Inequalities in the older population: Evidence from ELSA
James Banks, Carl Emmerson, Alastair Muriel and Gemma Tetlow
18th November 2008
© Institute for Fiscal Studies, 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
© Institute for Fiscal Studies, 2008
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
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£ p
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Mean p10 p25 Median
p75 p90 FRSMean FRSp10
FRSp25 FRSMedian FRSp75 FRSp90
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
Net income distribution: 2003
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
22%
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2004
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2005
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2006
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2007
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2008
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2009
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2010
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2011
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2012
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2013
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2014
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2015
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2016
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2017
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Poverty Threshold 2003/04, £189
Note: net incomes shown under “White Paper” policy baseline
5%
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
2017
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Poverty Threshold 2017, £247
Note: net incomes shown under “White Paper” policy baseline
19%
Source: Brewer, et al (2007).
© Institute for Fiscal Studies, 2008
Correlation between pension wealth and non-pension wealth
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Po
ore
st 2 3 4 5 6 7 8 9
Ric
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st All
Total non-pension wealth decile
Pe
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/£0
00
's
Mean p25 p75 Median
Total pension wealth
Correlation between pension wealth and non-pension wealth
Source: Banks, Emmerson, Oldfield and Tetlow (2005).
© Institute for Fiscal Studies, 2008
Distribution of predicted retirement resources
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Gross equivalised family income (£ p.a.)
% o
f th
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Pension wealth
Non-housing wealth
Total wealth (incl. expected inheritances)
…. plus Pension Credit
Note: Assumes baseline (probabilistic) likelihood of working to SPA.Source: Banks, Emmerson, Oldfield and Tetlow (2005).
© Institute for Fiscal Studies, 2008
Health and wealth at older ages
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0 250,000 500,000 750,000 1,000,000 1,250,000 1,500,000
Total w ealth (£)
Per
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of p
opul
atio
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Fair or poor health
Good health
Excellent or very good health
Source: Banks et al (2005) calculations from 2002 ELSA, Individuals aged 50 to SPA
© Institute for Fiscal Studies, 2008
Survival after wave 1 (months)by wealth quintile; age adjusted
0.70
0.80
0.90
1.00
0 12 24 36 48 60 72
Months since wave 1
Su
rviv
al p
rob
abili
ty
Richest
4
3
2
Poorest
Source: Nazroo, Zaniotto and Gjonca (2008), in Banks et al (2008), ELSA wave 3 report.
0.7
0.8
0.9
1
0 12 24 36 48 60 72
Months since wave 1
Su
rviv
al p
rob
abili
ty
Male Female
© Institute for Fiscal Studies, 2008
Odds for 5-year mortality after wave 1Hazard 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] 0.090Additional controls not reported: Sex, age (5-year dummies), Physical activity, Smoking, drinking
Source: Nazroo, Zaniotto and Gjonca (2008), in Banks et al (2008), ELSA wave 3 report.
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
Per cent without any CVD-related disease by age-specific wealth quintile, sex and age
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50-59 60-74 75+ 50-59 60-74 75+
Poorest234Richest
Angina, myocardial infarction, stroke, heart failure heart murmur, abnormal heart rhythm, diabetes
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
© Institute for Fiscal Studies, 2008
Per cent without any of six selected chronic physical diseases by age-specific wealth quintile, sex and age
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40
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80
100
50-59 60-74 75+ 50-59 60-74 75+
Poorest234Richest
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
Chronic lung disease, asthma, arthritis, osteoporosis, cancer (excl. primary skin cancer), Parkinson’s disease
© Institute for Fiscal Studies, 2008
Incidence of at least one major condition between 2002 and 2004by gender and age-specific wealth quintile in 2002
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Poorest 2 3 4 Richest
Men 50-59
Men 60-74
Women 50-59
Women 60-74
Source: Breeze et al (2006), in Banks et al (2006), ELSA wave 2 report.
© Institute for Fiscal Studies, 2008
Perceptions of work disability by wealth quintile
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Poorest 2 3 4 Richest
Pe
rce
nta
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in p
aid
wo
rk Extremely limited
Severely limited
Moderately limited
Mildly limited
Not limited
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?
Quintile of total non-pension wealth
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
© Institute for Fiscal Studies, 2008
Odds of work disability by wealth quintile
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1
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5
Unadjusted Adjusted for sex, age andeducation
Adjusted for sex, age,education and reporting
behaviour
Poorest234Richest
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
© Institute for Fiscal Studies, 2008
Probability of work disability onset; by work status and wealth
0
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Working Not working
Pe
rce
nta
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exp
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cin
g o
nse
t of w
ork
dis
ab
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Poorest2nd3rd4thRichest
Percentage who experience the onset of a work disability between waves 2 and 3
Source: Banks and Tetlow (2008), in Banks et al (2008), ELSA wave 3 report.
© Institute for Fiscal Studies, 2008
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
© Institute for Fiscal Studies, 2008
1975
Earnings mobility: Men aged 23–28 in 1975, transitions from 1975 to 1995
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
Inequalities in the older population: Evidence from ELSA
James Banks, Carl Emmerson, Alastair Muriel and Gemma Tetlow
18th November 2008
© Institute for Fiscal Studies, 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...’?)
Source: Emmerson and Muriel (2008), in Banks et al (2008), ELSA wave 3 report.
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