The interaction between minimum wages, income support, and poverty - Research note 10/2015 by Manos Matsaganis, Márton Medgyesi and Alexandros Karakitsios (2015) Minimum wages have emerged as a key policy issue in several countries in Europe (for example, in Germany and Italy) and beyond (for example, in the US). Furthermore, at EU level, discussions on a common European benchmark have gained momentum since European Commission President J.-C. Juncker came out in favour of an EU minimum wage as an essential component of the European Social Model. This Research Note attempts to throw light on the interaction between minimum wages, income support, and poverty. It focuses on two closely connected aspects of this issue. On the one hand, the latest EU-SILC data is used to examine the relationship between low wages and poverty, looking at the individual characteristics and household circumstances of those workers earning less than 50% of average hourly wages. On the other hand, the European tax-benefit model EUROMOD is deployed to simulate the effects on poverty of raising national minimum wages to that threshold (i.e. 50% of average hourly wages), taking into account interactions with social assistance and other tax-benefit policies, and assuming no negative impact on employment or behavioural effects. The main finding is that raising minimum wages to that level would have at best modest effects in terms of poverty reduction, though better coordination of minimum wages with other tax-benefit policies, and in particular with in-work benefits, could improve overall anti-poverty performance.
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).
Non-standard employment and access to social security benefits - Research note 8/2015 by Manos Matsaganis, Erhan Özdemir, Terry Ward and Alkistis Zavakou (2015) This Research Note:
• Reviews the literature on non-standard employment, and the definitions of it that have been adopted.
• Examines the extent of non-standard employment in the EU and the way it has changed over the recent past, especially over the crisis period.
• Considers social security systems in the different EU Member States as they apply to different types of non-standard employment, namely: self-employment, fixed-term contracts, and part-time work. The aim is to identify features that disadvantage, or are likely to disadvantage, workers in these types of employment as compared with those in standard jobs – i.e. with permanent contracts of employment and full-time work. The main focus is on unemployment, sickness, and maternity benefits, though the relevant features of public pension schemes are also considered.
• Assesses the relative number of people in these types of employment in different EU Member States (based on EU Labour Force Survey data), and therefore at risk of not being entitled to social benefits in the event of becoming unemployed, falling ill or having a child.
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 of older workers - Research note 5/2015 by E. Őzdemir, T. Ward M. Fuchs, S. Ilinca, O. Lelkes, R. Rodrigues, E. Zolyomi (2015) This Research Note is divided into two parts. The first part analyses the ad hoc module on the transition from work to retirement, examining the relative number of men and women in the EU in receipt of old-age pensions before they reach 65 (the official age of retirement in most Member States), the extent to which they continue to work both before and after reaching 65, the hours they work and the types of job they do. It also considers whether or not those with higher levels of education tend to be more inclined to remain in employment than those with lower levels, as well as the main reasons for staying in work and how far it is related to a desire, or need, to increase household income. The second part examines the health condition of older people and the extent to which they are affected by impairments, including mental disabilities. It also compares the health condition of those in employment with those who have retired or are unemployed as well as with those who are economically inactive but are not yet retired. It is based on data collected by the fifth wave of SHARE (Survey of Health, Ageing and Retirement in Europe), which covers men and women aged 55-69 in 14 European countries and relates to 2013.
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.
Accounting for gender differences in the distributional effects of tax and benefit policy changes - Research note 3/2015 by Silvia Avram, Daria Popova and Olga Rastrigina (2015) The distributional impact of policy changes is usually considered in terms of equivalised household income, assuming that each individual within the household is being affected in the same way, as a result of complete income pooling. The aim of this paper is to extend this approach by introducing a gender perspective in the analysis of policy effects. We use EUROMOD, the tax-benefit microsimulation model for the EU, to estimate the effects of changes in tax-benefit policies over the period 2008-2014 separately for men and women. The paper consists of two parts. First, we apply the standard approach based on the equal income sharing assumption but focus on lone parent families – a specific household type which makes gendered policy effects easier to observe. This analysis is performed for 18 EU countries: Belgium, Bulgaria, the Czech Republic, Denmark, Germany, Estonia, Ireland, Spain, France, Italy, Latvia, Luxembourg, Hungary, the Netherlands, Poland, Romania, Finland and Sweden. Second, we estimate the policy effects for men and women in couples. To obtain gender specific effects, we redefine income at the individual level by allocating income components to each adult within the household according to a set of assumptions. We present three alternative scenarios of intra-household income sharing. All scenarios assume that all individual incomes (e.g. earnings, individual benefits) are retained by their recipients, while common incomes (e.g. family benefits, housing allowances) are distributed following three different sets of sharing rules, which are defined in relation to the primary and the secondary earner status. We compare the outcomes of men and women in these three scenarios and in the baseline which assumes equal income sharing. This analysis is performed for six countries which differ in terms of the degree of defamilialisation their welfare regimes provide: Belgium, the Czech Republic, Spain, France, Romania and Finland.
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.