Transcript Proportions of immigrants across countries

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, Dublin
Introduction
 Increasing focus on multidimensional approaches to poverty &
social exclusion
 Variety of increasingly sophisticated analytic strategies
 Application of the Alkire & Foster multidimensional headcount
approach
 Framed in a development rather than a rich country context
 Apply to EU-SILC 2009 Data
The Alkire & Foster Approach
 Framework for multidimensional poverty, counting poor &
measure of extent of poverty (Bourguignon & Chakravarty,
2003)
 Axiomatic properties
 Limitations of counting approach – union & intersection
 Alkire & Foster dual cut-off approach
 Deprivation cut off for individual dimensions
 Poverty cut-of for number of dimensions – “breadth” of
deprivation
The Alkire & Foster Approach (ii)
 Transition between identification and aggregation can be
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understood as involving a progression of matrices
The achievement matrix Y shows the outcome for - n persons
on d dimensions
The 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
The Adjusted Head Count Ratio
 The Adjusted Head Count Ratio (AHCR) is the mean of the
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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 multidimensionally poor
The intensity A is the average deprivation share among the poor
H*A=AHCR
AHCR properties includes decomposability in terms of
dimensions & sub-groups
Data and Measures
 EU-SILC 2009, 28 countries
 Dimensions 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,
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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 Per capita
Multidimensional Poverty by Country, EU-SILC 2009
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Relative Income Poverty (ARP/100)
MD Intensity
Union
MD Headcount 2+
MD Adjusted Headcount Ratio
Intersection
Decomposition of the Adjusted Head Count Ratio by Dimension
by Country, EU-SILC 2009 (%)
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Basic
Consumption
Health
ARP
Neighbourhood
Adjusted Head Count Ratio by Social Class
and Country, EU-SILC 2009
Higher
Professional
&
Managerial
Norway
Netherlands
Denmark
Germany
UK
Ireland
Italy
Greece
Czech
Republic
Estonia
Hungary
Bulgaria
Lower
Intermediate
Professional
& Lower
&
Supv
Managerial
Small
Employer &
Self-employ
Farmers
Lower
services &
Clerical &
technical
Routine &
Never
Worked
.011
.026
.011
.053
.016
.048
.032
.056
.020
.050
.052
.069
.074
.121
.025
.034
.035
.032
.025
.033
.052
.030
.040
.054
.022
.038
.042
.066
.041
.086
.099
.071
.053
.080
.092
.042
.098
.101
.062
.092
.142
.050
.049
.135
.116
.040
.098
.187
.052
.050
.137
.137
.128
.113
.185
.119
.086
.195
.199
.180
.136
.181
.174
.054
.101
.135
.088
.166
.177
.107
.214
.246
.056
.139
.195
.094
.199
.309
.135
.272
.313
.190
.339
.371
Adjusted Head Count Ratio by Social Class
and Country, EU-SILC 2009
Norway
Netherlands
Higher Professional
& Managerial
Denmark
Germany
UK
Farmers
Ireland
Italy
Greece
Small Employer &
Self-employ
Czech Republic
Estonia
Routine & Never
Worked
Hungary
Bulgaria
0
0.1
0.2
0.3
0.4
Mean Adjusted Head Count Social Exclusion Ratio by
Age Group by Country EU-SILC 2009
Norway
Netherlands
<30
Denmark
Germany
UK
30-49
Ireland
Italy
Greece
50-64
Czech Republic
Estonia
65+
Hungary
Bulgaria
0
0.1
0.2
0.3
0.4
Multilevel Analysis of Multidimensional Poverty,
EU-SILC 2009
 Hierarchical multilevel regressions (AHCR dep variable)
a. Empty model (ICC:10.8%)
b. Households & HRP characteristics (social class, education...)
*Reduc in, country var (1.9%), indiv var (10.6%), tot var (9.2%)
c.
Macro-economic variables (GNDH & GINI)
*GINI not sig
* Reduc in, country var (67.9%), indiv var(0%), tot var (16.8%)
d.
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%)
Conclusion (i)
 Limitations of union & intersection approaches
 AHCR approach provides a middle ground
 Censoring central
 Identifies 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 dominate
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
measure
 Employing 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.