monitoring child well-being in the eu: measuring cumulative deprivation keetie roelen geranda notten...

Monitoring child well-being in the EU: measuring cumulative deprivation

Keetie RoelenGeranda Notten

ISCI Conference, 27 July 2011

The breadth of poverty

The breadth of poverty

The breadth of poverty

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

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

Data

• EU-SILC 2007, cross-sectional data

• Germany, France, Netherlands and UK

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

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 2nd 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

Domain deprivation

Overlap patterns

Overlap patterns

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 problemsDE 35.1 [33.2,37.0] 60.4 24.8 14.8 1.84*FR 35.8 [33.4,38.2] 56.1 29.1 14.8 1.61*

NL 37.6 [35.2,40.0] 63.2 29.1 7.7 0.71

UK 49.3 [47.1,51.6] 53.4 28.7 17.8 1.18Difficult access to basic servicesDE 32.7 [30.9,34.6] 32.5 62.1 5.3 1.43*

FR 27.0 [25.0,29.1] 7.1 89.9 3 1.1

NL 26.2 [23.9,28.6] 24.9 70.3 4.9 1.1

UK 31.1 [28.9,33.3] 3 95.4 1.7 1.75*

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 problemsDE 32.9 [31.0,34.8] 57.8 21.9 20.4 3.30*FR 35.9 [33.7,38.1] 56.1 19.2 24.7 4.03*

NL 32.4 [30.0,34.9] 57.1 25 17.9 2.59*

UK 40.4 [38.1,42.6] 43.2 29.3 27.5 3.23*Financial strainDE 41.4 [39.4,43.3] 66.3 9.4 24.2 5.48*

FR 45.0 [42.8,47.1] 65.1 8 26.9 6.30*

NL 28.5 [26.1,31.0] 51.2 24.2 24.6 4.92*

UK 47.3 [45.1,49.6] 51.5 12.9 35.7 5.99*

NeighborhoodProblems

Difficult accessto basic services

Financialstrain

Overlap (%) Odds Overlap (%) Odds Overlap (%) OddsHousing problemsDE 9.5 2.02* 7.1 1.45* 15.9 4.00*

[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* 4.7 1.33 19.4 4.53*

[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* 3.9 1.17 9.1 3.02*

[7.2,10.0] [1.33,2.19] [2.9,5.2] [0.82,1.66] [7.4,11.1] [2.29,4.00]UK 11.4 1.34* 5.3 2.17* 18.2 3.70*

[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 problemsDE 6.5 1.17 12.4 1.72*

[5.5,7.7] [0.93,1.46] [11.1,13.8] [1.43,2.07]FR 3.8 1.14 13.3 1.83*

[3.1,4.6] [0.87,1.51] [11.7,15.0] [1.51,2.22]NL 4.4 1.24 7.9 1.83*

[3.6,5.3] [0.94,1.64] [6.6,9.4] [1.41,2.38]UK 5.7 1.80* 16.5 1.44*

[4.6,7.0] [1.32,2.46] [14.8,18.4] [1.19,1.74]Difficult access to basic servicesDE 10.7 1.67*

[9.5,12.0] [1.38,2.03]FR 6.3 1.24

[5.2,7.5] [0.96,1.61]NL 4.4 1.78*

[3.4,5.9] [1.26,2.52]UK 7.0 2.17*

[5.6,8.6] [1.61,2.92]Source: own calculations with EU-SILC, wave 2007. * means significant at a 1% level.

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

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

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

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

Aggregation option II

Absolute vs. relative poverty line

Absolute: poverty line=2, headcount=4

Relative: poverty line=median, headcount=6

3

2

2

1

1

0

0

0

0

4

Headcount, absolute versus relative

Adjusted headcount, absolute versus relative

Adjusted headcount, absolute in UK

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