The dataset contains all the raw data and elaboration in support of the latest editions of the List of Critical Raw Materials for the EU

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from European Parliament hosted by the EU Open Data Portal. The Open Data Portal is found here and they update their information according the amount of data that is brought in. Explore European Parliament data using Kaggle and all of the data sources available through the European Parliament organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the EU ODP API and Kaggle's API.

This dataset is distributed under the following licenses: Dataset License

Cover photo by Tamara Menzi on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

From 2018 to 2023, data protection authorities (DPA) in countries across the European Union, (EU) have received numerous coumplaints — however, only 1.3 percent of total complaints resulted in a fine. Slovakia's DPA was ahead of every other country, as 6.84 percent of complaints resulted in fines.

Trade Balance: swda: EU 27E: Brazil: Food and Live Animals for Food data was reported at -1.214 EUR bn in Feb 2025. This records a decrease from the previous number of -0.935 EUR bn for Jan 2025. Trade Balance: swda: EU 27E: Brazil: Food and Live Animals for Food data is updated monthly, averaging -0.625 EUR bn from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of -0.353 EUR bn in Feb 2003 and a record low of -1.343 EUR bn in Aug 2022. Trade Balance: swda: EU 27E: Brazil: Food and Live Animals for Food data remains active status in CEIC and is reported by Eurostat. The data is categorized under Global Database’s European Union – Table EU.JA028: Eurostat: Trade Statistics: By SITC: European Union: Brazil.

Trade Balance: EU 27E: Extra EU: Raw Materials data was reported at 0.622 EUR bn in Feb 2025. This records an increase from the previous number of 0.254 EUR bn for Jan 2025. Trade Balance: EU 27E: Extra EU: Raw Materials data is updated monthly, averaging -0.067 EUR bn from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 0.681 EUR bn in Mar 2021 and a record low of -0.719 EUR bn in Oct 2022. Trade Balance: EU 27E: Extra EU: Raw Materials data remains active status in CEIC and is reported by Eurostat. The data is categorized under Global Database’s European Union – Table EU.JA020: Eurostat: Trade Statistics: By SITC: European Union: European Countries Outside of EU.

European Union Exports: swda: EU 27E: Extra EU: Beverages & Tobacco data was reported at 1.268 EUR bn in Feb 2025. This records a decrease from the previous number of 1.306 EUR bn for Jan 2025. European Union Exports: swda: EU 27E: Extra EU: Beverages & Tobacco data is updated monthly, averaging 0.851 EUR bn from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 1.378 EUR bn in Jun 2023 and a record low of 0.451 EUR bn in Jan 2002. European Union Exports: swda: EU 27E: Extra EU: Beverages & Tobacco data remains active status in CEIC and is reported by Eurostat. The data is categorized under Global Database’s European Union – Table EU.JA020: Eurostat: Trade Statistics: By SITC: European Union: European Countries Outside of EU.

A subset of Tenders Electronic Daily (TED) data covering public procurement for the European Economic Area, Switzerland, and the Republic of North Macedonia from 2006-01-01 to 2019-12-31 in comma separated value format. This data includes the most important fields from the contract notice and contract award notice standard forms, such as who bought what from whom, for how much, and which procedure and award criteria were used.

Generally, the data consists of tenders above the procurement thresholds. However, publishing below threshold tenders in TED is considered good practice, and thus a non-negligible number of below threshold tenders is present as well.

Please see the document below for important information on the data and its usage, including a version history of the export.

The European Commission is interested in the results of research on public procurement coming from the re-use of this data. Thus, we will be grateful to receive links to any papers, reports, or applications at GROW-B4@ec.europa.eu.

TED with broader coverage is also available in XML format at https://data.europa.eu/euodp/en/data/dataset/ted-1.

European Union Trade Balance: swda: EU 27E: Extra EU: Manufactured Gds data was reported at 2.153 EUR bn in Feb 2025. This records an increase from the previous number of 2.055 EUR bn for Jan 2025. European Union Trade Balance: swda: EU 27E: Extra EU: Manufactured Gds data is updated monthly, averaging 1.270 EUR bn from Jan 2002 (Median) to Feb 2025, with 278 observations. The data reached an all-time high of 2.655 EUR bn in Aug 2012 and a record low of -0.671 EUR bn in Oct 2021. European Union Trade Balance: swda: EU 27E: Extra EU: Manufactured Gds data remains active status in CEIC and is reported by Eurostat. The data is categorized under Global Database’s European Union – Table EU.JA020: Eurostat: Trade Statistics: By SITC: European Union: European Countries Outside of EU.

We collected data on almost the complete population of the merger control decisions by the Directorate-General Competition’s (DG COMP) of the European Commission. We started the data collection with the first year of common European merger control, 1990, and included all years up to 2014. This amounts to 25 years of data on European merger control. With regard to the scope of the decisions, we collected data in all cases where a legal decision document exists. This includes all cases settled in the first phase of an investigation (Art. 6(1)(a), 6(1)(b), 6(1)(c) and 6(2)) and all cases decided in the second phase of an investigation (Art. 8(1), 8(2), and 8(3)). Note that this also includes all cases settled under a ‘simplified procedure’, provided that a legal decision document exists. Furthermore, we also intended to collect data on cases that were either referred back to member states by DG COMP or aborted by the merging parties. While we have collected some data on such cases, data on these cases is not always available. Therefore, we cannot guarantee that the final dataset covers all of these cases. The level of observation is not a particular merger case but a particular product/geographic market combination concerned by a merger. In total, the final dataset contains 5,196 DG COMP merger decisions. For each of this decision, we record a number of observations equal to the number of product/geographic markets identified in the specific transaction. Hence, the total dataset contains 31,451 observations.

The 2016 EU-wide transparency exercise provides detailed bank-by-bank data on capital positions, risk exposure amounts and asset quality on 131 banks from 24 countries of the European Union (EU) and the European Economic Area (EEA). This exercise is part of the EBA's ongoing commitment to enhancing transparency in the EU banking sector.

The data, which is exclusively based on supervisory reporting, is published at the highest level of consolidation for the reference dates of 31 December 2015 and 30 June 2016.

The exercise has been coordinated by the EBA and carried out in close cooperation with the Competent Authorities (CAs) from all relevant jurisdictions. By disclosing comparable figures in a user-friendly format, the EBA aims to promote a greater understanding of capital positions and exposures in the EU banking sector and foster market discipline across the Single Market.

For the first time, the EU-wide transparency exercise is published along with the Risk Assessment Report (RAR) , which is based on a wider sample of 198 banks, of which 41 EU foreign subsidiaries of other EU banks. In the Transparency exercise database, as well as in the interactive tools, data is also disclosed for the bucket "All other banks", which includes the aggregated values for 26 banks which are in the RAR sample but not in the transparency exercise. These banks report to EBA at the highest level of consolidation and therefore their data contributes to the EU averages. The disclosure of figures for the rest of the sample allows users to reconcile Transparency data with respective figures for the EU in the RAR.

Abstract

In 2011, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 5th version 2011 Cross-Sectional User Database as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United Kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 7th version of the 2008 Cross-Sectional User Database (UDB) as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

The 7th version of the 2008 Cross-Sectional User Database (UDB) as released in July 2015 is documented here.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed

European Union - Share of trade with the EU: Share of imports from EU was 61.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for European Union - Share of trade with the EU: Share of imports from EU - last updated from the EUROSTAT on June of 2025. Historically, European Union - Share of trade with the EU: Share of imports from EU reached a record high of 62.00% in December of 2020 and a record low of 57.70% in December of 2012.

Over the last two observations, the revenue is forecast to significantly increase in all regions. From the selected regions, the ranking by revenue in the data center market is forecast to be led by Central & Western Europe with ***** billion euro. In contrast, the ranking is trailed by Eastern Europe with **** billion euro, recording a difference of ***** billion euro to Central & Western Europe. The Statista Market Insights cover a broad range of additional markets.

European Seabirds At Sea (ESAS) assembles offshore monitoring data on seabirds and marine mammals. This international database mostly includes data from the North Sea, yet large parts of the northeastern Atlantic Ocean are covered as well. It finds its origin in the 'Seabirds at Sea' project, which was initiated in 1979 following the discovery of major oil potential in the North Sea and an urgent need to gain more knowledge on the occurrence and distribution of seabirds in their offshore habitat. This led to the execution of large-scale ship-based surveys across the North Sea using a standardized data collection method and a first European-wide data assembly in 1991.

The indicator measures confidence among EU citizens in a selection of EU institutions: the European Parliament, the European Commission, and the European Central Bank. It is expressed as the share of positive opinions (people who declare that they tend to trust) about the institutions. Citizens are asked to express their confidence levels by choosing the following alternatives: ‘tend to trust’, ‘tend not to trust’ and ‘don’t know’ or ‘no answer’. The indicator is based on the Eurobarometer, a survey which has been conducted twice a year since 1973 to monitor the evolution of public opinion in the Member States.

This article examines the thermostatic responsiveness of EU public policy. It inquires into the conditions under which EU policy decisions are responsive to wavering public demands for policy change and how European citizens in turn respond to policy change. The main argument holds that the politicization of EU policy processes facilitates both public and policy responsiveness. My expectations are tested based on a novel database containing information on 15 EU policy issues (2010–2016). The analyses draw from panel data based on Eurobarometer polls and a large-scale content analysis of 5887 media statements in eight European news outlets. The results demonstrate that under politicized conditions, the adoption of EU policy decisions is preceded by increased public support and followed by decreased public support for EU policy change. The facilitating role of politicization is primarily triggered by the mobilization of civil society groups, while media salience and polarization are less consequential for responsiveness.

Belgium - Extra-EU trade: Trade balance was EUR-16221.30 Million in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Belgium - Extra-EU trade: Trade balance - last updated from the EUROSTAT on June of 2025. Historically, Belgium - Extra-EU trade: Trade balance reached a record high of EUR-216.20 Million in December of 2013 and a record low of EUR-55615.60 Million in December of 2022.