Inequalities in the older population:
Evidence from ELSA
James Banks, Carl Emmerson, Alastair Muriel and Gemma Tetlow
18th November 2008
ELSA and inequalities in the older population
•
Multidimensional outcomes…
Economic, social, biological, psychological, environmental
•
… and key dimensions of ‘capabilities’
e.g. Life; Bodily health, Bodily integrity; Senses, imagination and thought;
Emotion; Practical reason; Affiliation; Other species; Play; Control over one’s
environment (Nussbaum, 2000)
•
… over time
– 6-10 years of panel data now available
– Early life circumstances, including SES and geography
– Selected life-histories, including employment and housing
© Institute for Fiscal Studies, 2008
ELSA and inequalities in the older population
•
Strengths
– Multidimensionality means can measure correlation between dimensions
• Breadth versus depth of poverty and inequalities
• Targeting
– Subjective and objective measures of the same thing
– Link to mortality records (even for non-responders)
– Links to admin records, e.g earnings history, benefit take-up
•
Weaknesses
– Older population only
– Only available since 2002
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Overarching framework: A life-course approach to
inequalities in the older population
•
Short-medium term horizons
– Address current pensioner inequalities
– Alleviation of immediate pressures
• Address current employment/disability of older workers
• Quality of life and wellbeing more generally
• Health care and social services
•
Medium-long term horizons
– Address the causes of poor health, disability, social exclusion and
material poverty in the elderly
•
Very long term horizons
– The long shadow of early life circumstances
•
Considering past trends in returns to education, within-pensioner
inequalities may well increase over next 20 years
© Institute for Fiscal Studies, 2008
Simulating pensioner income to 2017–18
£ per week
900
800
700
600
500
400
300
200
Mean
p75
FRSp25
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p10
p90
FRSMedian
p25
FRSMean
FRSp75
2017–18
2016–17
2015–16
2014–15
2013–14
2012–13
2011–12
2010–11
2009–10
2008–09
2007–08
2006–07
2005–06
2004–05
2003–04
2002–03
2001–02
2000–01
1999–00
1998–99
1997–98
1996–97
100
0
Median
FRSp10
FRSp90
Source: Brewer, et al (2007).
Net income distribution: 2003
Poverty
Threshold
2003/04,
£189
Number of individuals (thousands)
500
400
22%
300
200
100
0
0
100
200
300
400
500
600
700
800
900
1,000
£ per week, 2003/04 prices
Note: net incomes shown under “White Paper” policy baseline
© Institute for Fiscal Studies, 2008
Source: Brewer, et al (2007).
2017
Poverty
Threshold
2003/04,
£189
Number of individuals (thousands)
500
400
5%
300
200
100
0
0
100
200
300
400
500
600
700
800
900
1,000
£ per week, 2003/04 prices
Note: net incomes shown under “White Paper” policy baseline
© Institute for Fiscal Studies, 2008
Source: Brewer, et al (2007).
2017
Poverty
Threshold
2017,
£247
Number of individuals (thousands)
500
400
19%
300
200
100
0
0
100
200
300
400
500
600
700
800
900
1,000
£ per week, 2003/04 prices
Note: net incomes shown under “White Paper” policy baseline
© Institute for Fiscal Studies, 2008
Source: Brewer, et al (2007).
Correlation between pension wealth and nonpension wealth
Total pension wealth
Pension wealth/£000's
700
Mean
p25
p75
Median
600
500
400
Correlation
between pension wealth and
300
non-pension
wealth
200
100
All
Richest
9
8
7
6
5
4
3
2
Poorest
0
Total non-pension wealth decile
© Institute for Fiscal Studies, 2008
Source: Banks, Emmerson, Oldfield and Tetlow (2005).
Distribution of predicted retirement resources
% of the population
100%
80%
60%
Pension wealth
40%
Non-housing wealth
Total wealth (incl. expected inheritances)
20%
…. plus Pension Credit
£50,000
£45,000
£40,000
£35,000
£30,000
£25,000
£20,000
£15,000
£10,000
£5,000
£0
0%
Gross equivalised family income (£ p.a.)
© Institute for Fiscal Studies, 2008
Note: Assumes baseline (probabilistic) likelihood of working to SPA.
Source: Banks, Emmerson, Oldfield and Tetlow (2005).
Health and wealth at older ages
Percentage of population
100%
90%
80%
70%
60%
50%
40%
30%
20%
Fair or poor health
Good health
10%
Excellent or very good health
0%
0
250,000
500,000
750,000
1,000,000
1,250,000 1,500,000
Total w ealth (£)
© Institute for Fiscal Studies, 2008
Source: Banks et al (2005) calculations from 2002 ELSA, Individuals aged 50 to SPA
Survival after wave 1 (months)
by wealth quintile; age adjusted
Richest
Male
Female
4
1.00
1
3
2
Poorest
0.9
Survival probability
Survival probability
0.90
0.80
0.70
0.8
0.7
0
12
24
36
48
Months since w ave 1
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60
72
0
12
24
36
48
60
72
Months since w ave 1
Source: Nazroo, Zaniotto and Gjonca (2008), in Banks et al (2008), ELSA wave 3 report.
Odds for 5-year mortality after wave 1
Hazard ratio
95% ci
p-value
Separated/Divorced
1.39
[1.11,1.74]
<0.001
Widowed
1.18
[1.02,1.37]
<0.001
Never Married
1.49
[1.18,1.89]
<0.001
Wealth quintile 4
1.03
[0.82,1.31]
0.775
Wealth quintile 3
1.15
[0.92,1.45]
0.223
Wealth quintile 2
1.46
[1.17,1.82]
<0.001
Wealth quintile 1
1.56
[1.24,1.95]
<0.001
Educ: Intermediate
0.91
[0.70,1.18]
0.488
Educ: No qualifications
0.90
[0.68,1.18]
0.455
Class: Intermediate
1.06
[0.88,1.28]
0.559
Class: Routine/manual
1.16
[0.98,1.38]
0.090
Additional controls not reported: Sex, age (5-year dummies), Physical activity, Smoking, drinking
Reference group: 50-54 yr old, male, non-smoker; high physical activity, non-drinker, highest wealth quintile,
education: degree, class: managerial/professional
© Institute for Fiscal Studies, 2008
Source: Nazroo, Zaniotto and Gjonca (2008), in Banks et al (2008), ELSA wave 3 report.
Per cent without any CVD-related disease
by age-specific wealth quintile, sex and age
Angina, myocardial infarction, stroke, heart failure heart murmur, abnormal heart rhythm, diabetes
Poorest
2
3
4
Richest
100
80
60
40
20
0
50-59
© Institute for Fiscal Studies, 2008
60-74
75+
50-59
60-74
75+
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
Per cent without any of six selected chronic physical diseases
by age-specific wealth quintile, sex and age
Chronic lung disease, asthma, arthritis, osteoporosis, cancer (excl. primary skin cancer), Parkinson’s disease
Poorest
2
3
4
Richest
100
80
60
40
20
0
50-59
© Institute for Fiscal Studies, 2008
60-74
75+
50-59
60-74
75+
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
Incidence of at least one major condition between
2002 and 2004
by gender and age-specific wealth quintile in 2002
40
35
30
Men 50-59
25
Men 60-74
20
Women 50-59
15
Women 60-74
10
5
0
Poorest
© Institute for Fiscal Studies, 2008
2
3
4
Richest
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
Perceptions of work disability by wealth quintile
e.g. Geoffrey suffers from back pain that causes stiffness in his back especially at work, but it is
relieved with low doses of medication. He does not have any pains other than this general
discomfort. How much is Geoffrey limited in the kind or amount of work he could do?
100
90
Percentage in paid work
80
Extremely limited
70
Severely limited
60
Moderately limited
50
Mildly limited
40
Not limited
30
20
10
0
Poorest
2
3
4
Richest
Quintile of total non-pension wealth
© Institute for Fiscal Studies, 2008
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
Odds of work disability by wealth quintile
5
Poorest
2
3
4
Richest
4
3
2
1
0
Unadjusted
© Institute for Fiscal Studies, 2008
Adjusted for sex, age and
education
Adjusted for sex, age,
education and reporting
behaviour
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
Probability of work disability onset;
by work status and wealth
Percentage who experience the onset of a work disability between waves 2 and 3
Poorest
2nd
3rd
4th
Richest
Percentage experiencing onset of work disability
35
30
25
20
15
10
5
0
© Institute for Fiscal Studies, 2008
Working
Not working
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
Average annual real earnings growth over ten years
Excludes those with earnings truncated at the UEL in either year and those with no
earnings above LEL in either year
Data removed awaiting approval for external dissemination
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Earnings mobility: Men aged 23–28 in 1975, transitions from 1975 to 1995
1975
Data removed awaiting approval for external dissemination
© Institute for Fiscal Studies, 2008
Ongoing ELSA work
•
Some analysis already underway:
– Late life consequences of previous employment/earnings differences
– Health and mortality differences and links to education/income/wealth
– Further understanding of disability and employment prior to SPA
•
Other possible issues:
–
–
–
–
–
More work on multi-dimensional inequalities
Link between ‘objective’ inequalities and subjective well-being measures
Within-household spillovers, e.g. caring
Household versus individual financial inequalities
Pensioner specific equivalence scales
© Institute for Fiscal Studies, 2008
Inequalities in the older population:
Evidence from ELSA
James Banks, Carl Emmerson, Alastair Muriel and Gemma Tetlow
18th November 2008
Well-being and quality of life (GHQ and CASP)
Factors associated with self-reported well-being/quality of life:
• Income (+)
• Physical functioning (+)
• Being above retirement age (+)
• Marital status:
–
–
–
–
Women in couples report highest quality of life...
... but men in couples report highest level of well-being.
Divorced/separated/widowed individuals report lowest quality of life
(It is not ‘better to have loved and lost...’?)
© Institute for Fiscal Studies, 2008
Source: Emmerson and Muriel (2008), in Banks et al (2008), ELSA wave 3 report.