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Showing 1 - 10 of 687

The characteristics of workers on low wages - Research note 9/2015 by Erhan Ozdemir and Terry Ward (2015)
This Research Note has two main aims. The first is to examine the characteristics of employees with low pay, which is defined in the main part of the study as those with hourly earnings of less than 50% of the average. The second is to compare the EU-SILC with the Labour Force Survey (LFS) as a source of data on the characteristics of the low-paid in order to assess their consistency. This is an important prelude to using the EU-SILC as the basis for examining the extent to which low pay is a major determinant of low household income and, accordingly, the strength of the link between low pay and in-work poverty. Since the LFS covers a much larger sample of households than the EU-SILC, it should be a more reliable source of data on the characteristics of those in employment. A comparison between the two in terms of low-wage earners, therefore, provides a check on the reliability of the EU-SILC data. In order to identify the low-paid in terms of their earnings relative to the average, the data on net monthly earnings reported by the LFS, which is in the form of deciles, is converted into monetary amounts using the EU-SILC, on the implicit assumption that the distribution of earnings according to the two surveys is similar. Earnings are then converted into hourly amounts on the basis of the LFS data on usual hours worked. The characteristics of the low-paid examined consist of gender, age, educational attainment levels, hours of work, the type of employment contract, occupation, sector of activity and country of birth (to reflect migrant background).

Micro and Macro Drivers of Material Deprivation Rates - Research note 7/2015 by Anna B. Kis, Erhan Özdemir, Terry Ward (2015)
This Research Note examines, first, macro drivers of material deprivation, essentially analysing the factors which seem to explain differences across countries in the proportion of the population that are identified as being materially deprived, secondly, micro drivers, or, more accurately, the effect of changes in household income on the situation of people in this regard. Both parts use the indicator of material deprivation developed for assessing and monitoring the extent of deprivation in the EU in the different Member States, which is based on the inability of households to afford a given number among nine items included in the EU-SILC. The first is based on the core EU_SILC dataset and focuses on the indicator of severe material deprivation, which is measured as the inability of households to afford any four of the nine items in question. The second is based on the longitudinal data included in the EU-SILC, which enables the situation of the same household to be tracked over time, in this case over three years, 2010-2012, and is focused on the standard indicator of deprivation, which is the inability to afford any three of the nine items.

Recent changes in self-employment and entrepreneurship across the EU - Research note 6/2015 by Nicole Fondeville, Erhan Ozdemir, Orsolya Lelkes and Terry Ward (2015)
The Research Note examines the widespread growth of self-employment across the EU over the period 2007-2014, distinguishing the self-employed without employees from those in self-employment with employees and breaking down the growth by age group, hours worked, and education level as well as the types of activity performed. Secondly, it assesses the extent of movement from unemployment into self-employment and from one-person independent self-employment to businesses employing other people. Thirdly, it examines both the changes in the income of the self-employed over the crisis period and the extent to which the apparent low level and the reduction that has occurred in many countries reflects the true standard of living of the people concerned. Fourthly, it considers how far the level of satisfaction with their life, job and financial situation of the self-employed reported in a recent survey compares with that of employees, and how it varies with education levels and the activities in which they work. Finally, it examines the access to social protection of the self-employed and the policies in place across the EU to encourage people to set up in business.

Employment, education and other means of reducing poverty - Research note 4/2015 by Réka Branyiczki (2015)
The paper assesses micro drivers of relative income poverty of those aged 20-59 in the EU Member States in 2011, and macro drivers during 2004-2011, focusing on the role of work and education. Both employment and educational attainment prove to be strong determinants of avoiding the risk of poverty. A cross-sectional multivariate regression analysis on the EU-SILC 2012 database, on the sample of 27 member countries, indicates that a household with high work intensity has a 47 percentage point lower probability on average to be at risk of poverty than a household with very low work intensity, with all else equal. Someone with tertiary education tends to have an 11 percentage point lower probability of being at risk than someone with only basic education. There is a marked variation across countries in these estimated probabilities, reflecting the importance of contextual factors, such as the macroeconomic and institutional environment. According to a macro level analysis on a sample of 20 EU Member States, a country with an employment rate 10 percentage points higher than average tends to have an at-risk-of-poverty rate 2 percentage points below average, while longer schooling and wider access to tertiary education are also associated on average with a lower rate. Nevertheless, policies aimed at reducing the number at risk of poverty by increasing employment need to pay attention to the distribution of the additional jobs across households.

The effect of changes in tax-benefit policies on the income distribution in 2008-2015 - Research note 2/2015 by De Agostini, Paulus and Tasseva (2015)
We apply microsimulation techniques to estimate the first-order effects of tax-benefit policy changes since the beggining of the financial and economic crisis in 2008. Using the EU tax-benefit model EUROMOD in combination with the EU-SILC 2012 micro-data, we provide comparative estimates for EU-27 in 2008-2014 as well as for 21 EU member states in 2014-2015. The analysis covers direct tax and cash benefit changes and evaluates their effects on the income distribution, poverty and inequality levels, holding population characteristics and market incomes constant, thereby, isolating direct policy effects from other factors shaping the income distribution. Two different indexation approaches are used to adjust benchmark policies over time – prices and market incomes – and explore the sensitivity of results. We find substantial cross-national variation throughout the whole period. At the EU level, policy changes in the first half of the period (2008-2011) were poverty-reducing and had a positive effect on mean incomes, while the effects were the opposite in the later period (2011-2014); and inequality-reducing in both periods.

Nowcasting: estimating developments in median household income and risk of poverty in 2014 and 2015 - RN 1/2015 by Olga Rastrigina, Chrysa Leventi, Sanja Vujackov and Holly Sutherland (2015)
The at-risk-of-poverty rate (AROP) 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 crucial for monitoring of the social situation and of the effectiveness of tax and benefit policies. However, partly due to the complexity of EU-SILC data collection, estimates of the number of people at risk of poverty are published with a significant delay. This paper extends and updates previous work on estimating (‘nowcasting’) indicators of poverty risk using the tax-benefit microsimulation model EUROMOD. The model’s routines are enhanced with additional adjustments to the EU-SILC based input data in order to capture changes in the employment characteristics of the population since the data were collected. The nowcasting method is applied to twenty-five EU Member States. AROP rates are estimated up to 2015 for twenty countries and 2014 for the remaining five countries. The performance of the method is assessed by comparing the predictions with actual EU-SILC indicators for the years for which the latter are available.

The redistributive and stabilising effects of an EMU unemployment benefit scheme under different hypothetical unemployment scenarios - Research note 3/2014 by H. Xavier Jara, Holly Sutherland and Alberto Tumino (2015)
The idea of a common unemployment benefit system for the European Monetary Union (EMU) has provoked increasing interest in both the political and academic spheres because of its potential to smooth fluctuations in income across member states and to strengthen income security for the unemployed. In this paper, we simulate two hypothetical negative employment shocks and make use of the microsimulation model EUROMOD to explore the implications for income protection of the introduction of an EMU unemployment insurance (EMU-UI) scheme, for a selected number of countries of the Monetary Union. Our results show that the EMU-UI has the potential to reduce the risk of poverty for those affected by the negative employment shock and to have an additional positive effect on within-country income stabilisation, although the effects of the EMU-UI vary considerably in size across the countries analysed.

Indebtedness of households and the cost of debt by household type and income group - Research note 10/2014 by Eva Sierminska (2014)
The research note examines the indebtedness of households in the EU. It focuses on several aspects of household indebtedness and considers the structure of debt, including bank loans and other types of credit from banks and individuals. It compares differences among household types, particularly for the young and the middle-income groups. It examines the costs of servicing debt and how far this imposes a burden on households with differing levels of income. It identifies those that have been experiencing financial distress, which have been increasing in number, and considers their coping mechanisms.. The analysis is based on the new Household Finance and Consumption Survey (HFCS), which provides harmonised information for 15 eurozone member countries on household balance sheets and related economic and demographic variables, including income, private pensions, employment, measures of consumption, gifts and inheritances and other behavioral variables. The sample consists of over 62 000 households and the first wave was carried out between the end of 2008 and the middle 2011.

Analysing equity in the use of long-term care in Europe - Research note 9/2014 by Ricardo Rodrigues, Stefania Ilinca, Andrea Schmidt (2014)
There are significant differences across social protection systems in Europe in the scope, breadth and depth of coverage of the risk to need long-term care in old-age. Together with other factors, such as education, household structure or societal values regarding care for frail older people, these differences can have a significant impact on the use of long-term care. Using SHARE data, this Research Note compares differences between European countries in the use of long-term care across income groups, for older people living at home. It analyses not only inequalities in the use of long-term care, but also differences in use that persist after differences in need have been taken into consideration, i.e. horizontal inequality. For this purpose, concentration indices, concentration curves and horizontal inequality indices are estimated for home care services and informal care. The countries analysed here are Austria, Germany, Sweden, the Netherlands, Spain, Italy, France, Denmark, Greece, Belgium and Czech Republic. The findings suggest that differences in use of home care services across income groups mostly reflect differences in need between those same groups. For informal care, the differences in use persist even after accounting for needs, and less affluent individuals are much more likely to use informal care. Some possible causes for these differences and policy implications are considered.

Inequality in the use of childcare - Research note 8/2014 by Márton Medgyesi and Niki Kalaverzou (2014)
Improving the availability and affordability of Early Childhood Education and Care (ECEC) services is high up on the EU policy agenda as affordable childcare supports parents’ access to the labour market, addresses child poverty and contributes to breaking the intergenerational transmission of poverty. In this research note, the objective is to propose a synthetic and functional way of measuring the social gradient of childcare use, which allows regular monitoring. Two issues in the measurement of the social gradient are investigated: the choice of an indicator of socioeconomic status and the choice of summary measure of the social gradient. In this analysis socioeconomic status is measured by equivalised disposable income, parental education and also by using a composite indicator of socioeconomic status. Problems of using simple frequency ratios as a measure of the social gradient are reviewed and other measures that have been proposed in the literature on health inequality are presented, such as measures of association and measures based on rankings of the socioeconomic variable (concentration index, relative index of inequality). In the second part of the research note the social gradient in formal childcare use is calculated with different methods and results are presented and compared.