving from the reporting country during the reference year

This domain comprises series of long-term international immigration and emigration during the reference year. Immigrants and emigrants are disaggregated by age group, sex, citizenship or country of previous/next residence. Since 2008 migration data by single age and immigration data by country of birth are also available. The data sources are administrative records or national surveys. For some datasets statistical estimation methods are applied. Data are presented country by country and for groups of countries. The completeness of the tables depends largely on the availability of data from the relevant national statistical institutes. For details on data sources used for compilation of statistics on immigration and emigration and for more country-specific data descriptions see Annexes attached.

Eurostat's annual collections of statistics on international migration flows are structured as follows:  

The annual Eurostat's collections on statistics on international migration flows are structured as follows:   Data Collection Info & Legislation NOWCAST Annual data collection on provisional monthly data on live births and deaths covering at least six months of the reference year (Article 4.3 of the Commission implementing regulation (EU) No 205/2014) and provisional monthly data on migrants covering at least six months of the reference year on voluntary basis DEMOBAL Demographic balance Annual data collection on provisional data on population, total live births and total deaths at national level (Article 4.1 of the Commission implementing regulation (EU) No 205/2014) and provisional data on total migrants at national level on voluntary basis UNIDEMO Unified Demographic The most extended annual collection on demography and migration, collecting data at national and regional level for population, births, deaths, immigrants,  emigrants, marriages and divorces by a large number of breakdowns. (Art. 3 of the Regulation (EU) No 1260/2013 and Art. 3 of the Regulation (EC) No 862/2007)   The annual demography data collections aim at collecting from the National Statistical Institutes both mandatory data and voluntary data. The mandatory data are those defined by the legislation listed on "6.1. Institutional Mandate - legal acts and other agreements".   The migration data collected on voluntary basis depend on the availability and on the quality of information available in the National Statistical Institutes.   For more specific information on mandatory/voluntary data collection see 6.1. Institutional Mandate - legal acts and other agreements.   The following data on migrants are collected under Unified Demographic data collection:   Immigrants by age, sex and by:                  a.   country of citizenship                  b.   country of birth                  c.   country of previous residenceImmigrants by country of citizenship and country of birthEmigrants by age, sex and by:                   a.   country of citizenship                   b.   country of birth                   c.   country of next residence 

This domain comprises series of long-term international immigration and emigration during the reference year. Immigrants and emigrants are disaggregated by age group, sex, citizenship or country of previous/next residence. Since 2008 migration data by single age and immigration data by country of birth are also available. The data sources are administrative records or national surveys. For some datasets statistical estimation methods are applied. Data are presented country by country and for groups of countries. The completeness of the tables depends largely on the availability of data from the relevant national statistical institutes. For details on data sources used for compilation of statistics on immigration and emigration and for more country-specific data descriptions see Annexes attached.

Greenhouse Gas (GHG) emissions from burning crop residues consist of methane (CH4) and nitrous oxide (N2O) gases produced by the combustion of a percentage of crop residues burnt on-site. The mass of fuel available for burning should be estimated taking into account the fractions removed before burning due to animal consumption, decay in the field, and use in other sectors (e.g., biofuel, domestic livestock feed, building materials, etc.). FAOSTAT emission estimates are computed at Tier 1 following the IPCC 2006 Guidelines for National GHG Inventories (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided by country, reguions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed both as Gg CH4, Gg N2O, Gg CO2eq and CO2eq from CH4 and N2O, by crop (maize, rice, sugarcane and wheat) and by aggregates. Implied emission factors for N2O and CH4 as well activity data (biomass burned) are also provided.

Greenhouse gas (GHG) emissions from crop residues consist of direct and indirect nitrous oxide (N2O) emissions from nitrogen (N) in crop residues and forage/pasture renewal left on agricultural fields by farmers. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the deposition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories, Vol. 4, Ch. 2 and 11(http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq, by crop and N content in residues.

Greenhouse gas (GHG) emissions from synthetic fertilizers consist of nitrous oxide gas from synthetic nitrogen additions to managed soils. Specifically, N2O is produced by microbial processes of nitrification and de-nitrification taking place on the addition site (direct emissions), and after volatilization/re-deposition and leaching processes (indirect emissions). The FAOSTAT emissions database is computed following Tier 1 IPCC 2006 Guidelines for National GHG Inventories vol. 4, ch. 11 (http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html). GHG emissions are provided as direct, indirect and total by country, regions and special groups, with global coverage, relative to the period 1961-present (with annual updates) and with projections for 2030 and 2050, expressed as Gg N2O and Gg CO2eq. Implied emission factor for N2O and activity data (consumption) are also provided.

The FAOSTAT domain Organic soils consist of nitrous oxide (N2O) and carbon dioxide (CO2) emissions associated with the drainage of organic soils ? using histosols as proxy ? for agriculture. Data are computed geospatially, using the Tier 1 method of the 2006 IPCC Guidelines for National greenhouse gas Inventories (IPCC, 2006). Estimates are available by country and with global coverage, in complete time series for the period 1990?2019. The database is updated annually. The FAOSTAT domain Organic soils disseminates information by country on: activity data (in hectares of organic soils drained for agriculture); and greenhouse gas (GHG) emissions (in kilotonnes of N2O and CO2). Drainage and associated emissions are assessed separately for IPCC land use categories cropland and grassland, corresponding to FAO land use categories ??cropland?? and ??permanent meadows and pastures.?? Data are available for all countries and territories, for standard FAOSTAT regional aggregations, and for Annex I and non-Annex I country groups. This FAOSTAT domain also disseminates the activity data and emissions data reported by countries to the United Nations Framework Convention on Climate Change (UNFCCC), under ?Cultivation of organic soils? for the N2O component and categories ?Cropland drained organic soils? and ?Grassland drained organic soils? for the CO2. Activity data are sourced from the most recently available GHG National Inventories (NGHGI) or from National Communications. Emission data are sourced directly from the UNFCCC data portal or from Biennial Update Reports (BURs). UNFCCC data are disseminated in FAOSTAT with permission, formalized via a FAO-UNFCCC Memorandum of Understanding.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE)  at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors under Annexes section. Within the sectoral approach, a second classification was created , named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions under Annexes section. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. . For more details, see definition of high-tech products under Annexes section. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents under Annexes section. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

The Human Resources in Science and Technology (HRST) domain provides data on stocks and flows (where flows in turn are divided into job-to-job mobility and education inflows). Stocks and flows are the main statistics for HRST. Their methodologies interlink and are therefore presented together in one single metadata-file. This metadata-file is duplicated in the structure of Eurostat's online database, while statistics for stocks and flows are found in separate folders. Several breakdowns are available for stocks and flows indicators: sex, age, region, sector of economic activity, occupation, educational attainment, fields of education, although not all combinations are possible. The data on stocks and job-to-job mobility are obtained from the European Union Labour Force Survey (EU LFS). The National Statistical Institutes are responsible for conducting the surveys and forwarding the results to Eurostat. The data on education inflows are obtained from Eurostat's Education database and in turn obtained via the UNESCO/OECD/Eurostat questionnaire on education. The National Statistical Institutes are responsible for conducting the surveys, compiling the results and forwarding the results to Eurostat. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '18.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metadata. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The section 'LFS series - detailed quarterly survey results' reports detailed quarterly results going beyond the EU-LFS main aggregates, which have a separate data domain and some methodological differences. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The annual Business demography data collection covers variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not considered. The data are drawn from business registers, although some countries improve the availability of data on employment and turnover by integrating other sources. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. Currently, business demography delivers key information for policy decision-making and for the indicators to support the Europe 2020 strategy. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The complete list of the basic variables, delivered from the data providers (National Statistical Institutes) and the derived indicators, calculated by Eurostat, is attached in the Annexes of this document (see Business demography indicators).  Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises. The methodology laid down in the Eurostat-OECD Manual on Business Demography Statistics  is followed closely by most of the countries (see Country specific notes in the Annexes).

Eurostat Dataset Id:bd_9fh_sz_cl_r2 The data category covers a group of variables which explain the characteristics and demography of the business population. The methodology allows for the production of data on enterprise births (and deaths), that is, enterprise creations (cessations) that amount to the creation (dissolution) of a combination of production factors and where no other enterprises are involved. In other words, enterprises created or closed solely as a result of e.g. restructuring, merger or break-up are not included in this data. Until 2010 reference year the harmonised data collection is carried out to satisfy the requirements for the Structural Indicators, used for monitoring progress of the Lisbon process, regarding business births, deaths and survival. It also provides key data for the joint OECD-Eurostat "Entrepreneurship Indicators Programme". In summary, the collected indicators are as follows:Population of active enterprisesNumber of enterprise birthsNumber of enterprise survivals up to five yearsNumber of enterprise deathsRelated variables on employmentDerived indicators such as birth rates, death rates, survival rates and employment sharesAn additional set of indicators on high-growth enterprises and 'gazelles' (high-growth enterprises that are up to five years old) The data are drawn from business registers, although some individual countries improve the availability or freshness of data on employment and turnover by integrating other sources. Geographically EU Member States and EFTA countries are covered. In practice not all Member States have participated in the first harmonised data collection exercises.

Regional accounts are a regional specification of the national accounts and therefore based on the same concepts and definitions as national accounts (see domain nama10). The main specific regional issues are addressed in chapter 13 of ESA2010, but not practically specified. For practical rules and recommendations on sources and methods see the publication "Manual on regional accounts methods": http://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-GQ-13-001 . Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It can be defined in three ways: 1. Output approach GDP is the sum of gross value added of the various institutional sectors or the various industries plus taxes and less subsidies on products (which are not allocated to sectors and industries). It is also the balancing item in the total economy production account. 2. Expenditure approach GDP is the sum of final uses of goods and services by resident institutional units (final consumption expenditure and gross capital formation), plus exports and minus imports of goods and services. At regional level the expenditure approach cannot be used in the EU, because there is no data on regional exports and imports.  3. Income approach GDP is the sum of uses in the total economy generation of income account: compensation of employees plus gross operating surplus and mixed income plus taxes on products less subsidies plus consumption of fixed capital. The different measures for the regional GDP are absolute figures in € and Purchasing Power Standards (PPS), figures per inhabitant and relative data compared to the EU28 average.

The 'LFS main indicators' section presents a selection of the main statistics on the labour market. They encompass indicators of activity employment and unemployment. Those indicators are based on the results of the European Labour Force Survey (EU-LFS), in few cases integrated with data sources like national accounts employment or registered unemployment. As a result of the application of adjustments, corrections and reconciliation of EU Labour Force Survey (EU-LFS), 'LFS main indicators' is the most complete and reliable collection of employment and unemployment data available in the sub-domain ' Employment and unemployment'. The EU-LFS data used for 'LFS main indicators' are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator.  The most common adjustments cover: - correction of the main breaks in the LFS series - estimation of the missing values, (i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU Labour Force Survey data with reference to the available quarter(s)) - reconciliations of the LFS data with other sources, mainly National Accounts (for Employment growth and activity branches) and national statistics on monthly unemployment (for Harmonised unemployment series). - for a number of indicators (employment, activity, unemployment, supplementary indicators) seasonally adjusted data are available Those adjustments may produce some differences between data published under 'LFS main indicators' and 'LFS series - Detailed survey results', particularly for back data. For the most recent years these two series converge, due to the implementation of a continuous quarterly survey and the improved quality of the data. This page focuses on the particularities of 'LFS main indicators' in general. There are special pages for indicators 'employment growth', 'population in jobless households', 'average exit age of labour market' and 'education indicators: life-long learning, early school leavers and youth education attainment level. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Number of employees and average weekly earnings (including overtime) for all employees by provinces, territories and North American Industry Classification System (NAICS), last 5 months.

National accounts are a coherent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. The data presented in this collection are the results of a pilot exercise on the sharing selected main GDP aggregates, population and employment data collected by different international organisations. It wasconducted by the Task Force in International Data Collection (TFIDC) which was established by the  Inter-Agency Group on Economic and Financial Statistics (IAG).  The goal of this pilot is to develop a set of commonly shared principles and working arrangements for data cooperation that could be implemented by the international agencies. The data sets are an experimental exercise to present national accounts data form various countries across the globe in one coherent folder, but users should be aware that these data are collected and validated by different organisations and not fully harmonised from a methodological point of view.  The domain consists of the following collections:

.. - data not available Source: UNECE Statistical Database, compiled from national and international (EUROSTAT, OECD, CIS) official sources. Definition:Employment, as referred to the System of National Accounts 1993, covers all persons - both employees and self-employed - engaged in a productive activity that falls within the production boundary of the system. It includes both the residents and the non-residents who work for resident producer units. In case of deviation, the actual definition is provided in the country footnote. Employment data provided in this table generally differ from employment data provided in Gender Statistics, which cover only residents. General note: The UNECE secretariat presents time series ready for immediate analysis. When appropriate, source segments with methodological differences have been linked or rescaled to build long consistent time series. As a result, absolute figures presented in this table may differ from those published by National Statistical Offices and should be taken with caution. However, the derived growth rates correspond to the originally reported series. Regional aggregates are computed by UNECE secretariat. For more details see the composition of regions note. Country: Albania Employment: end of period. Country: Armenia Employment: LFS - based. Country: Azerbaijan Geographical coverage: excludes Nagorno-Karabakh. Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS - based. Country: Bosnia and Herzegovina Employment:LFS - based. Country: Croatia Employment: LFS-based. Country: France Geographical Coverage: Data for France include the overseas departments (DOM). Country: Georgia Geographical Coverage: from 1993 excludes Abkhazia and South Ossetia (Tshinvali). Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: Register-based. Country: Israel Employment: LFS-based. Designation and data provided by Israel. The position of the United Nations on the question of Jerusalem is contained in General Assembly resolution 181 (II) and subsequent resolutions of the General Assembly and the Security Council concerning this question. Data include East Jerusalem. Country: Kazakhstan Employment: LFS-based. Country: Lithuania Employment: LFS-based. Country: Moldova, Republic of Geographical Coverage: from 1993 excludes Transnistria. Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS-based. Country: Romania Employment: LFS-based. For the years 1990-2001 UNECE estimates. Country: Russian Federation Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS-based. Data for Russian Federation was updated only until the end of 2013. Country: Serbia Geographical Coverage: from 1999, excludes Kosovo and Metohija. Employment: LFS - based. Country: The former Yugoslav Republic of Macedonia Employment: LFS-based. Country: Turkey Employment: Annual breakdowns by activity and quarterly data are LFS-based. Country: Ukraine Employment: LFS-based. Geographical coverage: from 2014, does not includes all territory of Ukraine.

.. - data not available Source: UNECE Statistical Database, compiled from national and international (EUROSTAT, OECD, CIS) official sources. Definition:Employment, as referred to the System of National Accounts 1993, covers all persons - both employees and self-employed - engaged in a productive activity that falls within the production boundary of the system. It includes both the residents and the non-residents who work for resident producer units. In case of deviation, the actual definition is provided in the country footnote. Employment data provided in this table generally differ from employment data provided in Gender Statistics, which cover only residents. General note: The UNECE secretariat presents time series ready for immediate analysis. When appropriate, source segments with methodological differences have been linked or rescaled to build long consistent time series. As a result, absolute figures presented in this table may differ from those published by National Statistical Offices and should be taken with caution. However, the derived growth rates correspond to the originally reported series. Regional aggregates are computed by UNECE secretariat. For more details see the composition of regions note.Country: Albania Employment: end of period.Country: Armenia Employment: LFS - based.Country: Azerbaijan Geographical coverage: excludes Nagorno-Karabakh. Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS - based.Country: Bosnia and Herzegovina Employment:LFS - based.Country: Croatia Employment: LFS-based.Country: France Geographical Coverage: Data for France include the overseas departments (DOM).Country: Georgia Geographical Coverage: from 1993 excludes Abkhazia and South Ossetia (Tshinvali). Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: Register-based.Country: Iceland Employment: LFS - based.Country: Israel Employment: LFS-based. Designation and data provided by Israel. The position of the United Nations on the question of Jerusalem is contained in General Assembly resolution 181 (II) and subsequent resolutions of the General Assembly and the Security Council concerning this question. Data include East Jerusalem.Country: Kazakhstan Employment: LFS-based.Country: Moldova, Republic of Geographical Coverage: from 1993 excludes Transnistria. Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS-based.Country: Romania Employment: LFS-based. For the years 1990-2001 UNECE estimates.Country: Russian Federation Population: Number of population for the latest year refers to the beginning of the year, not to an annual average as usually. Employment: LFS-based. Data for Russian Federation was updated only until the end of 2013.Country: Serbia Geographical Coverage: from 1999, excludes Kosovo and Metohija. Employment: LFS - based.Country: The former Yugoslav Republic of Macedonia Employment: LFS-based.Country: Turkey Employment: Annual breakdowns by activity and quarterly data are LFS-based.Country: Ukraine Employment: LFS-based. Geographical coverage: from 2014, does not includes all territory of Ukraine.

The 'LFS main indicators' section presents a selection of the main statistics on the labour market. They encompass indicators of activity employment and unemployment. Those indicators are based on the results of the European Labour Force Survey (EU-LFS), in few cases integrated with data sources like national accounts employment or registered unemployment. As a result of the application of adjustments, corrections and reconciliation of EU Labour Force Survey (EU-LFS), 'LFS main indicators' is the most complete and reliable collection of employment and unemployment data available in the sub-domain ' Employment and unemployment'. The EU-LFS data used for 'LFS main indicators' are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator.  The most common adjustments cover: - correction of the main breaks in the LFS series - estimation of the missing values, (i.e. in case of missing quarters, annual results and EU aggregates are estimated using adjusted quarterly national labour force survey data or interpolations of the EU Labour Force Survey data with reference to the available quarter(s)) - reconciliations of the LFS data with other sources, mainly National Accounts (for Employment growth and activity branches) and national statistics on monthly unemployment (for Harmonised unemployment series). - for a number of indicators (employment, activity, unemployment, supplementary indicators) seasonally adjusted data are available Those adjustments may produce some differences between data published under 'LFS main indicators' and 'LFS series - Detailed survey results', particularly for back data. For the most recent years these two series converge, due to the implementation of a continuous quarterly survey and the improved quality of the data. This page focuses on the particularities of 'LFS main indicators' in general. There are special pages for indicators 'employment growth', 'population in jobless households', 'average exit age of labour market' and 'education indicators: life-long learning, early school leavers and youth education attainment level. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

Source: UNECE Statistical Database, compiled from national and international (Eurostat) official sources. Definition: The employed are all the residents above a specified age who, during a specified brief period, either one week or one day, were in the following categories: (a) paid employment: (a1) at work: persons who, during the reference period, performed some work for wage or salary, in cash or in kind; (a2) with a job but not at work: persons who, having already worked in their present job, were temporarily not at work during the reference period and had a formal attachment to their job; (b) self-employment: (b1) at work: persons who, during the reference period, performed some work for profit or family gain, in cash or in kind; (b2) with an enterprise but not at work: persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who were temporarily not at work during the reference period for any specific reason. For additional information, see the International Conference of Labour Statisticians (ICLS). Part-time/full-time: A part-time worker is an employed person whose normal hours of work are less than those of comparable full-time workers. In most countries, the distinction between part-time and full-time work is based on self-declaration. In a few countries, work is defined as part-time when the hours usually worked are below a fixed threshold. Data for EU-27, Croatia, Iceland, Norway, the Former Yugoslav Republic of Macedonia and Turkey from the year 2008 corresponds to the NACE rev 2, before 2008 data is according to the NACE rev1.1. General note: Data come from the Labour Force Survey (LFS) unless otherwise specified. Data from the LFS and from population censuses normally comply with the definition above. .. - data not available Country: Albania 2007-2012: Part-time worker refers to an employed person whose usual hours of work are less than 35 hours/week. Country: Albania 2013-2015: Distinction between part-time and full-time workers is based on worker self-identification. Country: Armenia Break in methodlogy (2008): 2007 data refer to population aged 16-75. Since 2008 data refer to population aged 15-75. Break in methodlogy (2014): From 2007 to 2013 data are based on the Integrated Survey of the Household Living Standards. Since 2014 data are based on the Labour Force Survey. Country: Belarus 2014: changes in methodology Country: France Since 2014 data include also the French overseas departments (Guadeloupe, Martinique, Guyane, La Reunion) with the exception of Mayotte. Country: Georgia Territorial change (2002 onward): Data do not cover Abkhazia AR and Tskhinvali Region Country: Israel Break in methodlogy (2000): In 1998: 1) Changes in the weighting method; 2) Transition to the 1995 Population Census estimates; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Break in methodlogy (2001): Changes in the weighting method. See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_f1_comparison-mimi.f Country: Israel Break in methodlogy (2009): 1) Update of the definition of the civilian labour force characteristics; 2) Transition to the 2008 Population Census estimates. See explanations: http://www.cbs.gov.il/publications11/1460/pdf/intro05_e.pdf Country: Israel Break in methodlogy (2012): 1) Transitiom from a quarterly to a monthly LFS; 2) Changes in the definitions of labour force characteristics (including compulsory and permanent military service into labour force). See explanations: http://www.cbs.gov.il/publications/labour_survey04/labour_f--orce_survey/answer_question_e_2012.pdf Country: Israel Change in definition (1980): Data refers to population 14+. Country: Israel Change in definition (2005): 1) Update of the definitions of labour force characteristics; 2) Changes in the Standard Industrial Classification of Economic Activities; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Russian Federation Change in definition (1990 - 2013): Data present the population aged 15-72 years. Underemployment - the person who work less than 30 hours in the surveyed week Country: Russian Federation Reference period (1990): Data refer to 1992 Country: Russian Federation Territorial change (1990 - 2006): Data do not include the Chechen Republic Country: Serbia Data do not cover Kosovo and Metohija. Country: Ukraine From 2014 data cover the territories under the government control. Country: Ukraine Data do not cover the persons who are still living in the area of Chernobyl contaminated with radioactive material. Data do not cover the persons who are living in institutions and those who are working in the army. Data refer to the population aged 15-70.

Source: UNECE Statistical Database, compiled from national and international (Eurostat and ILO) official sources. Definition: The employed are all the persons above a specified age who, during a specified brief period, either one week or one day, were in the following categories: (a) paid employment: (a1) at work: persons who, during the reference period, performed some work for wage or salary, in cash or in kind; (a2) with a job but not at work: persons who, having already worked in their present job, were temporarily not at work during the reference period and had a formal attachment to their job; (b) self-employment: (b1) at work: persons who, during the reference period, performed some work for profit or family gain, in cash or in kind; (b2) with an enterprise but not at work: persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who were temporarily not at work during the reference period for any specific reason. For additional information, see the International Conference of Labour Statisticians (ICLS). The occupation groups correspond to first-level categories in the 2008 version of the International Standard Classification of Occupations (ISCO-08). For the EU and EFTA member-states the year of transition to ISCO-08 is 2011, for other countries please see Country footnotes. The level of education is the highest level successfully completed in the educational system of the country where the education is received. The levels are defined with reference to the International Standard Classifications of Education ISCED 1997 and ISCED 2011. For the EU and EFTA member-states the levels of education are classified according to ISCED 2011 from 2014. For other countries please see Country footnotes. The transition from ISCO-88 to ISCO-08 and from ISCED 1997 to ISCED 2011 could entail a break in time series. General note: Data come from the Labour Force Survey (LFS) unless otherwise specified. Data from the LFS and from population censuses normally comply with the definition above. .. - data not available Country: Armenia Data for 2001 are from Population Census. Since 2014 data are based on the Labour Force Survey. Country: Azerbaijan Data compiled according to ISCO-08. Country: Belarus Break in methodlogy (2000): Data refer to 1999 Population Census. Measurement: Employment (thousands) , Country: Belarus Data compiled according to ISCO-88 Measurement: Percent of corresponding total of both sexes , Country: Belarus Data compiled according to ISCO-88 Measurement: Employment (thousands) , Country: Belarus Parts by education level may not add up due to the persons who did not indicate their levels of education Measurement: Percent of corresponding total of both sexes , Country: Belarus Parts by education level may not add up due to the persons who did not indicate their levels of education Country: Bosnia and Herzegovina From 2006 to 2014 data compiled using ISCED 97, from 2015 using ISCED 11. Country: Canada Change in definition (1990 onwards): Data are annual averages. Cells with 0 are estimates with less than 1,500 employed. Country: Canada Data do not cover the three northern territories (Yukon, Northwest and Nunavuk ) Country: Israel Break in methodlogy (2000): In 1998: 1) Changes in the weighting method; 2) Transition to the 1995 Population Census estimates; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Break in methodlogy (2001): Changes in the weighting method. See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_f1_comparison-mimi.f Country: Israel Break in methodlogy (2009): 1) Update of the definition of the civilian labour force characteristics; 2) Transition to the 2008 Population Census estimates. See explanations: http://www.cbs.gov.il/publications11/1460/pdf/intro05_e.pdf Country: Israel Break in methodlogy (2012):1) Transitiom from a quarterly to a monthly LFS; 2) Changes in the definitions of labour force characteristics (including compulsory and permanent military service into labour force). See explanations: http://www.cbs.gov.il/publications/labour_survey04/labour_f--orce_survey/answer_question_e_2012.pdf Country: Israel Change in definition (2000 - 2012): Changes in the questionnaire (Highest Diploma Received, Discouraged Workers, Employees hired through employment agencies or employment contractors); See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_e_changes.pdf Country: Israel Change in definition (2013): Changes in the Standard Classification of Occupations based on ISCO-08; See explanations: http://www.cbs.gov.il/publications12/occupations_class11/pd--f/draft_h.pdf (draft, Hebrew only) Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Russian Federation Change in definition (2000 - 2013): Data present the population aged 15-72 years Country: Russian Federation Territorial change (2000 - 2006): Data do not include the Chechen Republic Country: Serbia Data do not cover Kosovo and Metohija. From 2013 data compiled according to ISCO-08. Country: Turkey Break in series (2014): Since 2014 series are not comparable with the previous years due to methodological changes in LFS. Country: Turkey Break in methodlogy (2004): Data are revised according to the 2008 population projections. Country: Turkey Until 2012, all occupations were coded according to ISCO-88. Since 2013, all occupations have been coded according to ISCO-08. Country: Ukraine Change in definition (2000 - 2012): Distribution by institutional sectors of the economy based on the assessment carried out in accordance with the National Classification of Occupations developed on the basis of ISCO 88. Country: Ukraine Territorial change (2000 - 2012): Data do not cover the area of radioactive contamination from the Chernobyl disaster. Country: United States Data for occupation refer to population 15+ and who have worked in the past 5 years. Data do not cover the armed forces. Occupation is classified according to the Standard Occupational Classification (SOC) 2000 manual (www.bls.gov/soc). For individuals with two or more jobs, data refer to the job having the greatest number of hours. For unemployed persons and persons who are not currently employed but report having a job within the last five years, data refer to their last job.

Employment consists of both employees and self-employed, who are engaged in some productive activity that falls within the production boundary of the system (ESA 2010, 11.11). Employment covers employees and self-employed working for production units resident on the economic territory (i.e. the domestic employment concept). Employment is measured in number of persons without distinction according to full-time or part-time work. The following countries provide employment data seasonally adjusted, without calendar adjustment: CZ, GR, FR, MT, PL, PT, SK and CH. The remaining countries provide employment data seasonally and calendar adjusted.

Source: UNECE Statistical Database, compiled from national and international (Eurostat and ILO) official sources. Definition: The employed are all the residents above a specified age who, during a specified brief period, either one week or one day, were in the following categories: (a) paid employment: (a1) at work: persons who, during the reference period, performed some work for wage or salary, in cash or in kind; (a2) with a job but not at work: persons who, having already worked in their present job, were temporarily not at work during the reference period and had a formal attachment to their job; (b) self-employment: (b1) at work: persons who, during the reference period, performed some work for profit or family gain, in cash or in kind; (b2) with an enterprise but not at work: persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who were temporarily not at work during the reference period for any specific reason. For additional information, see the International Conference of Labour Statisticians (ICLS). The occupation groups correspond to first-level categories in the 2008 version of the International Standard Classification of Occupations (ISCO-08). For the EU and EFTA member-states the year of transition from ISCO-88 to ISCO-08 is 2011. For other countries please see Country footnotes. The transition to ISCO-08 could entail a break in time series. General note: Data come from the Labour Force Survey (LFS) unless otherwise specified. Data from the LFS and from population censuses normally comply with the definition above. .. - data not availableCountry: AlbaniaFrom 2010 occupational groups according to ISCO-08.Country: Armenia Break in methodlogy (2014): since 2014 data refer to the population aged 15-75 and are based on the Labour Force Survey.2001: data come from Population Census.Country: AzerbaijanData compiled according to ISCO-08.Country: Azerbaijan Data are based on administrative registers.Country: BelarusData compiled according to ISCO-88Country: Belarus 2000 : data refer to 1999 and come from Population Census.Country: Belgium 1980 : data refer to 1983.Country: Bosnia and HerzegovinaFrom year 2006 to 2010 data compiling using ISCO 88, from 2011 using ISCO 08.Country: Bulgaria 1995 : data refer to 1997.Country: CanadaChange in definition (1990 onwards): Data are annual averages. Cells with 0 are estimates with less than 1,500 employed.Country: CanadaData do not cover the three northern territories (Yukon, Northwest and Nunavuk )Country: Cyprus Data cover only the area controlled by the Republic of Cyprus. 1990 : data refer to 1992.Country: Estonia 1990 and 1995 : data refer to the population aged 15-69. From 2000 : data refer to the population aged 15-74.Country: Finland Data refer to the population aged 15-74.Country: France Since 2014, data include also the French overseas departments (Guadeloupe, Martinique, Guyane, La Reunion), with the exception of Mayotte.Country: Georgia Data do not cover Abkhazia and South Ossetia (Tshinvali).Country: Germany 1980 : data refer to 1983.Country: Iceland Data refer to the population aged 16-74. 1990 : data refer to 1991.Country: IsraelBreak in methodlogy (2000): In 1998: 1) Changes in the weighting method; 2) Transition to the 1995 Population Census estimates; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdfCountry: IsraelBreak in methodlogy (2001): Changes in the weighting method. See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_f1_comparison-mimi.fCountry: IsraelBreak in methodlogy (2009): 1) Update of the definition of the civilian labour force characteristics; 2) Transition to the 2008 Population Census estimates. See explanations: http://www.cbs.gov.il/publications11/1460/pdf/intro05_e.pdfCountry: IsraelBreak in methodlogy (2012): 1) Transitiom from a quarterly to a monthly LFS; 2) Changes in the definitions of labour force characteristics (including compulsory and permanent military service into labour force). See explanations: http://www.cbs.gov.il/publications/labour_survey04/labour_f--orce_survey/answer_question_e_2012.pdfCountry: IsraelChange in definition (2000 - 2012): Changes in the questionnaire (Highest Diploma Received, Discouraged Workers, Employees hired through employment agencies or employment contractors); See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_e_changes.pdfCountry: IsraelChange in definition (2013): Changes in the Standard Classification of Occupations based on ISCO-08; See explanations: http://www.cbs.gov.il/publications12/occupations_class11/pd--f/draft_h.pdf (draft, Hebrew only)Country: KyrgyzstanUp to 2015 ISCO-88 has been usedCountry: Latvia 1995 : data refer to 1996.Country: Lithuania 1995 : data refer to 1997.Country: Moldova, Republic ofData exclude the territory of the Transnistria and municipality of BenderCountry: Portugal 1990 : data refer to 1992.Country: Russian FederationChange in definition (2000 - 2013): Data present the population aged 15-72 yearsCountry: Russian FederationTerritorial change (1995 - 2006): Data do not include the Chechen RepublicCountry: SerbiaData do not cover Kosovo and Metohija. Starting in 2013 data compiled according ISCO-08.Country: Slovakia 1995 : the persons working in the armed forces are counted in the other groups.Country: Sweden Data refer to the population aged 16-64.Country: Switzerland 1990 : data refer to 1991.Country: UkraineChange in definition (2000 - 2012): Distribution by institutional sectors of the economy based on the assessment carried out in accordance with the National Classification of Occupations developed on the basis of ISCO 88.Country: UkraineTerritorial change (2000 - 2012): Data do not cover the area of radioactive contamination from the Chernobyl disaster.Country: United Kingdom Data refer to the population aged 16+.Country: United States Data refer to the population aged 16+. Data do not cover the armed forces. Occupation groups : 'Professionals' includes 'Technicians and associate professionals'; 'Craft and related workers' includes 'Plant machine operators and assemblers'.

Source: UNECE Statistical Database, compiled from national and international (Eurostat and ILO) official sources. Definition: The employed are all the residents above a specified age who, during a specified brief period, either one week or one day, were in the following categories: (a) paid employment: (a1) at work: persons who, during the reference period, performed some work for wage or salary, in cash or in kind; (a2) with a job but not at work: persons who, having already worked in their present job, were temporarily not at work during the reference period and had a formal attachment to their job; (b) self-employment: (b1) at work: persons who, during the reference period, performed some work for profit or family gain, in cash or in kind; (b2) with an enterprise but not at work: persons with an enterprise, which may be a business enterprise, a farm or a service undertaking, who were temporarily not at work during the reference period for any specific reason. For additional information, see the International Conference of Labour Statisticians (ICLS). The breakdown by kind of economic activity is grouped into 3 categories. Agriculture includes agriculture, hunting, forestry and fishing (ISIC Rev.3.1 Sections A-B or ISIC Rev.4 Section A). Industry includes mining and quarrying, manufacturing, electricity, gas and water supply, and construction (ISIC Rev.3.1 Sections C-F or ISIC Rev.4 Sections B-F ). Services comprise all other economic activities (ISIC Rev.3.1 Sections G-Q or ISIC Rev.4 Sections G-U). Total employment provided in this table generally differ from total employment provided in Economic Statistics, which cover both residents and non-residents (according to the System of National Accounts 1993). General note: Data come from the Labour Force Survey (LFS) unless otherwise specified in country footnotes. Data from the LFS and from population censuses normally comply with the definition above. .. - data not available Country: Albania Break in methodology (1980): from 1990 to 2006, data are based on administrative registers with sector breakdown according of NACE rev 1.1 Country: Albania Break in methodology (2007): As of 2007 data are based on the Labour Force Survey. Sectors broken down according to NACE rev 1.1 (2007-2014) and NACE rev since 2015. Country: Armenia Break in methodlogy (2007, 2014): For the period of 1980-2000 and 2002-2006 data on employment are based on integrated data received from various sources. From 2007 to 2013 data are based on the Integrated Survey of the Household Living Standards. Since 2014 data are based on the Labour Force Survey. Country: Armenia Break in methodlogy (2008): Data for 2007 refer to the age group 16-75. Since 2008 data refer to the age group 15-75. Country: Austria 1980-1990 : data refer to national definition (Life Subsistence Concept). From 1995 : data comply with ILO definition. Country: Azerbaijan Official estimates. 1980 : data refer to 1983. Country: Belarus Data refer to the national classification. Services include construction. Country: Belgium 1980 : data refer to 1983. Country: Bosnia and Herzegovina From year 2006 to 2011, data compiled using ISIC Rev 3.1, from 2012 using ISIC Rev 4. Country: Bulgaria 1995 : data refer to 1997. Country: Canada Data do not cover the three northern territories (Yukon, Northwest and Nunavuk ). Country: Croatia 1995 : data refer to 1996. Country: Cyprus Data cover only the area controlled by the Republic of Cyprus. 1990 : data refer to 1992. Country: Denmark 1980 : data refer to 1982. Country: Estonia 1990-1995 : data refer to the population aged 15-69. From 2000 : data refer to the population aged 15-74. Country: Finland Data refer to the population aged 15-74. Country: France Data do not cover overseas departments (DOM). Country: Georgia Break in methodology (1980 - 1995): Data are based on administrative registers Country: Georgia Territorial change (1995 onward): Data do not cover Abkhazia AR and Tskhinvali Region Country: Germany 1980 : data refer to 1983. From 1991 : data cover former German Democratic Republic (East Germany). Country: Hungary 1990 : data refer to 1992. Country: Iceland 1980 : data refer to 1981 and are based on administrative registers. 1990 : data refer to 1991. 1980 : data refer to the population aged 15-74. From 1990 : data refer to the population aged 16-74. Country: Ireland 1980 : data refer to 1983. Country: Israel Break in methodlogy (2000): In 1998: 1) Changes in the weighting method; 2) Transition to the 1995 Population Census estimates; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Break in methodlogy (2001): Changes in the weighting method. See explanations: http://www.cbs.gov.il/www/saka_y/e_intro_f1_comparison-mimi.f Country: Israel Break in methodlogy (2009): 1) Update of the definition of the civilian labour force characteristics; 2) Transition to the 2008 Population Census estimates. See explanations: http://www.cbs.gov.il/publications11/1460/pdf/intro05_e.pdf Country: Israel Break in methodlogy (2012): 1) Transitiom from a quarterly to a monthly LFS; 2) Changes in the definitions of labour force characteristics (including compulsory and permanent military service into labour force). See explanations: http://www.cbs.gov.il/publications/labour_survey04/labour_f--orce_survey/answer_question_e_2012.pdf Country: Israel Break in methodlogy (2013): Changes in the Standard Industrial Classification of Economic Activities based on ISIC Rev.4; See explanations: http://www.cbs.gov.il/publications12/economic_activities11/--pdf/e_print.pdf Country: Israel Change in definition (1995): 1) Update of the definitions of labour force characteristics; 2) Changes in the Standard Industrial Classification of Economic Activities; See explanations: http://www.cbs.gov.il/www/publications/saka_change/tch_e.pdf Country: Israel Change in definition (2003): Changes in the Standard Industrial Classification of Economic Activities 2003, which mainly involved expanding the classification of high-tech industries; See explanations: http://www.cbs.gov.il/www/saka_y/e_int_g.pdf Country: Italy 1980 : data refer to 1983. 1980-1990 : data refer to the economically active population aged 14+, which includes the persons who have been seeking employment in the last 6 months. From 1995 : data refer to the economically active population aged 15+, which includes the persons who have been seeking employment in the last 30 days. Country: Kyrgyzstan Reference period (1995): Data refer to 1996 Country: Latvia 1995 : data refer to 1996. Country: Lithuania 1995 : data refer to 1997. Country: Luxembourg 1980 : data refer to 1983. Country: Moldova, Republic of Data exclude the territory of the Transnistria and municipality of Bender Country: Netherlands 1980 : data refer to 1983. Country: Poland 1990 : official estimates based on administrative registers. Country: Romania 1995 : data refer to the population aged 14+. Country: Russian Federation Change in definition (2000 - 2013): Data present the population aged 15-72 years Country: Russian Federation Territorial change (1990 - 2006): Data do not include the Chechen Republic Country: Serbia Territorial change (2000 onward): Data do not cover Kosovo and Metohija. Country: Sweden Data refer to the population aged 16-64. Country: Turkey Break in series (2014): Since 2014 series are not comparable with the previous years due to methodological changes in LFS. Country: Turkey Break in methodlogy (2004): Data are revised according to the 2008 population projections. Country: Turkey Up to 2008, economic activities in labour force survey (LFS) were coded by NACE Rev 1. From 2009 onwards, NACE Rev 2 has been used. Country: Ukraine For 2000-2011 data compiled according ISIC 3 Rev.1, since 2012 ISIC 4 is in use Country: Ukraine Territorial change (2000 - 2012): Data do not cover the area of radioactive contamination from the Chernobyl disaster. Country: United Kingdom Data refer to the population aged 16+. Country: United States Data refer to the population aged 16+. Agriculture excludes forestry and fishing. Country: Uzbekistan Services include construction

The section 'LFS series - detailed annual survey results' reports annual results from the EU-LFS. While LFS is a quarterly survey, it is also possible to produce annual results. There are several ways of doing it, see section '20.5 Data compilation' below for details. This data collection covers all main labour market characteristics, i.e. the total population, activity and activity rates, employment, employment rates, self employed, employees, temporary employment, full-time and part-time employment, population in employment having a second job, working time, total unemployment and inactivity. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)', see link in related metada. Detailed information on the main features, the legal basis, the methodology and the data as well as on the historical development of the EU-LFS is available on the EU-LFS (Statistics Explained) webpage.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

Source: UNECE Statistical Database, compiled from national and international (Eurostat and ILO) official sources. Definition: The status of employment is defined with reference to the distinction between 'paid employment' and 'self-employment' jobs. Workers holding paid-employment jobs have explicit (written or oral) or implicit employment contracts which give them a basic remuneration which is not directly dependent upon the revenue of the unit for which they work. Self-employment jobs are jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced. Employees are all the workers who hold paid employment jobs. Employers are workers who hold self-employment jobs and have engaged, on a continuous basis, one or more persons to work for them in their business as employees. Own-account workers are workers who hold self-employment jobs and have not engaged, on a continuous basis, any employees to work for them during the reference period. Members of producers cooperatives are workers who hold self-employment jobs in a cooperative producing goods and services, in which each member takes part on an equal footing with other members in determining the organisation of production, sales and/or other work of the establishment, the investments and the distribution of the proceeds of the establishment amongst their members. Family workers are workers who hold self-employment jobs in a market-oriented establishment operated by a related person living in the same household. For additional information, see the International Classification of Status in Employment (ICSE-93). General note: Data come from the Labour Force Survey (LFS) unless otherwise specified. Data from the LFS and from population censuses normally comply with the definition above. .. - data not available Country: Austria 1980-1990 : data refer to national definition (Life Subsistence Concept). 1980 : data on employers include own-account workers and family workers. 1990 : data on employers include own-account workers. Country: Azerbaijan Data are based on Population Census and administrative registers. Country: Belarus Break in methodlogy (2000): Data refer to 1999 Population Census. Country: Belarus 2009: data are from the Population Census. Parts do not equal the totals due to employed persons not indicated their status in employment. Country: Belgium 1980 : data refer to 1983. Country: Bosnia and Herzegovina Estimates for family workers are less reliable in 2014-2015. Country: Bulgaria 1990 : data refer to 1993. Data on own-account workers include members of producers cooperatives. Country: Croatia 1995 : data refer to 1996. Country: Cyprus Data cover only the area controlled by the Republic of Cyprus. 1990 : data refer to 1992. Country: Czechia From 2002 : data on own-account workers include members of producers cooperatives. Country: Denmark 1980 : data refer to 1983; data on employers include own-account workers. Country: Estonia Data on employers and own-account workers include members of producers cooperatives. 1990-1995 : data refer to the population aged 15-69. From 2000 : data refer to the population aged 15-74. Country: Finland 1980-1995 : data on employers include own-account workers. Country: France Data do not cover overseas departments (DOM). 1980 : data refer to 1983. Country: Germany 1980 : data refer to 1983. Country: Greece 1980 : data refer to 1983. Country: Iceland 1990 : data refer to 1991. Country: Ireland 1980 : data refer to 1983. Country: Israel 1990: data refer to 1992. 1998, 2001: methodology revised, data not strictly comparable. Country: Latvia 1995 : data refer to 1996. Country: Lithuania 1995 : data refer to 1997. Data on employers include own-account workers. Country: Netherlands 1980 : data refer to 1983. 1980-2001 : data on employers include own-account workers and members of producers cooperatives. Country: Norway 1980-2001 : data on employers include own-account workers and members of producers cooperatives. Country: Poland 1990 : data refer to 1992. Country: Romania 1995: data refer to population aged 14+. Country: Russian Federation Data refer to population aged 15-72. Country: Serbia Data do not cover Kosovo and Metohija. Country: Spain Data refer to population aged 16+. 2005: methodology revised, data not strictly comparable. Country: Switzerland 1990 : data refer to 1991. Country: Turkey 2000: data revision based on Population Census 2000 Country: Ukraine Data do not cover the persons who are still living in the area of Chernobyl contaminated with radioactive material. Data do not cover the persons who are living in institutions and those who are working in the army. Data refer to the population aged 15-70. Country: United Kingdom 1980 : data refer to 1983. Country: United States Data on employers include own-account workers. Data refer to population aged 16+. 1994: methodology revised, data not strictly comparable

Employment for all employees by enterprise size and North American Industry Classification System (NAICS), last 5 quarters.

The Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) collects, on an annual basis from all its participating countries, data on landings, aquaculture production, fleet, employment in the fisheries sector, and government financial transfers. Data are collected from Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. Concepts Classifications Data are collected by the OECD using the methodologies established by the Coordinating Working Party on Fishery Statistics (CWP) (www.fao.org/fishery/cwp/search/en). This inter-agency body, created in 1960 to develop common procedures and standards for the collation of fisheries statistics, provides technical advice on fishery statistical matters. Its handbook of Fishery Statistical Standards comprises definitions of the various concepts used in fishery statistics, with the exception of Government Financial Transfers which is unique to the OECD. All other statistics are based on the CWP definitions. The OECD, a partner with the CWP, additionally collects information on values for its landings and records the breakdown between the types of landings (i.e. landings in domestic ports, landings in foreign ports) data series which are not collected by the FAO. While a number of countries cover landings in a similar fashion, the same does not hold true for capacity (feet/meters, GRT/engine powers), or for employment for which both Full-time equivalents or numbers of people are used. The OECD therefore does not duplicate FAO statistics but requests complementary information to feed its analytical work.

Eurostat's database covers: 1) Production and trade in roundwood and wood products, including primary and secondary products; 2) Economic data on forestry and logging, including employment data; 3) Sustainable forest management, comprising forest resources (assets) and environmental data. The main types of primary forest products included in (1) are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. Secondary products include further processed wood and paper products. These products are presented in greater detail; definitions are available. All of the data are compiled from the Joint Forest Sector Questionnaire (JFSQ), except for table (e), which is directly extracted from Eurostat's international trade database COMEXT (HS/CN Chapter 44). The tables in (1) cover details of the following topics: - Roundwood removals and production by type of wood and assortment (a) - Roundwood production by type of ownership (b) - Production and trade in roundwood, fuelwood and other basic products (c) - Trade in industrial roundwood by assortment and species (d) - Tropical wood imports to the EU from Chapter 44 of the Harmonised System (e) - Production and trade in sawnwood, panels and other primary products (f) - Sawnwood trade by species (g) - Production and trade in pulp and paper & paperboard (h) - Trade in secondary wood and paper products (i) Data in (2) include the output, intermediate consumption, gross value added, fixed capital consumption, gross fixed capital formation and different measures of income of forestry and logging. The data are in current basic prices and are compatible with National Accounts. They are collected as part of Intergrated environmental and economic accounting for forests (IEEAF), which also covers labour input in annual work units (AWU). Under (2), two separate tables cover the number of employees of forestry and logging, the manufacture of wood and products of wood and cork, and the manufacture of paper and paper products, as estimated from the Labour Force Survey results. There are two separate tables because of the change in the EU's classification of economic activities from NACE Rev. 1.1 to NACE Rev. 2 in 2008. More detailed information on wood products and accounting, including definitions and questionnaires, can be found on our open-access communication platform under the interest group 'Forestry statistics and accounts'. Data in (3) are not collected by Eurostat, but by the FAO, UNECE, Forest Euope, the European Commission's departments for Environment and the Joint Research Centre. They include forest area, wood volume, defoliation on sample plots, fires and areas with protective functions.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

Sport employment statistics are derived from data on employment based on the results of the European Labour Force Survey (EU-LFS). Employment in sport statistics aim at investigating on the dimension of the contribution of sport employment to the overall employment. The EU-LFS is the main source of information about the situation and trends on the labour market in the European Union . The methodology for the design and development of sport employment statistics is based on the one proposed by the final report of the European Statistical System Network on Culture (ESS-Net Culture Report 2012) which takes into account two reference classifications: the NACE classification (‘Nomenclature générale des Activités économiques dans les Communautés Européennes’) which classifies the main economic  activitiesthe ISCO classification (‘International Standard Classification of Occupations’) which classifies occupations. Results from the EU-LFS allow characterizing employment in sport by different variables such as gender, age, educational attainment by cross-tabulating ISCO and NACE selected sport codes.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

'Statistics on high-tech industry and knowledge-intensive services' (sometimes referred to as simply 'high-tech statistics') comprise economic, employment and science, technology and innovation (STI) data describing manufacturing and services industries or products traded broken down by technological intensity. The domain uses various other domains and sources of  Eurostat's official statistics (CIS, COMEXT, HRST, LFS, PATENT, R&D and SBS) and its coverage is therefore dependent on these other primary sources. Two main approaches are used in the domain to identify technology-intensity: the sectoral approach and the product approach. A third approach is used for data on high-tech and biotechnology patents aggregated on the basis of the International Patent Classification (IPC) 8th edition (see summary table in Annex 1 for which approach is used by each type of data). The sectoral approach: The sectoral approach is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the Statistical classification of economic activities in the European Community (NACE) at 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-technology, medium low-technology and low-technology industries. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. The sectoral approach is used for all indicators except data on high-tech trade and patents. Note that due to the revision of the NACE from NACE Rev. 1.1 to NACE Rev. 2 the definition of high-technology industries and knowledge-intensive services has changed in 2008. For high-tech statistics it means that two different definitions (one according NACE Rev. 1.1 and one according NACE Rev. 2) are used in parallel and the data according to both NACE versions are presented in separated tables depending on the data availability. For example as the LFS provides the results both by NACE Rev. 1.1 and NACE Rev. 2, all the table using this source have been duplicated to present the results by NACE Rev. 2 from 2008. For more details, see both definitions of high-tech sectors in Annex 2 and 3. Within the sectoral approach, a second classification was created, named Knowledge Intensive Activities KIA) and based on the share of tertiary educated people in each sectors of industries and services according to NACE at 2-digit level and for all EU28 Member States. A threshold was applied to judge sectors as knowledge intensive. In contrast to first sectoral approach mixing two methodologies, one for manufacturing industries and one for services, the KIA classification is based on one methodology for all the sectors of industries and services covering even public sector activities. The aggregations in use are Total Knowledge Intensive Activities (KIA) and Knowledge Intensive Activities in Business Industries (KIABI). Both classifications are made according to NACE Rev. 1.1 and NACE Rev. 2 at 2- digit level. Note that due to revision of the NACE Rev.1.1 to NACE Rev. 2 the list of Knowledge Intensive Activities has changed as well, the two definitions are used in parallel and the data are shown in two separate tables. NACE Rev.2 collection includes data starting from 2008 reference year. For more details please see the definitions in Annex 7 and 8. The product approach: The product approach was created to complement the sectoral approach and it is used for data on high-tech trade. The product list is based on the calculations of R&D intensity by groups of products (R&D expenditure/total sales). The groups classified as high-technology products are aggregated on the basis of the Standard International Trade Classification (SITC). The initial definition was built based on SITC Rev.3 and served to compile the high-tech product aggregates until 2007. With the implementation in 2007 of the new version of SITC Rev.4, the definition of high-tech groups was revised and adapted according to new classification. Starting from 2007 the Eurostat presents the trade data for high-tech groups aggregated based on the SITC Rev.4. For more details, see definition of high-tech products in Annex 4 and 5. High-tech patents: High-tech patents are defined according to another approach. The groups classified as high-tech patents are aggregated on the basis of the International Patent Classification (IPC 8th edition). Biotechnology patents are also aggregated on the basis of the IPC 8th edition. For more details, see the aggregation list of high-tech and biotechnology patents in Annex 6. The high-tech domain also comprises the sub-domain Venture Capital Investments: data are provided by INVEST Europe (formerly named the European Private Equity and Venture Capital Association EVCA). More details are available in the Eurostat metadata under Venture capital investments. Please note that for paragraphs where no metadata for regional data has been specified, the regional metadata is identical to the metadata provided for the national data.

Canada: Employment insurance beneficiaries (regular benefits) by province, territory and occupation, monthly, seasonally adjusted

Regional (NUTS level 2) employment rate of the age group 15-64 represents employed persons aged 15-64 as a percentage of the population of the same age group. The indicator is based on the EU Labour Force Survey. The survey covers the entire population living in private households and excludes those in collective households such as boarding houses, halls of residence and hospitals. The employed persons are those aged 15-64, who during the reference week did any work for pay, profit or family gain for at least one hour, or were not at work but had a job or business from which they were temporarily absent.

The source for the regional labour market information down to NUTS level 2 is the EU Labour Force Survey (EU-LFS). This is a quarterly household sample survey conducted in all Member States of the EU and in EFTA and Candidate countries.  The EU-LFS survey follows the definitions and recommendations of the International Labour Organisation (ILO). To achieve further harmonisation, the Member States also adhere to common principles when formulating questionnaires. The LFS' target population is made up of all persons in private households aged 15 and over. For more information see the EU Labour Force Survey (lfsi_esms, see paragraph 21.1.).  The EU-LFS is designed to give accurate quarterly information at national level as well as annual information at NUTS 2 regional level and the compilation of these figures is well specified in the regulation. Microdata including the NUTS 2 level codes are provided by all the participating countries with a good degree of geographical comparability, which allows the production and dissemination of a complete set of comparable indicators for this territorial level. At present the transmission of the regional labour market data at NUTS 3 level has no legal basis. However many countries transmit NUTS 3 figures to Eurostat on a voluntary basis, under the understanding that they are not for publication with such detail, but for aggregation in few categories per country, i.e., metropolitan regions and urban-rural typology. Most of the NUTS 3 data are based on the LFS while some countries transmit data based on registers, administrative data, small area estimation and other reliable sources.

Number of employees, average hourly and weekly earnings (including overtime), and average weekly hours for the industrial aggregate excluding unclassified businesses, last 5 months.

Persons in employment are those who, during the reference week, did any work for pay or profit, or were not working but had a job from which they were temporarily absent. Anyone who receives a wage for on-the-job training that involves the production of goods or services is also considered as being in employment. Self-employed and family workers are also included. Employment is measured in number of persons without distinction according to full-time or part-time work. The data are expressed in 1000 persons. The quarterly data are not seasonally adjusted. Data are sourced from National accounts data. The ESA 2010 distinguishes two employment concepts depending on the geographical coverage: resident persons in employment (i.e. the national scope of employment) and employment in resident production units irrespective of the place of residence of the employed person (i.e. domestic scope). The table presents total employment, according to the domestic concept.

6.1. Reference area

BGR provides the biennial energy study which covers data and developments concerning German and Global energy supplies. In addition the study also provides information on the global generation of renewable energies, including geothermal energy and hydrogen. 

The indicator measures the total amount of energy tax revenue in millions of euro for all NACE activities plus households, non-residents and not allocated. This shows the size that the energy taxes take in absolute (currency) terms, to complement the share of energy taxes paid by paying sector. Energy taxes are one of the four tax categories that make up environmental taxes (the other three being pollution taxes, resource taxes (excluding taxes on oil and gas extraction) and transport taxes). As per environmental taxes, the energy tax base is a physical unit of something that has a proven specific negative impact on the environment, but it is restricted to certain items that are concerning the energy sector, which also includes CO2 taxes.

The indicator measures the percentage of energy taxes that are raised against seven paying sectors as a proportion of the total amount of tax revenue raised from energy taxes. The seven sectors are: Households, Industry (except Construction), Construction, Wholesale and retail trade and repair of motor vehicles and motorcycles, Transportation and storage, Services (except wholesale and retail trade, transportation and storage), and Agriculture, forestry and fishing. Energy taxes are one of the four tax categories that make up environmental taxes (the other three being pollution taxes, resource taxes (excluding taxes on oil and gas extraction) and transport taxes). As per environmental taxes, the energy tax base is a physical unit of something that has a proven specific negative impact on the environment, but it is restricted to certain items that are concerning the energy sector, which also includes CO2 taxes.

The focus of this domain is on the European Neighbourhood Policy (ENP) countries in Eastern Europe, namely Armenia (AM), Azerbaijan (AZ), Belarus (BY), Georgia (GE), Moldova (MD) and Ukraine (UA). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain.

Eurostat Dataset Id:enpr_inisoc The domain focuses on the Eastern European Neighbourhood Policy countries (ENP): Armenia (AM), Azerbaijan (AZ), Belarus (BY), Georgia (GE), Moldova (MD) and the Ukraine (UA). Data are provided for 200 to 300 indicators.

Eurostat Dataset Id:enpr_scienc The domain focuses on the Eastern European Neighbourhood Policy countries (ENP): Armenia (AM), Azerbaijan (AZ), Belarus (BY), Georgia (GE), Moldova (MD) and the Ukraine (UA). Data are provided for 200 to 300 indicators.

Data cited at: Wendling, Z. A., Emerson, J. W., Esty, D. C., Levy, M. A., de Sherbinin, A., et al. (2018). 2018 Environmental Performance Index. New Haven, CT: Yale Center for Environmental Law & Policy. https://epi.yale.edu/   The Environmental Performance Index (EPI) is constructed through the calculation and aggregation of 20 indicators reflecting national-level environmental data. These indicators are combined into nine issue categories, each of which fit under one of two overarching objectives. The two objectives that provide the overarching structure of the EPI are Environmental Health and Ecosystem Vitality. Environmental Health measures the protection of human health from environmental harm. Ecosystem Vitality measures ecosystem protection and resource management. These two objectives are further divided into nine issue categories that span high-priority environmental policy issues, including air quality, forests, fisheries, and climate and energy, among others. The issue categories are extensive but not comprehensive. Underlying the nine issue categories are 20 indicators calculated from country-level data and statistics. After more than 15 years of work on environmental performance measurement and six iterations of the EPI, global data are still lacking on a number of key environmental issues. These include: freshwater quality, toxic chemical exposures, municipal solid waste management, nuclear safety, wetlands loss, agricultural soil quality and degradation, recycling rates, adaptation, vulnerability, and resiliency to climate change, desertification.

The indicator is presented in two ways. Firstly, as the proportion of environmental tax revenues in total revenues from all taxes and social contributions. This evidences the different taxation splits that Member States have between environment and other factors such as labour and capital. Secondly, the indicator is presented as the proportion of environmental tax revenues in Gross Domestic Product (GDP). This allows a comparison of environmental taxation between Member States taking into account the size of the different national economies.

Definition of an environmental tax (Regulation (EU) N° 691/2011) An environmental tax is a tax whose tax base is a physical unit (or a proxy of a physical unit) of something that has a proven, specific negative impact on the environment, and which is identified in ESA2010 as a tax. Eurostat collects data on environmental tax revenue (by tax category - energy, transport, pollution and resource taxes) broken down by economic activities (tax payers) using the NACE classification for production activities plus households and non-residents. Eurostat with the European Commission's Directorate General for Taxation and Customs Union also produces annually an analysis of each tax listed in the national accounts of European countries including: - assigning an economic function to each tax; - attributing an environmental code to the environmental taxes (E for Energy, T for Transport, P for Pollution, RS for Resource). These function and environmental codes are reported by countries in their national tax list (NTL) and are validated by Eurostat. Efforts are made to ensure full consistency of the data on environmental taxes by economic activities and revenue data based on the national tax lists even if some discrepancies remain for some countries.

Estimated areas, yield and production of principal field crops by Small Area Data Regions.

This table contains 64 series, with data for years 2000 - 2017 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (2 items: Quebec; Ontario); Harvest disposition (8 items: Seeded area; Seeded area; Harvested area; Harvested area; ...); Type of crop (4 items: Total corn for grain; Genetically modified corn for grain; Total soybeans; Genetically modified soybeans).

The estimated resident population (ERP) is the official measure of the Australian population. This dataset contains annual ERP by country of birth, age and sex at the Australia level. At the state/territory level it is available for Census years only. Population_Estimates:_Concepts,_Sources_and_Methods_2009

Animal production statistics cover three main sub-domains based on three pieces of relevant legislation and related gentlemen’s agreements. Livestock and meat statistics are collected under Regulation (EC) No 1165/2008. They cover meat production, as activity of slaughterhouses (monthly) and as other slaughtering (annual), meat production (gross indigenous production) forecast (semi-annual or quarterly), livestock statistics, including regional statistics. A quality report is also collected every third year.Milk and milk product statistics are collected under Decision 97/80/EC implementing Directive 96/16/EC. They cover farm production and utilisation of milk (annual), collection (monthly for cows’ milk) and production activity by dairies (annual) and statistics on the structure of dairies (every third year). An annual methodological report is also collected.Statistics on eggs for hatching and farmyard poultry chicks are collected under Regulation (EC) No 617/2008, implementing Regulation (EC) No 1234/2007 (Single CMO Regulation). They cover statistics on the structure (annual) and the activity (monthly) of hatcheries as well as reports on the external trade of chicks. European Economic Area countries (EEA, Iceland, Liechtenstein and Norway) are requested to provide milk statistics, with the exception of those related to home consumption, as stated in Annex XXI of the EEA Agreement. As Iceland is now a candidate country and Liechtenstein is exempted in the Agreement, only Norway is concerned. The Agreement between the European Community and the Swiss Confederation on cooperation in the field of statistics states that Switzerland must provide Eurostat with national milk statistics. It has been amended in 2013 for covering also some livestock and meat statistics. The same statistics are requested from the candidate countries as acquis communautaire. Further data about the same topics refer to repealed legal acts or agreements. The tables on animal product supply balance sheets (apro_mk_bal, apro_mt_bal and apro_ec_bal), statistics on the structure of rearing (apro_mt_str) and the number of laying hens (apro_ec_lshen) are therefore no longer updated. The same applies to some variables (external trade of animals and meat), periods (surveys in April or August) or items (number of horses) included in other tables. The statistical tables disseminated by Eurostat are organised into three groups of tables on Agricultural products (apro), i.e. Milk and milk products (apro_mk), Livestock and meat (apro_mt) and Poultry farming (apro_ec). This last label covers statistics on hatcheries and on trade in chicks. The regional animal production statistics collected on livestock (agr_r_animal) and on cows’ milk production on farms (agr_r_milk_pr) are disseminated separately. Due to the change in the legal basis or in the methodology, the time series may be broken. This is indicated by a flag in the tables. The detailed content of each table and the reference to its legal definition is provided in the table below. Table 3.1: Data tables disseminated regarding animal production statistics <

The annual Eurostat's collections on population are structured as follows:

Dataset includes European Economic economic forecast releases from Autumn 2017 through Winter 2023.

Eurostat Dataset Id:ei_bsci_m_r2 Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Expenditure on social protection contain: social benefits, which consist of transfers, in cash or in kind, to households and individuals to relieve them of the burden of a defined set of risks or needs; administration costs, which represent the costs charged to the scheme for its management and administration; other expenditure, which consists of miscellaneous expenditure by social protection schemes (payment of property income and other). It is calculated in current prices.

Expenditure on social protection contain: social benefits, which consist of transfers, in cash or in kind, to households and individuals to relieve them of the burden of a defined set of risks or needs; administration costs, which represent the costs charged to the scheme for its management and administration; other expenditure, which consist of miscellaneous expenditure by social protection schemes (payment of property income and other).

ANNUAL Annual data on quantities for crude oil, petroleum products, natural gas and manufactures gases, electricity and derived heat, solid fossil fuels, renewables and wastes covering the full spectrum of the energy sector from supply through transformation to final consumption oby sector and fuel type. Also, annual imports and exports data of various energy carriers by country of origin and destination, as well as infrastructure information. Data on annual statistics are collected by standard questionnaires according to Annex B of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics   MONTHLY The monthly energy data collections cover the most important energy commodities: Crude oil & Petroleum productsNatural gasSolid fuelsElectricity For each of the above mentioned commodities the inflowing data are delivered by the reporting countries to Eurostat via separate dedicated questionnaires. Data on monthly statistics are collected by standard questionnaires according to Annex C of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics   SHORT-TERM MONTHLY Short-term monthly energy data collections cover the most important energy commodities: Oil & petroleum productsNatural gasElectricity Short-term monthly data provides information on main flows (quantities) on the supply side. Data on monthly short term statistics are collected by standard questionnaires according to Annex D of the Regulation (EC) No 1099/2008 of the European Parliament and of the Council of 22 October 2008 on energy statistics

Value of gross production has been compiled by multiplying gross production in physical terms by output prices at farm gate. Thus, value of production measures production in monetary terms at the farm gate level. Since intermediate uses within the agricultural sector (seed and feed) have not been subtracted from production data, this value of production aggregate refers to the notion of "gross production". Value of gross production is provided in both current and constant terms and is expressed in US dollars and Standard Local Currency (SLC). The current value of production measures value in the prices relating to the period being measured. Thus, it represents the market value of food and agricultural products at the time they were produced. Knowing this figure is helpful in understanding exactly what was happening within a given economy at that point in time. Often, this information can help explain economic trends that emerged in later periods and why they took place. Value of production in constant terms is derived using the average prices of a selected year or years, known as the base period. Constant price series can be used to show how the quantity or volume of products has changed, and are often referred to as volume measures. The ratio of the current and constant price series gives a measure of price movements. US dollar figures for value of gross production are converted from local currencies using official exchange rates as prevailing in the respective years. The SLC of a country is the local currency prevailing in the latest year. Expressing data series in one uniform currency is useful because it avoids the influence of revaluation in local currency, if any, on value of production

The Fertilizers by Product dataset contains information on product amounts for the Production, Trade, Agriculture Use and Other Uses of chemical and mineral fertilizers products, over the time series 2002-present. The fertilizer statistics data are validated separately for a set of over thirty individual products. Both straight and compound fertilizers are included.

Farm input price index (FIPI). Quarterly Data are available from from the first quarter of 2002. The table presents data for the most recent reference period and the last four periods. The base period for the index is (2012=100).

Farm product prices, crops and livestock, by province (in dollars per metric tonne unless otherwise noted). Data are available on a monthly basis.

Farm supply and disposition of grains as of March 31, July 31, August 31 (soybeans only) and December 31; data on supplies, production, stocks, deliveries, animal feed and waste for crops.

Source: UNECE Transport Division Database. Definitions Killed: Any person who was killed outright or who died within 30 days as a result of the accident. Injured: Any person, who was not killed, but sustained one or more serious or slight injuries as a result of the accident. Driver: Any person who drives a motor vehicle or other vehicle (including a cycle), or who guides cattle, singly or in herds, or flocks, or draught, pack or saddle animals on a road. Passenger: Any person, other than the driver, who is in or on a vehicle. Pedestrian: Any person other than a driver or a passenger according to the above definitions. Persons pushing or pulling a child?s carriage, a bath chair or invalid chair, or any other small vehicle without an engine, or pushing a cycle or moped, and handicapped persons travelling in invalid chairs propelled by such persons or moving at walking pace shall be treated as pedestrians. Road vehicle: A vehicle running on wheels and intended for use on roads. Motor vehicle: Any power-driven vehicle which is normally used for carrying persons or goods by road or for drawing, on the road, vehicles used for the carriage of persons or goods. This term embraces trolleybuses, that is to say, vehicles connected to an electric conductor and not rail-borne. It does not cover vehicles, such as agricultural tractors, which are only incidentally used for carrying persons or goods by road or for drawing, on the road, vehicles used for the carriage of persons or goods. Power driven vehicle: Any self propelled road vehicle, other than a moped and a rail-borne vehicle. Cycle: Any road vehicle which has at least two wheels and is propelled solely by the muscular energy of the person(s) on that vehicle, in particular by means of a pedal system, lever or handle (e.g. bicycles, tricycles, quadricycles and invalid carriages). Moped: Any two-wheeled or three-wheeled road vehicle which is fitted with an internal combustion engine having a cylinder capacity not exceeding 50 cc. (3.05 cu. in.) and a maximum design speed not exceeding 50 km (30 miles) per hour. Motor cycle: Two-wheeled road motor vehicle with or without side-car, including motor scooter, or three-wheeled road motor vehicle not exceeding 400 kg (900 lb.) unleaded weight. This term does not include mopeds. Passenger car: Road motor vehicle, other than a motor cycle, intended for the transport of passengers and seating not more than nine persons (including the driver). The term passenger car therefore covers taxis and hired vehicles, provided that they have fewer than ten seats. Motor coach or bus: Passenger road motor vehicle, seating more than nine persons (including the driver). Trolleybus: A passenger road vehicle, seating more than nine persons (including the driver), which is connected to electric conductors and which is not rail-borne. Tramcar: A passenger road vehicle, seating more than nine persons (including the driver), which is connected to electric conductors and which is rail borne. Please note that country footnotes are not always in alphabetical order. .. - data not available For European Union member states, Iceland, Norway, and Switzerland the source of data from year 2005 is CARE database. Country: Albania Included with motorcycles, if not available. Country: Ireland Included with motorcycles, if not available. Country: Poland Included with motorcycles, if not available. Country: Georgia ''<6 years'' refer to ''0-7 years''. ''10-14 years'' refer to ''8-16 years''. ''21-24 years'' refer to ''17-25 years''. ''25-64 years'' refer to ''26-60 years''. ''65 years and over'' refer to ''more than 60 years'' Country: Latvia Persons are recorded as killed who die at the scene of the accident or within 7 days; persons who die later are recorded as injured. Country: Moldova, Republic of From 2008, breakdown by category of user does not sum to total as unknown category of user is not reported. Country: Portugal Data refer to continent only. Country: Portugal Persons are recorded as killed who die at the scene of the accident or during or immediately after transport from the scene of the accident; persons who die later are recorded as injured. Country: Spain Persons are recorded as killed who die within 24 hours as a result of the accident; persons who die later are recorded as injured. Country: Turkey Data by age group cover accidents only at Police responsibility area for years between 2000-2011 whereas for years between 2012-2015 data cover both Police and Gendermarie responsibility area. Until year 2015 figures on persons killed include the deaths only at the accident scene; however since year 2015 figures on persons killed also include the deaths within 30 days after the traffic accidents due to related accident and its impacts for people injured and sent to health facilities. 6 to 9 years refers to less than 10 years old. Country: United Kingdom Data refer to Great Britain. Country: United States Sum by category of user is not equal to total as unknown category of user is not shown. Country: Uzbekistan Less than 6 years refers to less than 7 years. 10 to 14 years refers to 8 to 15 years.

For European Union member states, Iceland, Norway, and Switzerland the source of data from year 2005 is CARE database. Age Group: < 6 years For European Union members, less than 6 years refers to less than 5 years (data provided through CARE database). Age Group: 18 - 20 years For European Union members, 18 to 20 years refers to 18 to 19 years (data provided through CARE database). Age Group: 21 - 24 years For European Union members, 21 to 24 years refers to 20 to 24 years (data provided through CARE database). Age Group: 6 - 9 years For European Union members, 6 to 9 years refers to 5 to 9 years (data provided through CARE database). Country: Georgia ''<6 years'' refer to ''0-7 years''. ''10-14 years'' refer to ''8-16 years''. ''21-24 years'' refer to ''17-25 years''. ''25-64 years'' refer to ''26-60 years''. ''65 years and over'' refer to ''more than 60 years'' Country: Latvia Persons are recorded as killed who die at the scene of the accident or within 7 days; persons who die later are recorded as injured. Country: Portugal Persons are recorded as killed who die at the scene of the accident or during or immediately after transport from the scene of the accident; persons who die later are recorded as injured. Country: Spain Persons are recorded as killed who die within 24 hours as a result of the accident; persons who die later are recorded as injured. Country: Turkey Data by age group cover accidents only at Police responsibility area for years between 2000-2011 whereas for years between 2012-2015 data cover both Police and Gendermarie responsibility area. Until year 2015 figures on persons killed include the deaths only at the accident scene; however since year 2015 figures on persons killed also include the deaths within 30 days after the traffic accidents due to related accident and its impacts for people injured and sent to health facilities. 6 to 9 years refers to less than 10 years old. Country: United Kingdom Data refer to Great Britain. Country: Uzbekistan Less than 6 years refers to less than 7 years. 10 to 14 years refers to 8 to 15 years. Sex: Total Sum of males and females may not be equal to total in some countries where victim gender is unknown.

Federal expenditures on science and technology and its components, by type of science and performing sector for Canada, provinces, territories and foreign from 2004 to today.

Federal extramural expenditures on science and technology and its components, by type of science, performing sector, type of payment, for Canada and foreign, provinces and territories from 2003 to today.

Federal personnel engaged in science and technology and its components, by type of science, personnel category, for provinces and territories from 2000 to today.

Data on the shipments of various fertilizers such as ammonia, urea ammonium nitrate, ammonium sulfate, etc. to Canada's Eastern provinces, the Prairie provinces, the United States and other countries.

Data on fertilizer shipments within Canada by nutrient content such as nitrogen, phosphate, potash and sulphur.

Monthly updates of FIFA World Football Men's Ranking 

Metainformation:Last modified: New data set (year 2018) State of the database: 14.03.2019 Reference period: Cinema year Catchment area: Switzerland Survey: Swiss Film and Cinema StatisticsExcl. film festivals, open-air cinema and adult cinemas, up to 2015 also excluding cinema clubs, see methodology (in German)Corrections: Switzerland: 2014 (01.04.2016) United States: 2011 (01.04.2016) United Kingdom: 2011 (01.04.2016) Austria: 2014 (01.04.2016)Remarks The Cinématographe and Paderewski screens of the National film archive (Cinémathèque Suisse) were included in the statistics for the first time in 2018 and contribute significantly to the increase in the number of films shown compared with the previous year.

RMetainformation:Last modified: New data set (year 2018) State of the database: 14.03.2019 Reference period: Cinema year Catchment area: Switzerland Survey: Swiss Film and Cinema StatisticsExcl. film festivals, open-air cinema and adult cinemas, up to 2015 also excluding cinema clubs, see methodology (in German)Corrections: Germany: 2015 (15.03.2017)Remarks The Cinématographe and Paderewski screens of the National film archive (Cinémathèque Suisse) were included in the statistics for the first time in 2018 and contribute significantly to the increase in the number of films shown compared with the previous year.

Data in this domain constitute only a small part of the entire National Accounts data range available from Eurostat. Annual and quarterly national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013. The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information on the transition from ESA 95 to ESA 2010 is presented on the Eurostat website. The annual data of this domain consists of the following collections: 1. Main GDP aggregates: main components from the output, expenditure and income side. nama_10_gdp: GDP and main components (output, expenditure and income) The quarterly data of this domain consists of the following collections 1. Main GDP aggregates, main components from the output, expenditure and income side, expenditure breakdowns by industry and assets. namq_10_ma: Main GDP aggregatesnamq_10_gdp: GDP and main components (output, expenditure and income)namq_10_fcs: Final consumption aggregates by durabilitynamq_10_exi: Exports and imports by Member States of the EU/third countries 2. Breakdowns of GDP aggregates and employment data by main industries and asset classes. namq_10_bbr: Basic breakdowns main GDP aggregates and employment (by industry and assets)namq_10_a10: Gross value added and income by A*10 industrynamq_10_an6: Gross fixed capital formation by AN_F6 asset typenamq_10_a10_e: Employment by A*10 industry breakdowns Geographical entities covered are the European Union, the euro area, EU Member States, Candidate Countries, EFTA countries, US, Japan and possibly other countries on an ad-hoc basis. Data sources: National Statistical Institutes.

Final consumption expenditure by general government includes the value of goods and services purchased or produced by general government and directly supplied to private households for consumption purposes.

Private consumption expenditure consists of expenditure incurred for the direct satisfaction of individual or collective needs by private households or non-profit institutions serving households (such as religious societies, sports and other clubs, political parties, etc.).

Private consumption expenditure consists of expenditure incurred for the direct satisfaction of individual or collective needs by private households or non-profit institutions serving households (such as religious societies, sports and other clubs, political parties, etc.).

Private consumption expenditure consists of expenditure incurred for the direct satisfaction of individual or collective needs by private households or non-profit institutions serving households (such as religious societies, sports and other clubs, political parties, etc.). The data are presented in % of GDP and million units of national currency.

Final consumption expenditure (ESA 2010, 3.94) consists of expenditure incurred by resident institutional units on goods or services that are used for the direct satisfaction of individual needs or wants or the collective needs of members of the community. The consumption expenditure may take place on the domestic territory or abroad. Private final consumption expenditure includes households' (ESA 2010, 2.118) and NPISH's final consumption expenditure. Non Profit Institutions Serving Households (NPISH, ESA 2010, 2.129) are separate legal entities serving households. They include for example trade unions, professional societies, political parties, churches, charities, sports clubs etc. Values are seasonally adjusted (SA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

National accounts are a coherent and consistent set of macroeconomic indicators, which provide an overall picture of the economic situation and are widely used for economic analysis and forecasting, policy design and policy making. Eurostat publishes annual and quarterly national accounts, annual and quarterly sector accounts as well as supply, use and input-output tables, which are each presented with associated metadata. Even though consistency checks are a major aspect of data validation, temporary (usually limited) inconsistencies between datasets may occur, mainly due to vintage effects. Annual national accounts are compiled in accordance with the European System of Accounts - ESA 2010 as defined in Annex B of the Council Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013.   The previous European System of Accounts, ESA95, was reviewed to bring national accounts in the European Union, in line with new economic environment, advances in methodological research and needs of users and the updated national accounts framework at the international level, the SNA 2008. The revisions are reflected in an updated Regulation of the European Parliament and of the Council on the European system of national and regional accounts in the European Union of 2010 (ESA 2010). The associated transmission programme is also updated and data transmissions in accordance with ESA 2010 are compulsory from September 2014 onwards. Further information (including actual communications) is presented on the Eurostat website. The domain consists of the following collections:   1. Main GDP aggregates: main components from the output, expenditure and income side, expenditure breakdowns by durability and exports and imports by origin. <

Final decision on appeal means a decision granted at the final instance of administrative/judicial asylum procedure and which results from the appeal lodged by the asylum seeker rejected in the preceding stage of the procedure.

Data series on decisions on asylum applications and resettlement contain statistical information based on Article 4 of the Council Regulation (EC) no 862/2007 with reference to:First instance decisions by age, sex and citizenshipFinal decisions by age, sex and citizenshipDecisions withdrawing status granted at first instance by type of status withdrawn and by citizenshipDecisions withdrawing status granted as final decisions by type of status withdrawn and by citizenshipResettled persons by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented country by country and for groups of countries: the European Union (EU28 and the European Economic Area (EEA). Data are rounded to the nearest 5.

This indicator expresses the sum of the energy supplied to agriculture for all energy uses.

Financial flows and stocks data are often referred to collectively in the national accounts framework as 'financial accounts'. Financial flows consist of transactions and other flows, and represent the difference between the opening financial balance sheet at the start of the year and the closing balance sheet at the end of the year. The data are compiled in accordance with the European System of Accounts (ESA 2010), which came into force in September 2014, and are presented here in the following tables: 'Financial transactions', 'Other changes in volume', 'Revaluation account', and 'Financial balance sheets'. 

Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects:access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity). Breakdowns (see details of available breakdowns): Relating to households:by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals:by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg):Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work

The financial flows and stocks data are reported quarterly to the European Central Bank. Once validated the data are transmitted to Eurostat.  Financial flows consist of transactions and other flows and represent  the difference between opening balance sheet  at the beginning of the year and closing balance sheet at the end of the year.  Â

Financial flows and stocks data are often referred to collectively in the national accounts framework as 'financial accounts'. Financial flows consist of transactions and other flows, and represent the difference between the opening financial balance sheet at the start of the year and the closing balance sheet at the end of the year. The data are compiled in accordance with the European System of Accounts (ESA 2010), which came into force in September 2014, and are presented here in the following tables: 'Financial transactions', 'Other changes in volume', 'Revaluation account', and 'Financial balance sheets'. 

The international investment position (IIP) is a statistical statement that shows at a point in time the value and composition of: -financial assets of residents of an economy that are claims on non-residents and gold bullion held as reserve assets, and -liabilities of residents of an economy to non-residents. The difference between an economy’s external financial assets and liabilities is the economy’s net IIP, which may be positive or negative. According to the functional category, the cross-border financial positions are classified as: 1) For the assets - Direct investment; Portfolio investment; Financial derivatives and employee stock options ; Other investment and Reserve assets 2) For the liabilities - Direct investment; Portfolio investment; Financial derivatives and employee stock options and Other investment The financial positions are further classified according the different instruments. The data on portfolio investment are expressed in million units of national currency. The indicator is based on the Eurostat data from the Balance of payment statistics, these data are quaterly reported to the ECB by the EU Member States. Definitions are based on the IMF Sixth Balance of Payments Manual (BPM6).

The international investment position (IIP) is a statistical statement that shows at a point in time the value and composition of: -financial assets of residents of an economy that are claims on non-residents and gold bullion held as reserve assets, and -liabilities of residents of an economy to non-residents. The difference between an economy’s external financial assets and liabilities is the economy’s net IIP, which may be positive or negative. According to the functional category, the cross-border financial positions are classified as: 1) For the assets - Direct investment; Portfolio investment; Financial derivatives and employee stock options ; Other investment and Reserve assets 2) For the liabilities - Direct investment; Portfolio investment; Financial derivatives and employee stock options and Other investment The financial positions are further classified according the different instruments and institutional sectors. The data are expressed in million units of national currency. The indicator is based on the Eurostat data from the Balance of payment statistics, these data are quaterly reported to the ECB by the EU Member States. Definitions are based on the IMF Sixth Balance of Payments Manual (BPM6).

Eurostat Dataset Id:ei_bsfs_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Financial flows and stocks data are often referred to collectively in the national accounts framework as 'financial accounts'. Financial flows consist of transactions and other flows, and represent the difference between the opening financial balance sheet at the start of the year and the closing balance sheet at the end of the year. The data are compiled in accordance with the European System of Accounts (ESA 2010), which came into force in September 2014, and are presented here in the following tables: 'Financial transactions', 'Other changes in volume', 'Revaluation account', and 'Financial balance sheets'.Â

Starting from 1750 Population statistics have been digitised into PDF format in the National Library's Doria service: Publications on Population structure and Vital statistics in Doria (in Finnish) Publications on Population censuses in Doria (in Finnish) --- Description of statistic Quality descriptions Concepts and definitionsSecond nationalityCountries (ISO 3166). The used classification of continents is the classification of Eurostat, where Cyprus and Turkey belong to Europe. In the classification of continents, Europe does not include the figures for Finland. Non-autonomous states are combined with the mother country. Czech Republic = Czech Republic + Former Czechoslovakia Sudan = Sudan + Former Sudan If a person has two nationalities and one of them is Finnish, Finnish is as his/her first nationality in statistics. --- HDI = Human Development Index Ranking according to the 2016 HDI index by country: The former Soviet Union is included in the Russia HDI category The former Czechoslovakia is included in the Czech Republic HDI category The former Yugoslavia and Serbia and Montenegro are included in the Serbia HDI categoryAgeAge refers to a person's age in whole years as at 31 December.InformationFinnish citizens with dual nationalityFinnish citizens with dual nationality who are included in the Finnish population on 31 December

Data series on decisions on asylum applications and resettlement contain statistical information based on Article 4 of the Council Regulation (EC) no 862/2007 with reference to:First instance decisions by age, sex and citizenshipFinal decisions by age, sex and citizenshipDecisions withdrawing status granted at first instance by type of status withdrawn and by citizenshipDecisions withdrawing status granted as final decisions by type of status withdrawn and by citizenshipResettled persons by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented country by country and for groups of countries: the European Union (EU28 and the European Economic Area (EEA). Data are rounded to the nearest 5.

Data series on decisions on asylum applications and resettlement contain statistical information based on Article 4 of the Council Regulation (EC) no 862/2007 with reference to:First instance decisions by age, sex and citizenshipFinal decisions by age, sex and citizenshipDecisions withdrawing status granted at first instance by type of status withdrawn and by citizenshipDecisions withdrawing status granted as final decisions by type of status withdrawn and by citizenshipResettled persons by age, sex and citizenship These data are supplied to Eurostat by the national Ministries of Interior and related official agencies. Data is presented country by country and for groups of countries: the European Union (EU28 and the European Economic Area (EEA). Data are rounded to the nearest 5.

First instance decision means a decision made in response to an asylum application at the first instance level of the asylum procedure.

Residence permit means any authorisation valid for at least 3 months issued by the authorities of a Member State allowing a third country national to stay legally on its territory. First permit means the residence permit issued to a person for the first time. A residence permit is considered as a first permit also if the time gap between expiry of the old permit and the start of validity of the new permit issued for the same reason is at least 6 months, irrespective of the year of issuance of the permit.

Residence permits statistics refers to third-country nationals (persons who are not EU citizens) receiving a residence permits or an authorisation to reside in one of the EU or EFTA Member States. The definitions used for residence permits and other concepts (e.g. first permit) are presented in the section 3.4. Statistical concepts and definitions. The detailed data collection methodology is presented in Annex 8 of this metadta file. LEGAL FRAMEWORK - Residence data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007.  This legal framework refers to the initial residence permits data colection with 2008 first reference period (e.g. first residence permits; change of immigration status or reason to stay; all valid residence permits in the end of the year and long-term residence permits valid in the end of the year) and it provides also a general framework for newer data collections based on speciffic European legal acts (e.g. statistics on EU Blue Cards and statistics on single permits) or provided on voluntary basis (e.g. new long-term residence permits issued during the year and residence permits issued for family reunification with beneficiaries of  protection status). DATA SOURCE - Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following the reference year. AVAILABLE DATASETS I. Residence permits statistics by reason to stay, citizenship and permit's lenght of validity based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007. These statistics are avilable from 2008 reference year.     First Permits - see the definition in the section 3.4. Statistical concepts and definitions.First permits by reason, length of validity and citizenship (migr_resfirst)2. The totals presented in this tables are depended on data availability in the following four tables migr_resfam + migr_resedu+ migr_resocc+ migr_resoth.First permits issued for family reasons by reason, length of validity and citizenship (migr_resfam)First permits issued for education reasons by reason, length of validity and citizenship (migr_resedu)First permits issued for remunerated activities by reason, length of validity and citizenship (migr_resocc)First permits issued for other reasons by reason, length of validity and citizenship (migr_resoth)     Residence Permits issued with the occasion of changing the immigration status or reason to stayChange of immigration status permits by reason and citizenship (migr_reschange)               Residence permits valid in the end of the yearAll valid permits by reason, length of validity and citizenship on 31 December of each year (migr_resvalid)Long-term residents by citizenship on 31 December of each year (migr_reslong)     Share of long term residence permitsLong-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%) (migr_resshare) II. Residence permits statistics by age (5-year age groups) and sex collected on voluntary basis. These statistics are avilable from 2010 reference year.First permits by reason, age, sex and citizenship (migr_resfas)  All valid permits by age, sex and citizenship on 31 December of each year (migr_resvas)               Long-term residents by age, sex and citizenship on 31 December of each year (migr_reslas) III. EU Blue Cards data collection based on Article 20 of the Directive 2009/50/EC. These statistics are avilable from 2012 reference year2.EU Blue Cards by type of decision, occupation and citizenship (migr_resbc1)       Admitted family members of EU Blue Cards holders by type of decision and citizenship (migr_resbc2)EU Blue Cards holders and family members by Member State of previous residence (migr_resbc3) IV. Single Permit data collection based on Art 15 Directive 2011/98/EU. These statistics are avilable from 2013 reference year.Single Permits issued by type of decision, length of validity (migr_ressing)  V. Pilot data collections collected on voluntary basis. These statistics are avilable from 2016 reference year and the data quality assesment is ongoing.Long-term residence permits issued during the year (migr_resltr)First permits issued for family reunification with a beneficiary of protection status (migr_resfrps1)Permits valid at the end of the year for family reunification with a beneficiary of protection status (migr_resfrps2) VI. New statistics on Intra-Corporate Transfers and Seasonal Workers New data collections with 2017 first reference period are in the preparetion phase to be released in 2018: Intra-Corporate Transfers data collection under Art 24 of Directive 2014/66/EU and Seasonal Workers data collection under Art 26 Directive 2014/36/EU.   Share of long-tem residence permits The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories.   Data consistency between tables The data providers should use the same methodological specifications provided by Eurostat and some tables from Resper statistics should be consistent between them according to this methodology.  However, consistency issues between tables exist due to some technical limitations (e.g. different data sources) or different methodology applied to each table (see the quality information from below or the national metadata files) or different point in time of producing each tables.   1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions. 2 The EU Blue cards issued during the year are collected in two datasets: 1. in the table migr_resocc countig the EU Blue Cards issued as "first permits" and 2. in the EU Blue Cards counting all EU Blue Cards issued. The diference between these two categories is represented by the EU Blue cards that are not first permits. However these two tables might be updated/revised at a different point in time and the consistency between tables might be affected.

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to: first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on: EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

Residence permits data contain statistical information based on Article 6 of Council Regulation (CE) No 862 of 11 July 2007 with reference to:first permits granted to third-country nationals during the reference year, disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit; permits granted during the reference period on the occasion of person changing immigration status or reason to stay, disaggregated by citizenship, reason for the permit being issued and by the length of validity; permits valid at the end of the reference period, disaggregated by citizenship, reasons for the permit being issued and by the length of validity; number of long-term residents at the end of reference period. Statistics on EU Blue Cards contain information based on the Article 20 of the Council Directive 2009/50/EC of 25 May 2009 on:EU Blue Cards granted, renewed and withdrawn;Admitted family members of EU Blue Cards holders;EU Blue Cards holders and family members by Member State of previous residenceStatistics on Single permits contain information based on the Article 15 (2) Directive 2011/98/EU of the European Parliament and of the Council of 13 December 2011 on a single application procedure for a single permit for third-country nationals to reside and work in the territory of a Member State and on a common set of rights for third-country workers legally residing in a Member State. Eurostat collects data on first permits granted to third-country nationals (persons who are not EU citizens) during the reference year and data on permits valid at the end of the reference period. Statistics are disaggregated by citizenship, reason for the permit being issued and by the length of validity of the permit. In addition, Eurostat collects data on permits granted during the reference period on the occasion of the person changing immigration status or reason for stay (disaggregated by reason for the new permit being issued) and on the number of long-term residents at the end of the reference period. Since the 2010 reference year, data on first permits issued, stock of all valid permits and the number of long-term residents are additionally collected with a voluntary disaggregation by age (5-year age groups) and sex. These statistics are collected by Eurostat on an annual basis. Data are entirely based on administrative sources with the exception of the United Kingdom1 and are provided mainly by the Ministries of Interior or related Immigration Agencies. Data are generally disseminated in June and July in the year following  the  reference year. The indicators presented in the table 'Long-term residents among all non-EU citizens holding residence permits by citizenship on 31 December (%)' are produced within the framework of the pilot study related to the integration of migrants in the Member States, following the Zaragoza Declaration. The Zaragoza Declaration, adopted in April 2010 by EU Ministers responsible for immigrant integration issues, and approved at the Justice and Home Affairs Council on 3-4 June 2010, called upon the Commission to undertake a pilot study to examine proposals for common integration indicators and to report on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators. In June 2010 the ministers agreed "to promote the launching of a pilot project with a view to the evaluation of integration policies, including examining the indicators and analysing the significance of the defined indicators taking into account the national contexts, the background of diverse migrant populations and different migration and integration policies of the Member States, and reporting on the availability and quality of the data from agreed harmonised sources necessary for the calculation of these indicators". These indicators are produced on the basis of residence permit statistics collected by Eurostat on the basis of Article 6 of the Migration Statistics Regulation 862/2007. As a denominator data on the stock of all valid permits to stay at the end of each reporting year are used. As a numerator data on the stock of long-term residents are used.  Two types of long term residents are distinguished in accordance with the residence permit statistics: EU long-term resident status (as regulated by the Council Directive 2003/109/EC) and the National long-term resident status (as regulated by the national legislation in the Member States). Data for some countries may be a subject of revisions due to certain inconsistencies between categories. 1Please note that the statistics for the United Kingdom use different data sources to those used in other Member States. For that reason, the statistics on residence permits published by Eurostat for UK may not be fully comparable with the statistics reported by other countries. Statistics for the United Kingdom are not based on records of residence permits issued (as the United Kingdom does not operate a system of residence permits), but instead relate to the numbers of arriving non-EU citizens permitted to enter the country under selected immigration categories. According to the United Kingdom authorities, data are estimated from a combination of information due to be published in the Home Office Statistical Bulletin 'Control of Immigration: Statistics, United Kingdom' and unpublished management information. The 'Other reasons' category includes: diplomat, consular officer treated as exempt from control; retired persons of independent means; all other passengers given limited leave to enter who are not included in any other category; non-asylum discretionary permissions.

This table contains 7 series, with data starting from 1972 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Commodity (7 items: Total, all commodities; Total excluding energy; Energy; Metals and Minerals; ...).  

This database contains capture production statistics by country or territory, species item, and FAO Major Fishing Area.

The Fisheries R&D expenditures dataset contains the budgetary expenditures in research and development on total budgetary FSE. Three variables are presented in this dataset:  • R&D expenditures - they are budgetary expenditures that finance research and development activities related to fisheries, irrespective of the institution (private or public, ministry, university, research centre or fisher group) or where they take place, the nature of research (scientific, institutional, etc.), or its purpose. The focus is on research and development expenditures on applied research related to the fisheries sector. Social-sciences research related to fisheries is included. It is also included data dissemination when associated primarily with research and development (knowledge generation), e.g. reports from research and databases developed as an adjunct to research. •FISHERIES SUPPORT ESTIMATE - Budgetary - it is the annual monetary value of gross transfers from taxpayers to fishers arising from policy measures that support fisheries, regardless of their nature, objectives or impacts. Data on FSE are collected by the Fisheries Committee (COFI) from the Trade and Agriculture Directorate (TAD) on an annual basis from all its participating countries. Data are provided by Fisheries Ministries, National Statistics Offices and other institution designated as an official data source. The original financial data is collected in national currency at current values; they are converted and published also in US dollars, for analytical purposes and to allow data comparisons. • Share of R&D expenditures on FSE - it is the share of budgetary research and development expenditures on total budgetary FSE. Please notice that total budgetary FSE is defined ‘net’, i.e. it is adjusted for costs incurred by fishers in order to receive the support. Whenever these costs are of significant amount, total budgetary FSE becomes remarkably low or negative. The corresponding share of research and development expenditures turns into a percentage exceptionally high or negative.

The OECD Fisheries Support Estimates (FSE) database is intended to be the best source of information on fisheries policies in OECD members and participating non-OECD economies.   It is designed to monitor and quantify developments in fisheries policy, to establish a common basis for policy dialogue among countries, and to provide economic data to assess the effectiveness and efficiency of policies.   These tables report country programmes data aggregated according to the main categories presented in the FSE Manual.   More detailed documentation on country programmes can be found in country-level metadata; more data on country programmes can be found in the full dataset (Excel Format - link provided below). Statistics are organized in pivot tables to make possible cross-country comparisons and to filter disaggregated policy-level data by policy implementation criteria and country.   The FSE data collection is part of the more comprehensive data gathering carried out on an annual basis by the Fisheries Committee (COFI) of the Trade and Agriculture Directorate (TAD) from OECD members and participating non-OECD economies.   Data on landings, aquaculture production, inland fisheries catch, fleet, employment, total allowable catch (TAC) and fisheries support estimate (FSE) are collected from Fisheries Ministries, National Statistics Offices and other institutions designated as an official data source. The surveys used for this exercise are the OECD Fisheries questionnaires.

Fisheries fleet: The FAO has a two dimensional definition, of which the OECD only uses the concept of fishing vessel. Fishery Fleet: The term "fishery fleet" or "fishery vessels" refers to mobile floating objects of any kind and size, operating in freshwater, brackishwater and marine waters which are used for catching, harvesting, searching, transporting, landing, preserving and/or processing fish, shellfish and other aquatic organisms, residues and plants. Fishing vessel: The term "fishing vessel" is used instead when the vessel is engaged only in catching operations. Gross Register Tonnage: The Gross Register Tonnage represents the total measured cubic content of the permanently enclosed spaces of a vessel, with some allowances or deductions for exempt spaces such as living quarters (1 gross register ton = 100 cubic feet = 2.83 cubic metres).

The data are on the total number, tonnage and power of fishing vessels broken down by tonnage classes, power classes, length classes, age classes.

The data are on the total number, tonnage and power of fishing vessels broken down by tonnage, length, age and power classes, and by gear categories.

The total number of fishing vessels of EU Member States, Iceland and Norway. In general the data refer to the situation of the national fleets on 31 December of the reference year. EU data are extracted from the Community Fishing Fleet Register managed by the Directorate-General for Fisheries and Maritime Affairs, with the data for Iceland and Norway being supplied directly by the national authorities.

The total tonnage of the fishing fleets of EU Member States, Iceland and Norway. The period covered by this table is that of the transition of measuring the tonnage in Gross Registered Tonnage (GRT) to that in Gross Tonnage (GT). This change which has taken place at different speeds within the national administrations gives rise to the possibility of non-comparability of data over time and, particularly for the earlier period, of non-comparability between countries.

Canada: Fixed weighted index of average hourly earnings for all employees, by industry, monthly Fixed weighted index (2002=100) of average hourly earnings for all employees, by North American Industry Classification System (NAICS), last 5 months.

Annual provincial data for new residential construction, renovations and the total, by asset, price and type of flow or stock.

El flujo de salida de nacionales para el empleo hace referencia al número de ciudadanos legales de un país dado que cambiaron su país de residencia habitual por otro país en el período de referencia por motivos relacionados con el empleo. Para obtener más información, consulte la descripción de la base de datos Estadísticas internacionales de migración laboral (ILMS).

El flujo de salida de nacionales hace referencia al número de ciudadanos legales de un país dado que cambiaron su país de residencia habitual por otro país en el período de referencia. El país de residencia habitual de una persona es el país en que la persona tiene un lugar donde normalmente pasa su tiempo diario de reposo. Los viajes temporarios al extranjero por placer, vacaciones, negocios, tratamiento médico o peregrinación religiosa no implican ningún cambio en el país de residencia habitual. Para obtener más información, consulte la descripción de la base de datos Estadísticas internacionales de migración laboral (ILMS).

country of birthKosovo: 2008-03-04, Sweden declared Kosovos independence.country of birthData for countries with fewer than 100 persons in total are reported in the country group other countries of birth.Population for all countries of birth is reported in this table: Population by country of birth, age and sex.years since last immigrationYears since last immigration to Sweden is based on registered year of immigration. 0 years means that immigration to Sweden took place during the reference year, 1 year means that immigration took place the year before the reference year, etc.

Number of persons born abroad, (according to present time borders), whether in other EU Member States or non-EU countries, who are usually resident in the reporting country on 1 January of the respective year.

The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.

The database contains data on the production and trade in roundwood and primary wood and paper products for all countries and territories in the world. The main types of primary forest products included in are: roundwood, sawnwood, wood-based panels, pulp, and paper and paperboard. These products are detailed further. The definitions are available. The database contains details of the following topics: - Roundwood removals (production) by type of wood and assortment - Production and trade in roundwood, woodfuel and other basic products - Industrial roundwood by assortment and species - Sawnwood, panels and other primary products - Pulp and paper & paperboard. More detailed information on wood products, including definitions, can be found at http://www.fao.org/forestry/statistics/80572/en/

Fowl and chicken meat production, weight and farm value, Canada and provinces (birds unless otherwise noted x 1,000). Data are available on an annual basis.

This table includes the areas of all brassicas, leafy and stalked vegetables, vegetables cultivated for fruit, root, tuber and bulb vegetables, fresh pulses, other vegetables harvested fresh (not dry), including melons, and strawberries grown on arable land outdoor in rotation with other agricultural or horticultural crops and under glass or high accessible cover. This indicator uses the concepts of "harvested area". The "harvested area" corresponds to the total sown area for the production of a specific crop during the same year (i.e. the sum of the areas sown and harvested more than once in the same year) excluding the non-harvested area. For instance, radishes have a cropping time of between 4 and 6 weeks. If 1 ha is sown and harvested four times, within the same year, and all the sown area is harvested except the last one, where only 80% of the field is harvested, then the harvested area will be 3,8 hectares (4 hectares minus non harvested area 0,2 hectares).

Con el objetivo de promover la comparabilidad internacional, las estadísticas presentadas en ILOSTAT se basan en definiciones internacionales estándar siempre que sea posible y pueden diferir de las cifras nacionales oficiales. Esta serie se basa en las definiciones de la 13.ª CIET. Para la comparabilidad de series temporales, incluye países que han implementado las normas de la 19.ª CIET, cuyos datos también están disponibles en la base de datos Work Statistics -- 19.ª CIET (WORK). La fuerza de trabajo se refiere a la suma de todas las personas en edad de trabajar que están empleadas y las que están desempleadas. Para obtener más información, consulte la descripción de la base de datos Estadísticas del mercado laboral rural y urbano (RURBAN).

The Future of Business Survey is an original source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the survey is a partnership between Facebook, OECD, and the World Bank. It provides timely information on business owners’ assessment of the current state and future outlook of their business, job creation perspectives, main business challenges and participation in international trade. Several data breakdowns are available, in particular by size of the enterprise, age, sector, trading status and gender of owners or managers.

El concepto de ganancias, aplicado a las estadísticas de salarios, se refiere a la remuneración bruta en efectivo y en especie pagada a los asalariados, en general a intervalos regulares, por el tiempo trabajado o el trabajo realizado, junto con la remuneración por períodos de tiempo no trabajados, tales como vacaciones anuales y otros tipos de vacaciones pagas o días feriados. Para obtener más información, consulte la página de conceptos y definiciones.

Las ganancias de los asalariados se refieren a la remuneración bruta en efectivo y en especie pagada a los asalariados, en general a intervalos regulares, por el tiempo trabajado o el trabajo realizado, junto con la remuneración por períodos de tiempo no trabajados, tales como vacaciones anuales y otros tipos de vacaciones pagas o días feriados. Las ganancias excluyen las contribuciones que el empleador paga respecto de sus asalariados a los regímenes de seguridad social y de pensiones, así; como las prestaciones recibidas de esos regímenes por los trabajadores. También excluyen las indemnizaciones por despido y por terminación del contrato de trabajo. Las estadísticas de ganancias se refieren a las ganancias brutas de los asalariados, es decir, antes de cualquier deducción por parte del empleador. Se trata de una serie armonizada: (1) los datos referentes a ganancias semanales o anuales fueron convertidos a ganancias mensuales en moneda local utilizando datos sobre las horas de trabajo (donde estaban disponibles); y (2) los datos se presentan en dólares estadounidenses como moneda común, utilizando la tasa de cambio con el dólar US o las tasas de paridad de poder adquisitivo (PPA) de 2017 para el gasto de consumo privado. Esta última serie permite de realizar comparaciones internacionales teniendo en cuenta las diferencias de precio relativas entre países. Para obtener más información, consulte la página de conceptos y definiciones.

NEW METHODOLOGY (from 2007 onwards) Average half-yearly natural gas prices for households and industrial end-users. The end-users are characterised by predefined annual consumption bands.  The prices are collected and published considering three levels of taxation: prices excluding taxes and levies;prices excluding VAT and other recoverable taxes;prices including all taxes, levies and VAT   OLD METHODOLOGY (until 2007) Natural gas prices for households and industrial standard consumers, valid on 1st January and on 1st   July of each calendar year. Standard consumers are characterised by predefined annual consumption. The prices include gas basic price, transmission, system services, meter rental, distribution and other services. The prices are collected and published considering three levels of taxation (see above under new methodology): For structural indicators tables, where only annual data is displayed both for new and old methodology in the same table, the prices refer to the price on 1st January of each year (until 2007) and to the first semester of each year (2008 and later).For further details see : Data on energy prices are collected according to Directive 2008/92/EC of the European Parliament and of the Council of 22 October 2008 concerning a Community procedure to improve the transparency of gas and electricity prices charged to industrial end-users (recast) (Text with EEA relevance). Data for gas prices for household end-users are collected on a voluntary basis Gas prices are presented at national level for the Members of the European Union (except Cyprus and Malta for industrial end users, expect Cyprus (is not providing data for households), Malta and Finland, EFTA-country Liechtenstein, Candidate countries (except The former Yugoslav Republic of Macedonia, Albania for households and except Albania for industrial end-users), Potential candidate country Kosovo (under UNSCR 1244/1999). 

NEW METHODOLOGY (from 2007 onwards) Average half-yearly natural gas prices for households and industrial end-users. The end-users are characterised by predefined annual consumption bands.  The prices are collected and published considering three levels of taxation: prices excluding taxes and levies;prices excluding VAT and other recoverable taxes;prices including all taxes, levies and VAT   OLD METHODOLOGY (until 2007) Natural gas prices for households and industrial standard consumers, valid on 1st January and on 1st   July of each calendar year. Standard consumers are characterised by predefined annual consumption. The prices include gas basic price, transmission, system services, meter rental, distribution and other services. The prices are collected and published considering three levels of taxation (see above under new methodology): For structural indicators tables, where only annual data is displayed both for new and old methodology in the same table, the prices refer to the price on 1st January of each year (until 2007) and to the first semester of each year (2008 and later).For further details see : Data on energy prices are collected according to Directive 2008/92/EC of the European Parliament and of the Council of 22 October 2008 concerning a Community procedure to improve the transparency of gas and electricity prices charged to industrial end-users (recast) (Text with EEA relevance). Data for gas prices for household end-users are collected on a voluntary basis Gas prices are presented at national level for the Members of the European Union (except Cyprus and Malta for industrial end users, expect Cyprus (is not providing data for households), Malta and Finland, EFTA-country Liechtenstein, Candidate countries (except The former Yugoslav Republic of Macedonia, Albania for households and except Albania for industrial end-users), Potential candidate country Kosovo (under UNSCR 1244/1999).