workshop on well being over the life course agenda layard
TRANSCRIPT
WELLBEING OVER THE LIFE-COURSE
Richard LayardDirector, Wellbeing Programme, LSE CEP
27 March 2015
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THE AIMTo enable policy-makers to maximise
wellbeing by
(i) choosing where to develop new policies, and
(ii) evaluating those new policies.
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For (i) we need to compare influences (Xi ) in terms of their explanatory power
.
For (ii) we need to know /
Vital that measured simultaneously and in same units, for all Xi .
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OUTLINE1. Some evidence on .
•From British Cohort Study
•From household panel studies
2. Some thoughts on cost-effectiveness analysis.
WHAT PREDICTS A SUCCESSFUL LIFE?A LIFE-COURSE MODEL OF WELLBEING
Andrew E. ClarkFrancesca Cornaglia
Richard LayardNattavudh Powdthavee
James Vernoit
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A MODEL OF LIFE-SATISFACTIONFamily
backgroundChild
characteristicsAdult
outcomes‘Final
outcome’
Economic
Psycho-social
Intellectual performance
Good conduct
Emotional health
Income
Educational level
Employment
Conduct
Family status
Physical health
Emotional health
Adult life-
satisfaction
Experience
PREVIOUS WORKEither (1) Effects of current circumstances
(Oswald, etc.)
Or (2) Effects of background andchildhood (Shields, Goodman
etc.)
Our aim is to combine the two.8
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Age of childChild characteristics
Intellectual performance 5, 10, 16Good conduct 5, 10, 16Emotional health 5, 10, 16
Family background
Economic (FE) Father’s socio-economic group 10Family income 10Number of siblings 10Father in work 0, 5, 10 averageMother’s and father’s age on leaving full-time education --
Psycho-social (FP) Mother’s emotional health 5, 10 averageChild conceived within marriage --Both parents still together 10
British Cohort Study: Childhood Variables
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Economic Log income (equivalised) at 34
Educational achievement by 34 Employed (measured as not
unemployed)at 34
Social Good conduct (= -no. of crimes) at 16-34
Has a partner at 34
Personal Self-perceived healthEmotional health
at 26at 26
British Cohort Study: Adult outcomes
Physical health
(recorded 8 years earlier)
Emotional health
(recorded 8 years
earlier)
LIFE-SATISFACTION AT 34
Income Not un-employed
Education level
Married/ Cohabiting
Crimi-nality
.06 .09 .04 .12 -.07 .07 .20
(partial correlation coefficients)
The main immediate influences on adult life-satisfaction
Emotional development
Cognitive development
Behaviour
.05 .09 .17
The main childhood influences on adult life-satisfaction
(partial correlation coefficients)
LIFE-SATISFACTION AT 34
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What are the main childhood influences on different aspects of adult life (Britain)?
Emotional health
Physical health (self-report)
Married/Cohabiting
Non-Criminality
Employment
Qualifications
Income
-0.1 0.4
Test per-formance
Good Behaviour
Emotional health
Partial correlation coefficients*
Influences on:
*These numbers show how well each adult variable on the left hand side is predicted by childhood test performance, good behaviour and emotional health, holding other variables constant.
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(1) (2) (3)
Using adult variables only
Using childhood variables only
Using both
Log income 0.055 (0.012) 0.052 (0.012)
Educational achievement 0.035 (0.010) 0.029 (0.011)
Employed 0.085 (0.013) 0.082 (0.013)
Good conduct 0.066 (0.014) 0.061 (0.014)
Has a partner 0.116 (0.012) 0.113 (0.012)
Self-perceived health (26) 0.068 (0.013) 0.065 (0.013)
Emotional health (26) 0.204 (0.014) 0.181 (0.015)
Intellectual performance (5 10 16) 0.045 (0.016) -0.035 (0.020)
Good conduct (5 10 16) 0.085 (0.019) 0.052 (0.019)
Emotional health (5 10 16) 0.174 (0.021) 0.098 (0.020)
Family Economic 0.055 (0.018) 0.025 (0.014)
Family Psychosocial 0.030 (0.016) 0.024 (0.018)
Female 0.068 (0.021) 0.082 (0.022) 0.072 (0.021)
Observations 8,868 8,868 8,868
Adjusted R2 0.108 0.071 0.142
Predictors of life-satisfaction (Dependent variable: life-satisfaction at 34)
The case for early intervention
Depends on
1) Weight we should give to childhood wellbeing.
2) How strongly early characteristics persist, compared with later characteristics.
3) How costly it is to change characteristics earlier rather than later.
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(1) (2) (3) (4) (5) (6) (7) (8)
Log income
Education Employed Good conduct
Has a partner
Self-perceived health (26)
Emotional health
(26)
Life-satisfaction
Information on:
Family only 0.021 0.176 0.007 0.028 0.009 0.022 0.051 0.018
Up to age 5 0.029 0.176 0.008 0.043 0.016 0.027 0.061 0.022
Up to age 10 0.035 0.247 0.009 0.051 0.019 0.029 0.071 0.027
Up to age 16 0.050 0.376 0.010 0.070 0.029 0.067 0.207 0.071
Adjusted R2 for Equations Predicting Adult Outcomes, Using Different Amounts of Information
(Dependent variable: life-satisfaction at 34)
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SUMMARY OF THE BRITISH COHORT STUDY
1. For life-satisfaction, emotional health (as child and adult) v. important.
2. For economic outcomes, educational development much more important.
3. For family-building and crime, child behaviour crucial.
Problem 1: What determines these developments? (George Ward).
Problem 2: Definition of emotional health from self-reported symptomatology.
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DO MORE OF THOSE IN MISERY SUFFER FROM POVERTY, UNEMPLOYMENT OR MENTAL ILLNESS?
Sarah Flèche Richard Layard
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NEW FEATURES1. More objective measures of mental illness
“Ever diagnosed for depression or anxiety disorders”. Also “currently in treatment”.
2. Focus on misery (though results with continuous life-satisfaction very similar).
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PANEL DATAMental health Physical health
US (BRFSS) Diagnosis Numbers (Yes to problems)
US (PSID) Diagnosis Numbers (Yes to problems)
Australia (HILDA) Diagnosis + SF36 SF36
UK (BHPS) GHQ12 Numbers (Yes to problems)
Germany (GSOEP)
SF12 SF12
Mostly annual data.Focus is on contemporaneous or near contemporaneous.
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(1) (2) (3)Income (log) -0.06 (7) -0.03 (4) -0.01 (0)Unemployed 0.06 (5) 0.05 (4) 0.02 (1)Physical health problems 0.16 (14) 0.11 (12) 0.08 (4)Diagnosed with depression/anxiety
0.14 (14) 0.10 (11) 0.04 (2)
Misery lagged one year -- 0.33 (20) --Fixed effects -- -- √R2 0.09 0.19 0.01
T-statistics in parenthesesControls for age, age2, living with partner, education and gender.
Predictors of misery: Australia
Note: Misery in Australia is bottom 7.5% of life-satisfaction
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BRFSS PSID (1) (2) (3) (4)Income (log) -0.12 (14) -0.07 (8) -0.06 (6) -0.04 (3)Unemployed 0.06 (18) 0.06 (11) 0.05 (7) 0.02 (2)Physical health problems 0.05 (14) 0.05 (9) 0.03 (4) 0.04 (3)Diagnosed with depression/anxiety
0.17 (44) 0.08 (14) 0.08 (10) 0.09 (6)
Misery lagged one year -- -- 0.24 (30) --Fixed effects -- -- -- √R2 0.08 0.05 0.12 0.01
T-statistics in parenthesesControls for age, age2, living with partner, education and gender.
Predictors of misery: US
Note: Misery in the BRFSS is bottom 5.6% and in PSID bottom 6%.
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Percentage of those in misery having the above characteristics
Physical health problems (bottom 10%)
Currently in treatment for mental health condition
Ever diagnosed with depression/anxiety
Unemployed
Poor (bottom 10%)
0 10 20 30 40 50 60 70
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48
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20
Australia
Note: Misery is bottom 7.5% of life-satisfaction
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United States - BRFSS
Physical health problems (bottom 10%)
Currently in treatment for mental health condition
Ever diagnosed with depression/anxiety
Unemployed
Poor (bottom 10%)
0 10 20 30 40 50 60 70
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40
61
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Percentage of those in misery having the above characteristics
Note: Misery is bottom 5.6% of life-satisfaction.
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United States – PSID
Physical health problems (bottom 10%)
Ever diagnosed with emotional, nervous or psychiatric problems
Unemployed
Poor (bottom 10%)
0 5 10 15 20 25 30 35 40
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20
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Percentage of those in misery having the above characteristics
Note: Misery in the PSID is bottom 6% of life-satisfaction.
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INTERPRETATION (ignoring multiple causation)
Relative impact X Prevalence
M = population in misery
T = total population
For a binary variable, so ordered in the same way as the correlation of M with .
Q: Are these pictures helpful for the general reader?
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Australia Britain Germany
Income (log) -0·02 (3) -0·01 (2) -0·02 (4) -0·02 (4) -0·03 (5) -0·02 (2)
Unemployed 0·03 (5) 0·03 (4) 0·02 (5) 0·03 (7) 0·03 (4) 0·04 (5)
Physical health 0·03 (4) 0·06 (8) 0·03 (6) 0·06 (10) 0·04 (6)
Physical health in previous year 0·03 (4)
Mental health 0·15 (25) 0·33 (61) 0·23 (25)
Mental health in previous year 0·02 (3) 0·08 (15) 0·06 (7)
Fixed effects √ √ √ √ √ √
R2 0.03 0.01 0.10 0.01 0·05 0·01
T-statistics in parenthesesControls for age, age2, living with partner, and education.
Predictors of misery: using symptomatology
Note: Misery is bottom 7.5% in Australia, 9.9% in Britain and 8.7% in Germany.
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COST-EFFECTIVENESS ANALYSIS
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RECOMMENDATIONSpend money on policies for which
Or, more generally,
Net cost > 0
Assumes(i) total exp fixed(ii) social welfare = (this could be weighted
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AN EXPERIMENTUsing PSID fixed-effect life-satisfaction equation
(1) Diagnosis reduces LS by 0.3 SDs
∴ Therapy raises LS by 0.1 SDs (33% excess recovery)
(2) Cost reduces log Income by 0.05
∴ Cost reduces LS by 0.0015 SDs
= 1/70 of the benefit
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NEXT STAGE
The effect of childhood experiences.
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Book on Wellbeing over the Life-Course Contents
Non-technical summary
Ch 1. Policy relevance of research on subjective wellbeing
Ch 2. Our analytical framework and data
Part I Effects of childhood experience upon wellbeing
Ch 3. Economic background
Ch 4. Parenting behaviour and parents’ mental health
Ch 5. Family conflict
Ch 6. Parental employment, unemployment and childcare
Ch 7. Schooling (including class size, school size, school organisation and ethos, teacher quality and turnover)
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Part II Adult outcomes: their causes and their consequences for wellbeingCh 8. How adult outcomes affect life-satisfaction: overviewCh 9. IncomeCh 10. Educational achievementCh 11. Work and quality of workCh 12. Mental healthCh 13. Physical health and ageingCh 14. Family building and loneliness Ch 15. Criminal behaviourCh 16. Altruism Part III Policy implicationsCh 17. Public policy-making and a new method of cost-effectiveness
analysisCh 18. Case studies (Healthy Minds, Exploring what Matters, etc)Ch 19. Summary of conclusions
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