Estadísticas de la UE. CDE Universitat de València

Eurostat publishes a new synthetic indicator on total earning gaps

This article presents gender statistics for the European Union (EU), a selection of indicators from fields such as education, labour market, earnings and health, which are particularly important for measuring differences in the situation of women and men (i.e. gender gaps). Gender statistics constitute an area that cuts across traditional fields of statistics to identify, produce and disseminate data reflecting the realities of the lives of women and men, and policy issues relating to gender equality[1].
The indicators show gender gaps, together with levels achieved for the population as a whole, at EU level and across Member States (e.g. the gender employment gap with the employment rate). This approach shows gender gaps in access to resources and opportunities in the broader context of the actual resources and opportunities available. The article includes links to other articles and publications that provide more detailed analysis of gender gaps. [+]

Government expenditure on public order and safety
EU-27 government expenditure on public order and safety at 1.9 % of GDP in 2012
Statistics in focus 7/2014

In the framework of the European System of National Accounts (ESA95), Eurostat collects data on general government expenditure by economic function according to the international Classification of the Functions of Government (COFOG) – see methodological note. This publication presents for the first time detailed COFOG data on public order and safety for the European countries. This became possible due to progress in the availability and quality of voluntarily transmitted COFOG level II data. [+]

Three quarters of Europeans used the internet in 2013
Statistics in focus 29/2013
This article presents an overview of the findings of the 2013 ‘Survey on ICT (information and communication technology) usage in households and by individuals’. It takes a closer look at internet users’ activities and a set of newly released indicators on online interaction with public authorities and public services (‘e-government’). [+]

Intergenerational transmission of disadvantage statistics
Is the likelihood of poverty inherited?
Statistics in focus 27/2013
One of the headline targets of the Europe 2020 strategy for jobs and smart, sustainable and inclusive growth is the reduction of poverty by lifting at least 20 million people out of the risk of poverty or social exclusion by 2020. Poverty is a multidimensional socioeconomic phenomenon caused both by aggregated factors such as macroeconomic, social and labour policies and by individual factors like level of education, health or social interaction in society. The analysis of intergenerational disadvantages is aimed at measuring the extent of transmission or persistence of individual factors through generations. The European Union statistics on income and living conditions (EU-SILC) 2011 data are used for the purpose of the analysis. [+]

CoverThe use of registers in the context of EU–SILC: challenges and opportunities - 2013 edition
This Working Paper examines the following rules in the EU-SILC survey, that is, a set of rules defining which people will be followed and interviewed from year to year, and under what circumstances. More specifically the study look at these rules in terms both of the wording of the regulations, and on how these regulations are interpreted and implemented. Particular attention is paid to the percentages of the sample re-interviewed following household splits, and an assessment of the implications of these on the suitability of the EU-SILC for longitudinal analysis of the effects of household splits is made. Considerable variations are found in practice across the countries covered by the EU-SILC. Among households experiencing a split, large percentages of those remaining in the original sample household are followed, but only very low percentages of those moving to a split-off household. While this does not have a major impact on overall attrition rates, it does mean that the EU-SILC may not be suitable for longitudinal analysis of specific groups. Analysis of individuals leaving the family home following divorce or separation is particularly problematic, while analysis of young home-leavers is possible in a number of countries, though it should be undertaken with caution. [+]

CoverHousehold composition, poverty and hardship across Europe - 2013 edition
This Working Paper examines the relationship between household composition and several measures of income sufficiency, including two measures of relative poverty and two measures of subjective hardship. Data from the European Union Statistics on Income and Living Conditions (EU-SILC) are used to calculate the risk of poverty and hardship by household type for all countries in the EU. It is found that whereas the importance of different household types varies greatly between countries, the same household types are at the highest risk of poverty and hardship in virtually all countries: lone parents, single elderly people, and other single-adult households. However, while these at-risk groups account for a majority of the poor population across Northern and Western Europe, they account for only a minority of the poor population across Eastern and Southern Europe. [+]

CoverEuropean social statistics - 2013 edition
The pocketbook European social statistics, intended for both generalists and specialists, provides a comparative overview of the social statistics available in 27 Member States and the Candidate Countries of the European Union, as well as in the EFTA states. Different areas of the social field are described here by a selection of indicators which are presented in tables and graphs and accompanied by short commentaries. This pocketbook may be viewed as an introduction to European social statistics and provides guidance to the vast range of data freely available from the Eurostat website. [+]

CoverUsing EUROMOD to nowcast poverty risk in the European Union - 2013 edition
This Working Paper explains how estimates of current (2012) income, risk-of-poverty and inequality (“nowcasts”) can be made using 2008 Statistics on Income and Living Conditions data (EU SILC) and the European Union tax-benefit microsimulation model EUROMOD. The method is illustrated for eight EU countries, among those experiencing the most volatile economic conditions in the period of the projection (2007-2012): Estonia, Greece, Spain, Italy, Latvia, Lithuania, Portugal and Romania. The method is evaluated by comparing results for 2008 to 2010 with statistics available from the EU-SILC corresponding to the same income reference periods. Nowcasts for 2011 and 2012 are also provided. [+]

Página 4 de 5

Esta web utiliza cookies con una finalidad estadistica y para mejorar su navegación