in Europe An Application of the Adjusted Headcount Approach Christopher T Whelan Brian Nolan and Bertrand Maître School of Sociology and Geary Institute University College Dublin amp School of Sociology amp Social Policy Queens University Belfast ID: 152580
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Multidimensional Poverty Measurement in Europe: An Application of the Adjusted Headcount Approach
Christopher, T. Whelan*, Brian Nolan** and Bertrand Maître****School of Sociology and Geary Institute, University College Dublin & School of Sociology & Social Policy, Queen’s University Belfast** College of Human Sciences, University College Dublin *** Economic and Social Research Institute, DublinSlide2
IntroductionIncreasing focus on multidimensional approaches to poverty & social exclusionVariety of increasingly sophisticated analytic strategies
Application of the Alkire & Foster multidimensional headcount approachFramed in a development rather than a rich country contextApply to EU-SILC 2009 DataSlide3
The Alkire & Foster ApproachFramework for multidimensional poverty, counting poor & measure of extent of poverty (Bourguignon & Chakravarty
, 2003)Axiomatic propertiesLimitations of counting approach – union & intersectionAlkire & Foster dual cut-off approachDeprivation cut off for individual dimensions
Poverty cut-of for number of dimensions – “breadth” of deprivationSlide4
The Alkire & Foster Approach (ii)Transition between identification and aggregation can be understood as involving a progression of matrices
The achievement matrix Y shows the outcome for - n persons on d dimensionsThe deprivation matrix replaces each entry in Y that is below the deprivation cut-off with 0.The censored deprivation matrix multiplies each row in the deprivation matrix by the identification function. If the person is multi-dimensionally poor i.e. above the cut-off point the row remains unchanged.If not it is replaced with 0s. Information on non-poor has no effect of measurement Slide5
The Adjusted Head Count RatioThe Adjusted Head Count Ratio (AHCR) is the mean of the censored deprivation matrix.AHCR has a potential range of values going from 0 to 1.Where no one in the population experiences any deprivation it has a value of 0. Where everyone is deprived on all dimensions it takes on a value of 1.The headcount H is the proportion of people who are multi-dimensionally poor
The intensity A is the average deprivation share among the poorH*A=AHCRAHCR properties includes decomposability in terms of dimensions & sub-groupsSlide6
Data and MeasuresEU-SILC 2009, 28 countriesDimensions of deprivation: Basic (absence of meal, clothes, leisure activity, home heating, etc)
Consumption (PC, car, internet) Health HRP (health status, restricted activities, chronic illness) Neighbourhood environment (presence of litters, pollution, crime/violence etc...)Cronbach’s alpha 0.85 (basic) to 0.64 (neighbourhood env)Use of prevalence weights and normalised score-0(no deprivation) to 1 (deprived all items).At Risk of Poverty (60% median income)
Macro variables Gini & Gross Income
P
er capita Slide7
Multidimensional Poverty by Country, EU-SILC 2009 Slide8
Decomposition of the Adjusted Head Count Ratio by Dimension by Country, EU-SILC 2009 (%)Slide9
Adjusted Head Count Ratio by Social Class and Country, EU-SILC 2009
Higher Professional & ManagerialLower Professional & ManagerialIntermediate & Lower Supv
Small Employer & Self-employ
Farmers
Lower services &
Clerical & technical
Routine & Never Worked
Norway
.011
.011
.016
.032
.020
.052
.074
Netherlands
.026
.053
.048
.056
.050
.069
.121
Denmark
.025
.030
.041
.042
.049
.050
.086
Germany
.034
.040.086.098.135.137.195UK.035.054.099.101.116.137.199Ireland.032.022.071.062.040.128.180Italy.025.038.053.092.098.113.136Greece.033.042.080.142.187.185.181Czech Republic.052.066.092.050.052.119.174Estonia.054.088.107.056.094.135.190Hungary.101.166.214.139.199.272.339Bulgaria.135.177.246.195.309.313.371Slide10
Adjusted Head Count Ratio by Social Class and Country, EU-SILC 2009Slide11
Mean Adjusted Head Count Social Exclusion Ratio by Age Group by Country EU-SILC 2009Slide12
Multilevel Analysis of Multidimensional Poverty, EU-SILC 2009
Hierarchical multilevel regressions (AHCR dep variable)Empty model (ICC:10.8%)Households & HRP characteristics (social class, education...) *Reduc in,
country var
(1.9%),
indiv
var
(10.6%), tot
var
(9.2%)
Macro-economic variables (GNDH & GINI)
*
GINI not sig
*
Reduc
in,
country
var
(67.9%),
indiv
var
(0%), tot
var
(16.8%)
Interaction of b. with GNDH
*
more pronounced effects of socio-eco disadvantages at lower level of GNDH
* Reduc in, country var (71.0%), indiv var(11.7%), tot var (18.2%) Slide13
Conclusion (i)Limitations of union & intersection approaches
AHCR approach provides a middle groundCensoring centralIdentifies a non-trivial minority as poor in each country.Size of poor group varies systematically with average income per capita but is not related to Gini
Main source of variation head count rather than intensity
In less affluent countries basic & consumption deprivation play a more prominent role while in more affluent countries health & income poverty dominateSlide14
Conclusion (ii)Systematic variation by socio-economic group. Impact of social class is stronger in low income countries. Age group effects vary by country
Limitations of EU Poverty Target Approach. Diversity of profiles captured by EU measureEmploying the Alkire & Foster Approach makes it possible that the implications of crucial choices in relation to dimensions, thresholds and weighting can be assessed in a consistent and transparent fashion.