Differences in Gender Norms Between Countries: Are They Valid? The Issue of Measurement Invariance

The values and attitudes towards gender roles are often investigated and compared from a cross-country perspective without the proper statistical treatment of the measurement invariance (MI) assessment. This implies that the conclusions based on composite scales of gender norms, gender role attitudes or gender egalitarianism, to name only a few, may be questionable. In this study, we address this lack by investigating the cross-country MI properties of the Gender Equality Scale (GES) based on World Value Survey data. We use multi-group confirmatory factor analysis with and without alignment to determine the configural, weak, strong and strict MI. The results show that the concept of gender equality is not comparable across all countries involved in the survey. In particular, it seems to differ between Western Europe and Central and Eastern Europe. We claim that only selected Central and Eastern European countries exhibit a configural MI but fail to show full weak MI and definitely fail to show full strong and full strict MI. However, under the aligned measurement framework, we succeeded in showing that for these countries, comparisons of the country rankings with respect to the GES are valid provided that a correction for non-invariance of certain factor loadings and/or intercepts is applied. Our study shows that the most egalitarian gender role attitudes measured by the GES are observed in the Czech Republic, Hungary, Lithuania and Croatia. They are significantly higher than the gender equality attitudes recorded in the lowest scoring countries Poland, Slovakia, Albania and Romania.JRC.DDG.01-Econometrics and applied statistic

Trust, local governance and quality of public service in EU regions and cities

The aim of this report is to present the within-country variability in the EU citizens’ perceptions of the generalised and institutional trust, quality of public service and local governance based on their experiences and opinions expressed in three surveys. By within-country variability we understand differences in citizens’ perceptions between cities or between (1) cities and (2) towns, suburbs and rural areas. We deal with the citizens’ opinions expressed in the surveys we used. The within-country variability in EU citizens’ perceptions of the trust, corruption, local governance and quality of public service and governance are investigated using several composites presenting the differences in citizens’ perceptions from three different perspectives and using three different data sets. First, with the European quality of life survey, we explore the level of (1) general trust, (2) institutional trust and (3) quality of public service in different with respect to degree of urbanisation areas in the EU countries. Second, with the Social Diagnosis survey, we examine the level of general trust and attitude towards free riding in 27 of the largest Polish cities. Finally, using data from the World Justice Project we investigate perceptions of law enforcement, generalised and institutional trust, corruption, bribing and performance of the local government in 58 of the largest EU cities. Our results showed that in general, there are differences in measured phenomena between EU countries, and especially within EU countries in relation to the degree of urbanisation and at city level.JRC.DDG.01-Econometrics and applied statistic

Monitoring multidimensional poverty in the regions of the European Union

In this study, we measure the area-specific poverty in the European Union (EU). To this end, we measure poverty at the sub-national level in two ways: (i) using the EU nomenclature of territorial units (NUTS 1 mostly); (ii) using different with respect to the degree of urbanisation areas within countries. The measurement of poverty is based on the Multidimensional Poverty Index (UN MPI) by Alkire and Santos (2010, 2013). With the data from the European Union Survey on Income and Living Conditions (EU SILC), we formulate the Index of Multidimensional Poverty at the regional level, namely the Multidimensional Poverty Index (MPI-reg). The MPI-reg framework comprises three dimensions — health, education, and standard of living — quantified by three sub-indexes: Multidimensional Poverty in Health Index (MPI–H), Poverty in Education Index (MPI–E) and Multidimensional Poverty in Living Standards Index (MPI–L), respectively. The MPI-reg was computed for 23 EU countries in 2010, 24 EU countries in 2007 and 2011, and 25 countries in 2008 and 2009. Our results show that the level of poverty in the EU ranges from 2–3 % to 15–25 %, with Denmark and Sweden being unequivocally the least poor countries and Latvia, Bulgaria and Romania, the poorest countries. We also indicate that there is a positive relationship between the stratification level and all adjusted headcount ratios, headcount ratios and intensity of poverty scores. This positive relationship implies that there are countries where there is no stratification with respect to poverty (e.g. Sweden, Denmark, the Czech Republic, and Finland) and countries, usually poor ones, such as Romania, Bulgaria and Lithuania, but also Belgium and Italy, where considerable stratification with respect to poverty occurs. In general, in poor and moderately poor countries, the worst situation with respect to poverty is observed in sparsely populated areas, and the best situation occurs in densely populated areas. On the other hand, in the best scoring countries, poverty is relatively higher in the densely populated areas compared to the less well-populated areas. Additionally, our analysis showed that between 2005–07 and 2009–11, changes in inequality with respect to poverty occurred. We demonstrated that a decrease in inequality most often occurred in Poland and Spain, whereas Belgium and Italy we most often spotted as countries with growing regional differences. The results indicated that the European Union regions are strongly diversified with respect to poverty. This implies that regardless of the spatial location of the region and the definition of the region, considerable within-country differences are indicated if only sub-national levels are available. Therefore, relying only on countrywide estimates may be misleading when properly assessing the relative standing of a region with respect to poverty.JRC.DDG.01-Econometrics and applied statistic

Quality of Life at the sub-national level: an operational example for the EU

This study is the outcome of the European Commission joint project DG JRC / DG REGIO on the measure of quality of life of European regions. European Union cohesion policy supports the economic and social development of regions, especially lagging regions, throughout an integrated approach with the ultimate goal of improving citizens' wellbeing. In this setting, measuring quality of life at the sub-national level is the first step for assessing which regions can assure or have the potential to assure good quality of life and which cannot. The project simultaneously features three innovative points. First the attempt to measure QoL for the European Union regions (NUTS1/NUTS2). Second, the adoption of a type of aggregation, at the lowest level of QoL dimensions, which penalizes inequality across indicators, for mitigating compensability. Third, the inclusion of housing costs in the computation of individual's.JRC.G.3-Econometrics and applied statistic

Gaps and challenges in the knowledge of migration and demography: Proposals for new approaches and solutions

This report is the result of the research carried out under Task 5 of DG JRC's Task Force on Migration and Demography. The report is structured following the four pillars outlined in the European Agenda on Migration. A few additional chapters are included to cover some aspects not explicitly touched on in the Agenda, but still considered to have a relevant role in migration and an impact on demographic trends. Contributions answered the following questions: 1. What are main points/findings/debates concerning the priority area/sub-category allocated to you? 2. How does the information gathered in question 1 relate to the scope and the structure of the European Agenda on Migration? 3. What current information and data is available, who is producing it and how? 4. What and where are the main gaps and challenges? 5. What are the solutions or approaches to address these gaps and challenges based upon your research? To complement this review, two Annexes were created: the first being an overview of the main gaps and challenges as well as the suggested solutions for the whole report (Annex 1), and the second being a preliminary inventory of available migration data and data sources (Annex 2).JRC.E.6-Demography, Migration and Governanc

Worker Well-being and mistreatment - Sri Lanka 2018

This dataset comprises data on mistreatment at work and at home and work outcomes collected in three apparel factories in Sri Lank