Estadísticas de la UE. CDE Universitat de València

BannerCurious about the well-being of Europeans and how you personally compare to the EU27 average and other EU Member States? If so, take a look at our updated interactive visualisation to have an insight into the different aspects of quality of life by country.

Housing, employment, education, health, safety, governance, and the environment are all covered as well as people’s use of time and social relations. The mix of statistical indicators with objective information such as income, housing conditions and work situations together with subjective evaluations results in differing levels of satisfaction depending on an individual’s priorities and needs. Have fun discovering Europe’s quality of life (also available in French and German). [+]


CoverNew Eurostat visualisation tool for the circular economy

The transition towards a circular economy is not just about recycling more. The circular economy is a cross-cutting issue covering how we produce and use energy, emissions of greenhouse gases and pollutants to the air, food intake and food waste, and accumulation of material stocks in our society, among other things.

Eurostat is publishing a new experimental interactive visualisation tool for the circular economy: the Sankey diagram of material flows. We invite you to play around and explore material flows by country, year and material type. Discover what happens to the materials you use or discard every day. The diagram is now interactive and includes new features, such as time graphs, pie charts and animations where you can visualise the changes over time. You can display or hide data values and labels, and choose between different units (tonnes per capita, billion tonnes, and other).

The diagram shows the flow of materials as they pass through the EU economy and are eventually discharged back into the environment or re-fed into economic processes. The green loop represents materials recovered from waste recycled and other waste reused. The diagram shows them to scale with other flows such as imports, natural resources extracted from the natural environment, exports, emissions to air (mostly from energy production), and more. [+]

CoverEuropean Statistical System (ESS) handbook for quality and metadata reports — 2020 edition

The ESS handbook for quality and metadata reports is recognised as an ESS standard and included in the catalogue of ESS standards thus representing a visible component of the ESS standardisation process. It updates the 2014 ESS handbook on quality reports (EHQR) and has been profoundly revised after the endorsement of SIMS V2.0 by the ESSC in November 2015. This publication fully incorporates SIMS V2.0 combining the ESS Standard for Quality Report Structure (ESQRS) and the Euro-SDMX Metadata Structure (ESMS), and follows the structure of SIMS V2.0. The handbook includes revised guidelines, many examples of existing reports, new material on administrative data, big data, multi-source processes, and other information. [+]

CoverKey figures on Europe — Statistics visualised — 2020 edition

This digital publication called Key figures on Europe — Statistics visualised allows you to get a quick and interactive overview of the situation of your country and compare it to some other European countries. The different visualisation tools offers you a playful way to dig into selected statistics focusing on the following six subjects: population, living conditions, health, working life, income and expenditure and social life. [+]

CoverEuropean business profiling — Recommendations manual — 2020 edition

In official statistics, the enterprise has long been associated with its purely legal definition, the legal unit. With economic globalisation, large multinational enterprise groups (MNE groups) are more and more complex in terms of their legal organisation. This has led to a growing gap between the view of the productive system based on legal units and the economic reality. To address this challenge, the National Statistical Institutes (NSIs) decided to go beyond the legal unit and to implement a new statistical unit, the enterprise. The implementation of the enterprise is done by business profiling.

In the last decade, Eurostat has encouraged European NSIs to cooperate in order to achieve a relevant and consistent cross-border view of MNE groups. This method is called “European Business Profiling”. It is carried out collaboratively by the profiling teams of the NSIs of the different countries where an enterprise group is located. This manual provides recommendations on profiling MNE groups in the scope of European Business Profiling, and more generally guidance for business profiling. [+]

CoverEurostatistics — Data for short-term economic analysis — 2020 edition — 02/2020

Eurostatistics — Data for short-term economic analysis — shows the evolution of the economic activity in the European Union, euro area and Member States. This monthly review gives a synthetic picture of the macroeconomic situation in the recent past. It is based on Principal European Economic Indicators (PEEIs), complemented by some business cycle indicators. [+]

CoverEurostatistics — Data for short-term economic analysis — 2020 edition — 01/2020

Eurostatistics — Data for short-term economic analysis — shows the evolution of the economic activity in the European Union, euro area and Member States. This monthly review gives a synthetic picture of the macroeconomic situation in the recent past. It is based on Principal European Economic Indicators (PEEIs), complemented by some business cycle indicators. [+]

CoverMicro- and macro-drivers of child deprivation in 31 European countries — 2020 edition

This paper analyses child deprivation in 31 European countries, using the scale officially adopted in March 2018 to measure child-specific deprivation at EU level. It combines single level and multilevel models to get a full picture of child deprivation drivers in EU countries. With regard to within-country differences, our results confirm the combined impact of variables related to the “longer-term command over resources” and variables indicating “household needs”. However, our results also show that the relationship of these variables with child deprivation differs between countries. In the richest countries, the explanatory power of the variables related to household needs is the largest, whereas in the most deprived countries, the explanatory power of resource variables is generally greater. With regard to between-country differences, the specification of the model needs careful consideration. We argue that multilevel models should include household income at the micro level, if the aim is to fully gauge the impact of households’ “longer-term command over resources” at the micro level. The multilevel model then assesses how much country-level features that are not reflected in household income and other individual characteristics at the micro level contribute to explaining differences across countries in deprivation. We find that public spending on in-kind social benefits is significant in this respect. Public spending on cash transfers plays only a limited role, when household incomes at the micro level are included; they play a significant role when household income is excluded. This does not diminish the importance of cash transfers in fighting child deprivation, but it qualifies the conclusions of papers which have analysed the relationship of social transfers on deprivation, using multilevel models but without controlling for individual household income. Finally, we find a significant relationship of GDP per capita, even when individual household incomes are included. This is not self-evident: it shows that GDP per capita is a proxy for important contextual variables which are not reflected in individual incomes and other individual characteristics. [+]

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CoverQuality report of the European Union Labour Force Survey 2018 — 2020 edition

The purpose of this quality report is to provide the users of the European Union Labour Market Statistics with a tool for assessing the quality of these statistics which are based on the European Union Labour Force Survey. It provides a brief description of the survey and a summary of the main quality indicators which are: relevance, accuracy, accessibility and clarity, timeliness and punctuality, comparability, and coherence. The quality report is updated annually. [+]

CoverThe comparability of the EU-SILC income variables: review and recommendations — 2020 edition

EU-SILC is the most important microdata source for studying income and living conditions across the European Union. In this paper, we study variations between countries with respect to how individual income components are aggregated into the EU-SILC target variables. In particular, we look at compliance with Eurostat guidelines, misclassifications and omitted income sources, all potentially undermining cross-national comparability. On the basis of a survey among national statistical institutes, we compiled a database which maps the exact classification of income components onto the EU-SILC target variables. The focus of the database is on EU-SILC 2015, covering 26 EU-SILC countries. The database contains information on the composition of variables on total income before and after transfers; income from benefits, work and capital; social contributions and taxes. As a result of this exercise, we outline some general conclusions with regard to (1) cross-national deviations with regard to the calculation of the EU-SILC total income variables; (2) the classification of national income components (e.g. particular benefits) that can be considered “borderline cases” which are currently classified inconsistently across countries; (3) possibilities for improving the definition of target variables; (4) the (unjustified) omission of some income components from EU-SILC target variables; (5) recommendations that may be helpful to improve the comparability of EU-SILC in the future. [+]

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