ガイアナ

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 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.

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 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.

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.

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.

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

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

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).

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.

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.

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 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 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.

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

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 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.

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.

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 <

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).

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.

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.

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.

The Tax Foundation’s publication Corporate Tax Rates around the World shows how statutory corporate income tax rates have developed since 1980, with data for over 200 jurisdictions for the year 2023. The dataset we compiled for the years 1980 to 2023 is made available as a resource for research.  

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. <

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.

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.

In latest update, the total value of sovereign debt in default at US$443.2 billion in 2020 (0.5 percent of world public debt), up US$143.6 billion (48 percent) from the revised total of US$299.6 billion in 2019. This outpaces the 13 percent increase in gross world public debt. The data by major creditor categories show that the increase was driven mainly by foreign currency bonds in default, which rose by US$121.2 billion. This reflected:new defaults by Argentina, Belize, Ecuador and Surinamea first-time default on foreign currency bonds by Lebanona greater amount of interest arrears from ongoing bond defaults by Venezuela and Puerto Rico Local currency debt in default increased by US$0.9 billion. This was due mainly to Iraq’s restructuring of its short-term debt into debt with longer-term maturities and lower coupon rates.

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.

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.

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:  

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).

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.

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:

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

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.

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.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Data disaggregated by economic activity are provided according to the latest version of the International Standard Industrial Classification of All Economic Activities (ISIC) available for that year. Data may have been regrouped from national classifications, which may not be strictly compatible with ISIC. For more information, refer to the Labour Force Statistics (LFS and STLFS) database description.

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.

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.

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.

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.

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.

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:

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.

Monthly updates of FIFA World Football Men's Ranking 

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.

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.

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

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.

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/

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).

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). 

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 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.

Data from 1st of December 2019. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."

With the aim of promoting international comparability, statistics presented on ILOSTAT are based on standard international definitions wherever feasible and may differ from official national figures. This series is based on the 13th ICLS definitions. For time series comparability, it includes countries that have implemented the 19th ICLS standards, for which data are also available in the Work Statistics -- 19th ICLS (WORK) database. The gender wage gap is unadjusted and is calculated as the difference between average earnings of men and average earnings of women expressed as a percentage of average earnings of men. This indicator provides a measure of the relative difference between the earnings of men and those of women. Data disaggregated by occupation are provided according to the latest version of the International Standard Classification of Occupations (ISCO). Data may have been regrouped from the national classifications, which may not be strictly compatible with ISCO. For more information, refer to the Gender Equality and Non-Discrimination Indicators (GEND) database description.

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).

Public deficit/surplus is defined in the Maastricht Treaty as general government net borrowing/lending according to the European System of Accounts. The general government sector comprises central government, state government, local government, and social security funds. The relevant definitions are provided in Council Regulation 479/2009, as amended.

Public deficit/surplus is defined in the Maastricht Treaty as general government net borrowing/lending according to the European System of Accounts. The general government sector comprises central government, state government, local government, and social security funds. The relevant definitions are provided in Council Regulation 479/2009, as amended.

The general government deficit/surplus is defined in the Maastricht Treaty as general government net lending (+)/net borrowing (-) according to the European System of Accounts. The general government sector comprises central government, state government, local government, and social security funds. The relevant definitions are provided in Council Regulation 479/2009, as amended.

These indicators present total expenditure of general government devoted to three different socio-economic functions (according to the Classification of the Functions of Government - COFOG), expressed as a ratio to GDP. The COFOG divisions covered are 'health', 'education' and 'social protection'.

General government gross fixed capital formation (ESA 2010 code P.51g) consists of resident producers' acquisitions, less disposals of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of government producer or units. Fixed assets are produced assets used in production for more than one year.

The Treaty on the Functioning of the European Union defines this indicator as the ratio of government debt outstanding at the end of the year to gross domestic product at current market prices. For this calculation, government debt is defined as the total consolidated gross debt at nominal value in the following categories of government liabilities (as defined in ESA 2010): currency and deposits (AF.2), debt securities (AF.3) and loans (AF.4). The general government sector comprises the subsectors of central government, state government, local government and social security funds. For further methodological guidance and interpretation, please refer to the Eurostat Manual on Government Deficit and Debt. Total government gross debt in million EUR is shown as well.

The indicator is defined (in the Maastricht Treaty) as consolidated general government gross debt at nominal (face) value, outstanding at the end of the year in the following categories of government liabilities (as defined in ESA 2010): currency and deposits, debt securities and loans. The general government sector comprises the subsectors: central government, state government, local government and social security funds.

The data correspond to quarterly government debt. Public debt is defined in the Maastricht Treaty as consolidated general government gross debt at nominal (face) value, outstanding at the end of the year. Data for the general government sector are consolidated between subsectors at the national level. Data are non-seasonally adjusted.

For the purpose of the Excessive Deficit Procedure (EDP) in the Economic and monetary union (EMU), as well as for the Growth and Stability Pact, the current Protocol 12, annexed to the 2012 consolidated version of the Treaty on the Functioning of the European Union, provides a complete definition of government debt: debt means total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. In this context, the stock of government debt in the Excessive Deficit Procedure (EDP debt) is equal to the sum of liabilities, at the end of year, of all units classified within the general government sector (S.13) in the following categories: AF.2 (currency and deposits) + AF.3 (debt securities) + AF.4 (loans). Basic data are expressed in national currency, converted into euro using end-year exchange rates for the euro provided by the European Central Bank (ECB). The MIP headline indicator is calculated as: [GGDt/GDPt]*100. The indicative threshold is 60% of GDP. The data are expressed in millions of units of national currency and in % of GDP.

The quarterly government debt data are conceptually consistent with the corresponding annual data compiled on a national accounts (EDP and ESA 2010) basis. For the purpose of the Excessive Deficit Procedure (EDP) in the Economic and monetary union (EMU), as well as for the Growth and Stability Pact, the current Protocol 12, annexed to the 2012 consolidated version of the Treaty on the Functioning of the European Union, provides a complete definition of government debt: debt means total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. The data are expressed in million units of national currency and in % of GDP. Data are non-seasonally adjusted. The differences between the annual and quarterly debt figures may arise as a result of different timetables in the transmission on revised data. Annual EDP data notified by Member States in April and October are the subject of a thorough verification by Eurostat, which can lead to a revision of past quarterly data.

General government gross fixed capital formation (ESA 2010 code P.51g) consists of resident producers' acquisitions, less disposals of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of government producer or units. Fixed assets are produced assets used in production for more than one year.

General government output (ESA 2010 code P.1) consists of the products created by general government institutional units (i.e. units within the subsectors central government, state government, local government or social security funds). ESA 2010 category P.1 includes three types of output: market output, output for own final use and non-market output.

The indicator measures the general government total expenditure on law courts according to the classification of the functions of government (COFOG). This includes expenditure on administration, operation or support of civil and criminal law courts and the judicial system, including enforcement of fines and legal settlements imposed by the courts and operation of parole and probation systems; legal representation and advice on behalf of government or on behalf of others provided by government in cash or in services. Law courts include administrative tribunals, ombudsmen and the like, and exclude prison administrations. In computing the per capita indicator, the average National Accounts (NA) population data of the reference year is used as denominator (calculated as the arithmetic mean of the population on 1st January of two consecutive years).

This database contains statistics on production volume and value by species, country or area, fishing area and culture environment

The Global Debt Database (GDD) is the result of a multiyear investigative process that started with the October 2016 Fiscal Monitor. The dataset includes total gross debt of the (private and public) non financial sector for an unbalanced panel of 190 advanced economies, emerging market economies and low-income countries, dating back to 1950. For more details on the methodology and definitions, please refer to Mbaye, Moreno Badia and Chae (2018). 

Contains global production statistics (capture and aquaculture). This database contains the volume of aquatic species caught by country or area, by species items, by FAO major fishing areas, and year, for all commercial, industrial, recreational and subsistence purposes. The harvest from maricultural, aquaculture and other kinds of fish farming is also included

The Global Innovation Index 2023 captures the innovation ecosystem performance of 132 economies and tracks the most recent global innovation trends.  The GII 2023 tracks global innovation trends against a background of uncertainty caused by slow economic recovery from the COVID-19 pandemic, high-interest rates, and geopolitical conflict, but with the promise of the Digital Age and Deep Science innovation waves and technological progress.  

The Global Opportunity Index (GOI) answers a pressing need for information that's vital to a thriving global economy like what policies can governments pursue to attract foreign direct investment (FDI), expand their economies, and accelerate job creation, everything multinational companies, other investors, and development agencies need to know before making large-scale, long-term capital commitments.   Methodology The GOI considers economic and financial factors that influence investment activities as well as key business, legal and regulatory policies that governments can modify to support and often drive investments. Overall, it tracks countries’ performance on more than 50 variables aggregated in five categories, each measuring an aspect of a country’s attractiveness for investors: (1) its economic performance; (2) the ability for investors to access financial services; (3) the cost of doing business; (4) the level of support its institutions provide to businesses; and (5) the extent to which its institutions, policies, and legal system facilitate international integration.

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. <

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 <

Government debt is defined as total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. In this context, the stock of government debt in the Excessive Deficit Procedure (EDP debt) is equal to the sum of liabilities, at the end of year, of all units classified within the general government sector (S.13) in the following categories: AF.2 (currency and deposits) + AF.3 (debt securities) + AF.4 (loans). Basic data are expressed in national currency, converted into euro using end-year exchange rates for the euro provided by the European Central Bank (ECB).

Government Finance Statistics (GFS) form the basis for fiscal monitoring in Europe, most notably for the statistics related to the Excessive Deficit Procedure (EDP). The EDP is established in the Treaty and specified in the Stability and Growth Pact legislation. The Member States report data related to the EDP to the Commission (Eurostat) which, in turn, is responsible for providing the data to the Council. European GFS, including the statistics for the EDP, are produced in accordance with the European System of Accounts 2010 (ESA 2010), the EU manual for national accounts, which in September 2014 replaced the previous version of the national accounting framework ESA 95. It is supplemented by further interpretation and guidance from Eurostat, in particular the Manual on Government Deficit and Debt. Council Regulation 479/2009 as amended requires that Member States report government deficit/surplus (hereinafter deficit) and debt data related to the EDP twice per year: before 1 April and 1 October for the preceding four calendar years and a forecast for the current year. The data are reported in harmonised tables. These tables are designed specifically to provide a consistent framework, with a link to national budgetary aggregates and between the deficit and changes in the debt. They should be fully consistent with GFS data delivered to Eurostat in the ESA 2010 transmission programme. The EDP notification tables contain for general government and its sub sectors: Table 1: Summary table on deficit and debt, including auxiliary indicators (Gross Fixed Capital Formation, Interest and Gross Domestic Product - GDP)Tables 2A - 2D: Transition from the working balance to the deficit/surplus for general government sub sectorsTables 3A - 3E: Transition from the deficit/surplus to the change in debt for general government and its sub sectorsTable 4: Supplementary data. The data are presented in the Eurostat's Statistics Database in national currency, euro/ECU, and percentage of GDP. In order to reflect economic and technological developments and meet user needs, in September 2014 the new national accounting framework ESA 2010 replaced the previous framework ESA 95. This led to revisions of the time series for all Member States (please see Eurostat press release for the impact of the revisions on the government deficit and debt ratios). The main changes relate to the classification of certain entities into government and the treatment of transactions related to pension schemes. Also the concept of government deficit was changed as regards treatment of interest on swaps and forward rate agreements (Commission Regulation 220/2014 amending the Council Regulation 479/2009), according to which these flows are now recorded as financial transaction in line with the core ESA accounting framework.

Government final consumption expenditure (ESA 2010, 3.98) includes two categories of expenditures: the value of goods and services produced by general government itself other than own-account capital formation, and purchases by general government of goods and services produced by market producers that are supplied to households - without any transformation - as social transfers in kind. Values are seasonally adjusted (SA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

The data on contingent liabilities and potential obligations of government are collected in the context of the Enhanced Economic Governance package (the "six-pack") adopted in 2011. In particular, Council Directive 2011/85 on requirements for budgetary frameworks of the Member States requires the Member States to publish relevant information on contingent liabilities with potentially large impacts on public budgets, including government guarantees, non-performing loans, and liabilities stemming from the operation of public corporations, including the extent thereof. The liabilities are called “contingent” in the sense that they are by nature only potential and not actual liabilities. Non-performing loans could imply a potential loss for government if these loans were not repaid. This new data collection represents a step towards further transparency of public finances in the EU by giving a more comprehensive picture of EU Member States’ financial positions3 It is to be underlined that contingent liabilities are not part of the general government (Maastricht) debt as defined in the Council Regulation (EC) No 479/2009 of 25 May 2009 on the application of the Protocol on the excessive deficit procedure annexed to the Treaty establishing the European Community. Eurostat collects and publishes the following indicators: government guarantees, liabilities related to public-private partnerships recorded off-balance sheet of government, liabilities of government controlled entities classified outside general government (public corporations) and non-performing loans. Regarding government controlled entities, it should be mentioned that this refers to  government controlled units, not classified in general government, and which are controlled, directly or indirectly (through other public units), by government. In cases when the government share in a corporation is lower than 50% and government does not have control over an entity, the corporation is not considered as controlled by government. Regarding the control criteria, according to ESA 2010 paragraph 20.18: “Control over an entity is the ability to determine the general policy or programme of that entity (…)”. The criteria to be used for corporations are indicated in ESA 2010 paragraphs 2.38 and further detailed in paragraph 20.309. ESA 2010 paragraph 2.38 specifies that: “General government secures control over a corpo­ration as a result of special legislation, decree or reg­ulation which empowers the government to deter­mine corporate policy. The following indicators are the main factors to consider in deciding whether a corporation is controlled by government:(a) government ownership of the majority of the voting interest; (b) government control of the board or governing body; (c) government control of the appointment and removal of key personnel;(d) government control of key committees in the entity; (e) government possession of a golden share; (f) special regulations; (g) government as a dominant customer; (h) borrowing from government. A single indicator may be sufficient to establish control, but, in other cases, a number of separate indicators may collectively indicate control.”

Main revenue and expenditure items of the general government sector, notified by national authorities in Table 2 of the ESA2010 transmission programme. Data are presented in millions of Euro, millions of national currency units and percentages of GDP. Geographic coverage: EU and euro area, Iceland, Norway and Switzerland. Main sources of data: National authorities (National Statistical Institutes)

The indicator refers to Government Budget Appropriations or Outlays on R&D (GBAORD). GBAORD data measure government support to research and development (R&D) activities, or, in other words, how much priority governments place on the public funding of R&D. GBAORD data are built up using the guidelines laid out in the proposed standard practice for surveys of research and experimental development, the OECD’s Frascati Manual from 2002. GBAORD data are broken down by socio-economic objectives in accordance to the nomenclature for the analysis and comparison of scientific programmes and budgets (NABS 2007).

This table includes the productions of all grapes; in particular, for wine, for table use and for raisins. This indicator uses the concept of "harvested production" which 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.

Gross national disposable income (ESA 2010, 8.95) is the sum of the gross disposable incomes of the institutional sectors. It is equal to: Gross national income (at market prices) + current transfers receivable by resident units from the rest of the world - current transfers payable to non-resident units from the rest of the world. Values are seasonally and calendar adjusted (SCA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

The indicator provided is GERD (Gross domestic expenditure on R&D) as a percentage of GDP. "Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications" (Frascati Manual, 2002 edition, § 63 ). (i) More information on national targets can be found here

This table presents the relative shares of the different sources of funds in R&D. More specifically the indicators provided are percentage of GERD (Gross domestic expenditure on R&D) financed respectively by industry, government, the higher education and the private non profit sector. The fifth source of funds shown, which also make the breakdown complete, is GERD financed from abroad. R&D is an activity where there are significant transfers of resources between units, organisations, sectors and countries. The importance of the source of funding has been recognized in one of the Barcelona targets of the Lisbon agenda where it is said that the appropriate split for R&D is 1/3 financed by public funds and 2/3 by private.

The indicator measures gross domestic expenditure on R&D (GERD) as a percentage of the gross domestic product (GDP). "Research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications" (Frascati Manual, 2002 edition, § 63).

The research and experimental development (R&D) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications (Frascati Manual, 2002 edition, § 63 ). The GDP used in denominator of the MIP indicator comes from the ESA 2010 transmission programme.

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology. Data are presented in million units of national currency.

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology. Data are seasonally adjusted and presented in million units of national currency.

GDP (gross domestic product) is an indicator for a nation´s economic situation. It reflects the total value of all goods and services produced less the value of goods and services used for intermediate consumption in their production. Expressing GDP in PPS (purchasing power standards) eliminates differences in price levels between countries, and calculations on a per head basis allows for the comparison of economies significantly different in absolute size.

GDP (gross domestic product) is an indicator for a nation's economic situation. It reflects the total value of all goods and services produced less the value of goods and services used for intermediate consumption in their production.

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units (ESA 2010, 8.89). It can be defined in three ways: a production approach, an income approach and an expenditure approach. Values are seasonally adjusted (SA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross domestic product (GDP) at market prices is the final result of the production activity of resident producer units (ESA 2010, 8.89). It can be defined in three ways: a production approach, an income approach and an expenditure approach. Data are calculated as chain-linked volumes (i.e. data at previous year's prices, linked over the years via appropriate growth rates). Growth rates 'q/q-1 (sca)' with respect to the previous quarter and 'q/q-4 (sca)' with respect to the same quarter of the previous year are calculated from calendar and seasonally adjusted figures while growth rates 'q/q-4 (nsa)' with respect to the same quarter of the previous year are calculated from raw data.

Gross fixed capital formation consists of resident producers´ aquisitions, less disposals, of fixed tangible or intangible assets. This covers in particular machinery and equipment, vehicles, dwellings and other buildings.

Gross fixed capital formation (GFCF) consists of resident producers' acquisitions, less disposals, of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of producer or institutional units. GFCF includes acquisition less disposals of, e.g. buildings, structures, machinery and equipment, mineral exploration, computer software, literary or artistic originals and major improvements to land such as the clearance of forests. The input data are obtained through official transmissions of national accounts' country data in the ESA 2010 transmission programme. Data are expressed as % of GDP, in million euro and in million units of national currency.

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. <

Gross fixed capital formation (GFCF, ESA 2010, 3.124) consists of resident producers' acquisitions, less disposals, of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of producer or institutional units. GFCF includes acquisition less disposals of, e.g. buildings, structures, machinery and equipment, mineral exploration, computer software, literary or artistic originals and major improvements to land such as the clearance of forests. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology. Seasonally and calendar adjusted data (SCA).

Gross fixed capital formation (GFCF, ESA 2010, 3.124) consists of resident producers' acquisitions, less disposals, of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of producer or institutional units. GFCF includes acquisition less disposals of, e.g. buildings, structures, machinery and equipment, mineral exploration, computer software, literary or artistic originals and major improvements to land such as the clearance of forests. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology. Seasonally and calendar adjusted data (SCA).

Gross fixed capital formation (GFCF, ESA 2010, 3.124) consists of resident producers' acquisitions, less disposals, of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of producer or institutional units. GFCF includes acquisition less disposals of, e.g. buildings, structures, machinery and equipment, mineral exploration, computer software, literary or artistic originals and major improvements to land such as the clearance of forests. Values are seasonally and calendar adjusted (SCA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross national income (at market prices) (ESA 2010, 8.94) represents total primary income receivable by resident institutional units: compensation of employees, taxes on production and imports less subsidies, property income (receivable less payable), gross operating surplus and gross mixed income. It is equal to: GDP (Gross Domestic Product) + primary income receivable by resident institutional units from the rest of the world - primary incomes payable to the rest of the world. Values are seasonally and calendar adjusted (SCA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

This is an indicator of profitability that corresponds to the share of gross operating surplus in turnover. The gross operating surplus is the surplus generated by operating activities after the labour factor input has been recompensed. It can be calculated from the value-added at factor cost less the personnel costs. Turnover is the total of all sales (excluding VAT) of goods and services carried out by the enterprise of a given sector during the reference period.

Gross saving (ESA 2010, 8.96) measures the portion of gross national disposable income that is not used for final consumption expenditure. Gross national saving is the sum of the gross savings of the various institutional sectors. Values are seasonally and calendar adjusted (SCA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE A = Agriculture, forestry, fishing. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE B+C+D+E = Mining and quarrying, manufacturing, electricity, gas and water supply, water supply, sewerage, waste management and remediation activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE C = Manufacturing. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE F = Construction. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE G+H+I = Wholesale and retail trade, repair of motor vehicles and motorcycles, transportation and storage, accommodation and food service activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE J = Information and communication. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE K = Financial and insurance activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE L = Real estate activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE M + N = Professional, scientific and technical activities; administrative and support service activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE O+P+Q = Public administration and defence, compulsory social security, education, human health and social work activities. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is available in a breakdown by 10 main economic activities according to NACE Rev. 2 (Statistical classification of economic activities in the European Community). NACE R+S+T+U = Arts, entertainment and recreation, repair of household goods and other services. The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Gross Value Added (GVA) (ESA 2010, 9.31) is defined as output value at basic prices less intermediate consumption valued at purchasers' prices. GVA is calculated before consumption of fixed capital. GVA is conceptually close to GDP (Gross domestic product), but unlike GDP available in a breakdown by branch of economic activity. 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. <

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 source for regional typology statistics are regional indicators at NUTS level 3 published on the Eurostat website or existing in the Eurostat production database. The structure of this domain is as follows: - Metropolitan regions (met)    For details see http://ec.europa.eu/eurostat/web/metropolitan-regions/overview - Maritime policy indicators (mare)    For details see http://ec.europa.eu/eurostat/web/maritime-policy-indicators/overview - Urban-rural typology (urt)    For details see http://ec.europa.eu/eurostat/web/rural-development/overview

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:

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:

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 20.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

The maritime transport domain contains quarterly and annual data. Maritime transport data refer to gross weight of goods (in tonnes), passenger movements (in number of passengers) as well as for vessel traffic (in number of vessels and in gross tonnage of vessels). Data for transport of goods transported on Ro-Ro units or in containers are also expressed in number of units or number of TEUs (20 foot equivalent units). Data at regional level (NUTS 2, 1 and 0) are also available. The statistics on maritime transport are collected within Directive 2009/42/EC and Commission Decision 2008/861/EC, as amended by Commission Decision 2010/216/EU of the European Parliament and of the Council of 14 April 2010, by Regulation 1090/2010 of the European Parliament and of the Council of 24 November 2010 and by Commission Delegated Decision 2012/186/EU of 3 February 2012. Data are collected by the national competent authorities in the reporting countries using a variety of data sources, such as port administration systems, national maritime databases, customs databases or questionnaires to ports or shipping agents (see section 18.1). The maritime transport data have been calculated using data collected at port level. The data are displayed at port level, regional level, Maritime Coastal Area (MCA) level and country level. The data are presented in six collections, displaying main annual results, short sea shipping, passengers, goods vessel traffic and regional statistics.

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).

The Unemployment - LFS adjusted series (including also Harmonised long-term unemployment) is a collection of monthly, quarterly and annual series based on the quarterly results of the EU Labour Force Survey (EU-LFS), which are, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator. Harmonised unemployment is published in the section 'LFS main indicators', which is a collection of the main statistics on the labour market. However the harmonized unemployment indicators are calculated with special methods and periodidicty which justify the present page. This page focuses on the particularities of the estimation of harmonised unemployment (including unemployment rates). Other information on 'LFS main indicators' can be found in the respective ESMS page, see link in section 'related metadata'. General information on the EU-LFS can be found in the ESMS page for 'Employment and unemployment (LFS)'.  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.

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

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 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.  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).

'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.

Final consumption expenditure 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 (ESA 2010 3.94). Data are calculated as chain-linked volumes (i.e. data at previous year's prices, linked over the years via appropriate growth rates). Seasonally and calendar adjusted data

Final consumption expenditure 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 (ESA 2010 3.94). Data are calculated as chain-linked volumes (i.e. data at previous year's prices, linked over the years via appropriate growth rates). Seasonally and calendar adjusted data.

The gross saving rate of households is defined as gross saving (ESA 2010 code: B8g) divided by gross disposable income (B6g), with the latter being adjusted for the change in the net equity of households in pension funds reserves (D8net). Gross saving is the part of the gross disposable income which is not spent as final consumption expenditure (ESA 2010 8.96). Indicator described is calculated on the basis of quarterly sector accounts data by institutional sectors. Household sector comprises all households, household firms and Non Profit Institutions Serving Households (NPISH) (ESA 2010 codes S14 and S15). Sector accounts are compiled in accordance with European System of Accounts (ESA 2010). Data are expressed in percentage, in non-seasonal adjusted as well as in seasonal and calendar adjusted form.

The gross investment rate of households is defined as gross fixed capital formation (ESA 2010 code: P51g) divided by gross disposable income (B6g), with the latter being adjusted for the change in the net equity of households in pension funds reserves (D8net). Household investment mainly consists of the purchase and renovation of dwellings. Indicator described is calculated on the basis of quarterly sector accounts data by institutional sectors. Household sector comprises all households, household firms and Non Profit Institutions Serving Households (NPISH) (ESA 2010 codes S14 and S15). Sector accounts are compiled in accordance with European System of Accounts (ESA 2010). Data are expressed in percentage, in non-seasonal adjusted as well as in seasonal and calendar adjusted form.

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.

Data Cited at: UNITED NATIONS DEVELOPMENT PROGRAMME, Human Development Data Center The Human Development Index (HDI) is a summary measure of achievements in three key dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices for each of the the three dimensions.

Human resources in science and technology (HRST) as a share of the active population in the age group 25-64. The data shows the active population in the age group 25-64 that is classified as HRST (i.e. having successfully completed an education at the third level or being employed in science and technology) as a percentage of total active population aged 25-64. HRST are measured mainly using the concepts and definitions laid down in the Canberra Manual, OECD, Paris, 1995.

Human resources in science and technology (HRST) as a share of the active population in the age group 15-74 at the regional NUTS 2 level. The data shows the active population in the age group 15-74 that is classified as HRST (i.e. having successfully completed an education at the third level or being employed in science and technology) as a percentage of total active population aged 15-74. HRST are measured mainly using the concepts and definitions laid down in the Canberra Manual, OECD, Paris, 1995.

The objective of these data is to support the growing awareness of policy-makers of the importance of ICT specialists in the economic and social transformations related to digitisation. Eurostat works towards this objective by providing reliable official estimates based on a well-grounded and internationally agreed conceptual framework. A wide range of the EU policy initiatives have demonstrated a need for ICT specialists statistics, with the Agenda for New Skills and Jobs (2010), the Grand Coalition for Digital Jobs (2013) and the EU Skills Panorama (2014) being among the most cited ones. Moreover, the recently updated Digital Single Market strategy accentuates the need for policies aimed at boosting stability in the European labour markets and enhancing the EU competitive position; in this context, monitoring of the ICT specialists' employment gains in importance. ICT specialists' data are constructed using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data production. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. The ICT specialists' indicator and its breakdowns are based on the microdata from the Labour Force Survey (LFS). For this reason, LFS reference metadata needs to be consulted for all questions related to the underlying primary source data (see Related Metadata section). The ICT specialists data is conceptually in accordance with the data collected in the special module on ICT specialists and skills in the survey ICT usage and e-commerce in enterprises (see Related Metadata Section and Annexes for more information), i.e. it operates with the same definition of ICT specialists (see Section 3.4). Representation ICT specialists statistics contains four indicators updated on an annual basis: (1) ICT specialists, total (2) ICT specialists by gender (3) ICT specialists by level of education (4) ICT specialists by age Each indicator is presented in the country/year dimensions and is measured in absolute (1000s) and relative (%) terms. Time coverage Data covers all years starting from 2004 until the latest year available. Following the release practice of the EU LFS, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(4) are updated yearly from 2004 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made in the source data, the EU LFS.

The objective of these data is to support the growing awareness of policy-makers of the importance of ICT specialists in the economic and social transformations related to digitisation. Eurostat works towards this objective by providing reliable official estimates based on a well-grounded and internationally agreed conceptual framework. A wide range of the EU policy initiatives have demonstrated a need for ICT specialists statistics, with the Agenda for New Skills and Jobs (2010), the Grand Coalition for Digital Jobs (2013) and the EU Skills Panorama (2014) being among the most cited ones. Moreover, the recently updated Digital Single Market strategy accentuates the need for policies aimed at boosting stability in the European labour markets and enhancing the EU competitive position; in this context, monitoring of the ICT specialists' employment gains in importance. ICT specialists' data are constructed using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data production. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. The ICT specialists' indicator and its breakdowns are based on the microdata from the Labour Force Survey (LFS). For this reason, LFS reference metadata needs to be consulted for all questions related to the underlying primary source data (see Related Metadata section). The ICT specialists data is conceptually in accordance with the data collected in the special module on ICT specialists and skills in the survey ICT usage and e-commerce in enterprises (see Related Metadata Section and Annexes for more information), i.e. it operates with the same definition of ICT specialists (see Section 3.4). Representation ICT specialists statistics contains four indicators updated on an annual basis: (1) ICT specialists, total (2) ICT specialists by gender (3) ICT specialists by level of education (4) ICT specialists by age Each indicator is presented in the country/year dimensions and is measured in absolute (1000s) and relative (%) terms. Time coverage Data covers all years starting from 2004 until the latest year available. Following the release practice of the EU LFS, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(4) are updated yearly from 2004 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made in the source data, the EU LFS.

The objective of these data is to support the growing awareness of policy-makers of the importance of ICT specialists in the economic and social transformations related to digitisation. Eurostat works towards this objective by providing reliable official estimates based on a well-grounded and internationally agreed conceptual framework. A wide range of the EU policy initiatives have demonstrated a need for ICT specialists statistics, with the Agenda for New Skills and Jobs (2010), the Grand Coalition for Digital Jobs (2013) and the EU Skills Panorama (2014) being among the most cited ones. Moreover, the recently updated Digital Single Market strategy accentuates the need for policies aimed at boosting stability in the European labour markets and enhancing the EU competitive position; in this context, monitoring of the ICT specialists' employment gains in importance. ICT specialists' data are constructed using the secondary statistical analysis. This approach has a virtue of ensuring cost-efficient and high-quality data production. At the same time, this approach has limited options for designing new indicators, as well as for control over data quality and over data release timing. The ICT specialists' indicator and its breakdowns are based on the microdata from the Labour Force Survey (LFS). For this reason, LFS reference metadata needs to be consulted for all questions related to the underlying primary source data (see Related Metadata section). The ICT specialists data is conceptually in accordance with the data collected in the special module on ICT specialists and skills in the survey ICT usage and e-commerce in enterprises (see Related Metadata Section and Annexes for more information), i.e. it operates with the same definition of ICT specialists (see Section 3.4). Representation ICT specialists statistics contains four indicators updated on an annual basis: (1) ICT specialists, total (2) ICT specialists by gender (3) ICT specialists by level of education (4) ICT specialists by age Each indicator is presented in the country/year dimensions and is measured in absolute (1000s) and relative (%) terms. Time coverage Data covers all years starting from 2004 until the latest year available. Following the release practice of the EU LFS, the publication year is calculated as (t+1), with t being the reference year. Data for the indicators (1)-(4) are updated yearly from 2004 until the latest year available (as opposed to simply adding one additional year) to incorporate the latest revisions made in the source data, the EU LFS.

The Fiscal Monitor surveys and analyzes the latest public finance developments, it updates fiscal implications of the crisis and medium-term fiscal projections and assesses policies to put public finances on a sustainable footing. 

The baseline forecast is for the world economy to continue growing at 3.2 percent during 2024 and 2025, at the same pace as in 2023. A slight acceleration for advanced economies—where growth is expected to rise from 1.6 percent in 2023 to 1.7 percent in 2024 and 1.8 percent in 2025—will be offset by a modest slowdown in emerging market and developing economies from 4.3 percent in 2023 to 4.2 percent in both 2024 and 2025. The forecast for global growth five years from now—at 3.1 percent—is at its lowest in decades. Global inflation is forecast to decline steadily, from 6.8 percent in 2023 to 5.9 percent in 2024 and 4.5 percent in 2025, with advanced economies returning to their inflation targets sooner than emerging market and developing economies. Core inflation is generally projected to decline more gradually.

Total number of long-term immigrants arriving into 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:  

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

Eurostat's annual collections of statistics on international migration flows are structured as follows:   Data collection Info & Legislation NOWCAST Annual collection of provisional monthly data on live births and deaths covering at least 6 months of the reference year (Article 4.3 of Commission Implementing Regulation (EU) No 205/2014) and provisional monthly data on migrants covering at least 6 months of the reference year on a voluntary basis. DEMOBAL Demographic balance Annual collection of provisional data on population, total live births and total deaths at national level (Article 4.1 of Commission Implementing Regulation (EU) No 205/2014) and provisional data on total migrants at national level on a voluntary basis. UNIDEMO Unified demographic The most in-depth annual national and regional data collection on demography and migration, for population, births, deaths, immigrants, emigrants, marriages and divorces by a large number of breakdowns. (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EC) No 862/2007).   The aim is to collect annual mandatory and voluntary data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate — legal acts and other agreements’. The quality of the demographic data collected on a voluntary basis depends on the availability and quality of information provided by the national statistical institutes. For more 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:                  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:                   a.   country of citizenship                   b.   country of birth                   c.   country of next residence.

Eurostat's annual collections of statistics on international migration flows are structured as follows:   Data collection Info & Legislation NOWCAST Annual collection of provisional monthly data on live births and deaths covering at least 6 months of the reference year (Article 4.3 of Commission Implementing Regulation (EU) No 205/2014) and provisional monthly data on migrants covering at least 6 months of the reference year on a voluntary basis. DEMOBAL Demographic balance Annual collection of provisional data on population, total live births and total deaths at national level (Article 4.1 of Commission Implementing Regulation (EU) No 205/2014) and provisional data on total migrants at national level on a voluntary basis. UNIDEMO Unified demographic The most in-depth annual national and regional data collection on demography and migration, for population, births, deaths, immigrants, emigrants, marriages and divorces by a large number of breakdowns. (Article 3 of Regulation (EU) No 1260/2013 and Article 3 of Regulation (EC) No 862/2007).   The aim is to collect annual mandatory and voluntary data from the national statistical institutes. Mandatory data are those defined by the legislation listed under ‘6.1. Institutional mandate — legal acts and other agreements’. The quality of the demographic data collected on a voluntary basis depends on the availability and quality of information provided by the national statistical institutes. For more 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:                  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:                   a.   country of citizenship                   b.   country of birth                   c.   country of next residence.

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

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: l

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

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

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.

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 EU Member States average.

The basic or above basic overall digital skills represent the two highest levels of the overall digital skills indicator, which is a composite indicator based on selected activities performed by individuals aged 16-74 on the internet in the four specific areas (information, communication, problem solving, content creation). It is assumed that individuals having performed certain activities have the corresponding skills; therefore the indicator can be considered as a proxy of the digital competences and skills of individuals. The indicator is based on the EU survey on the ICT usage in households and by individuals and is available for the years 2015 and 2016 (it will be compiled in 2017 as well).

Eurostat Dataset Id:ei_bsin_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)

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_bsin_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:sbs_sc_ind_r2 SBS covers the Nace Rev.2 Section B to N and division S95 which are organized in four annexes, covering Industry (sections B-E), Construction (F), Trade (G) and Services (H, I, J, L, M, N and S95). Financial services are covered in three specific annexes and separate metadata files have been compiled. Up to reference year 2007 data was presented using the NACE Rev.1.1 classification. The SBS coverage was limited to NACE Rev.1.1 Sections C to K. Starting from the reference year 2008 data is available in NACE Rev.2. Double reported data in NACE Rev.1.1 for the reference year 2008 will be available in the first and second quarter of 2011. 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) Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. 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' in NACE Rev 1.1 sections H, I, K 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 Rev2 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 for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 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 N°1614/2002 and N°1669/2003. SBS data are collected primarily by National Statistical Institutes (NSI). Regulatory or controlling national offices for financial institutions or central banks often provides the information required for the financial sector (NACE Rev 2 Section K / NACE  Rev 1.1 Section J). 

Since September 2014, national accounts are compiled in accordance with the European System of Accounts - ESA 2010. Supply, use and input-output tables are part of the National Accounts transmission program. The timeliness for supply, use and input-output tables is set to 36 months after the end of the reference year. For example, data for the year 2011 should be transmitted to Eurostat not later tg-han by end of December 2014. The transmission program sets the requirements for the transmission of national data by Member States and partners countries. Every year countries transmit the supply and use tables. Every 5 years (for reference years ending with 0 or 5) countries transmit input-output tables (product by product) and detailed use tables at basic prices and valuation tables. Data are presented in million Euro in current prices (basic prices and a transformation into purchaser's prices for the supply side). The geographic coverage is the Member States of EU. Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union defines the requirements for Member States. The EU and EA consolidated Supply, use and input-output tables describe by product and industry the production processes and the transactions in products of the European Union economy with great detail. The consolidated supply, use and input-output tables for the EU describe the aggregation of the EU Member States data, from which the intra trade data has been treated (respectively for the Euro Area). The data is presented in a framework where the domestic part corresponds to the area of EU, the import part corresponds to imports from outside of the area EU.

Aquaculture, also known as aquafarming, refers to the farming of aquatic (freshwater or saltwater) organisms, such as fish, molluscs, crustaceans and plants, for human use or consumption, under controlled conditions. Aquaculture implies some form of intervention in the natural rearing process to enhance production, including regular stocking, feeding and protection from predators. Farming also implies individual or corporate ownership of, or contractual rights to, the stock being cultivated. European data on the quantity of aquaculture production, in tonnes life weight (TLW), have been recorded since 1950 [fish_aq_q]. Since 1984, data on the total value of the production in Thousand Euro are also available [fish_aq_v]. With the entry into force of the new Regulation (EC) No 762/2008 on the submission of aquaculture statistics aquaculture production data are collected and disseminated annually in 5 tables: fish_aq2a: Aquaculture production at first sale for human consumption (excluding hatcheries and nurseries)  by species, by FAO major area, by cultivation method, by aquatic environment in TLW (tonnes live weight), in Euro and Euro/TLW. fish_aq2b: Production of fish eggs (roe) at first sale for human consumption  by species, by FAO major area, by aquatic environment in TLW, Euro and Euro/TLW.fish_aq3: Input to capture-based aquaculture, i.e. wild seed, by species in TLW, Euro and Euro/TLW.fish_aq4a: Production of fertilised eggs at first sale for further on-growing or release to the wild by species in Millions.fish_aq4b: Production of juveniles at first sale for further on-growing or release to the wild by species in Millions.   According to Regulation (EC) No 762/2008, aquaculture production means the output from aquaculture at first sale intended for human consumption. Non-commercial aquaculture is thus not accounted for. Moreover, aquaculture production of aquarium and ornamental species is excluded as well as production for industrial, functional or research purposes. Every three years, these data are complemented by fish_aq5 data on the structure of the aquaculture sector by species group, FAO major area, production method, aquatic environment in hectares, 1000 cubic metres or metres. Data are submitted by all Member States of the European Economic Area by the 31st of December for the preceding year (reporting year -1). They are compiled by the respective competent authorities of the Member States, usually either the National Statistical Institute or the Ministry of Agriculture. EEA Member States do also provide three annual data on the structure of the aquaculture sector and annual methodological reports of the national systems for aquaculture statistics with details on the respective methods of collecting, processing and compiling aquaculture data as well as quality aspects. This information is currently not published.

Data cited at: International Financial Statistics (IFS), The International Monetary Fund. The International Financial Statistics database covers about 200 countries and areas, with some aggregates calculated for selected regions, plus some world totals. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates. The International Financial Statistics is based on various IMF data collections. It includes exchange rates series for all Fund member countries plus Anguilla, Aruba, China, PR: Hong Kong, China, PR: Macao, Montserrat, and the Netherlands Antilles. It also includes major Fund accounts series, real effective exchange rates, and other world, area, and country series. Data are available for most IMF member countries with some aggregates calculated for select regions, plus some world totals. National Accounts, Indicators of Economic Activity, Labor Markets, Prices, Government and Public Sector Finance, Financial Indicators, Balance of Payments, International Investment Position, International Reserves, Fund Accounts, External Trade, Exchange Rates, and Population.

The estimates are based on official statistics on the foreign-born or the foreign population, classified by sex, and age. Most of the statistics utilised to estimate the international migrant stock were obtained from population censuses. Additionally, population registers and nationally representative surveys provided information on the number and composition of international migrants. The designations employed and the material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory or area or its authorities, or concerning the delimitation of its frontiers or boundaries. The term “country” as used in this publication also refers, as appropriate, to territories or areas. The names and composition of geographical areas follow those presented in “Standard country or area codes for statistical use” (ST/ESA/STAT/SER.M/49/Rev.3), available at http://unstats.un.org/unsd/methods/m49/m49.htm.

The 2022 IPRI classifies 129 countries, representing 93.91% of the world population and 97.73% of the global GDP. The selection of countries was determined solely by the availability of sufficient data. The results continue to suggest that countries with high scores on the IPRI and its components also show high levels of income and development, indicating the positive relationship between a property rights regime and quality of life. The average score of the IPRI for 2022 is  5.19, where the Legal and Political Environment (LP) was the weakest component with a score of 5.06, followed by the Intellectual Property Rights (IPR) component with a score of 5.24; and quite close, the Physical Property Rights (PPR) was the strongest component with a score of 5.27  For the fourth consecutive year, we found a decrease in the overall score of the IPRI and this year, also for all of its components. Finland leads the IPRI (8.17) as well as its PPR component (8.53), while New Zealand leads the LP (8.76) and the USA the IPR component (8.73). Singapore ranks 2nd in its IPRI score (7.97) followed by Switzerland (7.94) and New Zealand (7.93).  

Sport and its spill-over effects in manufacturing, services and as well in international trade are gaining the growing impact in the worldwide economies and societies. As a consequence, sport has been awarded a significant role in numerous European programs and policies like Erasmus+. The comparable statistics on number of jobs created by sport related sectors, value added generated by sport related industries and services or impact of the trade of sport goods on total international trade volume are only few indicators that can assess the relative contribution of sport to the economic growth. The international trade in sport goods is the indicator enabling to measure the weight of trade of sport goods in the whole external trade of a given country or at EU-28 level as the Eurostat international trade domain provides the imports and exports values of goods traded among Member States and internationally. "Goods" in this particular case means all movable property, in other terms products having a physical dimension. So, external trade in licenses and copyrights is not included. Data source International trade statistics are stored in the administrated by Eurostat database on international trade - Comext. Comext contains statistics on goods traded between the EU Member States (intra-EU trade) and goods traded by the EU Member States with non-EU countries (extra-EU trade). The trade values for other political or geographical entities like EFTA and Candidate countries are as well collected. Comext database is built around 6 main dimensions:REPORTERPARTNERFLOWPRODUCTTIMEINDICATOR The Reporter dimension includes country declaring commercial transactions. In the Partner dimension the trade partners of declaring country are included. This dimension lists all the countries of the world. The Flow dimension distinguishes exports and imports. The Indicator dimension specifies the value or volume of traded products. The Product dimension contains the items by HS, CN or SITC depending on the dataset Concerning Time, both annual and monthly breakdowns are available. The Comext data are updated regularly and the CN classification undergoes a regular revision to ensure it is kept up to date in the light of changes in the technology and international trade patterns. Sport goods The frames for the establishment of the list of sport goods provided the Vilnius Definition, the Study on the Contribution of Sport to Economic Growth and Employment in the EU and UNESCO in its framework for cultural statistic. In the final selection of the list of sport goods Eurostat took into account the 'sport content' and ' sport intensity' of the codes identified within the Harmonised Systems (HS) nomenclature. The retained in the sport scope items are explicitly sport related – they are manufactured in sport manufacturing sector and they correspond explicitly to major sport disciplines or equipment. The identified codes by HS (6 digit) are aggregated in the meaningful groups  (see below):Skis and related equipmentSkatesWater sportGolfRacket sport (tennis and badminton)BallsGymnastic, athletic and swimming equipmentFishingBicyclesParachutesSportswearFootwearShotguns Detailed list of codes according to HS composing the aggregates can be found in the Annex 1 of Metadata. Based on the number of dimensions available in Comext, the following indicators can be extracted and then calculated for imports and exports of sport goods.Trade value in thousands of euroPercentage of total national trade (only for total of sport goods)Percentage of total EU-28 tradePercentage of total trade of sport goods Then the data are compiled for the following trade partners:Intra EU-28Extra EU-28 WorldMain trading partners

Sport and its spill-over effects in manufacturing, services and as well in international trade are gaining the growing impact in the worldwide economies and societies. As a consequence, sport has been awarded a significant role in numerous European programs and policies like Erasmus+. The comparable statistics on number of jobs created by sport related sectors, value added generated by sport related industries and services or impact of the trade of sport goods on total international trade volume are only few indicators that can assess the relative contribution of sport to the economic growth. The international trade in sport goods is the indicator enabling to measure the weight of trade of sport goods in the whole external trade of a given country or at EU-28 level as the Eurostat international trade domain provides the imports and exports values of goods traded among Member States and internationally. "Goods" in this particular case means all movable property, in other terms products having a physical dimension. So, external trade in licenses and copyrights is not included. Data source International trade statistics are stored in the administrated by Eurostat database on international trade - Comext. Comext contains statistics on goods traded between the EU Member States (intra-EU trade) and goods traded by the EU Member States with non-EU countries (extra-EU trade). The trade values for other political or geographical entities like EFTA and Candidate countries are as well collected. Comext database is built around 6 main dimensions:REPORTERPARTNERFLOWPRODUCTTIMEINDICATOR The Reporter dimension includes country declaring commercial transactions. In the Partner dimension the trade partners of declaring country are included. This dimension lists all the countries of the world. The Flow dimension distinguishes exports and imports. The Indicator dimension specifies the value or volume of traded products. The Product dimension contains the items by HS, CN or SITC depending on the dataset Concerning Time, both annual and monthly breakdowns are available. The Comext data are updated regularly and the CN classification undergoes a regular revision to ensure it is kept up to date in the light of changes in the technology and international trade patterns. Sport goods The frames for the establishment of the list of sport goods provided the Vilnius Definition, the Study on the Contribution of Sport to Economic Growth and Employment in the EU and UNESCO in its framework for cultural statistic. In the final selection of the list of sport goods Eurostat took into account the 'sport content' and ' sport intensity' of the codes identified within the Harmonised Systems (HS) nomenclature. The retained in the sport scope items are explicitly sport related – they are manufactured in sport manufacturing sector and they correspond explicitly to major sport disciplines or equipment. The identified codes by HS (6 digit) are aggregated in the meaningful groups  (see below):Skis and related equipmentSkatesWater sportGolfRacket sport (tennis and badminton)BallsGymnastic, athletic and swimming equipmentFishingBicyclesParachutesSportswearFootwearShotguns Detailed list of codes according to HS composing the aggregates can be found in the Annex 1 of Metadata. Based on the number of dimensions available in Comext, the following indicators can be extracted and then calculated for imports and exports of sport goods.Trade value in thousands of euroPercentage of total national trade (only for total of sport goods)Percentage of total EU-28 tradePercentage of total trade of sport goods Then the data are compiled for the following trade partners:Intra EU-28Extra EU-28 WorldMain trading partners

Research and experimental development (R) comprise creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society and the use of this stock of knowledge to devise new applications (Frascati Manual, 2002 edition, § 63 ). R intensity (R expenditures as a percentage of GDP) is an indicator of high political importance at the EU, national and regional levels.

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.

The gross investment rate of non-financial corporations is defined as gross fixed capital formation (ESA 2010 code: P.51g) divided by gross value added (B1g). This ratio relates the investment of non-financial businesses in fixed assets (buildings, machinery etc.) to the value added created during the production process. Non-financial corporation includes all private and public corporate enterprises that produce goods or provide non-financial services to the market (ESA 2010 code: S11) Indicator described is calculated on the basis of quarterly sector accounts data by institutional sectors. Sector accounts are compiled in accordance with European System of Accounts (ESA 2010). Data are expressed in percentage, in non-seasonal adjusted as well as in seasonal and calendar adjusted form.

The job vacancy rate (JVR) measures the proportion of total posts that are vacant, according to the definition of job vacancy above, expressed as a percentage as follows: JVR = number of job vacancies / (number of occupied posts + number of job vacancies) * 100. Data for Denmark, France, Italy, Malta are available in table jvs_q_nace2.

A job vacancy is defined as a newly created, unoccupied, or about to become vacant, post. The job vacancy rate (JVR) measures the proportion of total posts that are vacant expressed as a percentage as follows: JVR = number of job vacancies * 100 / (number of occupied posts + number of job vacancies). Data are non-seasonally adjusted except for Czech Republic and UK. Job vacancy rates for DK, FR, IT and MT are probably under-estimated due to a partial coverage of the respective economies.

Job vacancy statistics (JVS) provide information on the level and structure of labour demand. Eurostat publishes quarterly data on the number of job vacancies and the number of occupied posts which are collected under the JVS framework regulation and the two implementing regulations: the implementing regulation on the definition of a job vacancy, the reference dates for data collection, data transmission specifications and feasibility studies, as well as the implementing regulation on seasonal adjustment procedures and quality reports. Eurostat disseminates also the job vacancy rate which is calculated on the basis of the data provided by the countries. Eurostat publishes also the annual data which are calculated on the basis of the quarterly 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 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 non-financial Quarterly Sector Accounts (QSA) are compiled in accordance with the European System of Accounts (ESA 2010) and are transmitted by the EU Member States and EEA Members (Norway, Iceland) following ESA2010 transmission programme (Table 801) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). The QSA encompass non-financial accounts that provide a description of the different stages of the economic process: production, generation of income, distribution of income, redistribution of income, use of income and non-financial accumulation. The ASA record the economic flows of institutional sectors in order to illustrate their economic behaviour and interactions between them. They also provide a list of balancing items that have high analytical value in their own right: value added, operating surplus and mixed income, balance of primary incomes, disposable income, saving, net lending / net borrowing. All of them but net lending / net borrowing, can be expressed in gross or net terms, i.e. with and without consumption of fixed capital that accounts for the use and obsolescence of fixed assets. In terms of institutional sectors, a broad distinction is made between the domestic economy (ESA 2010 classification code S.1) and the rest of the world (S.2). Within S.1 and S.2, in turn, more detailed subsectors are distinguished as explained in more detail in section "3.2 Classification system". Data are presented in the table "Non-financial transactions" (nasq_10_nf_tr). The table contains data, as far as they are available, expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 1999 Q1 (unless subject to voluntary transmission option and/or country specific derogations). Available level of detail by sectors and transactions may also vary by country due to voluntary transmission of some items (as defined in ESA2010 transmission programme) and country specific derogations. QSA collected according ESA2010 Transmission programme include selected data on employment (in persons and hours worked) and seasonally adjusted variables by institutional sectors. However, as transmission of these variables is voluntary (except for the selected seasonally adjusted variables of Total economy and the Rest of the world), data availability may vary significantly across countries. A set of key indicators, deemed meaningful for economic analysis, is available in the table "Key indicators" (nasq_10_ki) for most of the members of the European Economic Area (EEA), of the Euro area and EU. Key indicators are generally released in non-seasonally adjusted terms. Only EA/EU aggregate key indicators are also available seasonally adjusted. Key ratios are derived from non-financial transactions as follows:Gross household saving rate (S.14_S.15): B8G/(B6G+D8rec-D8pay)*100Gross investment rate of households (S.14_S.15): P51G/(B6G+D8rec-D8pay)*100Gross investment rate of non-financial corporations (S.11): P51G/B1G*100Gross profit share of non-financial corporations (S.11): B2G_B3G/B1G*100 With the following transaction codes:B6G - Gross disposable incomeB8G -  Gross savingD8rec / D8pay - the adjustment for the change in pension entitlements (receivable / payable)P51G - Gross fixed capital formationB1G - Gross value addedB2G_B3G - Gross operating surplus/ mixed income. The following seasonally adjusted key indicators are calculated in real terms for European aggregates only: Nominal growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC)Real growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC*Price Deflator)Real growth of household actual consumption per capita (percentage change on previous period, S.14_S.15): P4/(POP_NC*Price Deflator) With the following codes (the codes already described above have not been listed): B7G - Gross adjusted gross disposable income (adjusted for social transfers in kind)P4 - Actual final consumption (adjusted for social transfers in kind)POP_NC - Total population national concept (source:Quarterly national accounts, Eurobase domain namq_10_pe)Price deflator - Price index/implicit deflator calculated as CP_MEUR/CLV05_MEUR – both indicators refer to households and NPISH final consumption expenditure (P31_S14_S15) (source: Quarterly national accounts, Eurobase domain namq_10_gdp) In the above, all ratios are expressed in gross terms, i.e. before deduction of consumption of fixed capital. The following key indicators combine non-financial with financial accounts:Household net financial assets ratio (BF90/(B6G+D8net)) With the following codes (the codes already described above have not been listed):BF90 – Financial net worth "rec" means resources, that is transactions that add to the economic value of a given sector. "pay" means "uses", that is transactions that reduce the economic value of a given sector. "liab" refers to the stock of liabilities incurred by a given sector and recorded in the financial balance sheets. See also the sector accounts dedicated website for more information.

The non-financial Annual Sector Accounts (ASA) are compiled in accordance with the European System of Accounts (ESA 2010) and are transmitted by the EU Member States, EEA Members (Norway, Iceland) and Switzerland following ESA2010 transmission programme (Table 8) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). The ASA encompass non-financial accounts that provide a description of the different stages of the economic process: production, generation of income, distribution of income, redistribution of income, use of income and non-financial accumulation. The ASA record the economic flows of institutional sectors in order to illustrate their economic behaviour and interactions between them. They also provide a list of balancing items that have high analytical value in their own right: value added, operating surplus and mixed income, balance of primary incomes, disposable income, saving, net lending / net borrowing. All of them but net lending / net borrowing, can be expressed in gross or net terms, i.e. with and without consumption of fixed capital that accounts for the use and obsolescence of fixed assets. In terms of institutional sectors, a broad distinction is made between the domestic economy (ESA 2010 classification code S.1) and the rest of the world (S.2). Within S.1 and S.2, in turn, more detailed subsectors are distinguished as explained in more detail in section "3.2 Classification system". Data are presented in the table "Non-financial transactions" (nasa_10_nf_tr). The table contains data, as far as they are available, expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 1995 (unless subject to voluntary transmission option and/or country specific derogations). Countries may transmit longer series on voluntary basis. Available level of detail by sectors and transactions may also vary by country due to voluntary transmission of some items (as defined in ESA2010 transmission programme) and country specific derogations. ASA collected according ESA2010 Transmission programme include selected data on employment (in persons and hours worked) by institutional sectors. However, as transmission of these variables is voluntary (except for the sector of General government), data availability may vary significantly across countries. A set of key indicators, deemed meaningful for economic analysis, is available in the table "Key indicators" (nasa_10_ki) for most of the members of the European Economic Area (EEA), of the Euro area and EU. Key ratios are derived from non-financial transactions as follows: Gross household saving rate (S.14_S.15): B8G/(B6G+D8rec-D8pay)*100Gross investment rate of households (S.14_S.15): P51G/(B6G+D8rec-D8pay)*100Gross investment rate of non-financial corporations (S.11): P51G/B1G*100Gross profit share of non-financial corporations (S.11): B2G_B3G/B1G*100Total investment to GDP ratio (S.1): P51G/B1GQ*100Business investment to GDP ratio: (S.11_P51G+S.12_P51G)/B1GQ*100Government investment to GDP ratio: S.13_P51G/B1GQ*100Households investment to GDP ratio: (S.14_S.15_P51G)/B1GQ*100 With the following transaction codes: B8G -  Gross savingB6G - Gross disposable incomeD8rec / D8pay - the adjustment for the change in pension entitlements (receivable / payable)P51G - Gross fixed capital formationB1G - Gross value addedB1GQ – Gross domestic productB2G_B3G - Gross operating surplus/ mixed income. In the above, all ratios are expressed in gross terms, i.e. before deduction of consumption of fixed capital. The following key indicators are calculated in real or nominal terms: Real growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC*Price Deflator)Nominal growth of household adjusted disposable income per capita (percentage change on previous period, S.14_S.15): B7G/(POP_NC)Real growth of household actual consumption per capita (percentage change on previous period, S.14_S.15): P4/(POP_NC*Price Deflator) With the following codes (the codes already described above have not been listed): B7G - Gross adjusted gross disposable income (adjusted for social transfers in kind)P4 - Actual final consumption (adjusted for social transfers in kind)POP_NC - Total population national concept (source:Quarterly national accounts, Eurobase domain namq_10_pe)Price deflator - Price index/implicit deflator calculated as CP_MEUR/CLV10_MEUR – both indicators refer to households and NPISH final consumption expenditure (P31_S14_S15) (source: Quarterly national accounts, Eurobase domain namq_10_gdp) The following key indicators combine non-financial with financial accounts: Gross return on capital employed, before taxes, of non-financial corporations (S.11): [B2G_B3G/(AF2+AF3+AF4+AF5, liab)]*100Net debt-to-income ratio, after taxes, of non-financial corporations (S.11): ([(AF2+AF3+AF4, liab)/(B4N-D5pay)]*100)Net return on equity, after taxes, of non-financial corporations (S.11): [(B4N-D5pay)/(AF5, liab)]*100Gross debt-to-income ratio of households (S.14_15): [(AF4, liab)/(B6G+D8net)]*100Household net financial assets ratio (BF90/(B6G+D8net)) With the following codes (the codes already described above have not been listed): B4N - Net entrepreneurial incomeD5pay - Current taxes on income and wealthAF2 - Currency and depositsAF3 - Debt securities (excluding financial derivatives)AF4 - LoansAF5 - Equity and investment fund sharesBF90 – Financial net worth "rec" means resources, that is transactions that add to the economic value of a given sector. "pay" means "uses", that is transactions that reduce the economic value of a given sector. "liab" refers to the stock of liabilities incurred by a given sector and recorded in the financial balance sheets. See also the sector accounts dedicated website for more information.