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

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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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31

48

7

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

14

40

61

13

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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

14

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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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