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Tessa PeasgoodCentre for Well-being in Public PolicySheffield University
Modelling Subjective Well-being. Do strong social relations lead to increases in well-being?
SWB in the British Household Panel Survey “Please tick the number which you feel best describes how
dissatisfied or satisfied you are with the following aspects of your current situation….......……. your life?”
1 2 3 4 5 6 7Not satisfied Completely
satisfied
12-item General Health Questionnaire (GHQ) - used to detect the presence of non-psychotic psychiatric morbidity in community settings
THE GHQa) been able to concentrate on whatever you're doing ?c) felt that you were playing a useful part in things ?d) felt capable of making decisions about things ?g) been able to enjoy your normal day-to-day activities ?h) been able to face up to problems ?l) been feeling reasonably happy, all things considered ?
More so than usual (1), Same as usual (2), Less so than usual (3), Much less than usual (4)
b) lost much sleep over worry ?e) felt constantly under strain ? f) felt you couldn't overcome your difficulties ?i) been feeling unhappy or depressed ?j) been losing confidence in yourself ? k) been thinking of yourself as a worthless person ?
Not at all (1), No more than usual (2), Rather more than usual (3), Much more than usual (4)
BHPS Satisfaction with life overall, waves 7 to10 & 12
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7
Satisfaction with life
Perc
enta
ge o
f res
pons
es
Male
Female
Why use both life satisfaction and GHQ? May measure different aspects of SWB
Different time period (4 weeks vs.1 year+) Life satisfaction more evaluative GHQ externally determined affects, may not be
what is important to the individual
Different measures have different problems, if results are similar, or we understand why they vary, should give confidence in results.
How valid are these SWB measures?Interpretation problems
Not clear what time period are people using for life satisfaction Not clear if people are including non self-referencing concerns
e.g. others well-being GHQ compares to ‘usual’ but may be using scale absolutely
a third of respondents who answer better than, or less than usual to the general happiness question in wave 12 also do so in wave 13
Measurement error Situational factors & question ordering – what attention is drawn
to at the time Life satisfaction influenced by mood - BUT life satisfaction more
stable than mood Culturally appropriate responses
problematic if adjusting responses is linked to circumstances e.g. unemployment
Are life satisfaction responses internally consistent?
Actual change in life satisfaction score
Would you say that you are more satisfied with life, less satisfied or feel about the same as you did a year ago?
Increased Decreased Same
More satisfied 34% 18% 48%
Less satisfied 17% 52% 31%
Same 25% 26% 48%
Why the inconsistency?
Poor memory for what life was like a year ago
Measurement error (current year, previous year or both)
Not a clear concept
Revaluate past based on new information Need to assume people use the scales in the same way &
that current evaluation of current time is privileged
Some confidence derived from: SWB correlates with informant reports, smiling and
interviewer ratings
SWB predicts suicide
Other subjective measures have predictive powers Job satisfaction predicts quitting job Subjective health predicts suicide and longevity
Life satisfaction & GHQ will tell use something about SWB but will have considerable measurement error.
Social capital and well-being Has been found to be linked to beneficial outcomes e.g.
lower crime rates, child welfare, public health, market performance, education performance (Helliwell & Putnam 2004)
Some evidence of direct link social capital to individual well-being/happiness (Putman 2000, Helliwell 2004, Diener and Seligman 2002), using range of measures for social capital
Focus here on social and personal relationships Intimate relationship & marriage status How often meet friends and family How often talk to neighbours Average level of social relationship scale for the district
The Model
SWBit = β’Xit + αi + uit
SWB (Life satisfaction or GHQ score)
for individual i
at wave t
Matrix of explanatory variables e.g. income & health
of individual i
at wave t
Individual effect
Shifts SWB up/down but doesn’t change how much Xs effect Y (β same for everyone)
If happy disposition would shift Y upward in all time periods
Error term
All change in SWBit not captured by Xit and αi
SWBit = β’Xit + αi + uit
To estimate β need to either remove or estimate αi
Fixed effects Using deviations from individual means individual effect (αi)
drops out (αi is the same as the individual mean αi)
Comparing individual to themselves at different time periods
Can’t say much about variables which don’t vary ‘within’ the individual over the time period
Can use OLS fixed effects on life satisfaction and GHQ but assumes cardinality
Ordered logitTreat life satisfaction as latent, continuous variable LS*
LSit = 1 if -∞ <= LS* <= μ1= 2 if μ1 < LS* < μ2
= 3 if μ2 < LS* < μ3 etc.
Probability of an outcome (e.g. Life sat = 5) calculated as linear function of explanatory variables plus set of thresholds or cut points.
Control for unobserved individual effects by including individual level means of all explanatory variables (Mundlak approach)
Since model uses logit assumption on error term the log odds of being in higher life satisfaction category are linearly dependent on the explanatory variables.
itiitit uXLS *
Explanatory Variables: Social relationships Ordered Logit on life satisfaction (All)
Base category: sees friends or family and talks to neighbours most days, married, no accommodation problems
Odds ratio P value
Sees friends or family once or twice a week 0.954 0.018
Sees friends or family once or twice a month 0.955 0.154
Sees friends or family less than once a month 0.898 0.086
Never sees friends or family 0.611 0.043
Talks to neighbours once or twice a week 0.925 0.000
Talks to neighbours once or twice a month 0.773 0.000
Talks to neighbours less than once a month 0.840 0.000
Never sees neighbours 0.830 0.007
Mean social relationships scale of district 1.296 0.011
Divorced/Separated 0.764 0.002
Co-habiting 1.027 0.647
Widowed 0.621 0.001
Never married and not co-habiting 0.823 0.021
Living alone 0.998 0.969
Problem with accommodation: noisy neighbours 0.971 0.354
Problem with accommodation: street noise 0.994 0.822
Problem with accommodation: vandalism / crime 0.960 0.108
Explanatory variables: Income Ordered Logit on Life satisfaction (all)
Base category: top income quintile, ‘living comfortably’, no problems paying for accommodation
Odds ratio P value
Bottom income quintile 0.946 0.204
Second income quintile 0.973 0.476
Third income quintile 0.951 0.127
Fourth income quintile 0.983 0.524
Doing OK financial 0.834 0.000
Just financial 0.639 0.000
Difficult financial 0.466 0.000
Very difficult financial 0.295 0.000
Problems paying for accommodation 0.839 0.000
Mean equivalent household net income for the individuals district and age group
1.000 0.566
Explanatory variables: Health Ordered Logit on Life satisfaction (All)
Base category: Subjective health good, not disabled, no problems walking
Odds ratio P value
Subjective health poor or very poor 0.502 0.000
Subjective health fair 0.717 0.000
Subjective health excellent 1.223 0.000
Problems walking 0.721 0.000
Disabled 0.903 0.092
Days hospital stays (excl. births) 0.928 0.027
Problems with sleep 0.650 0.000
Explanatory variables: Employment status Ordered Logit on Life satisfaction (All)
Base category: employed Odds ratio P value
Long term sick 0.616 0.000
Retired 1.087 0.203
Unemployed 0.728 0.000
Maternity leave 1.519 0.000
Self-employed 0.972 0.617
Family carer 0.910 0.099
Student 1.070 0.281
Government training 0.788 0.331
Other employment status 0.939 0.670
Explanatory variables: Education and demographics Ordered logit on Life satisfaction (All)
Base category: No education, not high burden carer Odds ratio
P value
Commercial qualification 1.240 0.223
O level 1.018 0.889
A level 1.176 0.201
Degree or higher education 1.143 0.282
Cares for someone > 50 hours a wk 0.786 0.024
Number children in household 12-18 0.935 0.012
Number children in household 5-11 0.973 0.349
Number children in household 0-4 0.949 0.107
Age 0.823 0.000
Age squared / 100 1.363 0.000
Age cubed / 1000 0.978 0.000
Results Broadly the same using for life satisfaction, GHQ, ‘not at all’
unhappy, and modelling as ordered variable or cardinal, and for males and females
Social relationships important Financial coping and health biggest knock to well-being Financial coping related but not identical to income
50% of top income, and 15% of bottom quintile ‘living comfortably’
14% of those in the top income quintile think they are just about getting by or are finding it difficult or very difficult financially.
Need to look at ‘real’ household income, accounting for the costs of living, where those ‘costs of living’ may be influenced by geographical costs differences, or individually held (and socially driven) expectations of ‘necessary’ expenditures.
Direction of causality?
Income SWBHealth SWB
Social relationships SWB
May be other factors influencing SWB and X’s e.g. life events like having sick child
Could address endogeneity using Instrument Variables but hard to think of truly exogenous variables
Likely that route from SWB to X’s slower. Some evidence that cheerfulness in college students predicted higher income 19 years later (Diener et al 2002)
Still confident people matter.. A lot
One very clear message from this range of different modelling techniques on different SWB measures is that the people around you really matter. Those times when we have people who we see regularly and who create a friendly and peaceful local environment are the times when we are more satisfied with our lives and less likely
to experience unhappiness.
But is this a policy concern?
Some indication of positive externalities, social connectedness not entirely private good - role for intervention
Indirect impact on social relationships of other policies (e.g. flexible labour force, hours worked) should be considered
Increasing income may reduce social connectedness.
Income quintile Mean social relationships
1 (bottom) 6.56
2 6.54
3 6.40
4 6.27
5 (top) 6.07
Fixed effects OLS on social relations scale When other variables are controlled for, the negative
relationship between income and social relationships scale remains.
Being in the bottom two income quintiles is significantly related to having a higher social relationships scale, although perceived inability to cope financially is associated with reduced social relationships
Conclusion
Can’t say income isn’t important to SWB, financially difficulties very important
Increased income may contribute to other sources of SWB e.g. health
BUT Policies which focus on increasing income risk
undermining other sources of SWB Policies shouldn’t confuse means to well-being as
ends