1. Monitoring child well-being in the EU: measuring cumulative deprivation Keetie Roelen Geranda Notten ISCI Conference, 27 July 2011

2. The breadth of poverty

5. Academic and policy relevance  fits widespread and increased attention for child poverty;  seeks to address questions around construction of measures, overlap between indicators and measures and concurrent implications for policy We know about child well-being in the EU at: Macro-level: Bradshaw et al., 2006; IRC RC 7; OECD, 2009 Micro-level: TARKI, 2011 BUT we know little about: overlap and breadth of child poverty composite measures of poverty at micro-level

6. This study Overlap and breadth of child poverty in the EU – Across domains – Across countries – Underlying factors Options for constructing a multidimensional measure of cumulative child well-being in the EU

7. Data EU-SILC 2007, cross-sectional data Germany, France, Netherlands and UK

8. Domains and indicators Housing conditions -Dwelling has leaking roof, damp walls/floors/foundation, rot in window frames or floor -Dwelling is not comfortably warm during winter time -Dwelling is overcrowded Neighborhood conditions -Pollution, grime or other environmental problems -Crime violence or vandalism in the area Access to basic services -Accessibility of primary health care services -Accessibility of compulsory school

9. Domains and indicators - continued Financial means -Household has payment arrears on mortgage/ rent, utility bills, loan payments -Household can’t afford meal w. meat, chicken, fish (vegetarian equivalent) every 2 nd day -Household can’t afford paying for one week annual holiday away from home -Household can’t afford a computer for financial reasons -Household can’t afford a car for financial reasons -Ability to make ends meet (very difficult) Monetary poverty -60% of median income

10. Domain deprivation

11. Overlap patterns

13. Monetary vs. multidimensional poverty A, B or AB (as % of total population) A - deprived but not income poor (as % of A+B+AB) B- income poor but not deprived (as % of A+B+AB) AB - deprived and income poor (as % of A+B+AB) odds Neighborhood problems DE35.1 [33.2,37.0]60.424.814.81.84* FR35.8 [33.4,38.2]56.129.114.81.61* NL37.6 [35.2,40.0]63.229.17.70.71 UK49.3 [47.1,51.6]53.428.717.81.18 Difficult access to basic services DE32.7 [30.9,34.6]32.562.15.31.43* FR27.0 [25.0,29.1]7.189.931.1 NL26.2 [23.9,28.6]24.970.34.91.1 UK31.1 [28.9,33.3]395.41.71.75*

14. Monetary vs. multidimensional poverty A, B or AB (as % of total population) A - deprived but not income poor (as % of A+B+AB) B- income poor but not deprived (as % of A+B+AB) AB - deprived and income poor (as % of A+B+AB) odds Housing problems DE32.9 [31.0,34.8]57.821.920.43.30* FR35.9 [33.7,38.1]56.119.224.74.03* NL32.4 [30.0,34.9]57.12517.92.59* UK40.4 [38.1,42.6]43.229.327.53.23* Financial strain DE41.4 [39.4,43.3]66.39.424.25.48* FR45.0 [42.8,47.1]65.1826.96.30* NL28.5 [26.1,31.0]51.224.224.64.92* UK47.3 [45.1,49.6]51.512.935.75.99*

15. Neighborhood Problems Difficult access to basic services Financial strain Overlap (%)OddsOverlap (%)OddsOverlap (%)Odds Housing problems DE 9.5 2.02*7.11.45*15.94.00* [8.4,10.8] [1.66,2.46][6.2,8.3][1.18,1.79][14.5,17.4][3.29,4.85] FR 10.5 2.14*4.71.3319.44.53* [9.0,12.2] [1.74,2.64][3.7,5.8][1.00,1.77][17.6,21.3][3.69,5.56] NL 8.5 1.71*3.91.179.13.02* [7.2,10.0] [1.33,2.19][2.9,5.2][0.82,1.66][7.4,11.1][2.29,4.00] UK11.41.34*5.32.17*18.23.70* [10.0,13.0][1.09,1.66][4.0,6.8][1.56,3.01][16.2,20.4][2.99,4.57] Neighborhood problems DE6.51.1712.41.72* [5.5,7.7][0.93,1.46][11.1,13.8][1.43,2.07] FR3.81.1413.31.83* [3.1,4.6][0.87,1.51][11.7,15.0][1.51,2.22] NL4.41.247.91.83* [3.6,5.3][0.94,1.64][6.6,9.4][1.41,2.38] UK5.71.80*16.51.44* [4.6,7.0][1.32,2.46][14.8,18.4][1.19,1.74] Difficult access to basic services DE10.71.67* [9.5,12.0][1.38,2.03] FR6.31.24 [5.2,7.5][0.96,1.61] NL4.41.78* [3.4,5.9][1.26,2.52] UK7.02.17* [5.6,8.6][1.61,2.92] Source: own calculations with EU-SILC, wave 2007. * means significant at a 1% level.

16. Factors influencing domain deprivation Single-parenthood: Significantly increases probability to being financially strained, income poor and experiencing housing problems No or low work intensity in household: Significantly increases probability to being financially strained, income poor and experiencing housing problems Living in rented dwellings: Significantly increases probability to be financially strained and experiencing housing problems and, to a lesser extent, being environmentally deprived, and income poor Low educational attainment parents: Significantly increases probability to being financially strained and income poor

17. In conclusion A diverse picture Limited overlap with considerable size and group differences between indicators of monetary and multidimensional poverty; Considerable differences across countries; Indicators of monetary poverty and multidimensional poverty can not serve as a proxy for one another; Higher levels of overlap are not necessarily an indication of higher odds for experiencing cumulative deprivation

18. What are appropriate measures of cumulative deprivation? Why? - more deprivations are worse than one - one headline statistic is practical EU policy context - search for child specific indicators - many single indicators, one composite index Criteria - sensitive to changes in breadth of deprivation - intuitive interpretation

19. Aggregation option I Simple headcount vs. adjusted headcount Simple headcount =   or the proportion of poor in the population Adjusted headcount =  (x1 deprivation)  (x3 deprivations) or the proportion of deprivations in the population

20. Aggregation option II Absolute vs. relative poverty line Absolute: poverty line=2, headcount=4 Relative: poverty line=median, headcount=6 33 22 22 11 11 0 0 0 0 44

21. Headcount, absolute versus relative

22. Adjusted headcount, absolute versus relative

23. Adjusted headcount, absolute in UK

24. In conclusion Adjusted headcount (CDI) with cumulative deprivation threshold of 1 works best Can be complemented with headcount with higher cumulative deprivation threshold Need other method to determine relative cumulative deprivation threshold