The European Union Statistics on Income and Living Conditions (EU-SILC) was first conducted in Germany in 2005 under the name "Live in Europe". For this survey, around 14.000 private households and the persons aged 16 and older living in them are interrogated on a voluntary basis.The emphasis of this survey is on personal and household income, living conditions of the household, health of the respondents, questions on childcare, on employment, and on the assessment of ones finalcial situation. In addition, there are survey emphases that change anually. The EU statistics on income and living conditions is designed as a rotating panel, so it allows for cross section as well as longitudinal section analyses. The survey years are only processed up to 2013. If you are interested in using more up-to-date data, please consider using the Eurostat data supply. Further information on the method can also be found on the Eurostat homepage.
The European Union Statistics on Income and Living Conditions (EU-SILC) was first conducted in Germany in 2005 under the name "Live in Europe". For this survey, around 14.000 private households and the persons aged 16 and older living in them are interrogated on a voluntary basis.The emphasis of this survey is on personal and household income, living conditions of the household, health of the respondents, questions on childcare, on employment, and on the assessment of ones finalcial situation. In addition, there are survey emphases that change anually. The EU statistics on income and living conditions is designed as a rotating panel, so it allows for cross section as well as longitudinal section analyses. The survey years are only processed up to 2013. If you are interested in using more up-to-date data, please consider using the Eurostat data supply. Further information on the method can also be found on the Eurostat homepage.
Purpose: The authors aim to demonstrate the impact of allowing for unequal intra-household distribution of resources on income poverty and income inequality. Design/methodology/approach: The paper applies a collective consumption model to study the intra-household distribution of resources in Visegrád countries (V4). It utilises subjective financial satisfaction as a proxy for indirect utility from individual consumption to estimate the indifference scales within couples instead of the traditional equivalence scale. The European Union Statistics on Income and Living Conditions (EU-SILC) 2013 and 2018 data are applied. Findings: This study's results indicate substantial economies of scale from living in a couple that are generally higher than implied by the commonly applied equivalence scale. The sharing rule estimates suggest that at the mean of distribution factors, women receive a consumption share between 0.4 and 0.6; however, some of the results are close to an equal sharing of 0.5. The female consumption share rises with her contribution to household income. Regarding income poverty and inequality, the authors show that both these measures might be underestimated in the traditional approach to equal sharing of resources. Originality/value: The authors add to the empirics by estimating indifference scales for Czechia (CZ), Hungary (HU), Poland (PL) and Slovakia (SK), countries that have not been involved in previous research.
DDas Europäische System sozialer Indikatoren umfasst eine systematische Auswahl von Zeitreihendaten, die darauf ausgerichtet ist, die individuelle und gesellschaftliche Wohlfahrt sowie Dimensionen des sozialstrukturellen Wandels im europäischen Rahmen vergleichend zu messen und zu beobachten. Neben den Mitgliedsländern der Europäischen Union umfasst das Indikatorensystem zwei weitere europäische Länder sowie – soweit es die Datenlage erlaubt – mit Japan und den USA zwei nicht-europäische Referenzgesellschaften. Durch einen konzeptuellen Rahmen angeleitet, orientierte sich die Entwicklung des Europäischen Systems sozialer Indikatoren an drei Konzepten: Lebensqualität, soziale Kohäsion und Nachhaltigkeit. Während sich das Konzept der Lebensqualität auf Dimensionen der individuellen Wohlfahrt bezieht, umfassen die Konzepte der sozialen Kohäsion und Nachhaltigkeit Merkmale und Dimensionen der gesellschaftlichen oder kollektiven Wohlfahrt. Das Indikatorensystem ist zudem in insgesamt 13 Lebensbereiche untergliedert. Zeitreihendaten liegen für 9 Lebensbereiche vor, die voll implementiert wurden.
Die Zeitreihen beginnen frühestens 1980 und enden in der Regel spätestens 2013. Soweit es die Datenquellen erlauben, umfassen die Zeitreihen jährliche Beobachtungswerte. Die Indikator-Zeitreihen sind überwiegend nach ausgewählten soziodemographischen Merkmalen untergliedert, wie Geschlecht, Altersgruppen, Erwerbsstatus oder Gebietsmerkmalen. Regionale Untergliederungen liegen – soweit sinnvoll und soweit es die Datenquellen erlauben – auf dem NUTS-1 oder ähnlichem Niveau vor. Das Europäische System sozialer Indikatoren stützt sich bevorzugt auf harmonisierte Datenquellen, die eine bestmögliche internationale und intertemporale Vergleichbarkeit gewährleisten. Die verwendeten Datenquellen umfassen sowohl Aggregatdaten der offiziellen Statistik, wie sie z.B. von EUROSTAT oder der OECD bereitgestellt werden, als auch Mikrodaten aus offiziellen und wissenschaftsbasierten internationalen Surveys, wie z.B. der Europäischen Erhebung über Einkommen und Lebensbedingungen (EU-SILC), den Eurobarometer und World Value Surveys oder dem European Social Survey.
Das Europäische System sozialer Indikatoren ist das Ergebnis von Forschungsaktivitäten im Rahmen des früheren Zentrums für Sozialindikatorenforschung von GESIS, die zunächst als Teilprojekt des EuReporting-Projekts (Towards a European System of Social Reporting and Welfare Measurement) durchgeführt und von 1998 bis 2001 von der Europäischen Kommission über das 4. Europäische Forschungsrahmenprogramm gefördert wurden. Für ausführlichere Informationen zum Europäischen System sozialer Indikatoren vergleiche den Methodenbericht unter "andere Dokumente".
Although previous studies have explored how satisfied people are with their travel, the link with the built environment and available travel options is unclear. This research investigates whether travel options influence how commute time satisfaction relates to the built environment. First, profiles among commuters in terms of commute time satisfaction (CTS) and residential built environment (RBE) were identified by performing a cluster analysis using a large European sample with the European Union Statistics on Income and Living Conditions (EU-SILC) 2013 survey. Following, whether travel options (mode availability) could inform differences among CTS-RBE profiles was investigated, while accounting for neighborhood characteristics and satisfaction with life and life domains, by performing logistic regression analyses. Travel options were found to indicate CTS-RBE profiles. This research supports the idea that travel options can affect the CTS-RBE relationship, and can therefore be useful to measuring and correcting travel option unavailability or travel captivity. The contributions of this study to the travel behavior field, in addition to being the first study to examine CTS, is important to urban planning and policy to not only identify the places in which travel options can be improved, but for whom.
In this study, we merge the literature on homeownership regimes, which focuses to a lesser extent on the consequences of wealth and social inequality, with the literature on wealth and social stratification, which overlooks the importance of homeownership regimes in contributing to those inequalities. Within this framework, we examine to what extent homeownership regimes shape class inequality in homeownership among young adults and the mortgage debt burden that usually accompanies it. We first develop an updated typology of homeownership regimes that incorporates the role of the family via intergenerational wealth transfers (IWT) such as gifts and housing assets. This dimension was theoretically underdeveloped and empirically absent from previous homeownership typologies. Second, we employ this typology to investigate class-based gaps in homeownership and mortgage debt burden within and between homeownership regimes. This is done by pooling data for a total of 20 countries from two sources: the European Union Statistics on Income and Living Conditions (EU-SILC) 2013–2014 (EuroStat) for EU countries, and the Household Expenditure Survey 2012–2013 (CBS) for Israel. Using multivariate modeling, we find that homeownership regimes in which IWT in the form of financial support is common practice increase class inequality in homeownership compared to regimes in which IWT of assets is common practice. Contrary to the literature suggesting that liberal mortgage markets advance inclusion, it appears that in the homeownership regime characterized by the most liberal housing finance system (which includes Northern European countries and the Netherlands), class inequality in mortgaged homeownership is the widest but class inequality in mortgage debt burden is the narrowest. Homeownership regimes characterized by IWT of assets (which include Southern and Central Eastern European countries) reveal the opposite patterns. We discuss the implications of our findings for the literature on homeownership regimes and wealth inequality, with a specific focus on young adults.
Background: The article investigates the phenomenon of economic insecurity from a feminist perspective, assessing the role of women's labour market participation in predicting the phenomenon. It draws on the work of Trifiletti (1999) to analyse women's role in providing welfare for the entire family. Methods: Stemming from a cross-sectional analysis of European Union statistics on Income and Living Conditions (EU-SILC) 2013, logistic regression models (for women in a couple and for single women) are provided for six countries. Results: The descriptive analysis shows that economic insecurity affects single women more than single men, while couples fare better in all countries considered. Transversal factors that explain the phenomenon in logistic regressions are household type and wealth of the family, while the role of women's labour market participation and economic dependency from partners or from a welfare system varies across countries. Conclusions: Empirical results show that countries only partially comply with the theoretical model proposed by Trifiletti (1999), which proceeded from the welfare regime debate. Italy and Spain show more difference than similarity. The results for Italy and the United Kingdom confirm those of previous investigations that indicate their similarity, while France and Spain are closer to the Mediterranean archetype. The results for the Czech Republic confirm its proximity to the breadwinner model, as Denmark epitomises the heuristic capacity of the Universalist model in Northern European countries.
Background: The article investigates the phenomenon of economic insecurity from a feminist perspective, assessing the role of women's labour market participation in predicting the phenomenon. It draws on the work of Trifiletti (1999) to analyse women's role in providing welfare for the entire family. Methods: Stemming from a cross-sectional analysis of European Union statistics on Income and Living Conditions (EU-SILC) 2013, logistic regression models (for women in a couple and for single women) are provided for six countries. Results: The descriptive analysis shows that economic insecurity affects single women more than single men, while couples fare better in all countries considered. Transversal factors that explain the phenomenon in logistic regressions are household type and wealth of the family, while the role of women's labour market participation and economic dependency from partners or from a welfare system varies across countries. Conclusions: Empirical results show that countries only partially comply with the theoretical model proposed by Trifiletti (1999), which proceeded from the welfare regime debate. Italy and Spain show more difference than similarity. The results for Italy and the United Kingdom confirm those of previous investigations that indicate their similarity, while France and Spain are closer to the Mediterranean archetype. The results for the Czech Republic confirm its proximity to the breadwinner model, as Denmark epitomises the heuristic capacity of the Universalist model in Northern European countries.
The at-risk-of-poverty rate is one of the three indicators used for monitoring progress towards the Europe 2020 poverty and social exclusion reduction target. Timeliness of this indicator is critical for monitoring the effectiveness of policies. However, due in part to the complicated nature of the European Union Statistics on Income and Living Conditions (EU-SILC), estimates of the number of people at risk of poverty are published with a 2 to 3 year delay. This paper presents a method of estimating ('nowcasting') the current distribution of income between households, including the at-risk-of-poverty rate, using a tax-benefit microsimulation model (EUROMOD) based on the EU-SILC, combined with up-to-date macro-level statistics. The method is applied to 13 EU Member States experiencing differing economic conditions over the period, including those which have been affected comparatively little by the crisis as well as those which have suffered a major reduction in economic activity and employment.
Previous studies suggest the relative importance of the impact of childcare policies on mental health in parents. There have also been studies showing that welfare states have differing policy packages, consisting of a mixture of familizing and individualizing policy measures. This study builds on and extends this knowledge by carrying out a European comparison of the association between mental well health and family policies. We use Lohmann and Zagel's familizing and individualizing policy indices to describe family policies. Our main interest is differences in mental health depending on the country, household, and individual-level characteristics. Therefore, we apply a multilevel model to 26 countries included in the 2013 wave of the European Union Statistics on Income and Living Conditions survey (N = 141,648). The analysis found that, in general, parents of children under 13 have better mental health than other adults. We found individualizing policy measures to be positively related to mental health in parents, while familizing policies had a negative relationship. No evidence was found for the combined presence of individualizing and familizing policies making a difference to mental health in parents. These results suggest that welfare states could help parents by promoting individualizing policies to make parenthood a less stressful experience.
The article deals with identifying key determinants of poverty in Slovakia. The two main goals of this article are to examine which factors have a significant effect on poverty and to determine the influence of relevant factors on poverty of Slovak households. A logistic regression model was used to quantify the impact of selected factors on the risk of the poverty and for probability modelling. We compared two models, using data from EU SILC 2013 and EU SILC 2016. Statistically significant differences are by the region and also by the degree of urbanization. We found that variables such as gender, age, household type, households' economic activity, marital status, education, health, and tenure status significantly affected the occurrence of poverty. According to contingency coefficients, the rate of poverty was at most influenced by the economic activity, on the other hand, the lowest rate was obtained for general health of the person at the head of the household. The obtained results are compared with the known researches in this field.
O presente estudo visou a construção e validação de um instrumento de avaliação da literacia em saúde oral para a população adulta portuguesa. A escala de Literacia em Saúde Oral (ELSO) é constituída por 107 itens, organizados em 3 subescalas de literacia em saúde oral: Funcional; Comunicacional; Crítica. 108 indivíduos, 73,1% do sexo feminino, com idades entre 18 e 72 anos (M=32.08; DP=12.33) responderam a um questionário sociodemográfico-clínico, à ELSO e à Dental Anxiety Inventory - DAI. O questionário apresenta boa sensibilidade, elevada fidelidade e uma validade aceitável, sendo que o estudo da sua estrutura deverá merecer aprofundamento.
La Organización Mundial de la Salud (OMS) define salud como un estado de perfecto (completo) bienestar físico, mental y social, y no sólo la ausencia de enfermedad. Alcanzar este estado es objetivo natural del ser humano y de las administraciones públicas y gobiernos. Establecer cuáles son los factores determinantes de la salud y su incidencia ayuda a conseguir este objetivo. La Unión Europea ha llevado a cabo la European Health Interview Survey (EHIS), cuya segunda oleada se realizó entre 2013 y 2015, actualizada en Abril de 2019 y la European Union Statistics on Income and Living Conditions (EU-SILC), con datos hasta 2013. En estas encuestas se recogieron entre otros datos el estado de salud de la población, costumbres de alimentación y consumo (alcohol, tabaco) y apoyo social en el ámbito de la Unión Europea. Los objetivos de este Trabajo Fin de Máster son a partir de estos datos analizar el grado de influencia de los factores determinantes del estado de salud mediante técnicas de Regresión Logística, además de detectar posibles patrones entre los países mediante Análisis de Componentes Principales y técnicas de Agrupamiento (clusterización). Es también objetivo la visualización de los resultados obtenidos de forma que permita una comparación en el ámbito de la Unión Europea y un mejor entendimiento de las conclusiones obtenidas. Como conclusión se analizó la influencia de los factores determinantes detectados, así como la segmentación en grupos de los países con características afines en cuanto a las variables de estudio. ; The World Health Organization (WHO) defines health as a state of perfect (complete) physical, mental and social well-being, and not just the absence of disease. Achieving this state is a natural goal of any individual, public administrations and governments. Establishing the health determinants and its impact helps to achieve this goal. The European Union has carried out the European Health Interview Survey (EHIS), whose second wave was collected between 2013 and 2015 and updated in April 2019, and the European Union Statistics on Income and Living Conditions (EU-SILC, 2013). Among other data these surveys gathered the health status of the population, consumption of food and products harmful to health (alcohol, tobacco) and social support in the whole European Union. The aims of this Master's degree final project are, based on this data, to analyse the level of influence of the health determinants using Logistic Regression techniques, as well as to detect any patterns between countries using Principal Component Analysis and Clustering techniques. It is also the aim of this Master's degrees final project to visualize the results obtained in such way it could allow us to compare them at European Union level and thus to have a better understanding of the conclusions of this project. To conclude, the influence of the determining factors detected was analysed, as well as the segmentation into groups of countries with similar characteristics in terms of the study variables. ; L'Organització Mundial de la Salut (OMS) defineix salut com un estat de perfecte (complet) benestar físic, mental i social, i no sols l'absència de malaltia. Aconseguir aquest estat és objectiu natural de l'ésser humà i de les administracions públiques i governs. Establir quins són els factors determinants de la salut i la seva incidència ajuda a aconseguir aquest objectiu. La Unió Europea ha dut a terme la European Health Interview Survey (EHIS), la segona onada de la qual es va realitzar entre 2013 i 2015, actualitzada a l'abril de 2019 i la European Union Statistics on Income and Living Conditions (EU-SILC), amb dades fins a 2013. En aquestes enquestes es van recollir entre altres dades l'estat de salut de la població, costums d'alimentació i consum (alcohol, tabac) i suport social en l'àmbit de la Unió Europea. Els objectius d'aquest Treball Fi de Màster són a partir d'aquestes dades analitzar el grau d'influència dels factors determinants de l'estat de salut mitjançant tècniques de Regressió Logística, a més de detectar possibles patrons entre els països mitjançant Anàlisis de Components Principals i tècniques d'Agrupament (clusterización). És també objectiu la visualització dels resultats obtinguts de manera que permeti una comparació en l'àmbit de la Unió Europea i un millor enteniment de les conclusions obtingudes. Com a conclusió es va analitzar la influència dels factors determinants detectats, així com la segmentació en grups dels països amb característiques afins quant a les variables d'estudi.
Urban areas are major consumers of environmental resources and thus often place unsustainable demands on natural resources. As half of the world's population (55%) lives in urban areas, the environmental degradation produced by cities threatens the health and quality of life of a fair share of the world's population. For these reasons, progress towards sustainable urban development must be monitored and measured through suitable indicators. With reference to the assessment of air quality as a specific dimension of environmental quality in urban areas, existing studies have introduced various methodologies that mostly focus on objective measures (typically, exposure to outdoor air pollutants) while neglecting measures based on individual perceptions. Our goal is to contribute to filling this gap. To this end, we explore the relationship between objective and subjective measures of urban air quality in European countries. While the objective indicator is based on concentrations of PM2.5, our subjective indicator is reconstructed from individual perceptions collected through the European Union Statistics on Income and Living Conditions (EU-SILC) sample survey. Finally, through a cluster analysis, we classify the countries into homogeneous groups based on the values of these indicators. Our analysis reveals several differences in the country rankings according to the two indicators. For one group of countries, both approaches converge, thus leading to more definitive conclusions. For other countries, the mismatch between the two indicators suggests that either approach alone is not able to capture the full picture on air quality in urban environments.
