Estadísticas de la UE. CDE Universitat de València

CoverA decomposition of the unadjusted gender pay gap using Structure of Earnings Survey data

This publication provides information on the data source, the methodology and statistical software used by Eurostat to decompose the unadjusted gender pay gap, and the results of this decomposition. The unadjusted gender pay gap combines possible differences in pay between men and women, for ‘equal work or work of equal value’, with the impact of differences in the average characteristics of men and women in the labour market. To measure the impact of differences in the average characteristics of men and women, Eurostat has used microdata from the Structure of Earnings Survey 2014. A statistical method known as the Blinder-Oaxaca decomposition method was applied on this dataset to isolate the contribution of each observed characteristic to the unadjusted gender pay gap. Eurostat’s methodology and results should help data users and policy makers to better interpret the unadjusted gender pay gap. [+]

 

CoverQuality issues regarding the measurement of working time with the Labour Force Survey (LFS)

This report describes the problems with measuring working time coherently across countries in the European Labour Force Survey, with a special focus on actual working time in the reference week of the survey. The first part of the report gives a brief overview of the results for all EU member states, plus Iceland, Norway, Switzerland, the Former Yugoslav Republic of Macedonia, and Turkey. More in-depth case studies are provided for Denmark, Finland, France, Germany, Italy and Switzerland.

As working time is a key component of labour market statistics, Eurostat commissioned a task force to solve these comparability and measurement problems. The recommend improvements from the task force are also presented here. [+]

CoverLabour market attractiveness in the EU

In this work we present a framework developed for the European Big Data Hackathon 2017. This framework is divided in two parts: an exploration part, which is aimed to better understand the EU global labour market and to capture its heterogeneity; and an inferential part, whose goal is to establish associations between characteristics of the EU labour market and indicators designed to capture important aspects of the labour market (i.e. Skills mismatch, Mobility and Emigration). For the exploration part, we developed the concept of Labour Market Attractiveness, which consists of a combination of socio-economic and demographic variables from Eurostat datasets. Using data mining techniques, such as social networks and clustering analysis, we showed that this combined set consistently captured the country-level heterogeneity in the EU, forming well-defined clusters. For the inferential part, we used model selection analysis and weighted network correlation analyses to establish associations between the characteristics of the EU labour market and the labour market indicators. We argue that the combination of both exploration and inferential parts can disentangle the complex dynamics of the EU labour market and help setting effective policies to tackle typical problems of a fast-changing global labour market environment. [+]

CoverLabour Force Survey in the EU, candidate and EFTA countries – Main characteristics of national surveys 2016

The present report describes the main characteristics of the Labour Force Surveys in the 28 Member States of the European Union, as well as two Candidate Countries and three EFTA countries in 2016. All these countries provide Eurostat with LFS micro-data for publication. The aim of this report is to provide users with the means to accurately interpret the LFS results by providing information regarding the technical features of the Labour Force Surveys carried out in these countries. [+]

CoverQuality report of the European Union Labour Force Survey 2015

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. [+]

CoverHigh income and affluence: Evidence from the European Union statistics on income and living conditions (EU-SILC)

This working paper examines the top tail of the income distributions in the 2012 EU-SILC data. First, it discusses issues related to data quality, including under-estimation of top incomes. Then, the data are used as they are to compute several income-based measures of affluence. Finally, the link between non-income information and high incomes is analysed. The working paper shows that EU-SILC is a useful complementary source on high incomes, in particular when the aim is to measure the size of the economically very well-off group. It also shows that identifying the affluent only on the basis of relative incomes is not sufficient. In a number of countries, many households in the upper tail of the income distribution report having difficulties in making ends meet. [+]

CoverKey Figures on Europe — 2016 edition

Key figures on Europe presents a selection of topical data. Most data cover the European Union and its Member States, while some indicators are provided for other countries, such as members of EFTA, enlargement countries to the European Union. This publication may be viewed as an introduction to European statistics and provides a starting point for those who wish to explore the wide range of data that is freely on Eurostat’s website. [+]

CoverLabour force survey in the EU, candidate and EFTA countries — Main characteristics of national surveys, 2015

The present report describes the main characteristics of the Labour Force Surveys in the 28 Member States of the European Union, as well as two Candidate Countries and three EFTA countries in 2015. All these countries provide Eurostat with LFS micro-data for publication. The aim of this report is to provide users with the means to accurately interpret the LFS results by providing information regarding the technical features of the Labour Force Surveys carried out in these countries. [+]

CoverQuality report of the European Union Labour Force Survey 2014

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. [+]

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