Determinants of child poverty and policy responses in the European Union András Gábos

1. 8th ESPAnet Conference 2010 Social Policy and the Global Crisis: Consequences and Responses Stream 2 Poverty and Social Exclusion Budapest, 2-4 September 2010 Determinants of child poverty and policy responses in the European Union András Gábos TÁRKI Social Research Institute

2. The „Study on child poverty” project Commissioned by: DG Employment of the European Commission, Unit E2 Consortium: Tárki Social Research Institute, Budapest Applica sprl, Brussels Steering Committee: Terry Ward (chair) Applica Michael F. Förster OECD Hugh Frazer National Univ. of Ireland Petra Hoelscher UNICEF Eric Marlier CEPS/INSTEAD Holly Sutherland University of Essex István György Tóth TÁRKI

3. Tasks within the project Task 1. „An in-depthempirical analysis of child povertyand the related key challenges for each Member State, starting from the analytical framework developed up by the EU Task-Force report.” Task 2. „Anassessment of the effectiveness of policiesfor combating child poverty and promoting social inclusion among children and the identification of policy mixes that seem to be most effective in tackling the specific factors underlying child poverty.” Task 3. Recommendations for a limited set of child well-being indicators

4. Aim and methodology • Aim of the paper: to provide international benchmarking and to identify key challenges for each Member State to assist national policy practices • Methodology (building on EU Task-Force 2008) • To assess the performance of countries in the field of child poverty relative to • the national average/adult population • the EU-average • Four dimensions • Child poverty risk outcomes • Joblessness • In-work poverty • Impact of social transfers

5. Poverty among children, in general, is higher than that of the overall population • Every fifth child is at-risk-of-poverty in the EU-27 • Child poverty is specifically high in RO • Much higher than the population average: HU, also in CZ, LU, RO, SK • Lower than the population average in: DK, EE, CY, FI -------------------------------------- • The severity of poverty is more similar to the population as a whole • Relatively high in: BG, RO • Relatively low in: FR, CY, NL At-risk-of-poverty rates: overall population and children, EU-27, 2008 Source: EUROSTAT

6. Child poverty outcomes – country clusters • Indicators included in this task: • at-risk-of-poverty rate • relative median poverty gap • both based on EU-SILC • z-scores based on • the difference between thenational figurefor children and the overall national figure • the difference between the national figure and the EU average for children • z-scores added together, without weighting • Six clusters • to maximise the “steps” between the groups • to minimise the variations within the groups • Good performers: Northern countries, DK, CY, FR, SI • Bad outcomes: BG, RO, Southern countries, PL, LT

7. Almost 1 children in 10 in the EU lives in jobless households Share of children (0-17) and adults (18-59 – not students) living in jobless households, EU-27*, 2008 (%) • Reasons for joblessness can be found on both the supply and demand side • Lack of or inadequate human capital of parents • Counter-incentives of income supports • Shortage of childcare • Regional and/or ethnic segregation • Children in jobless households are likely to live in lone parent families: BE, EE, IE and the UK • Children in large families are affected in HU Source: EUROSTAT (EU-LFS) *Data for Sweden are from EU-SILC (WI=0)

8. Joblessness – country clusters • Input indicators: • share of children in jobless households • based on EU-LFS • z-scores based on • the difference between the national figure for children and the overall national figure • the difference between the national figure for children and the EU average for children • z-scores added together, without weighting • Six clusters • to maximise the “steps” between the groups • to minimise the variations within the groups • Good performers: Northern countries, SI, LU, EL, DK, FI • Bad outcomes: UK, HU, IE

9. In-work poverty • Similar share of children in in-work (WI>=0.50) households across countries • Large variation in the risk of poverty • High in RO, Southern countries, Baltic States, LU, PL • Reasons behind • Low wages • Not full participation in the labour market • Only one parent in employment • Part-time work • Shortage of childcare • Social norms In-work (WI>=0.50) poverty in the EU-27*, 2008 Source: own calculations based on EU-SILC 2008 *No data available for Malta. Data for France are from 2007

10. In-work poverty – country clusters • Input indicators: • in-work poverty: at-risk-of-poverty rate for those living in hhs with WI>=0.50, • based on EU-SILC • z-scores based on • the difference between the national figure for children and the overall national figure • the difference between the national figure for children and the EU average for children • z-scores added together, without weighting • Six clusters • to maximise the “steps” between the groups • to minimise the variations within the groups • Good performers: DK, SE, FI, SI, CZ, DE • Bad outcomes: RO, ES, IT

11. Social transfers reduce the proportion of children at risk of poverty by 38% in the EU as a whole The effectiveness of social transfers (excl. pensions), EU-27, 2008 • The effectiveness of transfers reflects both the scale of expenditure level and the extent of targeting • Highest impact in: DK, FI, SE, as well as in DE, FR, HU, AT, SI • Lowest: EL, ES, IT • Serious limitations of the EU-SILC • No behavioural responses are considered • No full account of taxes and social contributions • No account of transfers via the tax system • Hard to identify child-contingent payments • Effects are likely to be over-estimated Source: EUROSTAT, own calculations based on EU-SILC 2008 (version 01.03.2010).

12. Impact of social transfers • Input indicators: • at-risk-of poverty rate after and before social tranfers (excl. pensions), • poverty reduction effect of transfers • based on EU-SILC • z-scores based on • the difference between the national figure for children and the EU average for children • z-scores added together, without weighting • Six clusters • to maximise the “steps” between the groups • to minimise the variations within the groups • Good performers: Northern countries, AT, HU, CZ, IE • Bad outcomes: BG, RO, Southern countries, Baltic States

13. Relative outcomes of countries related to child poverty risk and main determinants Group A: good performers in all dimensions

14. Determinants and policies in place in Group A countries • High levels of economic activity and employment generally – high share of dual earner families in most countries • The Netherlands: the second earner being in part-time job is predominant • Austria: the single earner model is dominant, high earnings and income support compensating for the lack of a second earner; the model featuring one full-time earner and a part-time earner is also considerable • Extensive and affordable childcare provision • Cyprus: informal childcare arrangements • Adequate income support • DK, SE, FI: high level of universal income support and extensive support for parents to enter/re-enter employment • Slovenia: high level of support targeted on low-income families in SI • Income support narrowly targeted, focus on maternity benefits in France

15. Relative outcomes of countries related to child poverty risk and main determinants Group B: joblessness is key challenge

16. Determinants and policies in place in Group B countries • Large number of children living with lone parents (BE, DE, IE) • Children with migrant background are at high risk and count for a large share of those at risk of poverty in most of these countries • Relatively effective income support • Inadequate childcare provision – limited in number of place, opening hours and affordability • Low level of support to help women with children into employment • Inflexible working hours

17. Relative outcomes of countries related to child poverty risk and main determinants Group C: relatively bad performance in all dimensions

18. Determinants and policies in place in Group C countries • The cluster is fairly unstable across the 2005-2008 period • Poor outcomes are rooted in the • inadequate labour market participation of families with children • inadequate income support to prevent children to a large extent from staying poor • SK, UK: better outcomes compared to the others, mostly due to relatively effective benefits

19. Relative outcomes of countries related to child poverty risk and main determinants Group D: in-work poverty is key challenge

20. Determinants and policies in place in Group D countries • Low levels of income support, especially for older children • Support narrowly targeted – in PL on very poorest or lone parents (6% of children), in EL on large families (10%) • Lack of childcare provision • Traditional reliance on extended family for childcare in IT, ES+EL • Employment rates low generally and support policies limited; fixed term jobs common except in IT • No minimum wages in EL or IT and set at low level in PL • But in ES especially, signs of change – reduction in fixed-term jobs, rise in minimum wages, new child tax allowances

21. Determinants and policies in place in Hungary • Key challenge: large number of children in jobless and low work intensity households • Main characteristics of the poverty profile: • large families (two parents with 3+ children) are affected most • the role of education is very strong • the settlement gradient exists • important regional inequalities • strong effect of the ethnic background • Income supports are effective in a cross-EU comparison • There are important obstacles for parents to enter the labour market: high costs of searching jobs, regionally unequal demand, the lack of adequate human capital, inadequate childcare opportunities, counter-incentive effect of income supports

22. How to go ahead with the analysis? • To extend the analysis using multilevel modelling: • to take into account additional dimensions on the explanatory side at individual (hh) level (hh composition, socio-economic status of parents, settlement, migrant status) • national level institutional variables to better differentiate between countries in terms of policy effectiveness and efficiency • Microsimulation

23. Thank you for your attention! www.tarki.hu