Transcript Analyzing Health Equity Using Household Survey Data Lecture 13 Explaining Socioeconomic-Related Health Inequality: Decomposition of the Concentration Index “Analyzing Health Equity Using Household Survey Data”

Analyzing Health Equity Using
Household Survey Data
Lecture 13
Explaining Socioeconomic-Related Health Inequality:
Decomposition of the Concentration Index
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Decomposition of the Concentration Index
For any linear additive explanatory model of ‘health’ (y)
such as : y i     k x ki  i
k
the concentration index of y can be decomposed (Wagstaff
et al 2003):
C
  (k x k /  )C k  GC  / 
k
 k C k  GC  / 
k
where  is the mean of y, xk is the mean of xk, Ck is the
concentration index for xk , GCε is the generalized
concentration index for the error term, and ηκ is the
elasticity of y with respect to xk .
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Age-sex standardization through
decomposition
The indirectly standardized concentration index
(CIS) can be obtained by subtracting the
contributions of all standardizing variables (s)
from the unstandardized concentration index
(Van Doorslaer et al, 2004):
CIS  C  sCs
s
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Decomposition of Concentration Index for Heightfor-Age z-Scores of kids<10 Years, Vietnam
Aggregate contributions
Age
1998
Male
Consumption
Water
Sanitation
1993
Educ - head
Educ -mother
Commune
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
0.00
0.02
Residual
Contributions to concentration index
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Magnitudes of contributions
The contribution of variable xk to incomerelated health inequality is given by k C k
and is larger:
• The greater is the elasticity of health in
relation to the variable (ηκ)
• The more unequally is the variable
distributed in relation to income (Ck)
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Detailed decomposition of concentration index for
HAZ-Scores in Vietnam
1993
1998
Elasticities
CIs
Contributions
Elasticiti
es
CIs
Contributions
Child’s age (in months)
1.137
0.020
0.023
1.630
0.018
0.030
Child’s age squared
–0.634
0.030
–0.019
–0.880
0.028
–0.025
Child = male
0.022
0.003
0.000
0.045
0.014
0.001
(log)household
consumption p.c.
–0.936
0.038
–0.035
–1.288
0.040
–0.052
Safe drinking water
–0.003
0.312
–0.001
–0.017
0.256
–0.004
Satisfactory sanitation
–0.009
0.468
–0.004
–0.006
0.508
–0.003
Years schooling
household head
–0.017
0.065
–0.001
–0.015
0.094
–0.001
Years schooling
mother
–0.037
0.075
–0.003
–0.003
0.108
0.000
Fixed commune effects
1.477
–0.024
–0.035
1.534
0.031
–0.047
“Residual”
–0.002
0.002
Total
–0.077
–0.099
Decomposition of income-related
health inequality in Europe
Portugal
UK
Greece
Luxembourg
Income (log)
Denmark
Male age
Female age
Ireland
Education
Austria
Activity status
Belgium
Marital status
Spain
Foreign origin
Region
France
Italy
Germany
Netherlands
-0.005
0.000
0.005
0.010
Conc Index
0.015
0.020
0.025
Decomposition of change in the
concentration index - Oaxaca
Applying Oaxaca-type decomposition to the difference
between the concentration indices of two populations:
C   k k t  Ckt  Ckt 1    k Ckt 1 kt  kt 1     GC t / t 
i.e. a sum of the differences in the
- CIs for determinants k weighted by their elasticities
- elasticities weighted by their respective CIs
- generalised CIs of the residuals
Of course, the weights could be reversed
Decomposition of increase in
inequality in child HAZ-scores in
Vietnam 1993-98
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Decomposition of change in the
concentration index – total differential
To identify the contribution of the change in each
component of the elasticity, take the total differential
of the decomposed CI:
xk
k
C
dC   d   k  Ck  C  d  k   k  Ck  C  dxk



 k xk
GC
 k
dCk  d
.


“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Decomposition of Change in HAZ
Concentration Index of kids <10 Years,
Vietnam 1993–98

’s
Decomposition of change in concentration index
Oaxaca-type
Total differential approach (13.4)
approach (13.3)
Means
CIs
Total
Percent
Total
Percent
of x’s
0.011
0.012
0.007
 0.002
 57
 30
Child’s age (in months)
0.003
Child’s age squared
0.003
 0.010
0.001
 0.006
Child = male
0.001
0.000
0.000
0.001
29
5
 0.005
 0.005
 0.002
 0.011
52
 0.002
0.000
0.000
 0.003
Satisfactory sanitation
0.003
 0.002
0.000
0.001
Years schooling hhold. head
0.001
0.000
 0.001
0.000
Years schooling mother
0.005
0.000
 0.001
0.004
Fixed commune effects
0.000
 0.014
 0.010
 0.025
Household consumption
Safe drinking water
“Residual”
Total
0.010
 0.021
 0.016
14
5
0
 19
0.005
119
 24
 0.021
100
 0.006
26
0.001
3
 0.016
74
 0.003
16
0.001
5
0.000
1
0.003
 11
 0.012
55
0.005
 24
 0.022
100
Oaxaca method can be used to explain
cross-country differences in incomerelated health inequality
• Netherlands has lowest income-related health
inequality
• Define ‘excess’ inequality of each country
relative to the Netherlands
• Compute contribution of each factor to
‘excess’ income-related health inequality
“Analyzing Health Equity Using Household Survey Data” Owen O’Donnell, Eddy van Doorslaer, Adam Wagstaff and
Magnus Lindelow, The World Bank, Washington DC, 2008, www.worldbank.org/analyzinghealthequity
Contribution of each factor to ‘excess’
income-related health inequality relative
to the Netherlands
Portugal
UK
Greece
Luxembourg
Income
Educ
Denmark
Unemployed
Retired
Ireland
Econ Inact
France
Other inact
Single
Austria
Foreign
Belgium
Region
Spain
Italy
Germany
-0.005
0.000
0.005
0.010
I* Index
0.015
0.020
Conclusions
• Decomposition is useful explanatory tool for
partitioning inequality
• Contributions can be further decomposed into
elasticity of health and inequality of
determinants
• Oaxaca-type decomposition useful for
explaining differences or changes
• Limitations:
– Linearity of underlying model
– Explanatory model usually does not allow for
causal interpretation