THE MULTIDIMENSIONAL MEASUREMENT OF POVERTY
Conceptual Underpinnings of Individual, Family and Spatial
Measurements of Poverty and Deprivation
Trutz Haase
Presentation at the IRCHSS Summer School on Poverty Measurement, UCC, Cork, June 2012
FORMAT OF PRESENTATION
 Measuring Poverty and Social Inclusion at the Level of Individuals or
Households
 Measuring Child and Family Well-being
 Deprivation and its Spatial Articulation
Measuring Poverty and Social Inclusion
at the Level of Individuals or Households
POVERTY - A MULTIDIMENSIONAL CONCEPT
 While poverty is widely accepted to be an inherently multi-dimensional concept, it has
proved difficult to develop measures that

adequately capture this multidimensionality

account for the “ecological” and multilevel context of well-being

facilitate comparisons over time
 This presentation explores the role of Structural Equation Modelling (SEM) as a
technique for constructing improved measurements of poverty, child and family wellbeing and spatial deprivation.
DEFINING POVERTY

Townsend - the conceptual bedrock for the European concept of poverty
“People are in poverty when “their resources are so seriously below those
commanded by the average individual or family that they are, in effect, excluded
from ordinary living patterns, customs and activities.”
(Townsend, P., 1979)

Relative Poverty
“People are living in poverty if their income and resources (material, cultural and
social) are so inadequate as to preclude them from having a standard of living which
is regarded as acceptable by Irish society generally.”
(Government of Ireland, NAPS, 1997,
reflecting the definition adopted in the mid-1980s by the European Council)
FROM AT-RISK-OF-POVERTY TO
MATERIAL DEPRIVATION
 The purpose of EU deprivation indicators is to capture a situation of exclusion from a
minimum acceptable way of life due to a lack of resources. (EU Council of Ministers, 1985)
 Originally, this focused solely on the relative at-risk-of-poverty rate, essentially a
unidimensional measure related to income, which takes as its sole reference point the
individual nation state.
 In an attempt to develop a wider European perspective on the measurement and
interpretation of poverty, this has been accompanied in recent years by measures of
“material deprivation”, which assess relative poverty in terms of the affordability of a
basket of consumption items, defined in a unified manner across EU Member States.
 This partially reflects a shift in focus from social cohesion within each country to social
cohesion within the enlarged community.
MATERIAL DEPRIVATION (EU-SILC)
Economic strain, i.e. the Enforced lack of
household cannot afford: durables, i.e. the
household cannot afford
(but would like to):
Housing, i.e. the households dwelling
suffers from:
to face unexpected
expenses
a washing machine
leaking roof or damp walls/floors/
foundations or rotten window frames
one-week annual holiday
away from home
a colour TV
lack of light
to pay arrears (mortgage or a telephone
rent, utility bills or hire
purchase instalments)
no bath or shower
a meal with meat, chicken
or fish every second day
a computer
no indoor flushing toilet for the sole use
of the household
to keep home adequately
warm
a car
lack of space, as measured by the
number of rooms available for each
household member in the dwelling
SERIOUS QUESTIONS REMAIN WITH RESPECT TO THE
MATERIAL DEPRIVATION INDICATORS
 reliability: Because the cost of most of these items varies dramatically, it is difficult to
interpret individual responses. This is compounded by the fact that the material
deprivation index does not lend itself to longitudinal analysis, as the cost of individual
items (and their diffusion within the population) varies considerably over time.
 policy relevance: The poor correlation (r=0.3) between the at-risk-of-poverty rates and
material deprivation across the EU countries generates confusion: e.g. the risk of
poverty is much lower in a number of former Eastern European countries, but so is the
median income, which correlates highly (r=0.83) with material deprivation.
 aggregation into a household deprivation score: The simple additive approach
based on a 0/1 scoring assigns equal value to each item, effectively giving the same
importance to not affording a PC to not having an indoor toilet. (Gilbert, N., 2011)
QUESTIONS ALSO REMAIN AS TO WHAT CONSTITUTES
A TRULY MULTIDIMENSIONAL CONCEPT OF POVERTY
 Some argue that the shift from the relative at-risk-of-poverty rate to the concept of
material deprivation represents at least a partial move from a simple to a more complex
concept of poverty (Fahey, 2010).
 Others questions the extent to which material deprivation provides a more valid, reliable
and transparent depiction of poverty than a direct measure of income (Gilbert, 2011).
 Researchers have sought to broaden the financial measures to include wealth, imputed
rent and the psychological consequences of financial strain.
 There is a widespread realisation that comprehensive measurement of social exclusion
must include many other dimensions.
 Few studies have managed to successfully operationalise the measurement of these
additional dimensions when developing poverty indices.
EU COMMONLY AGREED PRIMARY SOCIAL INCLUSION
INDICATORS
Name
Description
Income Poverty
P1) 60% median income at-risk-of-poverty rate
P2) persistent at-risk-of-poverty rate
P3) relative median poverty risk gap
Unemployment and Joblessness
P4) long-term unemployment rate
P5) population living in jobless households
Low Educational Qualifications
P6) early school leavers not in education or training
Employment Situation of
Immigrants
P7) employment gap of immigrants
Material Deprivation
P8) population living in materially deprived households
Housing
P9) indicator(s) to be developed
Access to Healthcare
P10) self-reported unmet need for medical care
Child Well-being
P11) indicator(s) to be developed
THE CONVENTIONAL APPROACH TO ANALYSING
DIMENSIONALITY: EXPLORATORY FACTOR ANALYSIS (EFA)
 Exploratory Factor Analysis (EFA) reduces variables to a smaller number of underlying
Dimensions or Factors
V1
F1
V2
V3
V4
V5
F2
V6
 EFA is an exploratory technique (i.e. data-driven)
 all variables load on all factors
 the structure matrix is determined by the nature of the variables
 Principal Components Analysis (a commonly-used EFA technique) does not account for
measurement error (v1-v6 are assumed to be perfect indicators)
 EFA can not be used to compare outcomes over time
THE DIMENSIONALITY OF MATERIAL DEPRIVATION
(EU-SILC)
Using EFA, Nolan (2010) identifies three dimensions in the EU-SILC indicators:
 Consumption deprivation – items relating to food, heat, a holiday, a car or a PC, and
avoiding arrears on rent or utilities.
 Household facilities – such as bath or shower and indoor toilet, a telephone, a colour
TV and a washing machine.
 Neighbourhood environment - noise, pollution, crime and violence.
But note, that this structure already differs from that postulated.
A SUPERIOR APPROACH: CONFIRMATORY FACTOR
ANALYSIS (CFA)
 variables are conceptualised as the (imperfect) manifestations of underlying, latent
concepts
d1
V1
d2
V2
d3
V3
d4
V4
d5
V5
d6
V6
L1
L2
 CFA requires a strong theoretical justification before the model is specified
 the researcher decides which of the observed variables are to be associated with which of
the latent variables
 variables are assumed to only partially reflect the latent variable
 CFA model (with factorial invariance) allows for the comparison of outcomes over time
 CFA facilitates the objective evaluation of model “fit” using statistical tests and indices
APPLYING CFA TO THE BRITISH HOUSEHOLD PANEL
STUDY (BHPS)
Walker, R., Tomlinson, M, Williams, G. Multi-dimensional Measurement of Poverty and Well-being: A UK Case-Study
A MULTIDIMENSIONAL MODEL OF POVERTY
(BHPS 1991-2003)
Walker, R., Tomlinson, M, Williams, G. Multi-dimensional Measurement of Poverty and Well-being: A UK Case-Study
CONVENTIONAL AND SEM-BASED POVERTY MEASURES
IN COMPARISON
The relative income measures show a pattern of stable or slightly increasing poverty during the John
Major period 1992–97 and then a decline when New Labour took office from 1997 onwards while the
absolute income measure, with the poverty threshold held constant in real terms, shows a continuous
decline.
The analogous PI-based measures, on the other hand, both show steady declines throughout the
whole period, which is to be expected since a portion of the index is designed to capture aspects of
poverty theorised to be more stable and less sensitive to short-term fluctuations in the national
economic situation.
Measuring Child and Family Well-being
MEASURING
CHILD AND
FAMILY WELLBEING GROWING UP
IN IRELAND
Bronfenbrenner’s Ecological Perspective
on Child Development
TAKING THE THEORETICAL FRAMEWORK SERIOUSLY
 There is a need to take the theoretical framework seriously in the study design
 The nested structure of potential influences on child well-being needs to find explicit
expression
 This requires latent variable modelling and testing influences along the direct and
indirect pathways postulated by the theoretical framework
 Classical statistical models, such as ANOVA and multiple regression, can only test the
influence of a set of risk and protective factors on a single outcome variable and do not
account for mediated effects
 Structural Equation Modelling offers a feasible solution to this problem
AN ECOLOGICAL MODEL OF CHILD WELL-BEING
Measurement Model
for SCG Well-being
SCG Well-being
PCG Well-being
Child Well-being
Measurement Model for Child Well-being
Risk and Protective Factors
Risk and Protective Factors
Measurement Model
for PCG Well-being
RISK AND PROTECTIVE FACTORS
Financial Difficulties
Non-Irish Ethnicity
Local Problem Scale
SCG Well-being
Low Social Class
Local Services Scale
Equivalised Household
Income Decile
Haase-Pratschke
Deprivation Score
ESRI Basic Deprivation
PCG Well-being
Health Status (Child)
Low Education (PCG)
Life Events (Child)
Gender (Child)
Health Status (PCG)
Child Well-being
Age (PCG)
Pratschke, J., Haase, T., McKeown, K. 2011 Well-being and the family system: A structural equation model of relational and contextual influences.
GUI Conference, December.
d
P3_SCG
Parenting
SCG
Dyadic
PCG
Depression
PCG
P2_SCG
Parenting
PCG
d
d
Depression
SCG
Dyadic
SCG
d
d
Financial
difficulties
SCG wellbeing
Local
services
Non-Irish
ethnicity
Low social
class
HaasePratschke
Life Events
of child
ESRI
Deprivation
Low educ.
of PCG
Child wellbeing
Gender
of child
Health
of PCG
Child
Difficulties
Age of
PCG
Scholastic
Achievement
T_EVAL
d
D_MATH
PH_INT
d
D_READ
PH_POP
d
PH_APP
d
PH_HAP
HYP_P
d
SelfConcept
REL_P
CON_P
EMO_P
d
HH
income
PCG wellbeing
Health of
Child
Note 2:
all covariances between
independent variables omitted
from figure
d
d
d
Local
problems
Note 1:
covariances between disturbance
terms for Child Well-being and
Parenting (PCG and SCG) not
included in figure.
d
DSAT_S
d
DCOH_S
d
DCON_S
d
P1_SCG
P3_PCG
d
DSAT_P
P2_PCG
d
DCOH_P
d
DCON_P
d
d
P1_PCG
A
STRUCTURAL
EQUATION
MODEL OF
CHILD AND
FAMILY
WELL-BEING
d
INFLUENCES ON CHILD AND FAMILY WELL-BEING
Goodness of Fit:
N:
CFI:
RMSEA:
All effects significant at p < .05
4,881
.951
.023
Financial Difficulties
- . 08
- . 10
Local Problem Scale
SCG Well-being
Non-Irish Ethnicity
- . 10
Low Social Class
R²=.04
- . 06
Local Services Scale
Equivalised Household
Income Decile
Haase-Pratschke
Deprivation Score
- . 15
ESRI Basic Deprivation
- . 11
PCG Well-being
. 09
R²=.17
Health Status (Child)
- . 10
- . 06
- . 11
. 41
. 04
- . 10
Life Events (Child)
Gender (Child)
. 08
- . 07
- . 04
. 07
- . 28
Child Well-being
R²=.31
Low Education (PCG)
Health Status (PCG)
- . 04
. 12
Age (PCG)
Pratschke, J., Haase, T., McKeown, K. 2011 Well-being and the family system: A structural equation model of relational and contextual influences.
GUI Conference, December.
KEY FINDINGS ON THE DETERMINANTS OF CHILD
WELL-BEING
1. The analysis confirms the importance of the mother’s well-being as a mediating factor
on the child. A one unit improvement in the mother’s well-being is associated with a 0.4
unit direct improvement in child well-being.
2. In stark contrast, the direct effect of the father’s well-being on the child (.04) is almost
negligible once we control for other factors.
3. A striking result is the strongly mediated effect of many contextual influences, in
harmony with the ecological model of child well-being.
4. With the exception of the mother’s health and the Haase-Pratschke Deprivation Index,
which have a significant direct effect on child well-being, all other socio-economic
factors, including financial variables and local area problems, have a distal effect on
child well-being that is mediated by the mother’s well-being.
REFLECTION ON METHODOLOGICAL ISSUES IN THE
MEASUREMENT OF CHILD WELL-BEING
1. The conceptualisation of well-being as a higher-order latent concept reveals itself to be
a powerful and well-supported hypothesis.
2. The assumption that the well-being of children cannot be understood without
simultaneously analysing the well-being of their parents is reinforced.
3. All of the key influences identified in this analysis are in line with our previous research
on child and family well-being using independent data – including the finding that a unit
change in maternal well-being is associated with almost half a unit change in child wellbeing.
4. Parents act as a buffer between economic risk factors and child well-being.
5. Socio-economic risks do influence parental well-being, and thus have a mediated effect
on children.
Deprivation and its Spatial Articulation
RECONSIDERING THE DEFINITION OF POVERTY AND
DEPRIVATION
 Relative Poverty
“People are living in poverty if their income and resources (material,
cultural and social) are so inadequate as to preclude them from having
a standard of living which is regarded as acceptable by Irish society
generally.”
(Government of Ireland, NAPS, 1997)
 Relative Deprivation
“The fundamental implication of the term deprivation is of an absence –
of essential or desirable attributes, possessions and opportunities
which are considered no more than the minimum by that society.”
(Coombes et al., DoE – UK, 1995)
THE IMPORTANCE OF THE CONCEPT OF
OPPORTUNITY DEPRIVATION
 Attributes can be measured using Census or administrative data on
the individual (e.g. ethnicity, education, social class etc.)
 Possessions can also be measured through individual-level Census
or administrative data (e.g. income, wealth, consumption etc.)
However,
 Opportunities cannot be measured in the individual. Opportunities
reflect interactions, and require specific measures
 Any measure of poverty or deprivation that rests on individual-level
data alone will inevitably be biased towards urban forms of deprivation
A HYPOTHESIS OF THE UNDERLYING DIMENSIONS OF
SOCIAL DISADVANTAGE
 Demographic Decline (predominantly rural)
 population loss and the social and demographic effects of emigration (age
dependency, low education of adult population)
 Social Class Deprivation (applying in rural and urban areas)
 social class composition, education, housing quality
 Labour Market Deprivation (predominantly urban)
 unemployment, lone parents, low skills base
THE BASIC MODEL OF AFFLUENCE AND DEPRIVATION
d1
Age Dependency Rate
d2
Population Change
d3
Primary Education only
d4
Third Level Education
d5
Professional Classes
d6
Persons per Room
d7
Lone Parents
d8
Semi- and Unskilled Classes
d9
Male Unemployment Rate
d10
Female Unemployment Rate
Demographic
Growth
Social Class
Composition
Labour Market
Situation
DYNAMIC PATH DIAGRAM FOR IRISH DEPRIVATION
MEASURES, 1991 - 2006
Initial Growth
Rapid Growth
Slow-Down
R2= .80
Demographic
Growth 91
0.20
0.15
R2= .85
R2= .83
Demographic
Growth 96
0.80
7
7
4
5
Demographic
Growth 02
1.19
0.08
-0.51
8
Demographic
Growth 06
0.93
-0.16
-0.03
8
0.86
R2= .95
R2= .90
0.04
Social Class
Composition 91
0.28
0.30
Social Class
Composition 96
0.66
-0.04
Social Class
Composition 02
0.81
0.31
-0.16
Labour Market
Situation 91
0.97
-0.02
R2= .94
9
9
0.12
Labour Market
Situation 96
Social Class
Composition 06
0.83
0.01
6
0.56
0.23
R2= .89
-0.33
1.11
-0.06
0.27
Labour Market
Situation 02
R2= .92
Haase, T. & Pratschke, J. 2008 The New Measures of Deprivation in the Republic of Ireland. Dublin: ADM.
1.02
Labour Market
Situation 06
R2= .94
CHANGE IN ABSOLUTE DEPRIVATION SCORES,
1991-2006
Number of EDs
1200
1000
1991
1996
800
2002
2006
600
400
200
0
-42.5 -37.5 -32.5 -27.5 -22.5 -17.5 -12.5 -7.5 -2.5
2.5
7.5
12.5
17.5 22.5 27.5 32.5 37.5 42.5
The figure shows the unprecedented growth in Ireland over the 1991 to 2006 period, with
greatest changes occurring between 1996 and 2002.
CHANGE IN RELATIVE DEPRIVATION SCORES, 1991-2006
Number of EDs
1000
1991
800
1996
2002
600
2006
400
200
0
ext r emel y
ver y
di sadvant aged
di sadvant ageddi sadvant aged
mar gi nal l y
mar gi nal l y
bel ow aver age
above aver age
af f l uent
ver y af f l uent
ext r emel y
af f l uent
The figure shows the final distribution of Relative Deprivation Scores, after controlling for the
underlying trend and standardising its spread. The scores thus look at deprivation at each point in
time; i.e. as it might be perceived in relative terms.
ABSOLUTE
AFFLUENCE
AND
DEPRIVATION
1991 - 2006
1991
1996
2002
2006
Absolute Index Scores, 1991-2006
Haase & Pratschke 2008
30 to 50
20 to 30
10 to 20
0 to 10
-10 to 0
-20 to -10
-30 to -20
-50 to -30
COMPARISON OF ABSOLUTE DEPRIVATION SCORES,
1991-2006
 Shows how affluence has grown throughout the whole country.
 Greatest change between 1996 and 2002.
 Shows how affluence has grown in concentric rings around the main urban
centres, effectively demarcating the urban commuter belts.
 Shows that, with the exception of Dublin Inner City, cities in general have not
improved in their affluence as much as the rest of the country.
RELATIVE
AFFLUENCE
AND
DEPRIVATION
1991 - 2006
1991
1996
2002
2006
Relative Index Scores, 1991-2006
Haase & Pratschke 2008
very affluent
affluent
marginally above average
marginally below average
disadvantaged
very disadvantaged
extremely disadvantaged
COMPARISON OF RELATIVE DEPRIVATION SCORES,
1991-2006
 Apart from Dublin Inner City, where there is evidence of substantial gentrification,
there are only small differences in Relative Deprivation Scores between 1991 and
2006.
STRENGTHS OF CFA-BASED DEPRIVATION INDICES
 true multidimensionality, based on theoretical considerations
 no double-counting
 rational approach to the selection/construction of indicators
 statistical tests and alternative fit indices to test model adequacy
 identical structure matrix can be imposed across multiple waves
 identical measurement scale can be obtained across multiple waves
 true distances to means are maintained (i.e. measurement, not ranking)
 distinguishes between absolute and relative deprivation
 allows for true inter-temporal comparisons
WHAT ARE THE ATTRIBUTES OF A SATISFACTORY
MEASURE OF POVERTY OR DEPRIVATION?
1. facilitates the comprehension of multiple indicators.
2. provides a basis for the effective targeting of the most disadvantaged individuals,
families or areas.
3. improves our understanding of the pathways through which poverty and well-being are
mediated.
4. provides a means by which to compare relative need, assess change over time, and
facilitate monitoring and evaluation.
5. enjoys broad support amongst key stakeholders, including government departments,
state agencies and community representatives.
www.trutzhaase.eu